MD Jean-David Werthel

PhD François Boux De Casson

MD Gilles Walch

MD Pascal Gaudin

MD Philipp Moroder

MD Joaquin Sanchez-Sotelo

PhD Jean Chaoui

PhD Valérie Burdin

3D Muscle Loss (3DML) assessment: A novel CT-based quantitative method to evaluate rotator cuff muscle fatty infiltration Short running title: Quantitative 3D Muscle Loss Assessment

Introduction

Rotator cuff fatty infiltration (FI) is one of the most important parameters to predict the outcome of certain shoulder conditions. The primary objective of this study was to define a new computed tomography (CT)-based quantitative 3-dimensional (3D) measure of muscle loss (3DML) based on the rationale of the 2-dimensional (2D) qualitative Goutallier score.

The secondary objective of this study was to compare this new measurement method to traditional 2D qualitative assessment of FI according to Goutallier et al and to a 3D quantitative measurement of fatty infiltration (3DFI).

Materials and Methods

102 CT scans from healthy shoulders (46) and shoulders with cuff tear arthropathy (21), irreparable rotator cuff tears (18), and primary osteoarthritis (17) were analyzed by three experienced shoulder surgeons for subjective grading of fatty infiltration according to Goutallier and their rotator cuff muscles were manually segmented. Quantitative 3D measurements of fatty infiltration (3DFI) were completed. The volume of muscle fibers without intra-muscular fat was then calculated for each rotator cuff muscle and normalized to the patient's scapular volume to account for the effect of body size (NVfibers). Threedimensional muscle mass (3DMM) was calculated by dividing the NVfibers value of a given muscle by the mean expected volume in healthy shoulders. Three-dimensional muscle loss (3DML) was defined as 1-(3DMM). The correlation between Goutallier grading, 3DFI, and 3DML was compared using a Spearman Rank correlation.

Results

Interobserver reliability for the traditional 2D Goutallier grading was moderate for the infraspinatus (ISP=0.42) and fair for the supraspinatus (SSP=0.38), subscapularis (SSC=0.27) and teres minor (TM=0.27). 2D Goutallier grading was found to be significantly and highly correlated with 3DFI (SSP=0.79, ISP=0.83, SSC=0.69, TM=0.45) and 3DML (SSP=0.87, ISP=0.85, SSC=0.69, TM=0.46) for all four rotator cuff muscles (p<0.0001). This correlation was significantly higher for 3DML than for the 3DFI for the SSP only (p=0.01).

The mean values of 3DFI and 3DML were 0.9% and 5.3% for Goutallier-0, 2.9% and 25.6% for Goutallier-1, 11.4% and 49.5% for Goutallier-2, 20.7% and 59.7% for Goutallier-3, and 29.3% and 70.2% for Goutallier-4, respectively.

Conclusion

The Goutallier score has been helping surgeons by using 2-dimensional CT-scan slices.

However, this grading is associated with suboptimal interobserver agreement. The new measures we propose provide a more consistent assessment that correlates well with Goutallier's principles. As 3DML measurements incorporate atrophy and fatty infiltration, they could become a very reliable index for assessing shoulder muscle function. Future algorithms capable of automatically calculating the 3DML of the cuff could help in the decision process for cuff repair and the choice of anatomic or reverse shoulder arthroplasty.

Level of Evidence: Anatomy Study; Imaging Keywords: Goutallier; 3D Goutallier; muscle volume; 3D CT scan; atrophy; volumetric analysis Rotator cuff fatty infiltration (FI) is recognized as one of the most important parameters to predict the outcome the outcome of certain shoulder procedures 5; 8; 9; 11; 23; 33 and it is considered crucial for clinical decision-making prior to rotator cuff repair and shoulder arthroplasty 14; 20; 43 . Goutallier et al [START_REF] Goutallier | Fatty muscle degeneration in cuff ruptures. Pre-and postoperative evaluation by CT scan[END_REF] first reported a method to subjectively and qualitatively stage intra-muscular fatty infiltration into 5 grades using computed tomography (CT) on axial views. This method was then adapted by Fuchs et al for its application on magnetic resonance imaging (MRI) on T1-weighted sequences [START_REF] Fuchs | Fatty degeneration of the muscles of the rotator cuff: assessment by computed tomography versus magnetic resonance imaging[END_REF] . These two qualitative 2-dimensional (2D) classifications are known to have poor intra-and inter-observer reliability between 0.26 and 0.81 for intra-observer reliability and between 0.36 and 0.6 for inter-observer reliability. 30; 35; 41 , and several recent studies have shown how modern imaging sequences and techniques have the potential to provide a better estimate of FI by allowing accurate quantitative calculation of the intra-muscular fat fraction after manual segmentation of rotator cuff muscle boundaries either on 2D sagittal Y-views 17; 22; 28; 29; 31 or in 3 dimensional (3D) images 16; 26; 28; 41 . A number of imaging techniques (single-voxel MR spectroscopy [START_REF] Pfirrmann | Assessment of fat content in supraspinatus muscle with proton MR spectroscopy in asymptomatic volunteers and patients with supraspinatus tendon lesions[END_REF] , spectroscopic gradient echo imaging [START_REF] Kenn | 2D SPLASH: a new method to determine the fatty infiltration of the rotator cuff muscles[END_REF] , two-point Dixon imaging 16; 26; 29 or chemical shift-based water-fat separation techniques 22; 28 ) have been reported to correlate with Goutallier scores. However, the objective quantitative percentage of intramuscular fat calculated with these methods was much lower than the expected fat ratio as determined qualitatively according to Goutallier 28;[START_REF] Vidt | Assessments of Fatty Infiltration and Muscle Atrophy From a Single Magnetic Resonance Image Slice Are Not Predictive of 3-Dimensional Measurements[END_REF] . This is probably due to two reasons: first, distribution of intra-muscular fat is not uniform inside the muscle body 15 2; 18; 27; 28 and as such 2-dimensional assessments cannot capture 3dimensional FI measurements 19; 41 ; and secondly, the subjective qualitative assessment of the Goutallier score may sometimes be difficult to apply, since the precise distinction between atrophy and fatty infiltration is often unclear in the literature as it is often difficult to distinguish the boundaries between intra-and extra-muscular fat in cases of severe muscle atrophy and FI (Figure 1).

We therefore hypothesized that the qualitative Goutallier score would be better translated quantitatively by calculating the percentage of remaining muscle tissue (independent of intraor extra-muscular fat) rather than by calculating the percentage of fat within the muscle. The primary objective of this study was to define a new quantitative 3-dimensional (3D) measure of muscular loss (3DML) based on rationale of the 2-dimensional (2D) qualitative Goutallier score. The secondary objective of this study was to compare this new measurement method to the traditional 2D qualitative assessment of FI according to Goutallier et al and to a 3D quantitative measurement of fatty infiltration (3DFI).

Materials and Methods

This study was approved by the Institutional Review Board of the Ethical Committee of Hôpital Privé Jean Mermoz, Lyon, France (COS-RGDS-2020-05-001-WALCH-G).

Study Cohort

We retrospectively reviewed shoulder CT-scans performed between 2015 and 2020 and obtained from a database incorporating 4 institutions (Lyon, Nice and Paris, France, Belo Horizonte, MG, Brazil). The CT-scan exams had been performed using one of two CT scan systems (Revolution CT, GE Healthcare, Chicago, IL, USA or Siemens Somatom CT Scanner, Siemens Healthcare, Erlangen, Germany) with the patient positioned supine on the CT table. CT-scan exams of healthy shoulders and shoulders with primary osteoarthritis (OA), cuff tear arthropathy (CTA), and irreparable rotator cuff tears (IRCT) were included provided they had been obtained using the following acquisition parameters: slice thickness <1.2 mm, number of slices > 200, field of view: whole scapula, X-Y resolution <0.5mm, matrix size: 512 x 512, kV140, mA>300, and both bone and soft-tissue algorithms.

Our final study sample included a total of 102 CT-scans (healthy shoulders 46, CTA 21, ICRT 18, and OA 17 shoulders). The CT of healthy shoulders had been obtained from patients aged older than 18 years without shoulder pathology or injury in the setting of (1) polytrauma, (2) traumatic head injury, or (3) unilateral shoulder trauma with a contralateral normal shoulder. The CT-scan images of patients with CTA, IRCT or OA were preoperative CT-scans performed prior to shoulder arthroplasty. Shoulders with full-thickness rotator cuff tears were classified as CTA if they were ≥ grade 4 in the Hamada classification [START_REF] Hamada | Roentgenographic findings in massive rotator cuff tears. A long-term observation[END_REF] and as IRCT if they had at least two irreparable rotator cuff tendons but no glenohumeral arthritis (Hamada < 4). Patient's demographics are detailed in Table 1.

Qualitative 2D analysis of FI: traditional Goutallier score using 2D CT images

Axial and sagittal CT slices were analyzed according to the principles underlying the Goutallier et al [START_REF] Goutallier | Fatty muscle degeneration in cuff ruptures. Pre-and postoperative evaluation by CT scan[END_REF] and Fuchs et al [START_REF] Fuchs | Fatty degeneration of the muscles of the rotator cuff: assessment by computed tomography versus magnetic resonance imaging[END_REF] protocols for the presence of FI, which was classified according to the 5-grade qualitative scale described by Goutallier et al 9 : Grade 0, normal; Grade 1, some fatty streaks; Grade 2, more muscle than fat; Grade 3, equal amounts of fat and muscle; and Grade 4, more fat than muscle. All the CT-scans were examined independently by 3 different fellowship-trained shoulder surgeons (J.D.W, P.M., P.G.) in order to assess the inter-rater reliability of this subjective quantitative method. The final grading of each muscle used for analysis was based on consensus agreement where 2/3 or 3/3 surgeons had classified the same grade. A difference of more than 1 grade required that all surgeons reviewed the examination together again in order to reach consensus.

Three-Dimensional Muscle Reconstruction

The soft-tissue DICOM (Digital Imaging and Communications in Medicine) images for each CT scan were manually segmented using the Slicer version 4.10.0 software (Slicer Community Boston, MA, USA; http://slicer.org). Muscle boundaries were manually identified and marked to segment the four rotator cuff muscles: supraspinatus, subscapularis, infraspinatus and teres minor. To create a robust process, muscle boundaries were identified on each image slice in all 3 planes (coronal, axial and sagittal). The segmentations were performed either by a shoulder fellowship-trained orthopedic surgeon or by trained technicians; segmentation performed by technicians was verified and corrected when needed by the same orthopedic surgeon that had completed manual segmentation of a proportion of the CT. Published threshold values were used to identify muscle and fat tissue 1 . Extramuscular fat was not assessed. The volume of muscle fibers without intra-muscular fat (Vfibers) and the volume of intra-muscular fat (Vimfat) were calculated in cm 3 for each muscle.

Quantitative 3D analysis of FI (3DFI), muscle mass (3DMM) and muscle loss (3DML)

Quantitative calculation of FI (3DFI) was possible once the muscle fiber volume (Vfibers) and the intra-muscular fat volume (Vimfat) have been calculated. The following formula was applied to each rotator cuff muscle:

3𝐷𝐹𝐼 = 𝑉 𝑖𝑚𝑓𝑎𝑡 𝑉 𝑓𝑖𝑏𝑒𝑟𝑠 + 𝑉 𝑖𝑚𝑓𝑎𝑡
The bone DICOM series were then automatically segmented using a validated 3D-software (BluePrint, v2.1.6, Tornier SAS, France) which provides a 3D model of the scapula and allows automatic calculation its volume in cm [START_REF] Conze | Healthy versus pathological learning transferability in shoulder muscle MRI segmentation using deep convolutional encoder-decoders[END_REF] . Each measurement of muscle fiber volume was then normalized to the patient's scapular volume to account for the effect of body size on muscle volume [START_REF] Maden-Wilkinson | Thigh muscle volume in relation to age, sex and femur volume[END_REF] . This allowed us to calculate the normalized volume of muscle fibers (NVfibers) for each rotator cuff muscle. Mean NVfibers were calculated for each muscle in the 4 different groups of patients (Healthy Controls, IRCT, CTA, OA). In order to establish a frame of reference for normal muscle volume, the NVfibers value for each muscle was divided by the theoretical volume that this muscle would have if it were healthy. This theoretical volume was determined by calculating the mean NVfibers of the healthy shoulders, which were used to obtain a reference value for males and females for each of the rotator cuff muscles (Ref NVfibers). Table 2 summarizes mean NVfibers for each muscle and each group. Quantitative calculation of three-dimensional muscle mass (3DMM) was completed by dividing the NVfibers value for a given muscle by the RefNVfibers of that muscle.

3𝐷𝑀𝑀 = 𝑁𝑉 𝑓𝑖𝑏𝑒𝑟𝑠 𝑅𝑒𝑓 𝑁𝑉 𝑓𝑖𝑏𝑒𝑟𝑠 ,

3D muscle loss (3DML) is then determined by subtracting 3DMM from 100.

3𝐷𝑀𝐿 = 100 -3𝐷𝑀𝑀

For example, the average RefNVfibers value of the infraspinatus for males is 1.4 (Table 1). If the NVfibers infraspinatus measurement of a given shoulder of a male patient is 0.88, the infraspinatus 3DMM for such shoulder would be 0.88/1.40 = 63%, which means that 63% of the expected muscle mass is still present and the remaining 37% of the expected muscle mass is been replaced by infiltrated fat (3DML = 1 -0.88/1.4 = 37%). Two examples can be seen in Figures 2 and3.

Statistical Analysis

Reliability of agreement between the three raters of the Goutallier grade was assessed using a Fleiss kappa (k). Fleiss Kappa value and 95% CI were computed for each muscle, for the whole cohort but also for each diagnostic group (Healthy Controls, CTA, IRCT, OA).

Concordance was evaluated using the table of Landis et al [START_REF] Landis | The measurement of observer agreement for categorical data[END_REF] .

One-way analysis of variance was used to test the difference between the means of several diagnostic subgroups (Healthy Controls, CTA, MRCT, OA) of a continuous variable (3DFI or 3DML). Levene's test was used to check the equality of variances. The hypothesis that the means of at least two of the subgroups differ significantly is accepted if the P value of the F statistic is less than 0.05. The pairwise comparison of the subgroups was then calculated using the Tukey-Kramer test. If the Levene test is positive (p<0.05), then the variances in the different groups are different and we used a non-parametric statistic. In that case, the Kruskal-Wallis test (H-test) was used. For the whole cohort, but also each diagnostic group (Healthy Controls, CTA, MRCT, OA), the correlation between the consensus Goutallier score and the quantitative 3D analysis of fatty infiltration (3DFI) and 3DML was computed using a Spearman Rank Correlation. The coefficient of rank correlation, rho, was assessed using a Steiger test.

For all tests, the level of statistical significance was set at p<0.05. Statistical analyses were performed using R (v3.6.1, R Foundation) or MedCal (v19.4.0, MedCalc Software Ltd.)

depending on the test.

Results

Goutallier inter-observer reliability

Analysis of the interobserver reliability showed fair interobserver reliability for supraspinatus, subscapularis and teres minor FI, with k values of 0. 3.

Quantitative 3D analysis of fatty infiltration (3DFI) and muscle loss (3DML)

The mean 3DFI and 3DML are detailed for each rotator cuff muscle and for each patient group (Healthy Controls, CTA, MRCT, OA) in Tables 4 and5.

The mean 3DFI was significantly greater for all four rotator cuff muscles in pathological groups than in the healthy control group (p<0.0001). Among the pathological groups, the mean FI was significantly higher for the supraspinatus of CTA and MRCT patients than for OA patients (p<0.02) and for the infraspinatus of CTA patients than for OA patients (p<0.001).

The mean 3DML was significantly greater for all four rotator cuff muscles in pathological groups than in the healthy control group (p<0.0001). Among the pathological groups, the mean 3DML was significantly higher for the supraspinatus of CTA and MRCT patients than for OA patients (p<0.001) and for the infraspinatus of CTA patients than for OA patients (p<0.005).

The correlation between the consensus 2D Goutallier score and the quantitative 3D analysis of FI and ML is detailed in Table 6. For all rotator cuff muscles, mean values of 3DFI were 0.9% ± 1.5 for Goutallier 0 muscles, 2.9% ± 4.6 for Goutallier 1 muscles, 11.4% ± 9.9 for for all four rotator cuff muscles (p<0.0001). This correlation was significantly higher for the 3DML than for the measure of 3DFI for supraspinatus (p=0.01).

Discussion

Rotator cuff FI is extremely important in the decision-making process prior to rotator cuff repair or shoulder arthroplasty. Despite advances in preoperative planning for shoulder arthroplasty using dedicated software with three-dimensional assessments, currently most surgeons grade rotator cuff FI subjectively on two-dimensional CT or MRI. The results of our study seem to indicate that the interobserver reliability of the Goutallier classification for FI on CT is only fair to moderate, in accordance with prior studies 30; 34; 41 . In addition, our study seems to indicate that quantitative measurements of muscle mass and muscle loss may be of value when assessing rotator cuff degeneration in shoulders with OA, CTA and IRCT.

Several authors have proposed to improve the assessment of FI by using 2-dimensional quantitative methods 28; 37 . These methods were reported to be significantly correlated with Goutallier grades. However, we believe that analyzing a 3-dimensional structure on a single two-dimensional slice is incorrect and subject to significant bias, particularly considering that fat is not homogeneously distributed inside rotator cuff muscles 27; 42 .Vidt et al [START_REF] Vidt | Assessments of Fatty Infiltration and Muscle Atrophy From a Single Magnetic Resonance Image Slice Are Not Predictive of 3-Dimensional Measurements[END_REF] have recently demonstrated that single-image assessments are not able to capture 3D measures of fatty infiltration, and that the use of a 3D quantitative method allows better discrimination between the various Goutallier grades.

In our study, when we calculated 3DFI values, we found a very different percentage of fat to muscle ratio than expected according to Goutallier criteria. Indeed, Goutallier grades 3 and 4 are traditionally considered to correspond to a muscle replacement by fat of 50% or more, but our mean 3DML values were 20.7% and 29.3% respectively. This finding is in agreement with previous studies 28; 41 which have also found much lower quantitative values than expected after qualitative assessment. In other words, it only takes loss of 30% of muscle volume to translate into a two-dimensional visual estimate of over 50% fatty infiltration replacement.

Muscle atrophy and FI have been recognized as independent predictive parameters of outcome for a number of surgical procedures 5; 8; 9; 11; 23; 33 . However, as independent as these parameters may be, all the methods that we currently use to assess them inevitably make them dependent on each other. Indeed, measures of muscle volume and muscle atrophy (tangent sign [START_REF] Zanetti | Quantitative assessment of the muscles of the rotator cuff with magnetic resonance imaging[END_REF] , occupation ratio [START_REF] Thomazeau | Atrophy of the supraspinatus belly. Assessment by MRI in 55 patients with rotator cuff pathology[END_REF] ) typically include intra-muscular fat 6-8; 25; 39 and, the measures of fatty infiltration depend on muscle volume as they are expressed as the ratio of intra-muscular fat volume to muscle volume 5; 9 . Therefore, a decrease in muscle volume, with no change in the volume of intra-muscular fat, automatically leads to an increase in the fatty infiltration ratio. It has been shown that increased percentages of fat observed in cases of severe fatty infiltration are more related to muscle atrophy than to increased fat volume [START_REF] Vidt | Assessments of Fatty Infiltration and Muscle Atrophy From a Single Magnetic Resonance Image Slice Are Not Predictive of 3-Dimensional Measurements[END_REF] . Furthermore, it is not clear from the Goutallier score whether fatty infiltration includes only intra-muscular fat or both intra-and extra-muscular fat, especially in cases of severe fatty infiltration and muscle atrophy.

For these reasons, we reasoned that assessment of rotator cuff muscle degeneration could be much improved by developing quantitative three-dimensional assessments of remaining muscle mass and muscle loss. The method presented in our study is complex and tedious, since it requires manual segmentation and two normalization steps. However, they provided the basis and ground truth for training algorithms that in the near future will incorporate automatic muscle segmentation using statistical models and deep learning techniques 3; 32 .

Furthermore, a major benefit of the proposed 3DML measurement is that it integrates both atrophy and fatty infiltration into a single value, which will hopefully best correlate with remaining strength as well as predicted outcomes after surgery 12; 13; 40 .

Interestingly, although the Goutallier score was found to be relatively unreliable when evaluated by a single shoulder-specialized surgeon, this was no longer the case when a consensus Goutallier score was determined among 3 surgeons. Indeed, the consensus values were strongly and significantly correlated with both 3DFI and 3DML measurements, with superior correlation with the 3DML measurements for the supraspinatus muscle (Table 6). In addition, 3DML values were found to be much closer to the expected Goutallier fat ratio than 3DFI values. Indeed, the mean 3DML values were found to be 5.3% for Goutallier-0 muscles, 25.6% for Goutallier-1, 49.5% for Goutallier-2, 59.7% for Goutallier-3 and 70.2% for Goutallier-4, suggesting that 3DML values correspond better to the traditional Goutallier grading currently used in practice. We suspect that calculation of 3DML values will be the most useful FI parameter to consider when assessment of muscle atrophy and FI is fully automated.

Our study has several limitations. Firstly, the size of the cohort of pathological shoulders was relatively small; this was due to difficulties obtaining CT scans with both bone and soft tissue algorithms and the entire scapula, which was unfortunately often truncated at its medial or distal tip. With the recent trend to use high quality CT protocols in preoperative planning software, it is likely that future CT scans will routinely include the entire scapula. Secondly, we did not perform inter-and intra-observer reliability analysis for manual segmentation because of the high number of cases and the extensive amount of time needed to segment the entire rotator cuff. Thirdly, most studies analyzing muscle volume have been based on MRimaging, using techniques that generate more accurate quantitative fat-fraction maps which distinguish fat and muscle from other tissues such as vessels ; however, we chose to investigate CT-imaging with a soft-tissue algorithm for four main reasons: (1) MRI and CT have been shown to be equally effective in assessing supraspinatus atrophy [START_REF] Tae | Evaluation of fatty degeneration of the supraspinatus muscle using a new measuring tool and its correlation between multidetector computed tomography and magnetic resonance imaging[END_REF] and in measuring rotator cuff cross-sectional area; (2) CT-imaging allowed us to automatically segment the scapula using a validated 3D-software (BluePrint, v2.1.6, Tornier, France) and calculate the volume of the scapula in cm 3 ; (3) the proportion of pixels not clearly attributable to muscle or fat was neglectable compared to the number of pixels which are clearly identifiable as muscle or fat, (4) it is easy to obtain CT-scans including the whole scapula with enough slices to perform multiplanar and 3D reconstructions, while this is more challenging to obtain on MRI; and (5) CT is widely available, fast and routinely used in preoperative planning for shoulder arthroplasty [START_REF] Dekker | Current peri-operative imaging concepts surrounding shoulder arthroplasty[END_REF] , where adding soft tissue algorithms to bone algorithms is simple, fast and relatively inexpensive. At present time, the method described in our study is not intended to be incorporated into routine surgical practices until automation of this process will easily allow us to accurately and objectively determine rotator cuff muscle mass and muscle loss.

Conclusion

Assessment of fatty infiltration (FI) in rotator cuff muscles is important for predicting shoulder conditions. Since 1994, the Goutallier score has been helping surgeons by using 2dimensional CT-scan slices. However, this 2D grading is associated with suboptimal interobserver agreement. In this paper, we proposed three CT-based measurements for a three-dimensional quantitative assessment of fatty infiltration (3DFI), muscle mass (3DMM), and muscle loss (3DML). These new measures seem to provide a more consistent assessment that still correlates well with Goutallier's principles. As 3DML measurements incorporate atrophy and fatty infiltration, they have the potential to become a very reliable index for assessing shoulder muscle function. Future algorithms capable of automatically calculating the 3DML of the rotator cuff could be of great help in the decision process for rotator cuff repair and the choice of anatomic or reverse shoulder arthroplasty.

Figure 1 :

 1 Figure 1: Sagittal view of a right shoulder in a MRCT patient with severe fatty infiltration of the supraspinatus and infraspinatus. Intra-and extra-muscular fat can be seen. This example shows the difficulty to define precisely the difference between intra-and extra-muscular fat.

Figure 2 :Figure 3 :

 23 Figure 2: Example of a 42-year-old male from the healthy cohort. Three-dimensional reconstruction and sagittal view of the left infraspinatus (red) and intramuscular fat (yellow). Vfibers: muscle fiber volume Vimfat: intra-muscular fat volume Vscapula: scapular volume NVfibers: normalized volume of muscle fibers Ref NVfibers: reference value for males for the infraspinatus 3DMM: three-dimensional muscle mass 3DFI: three-dimensional quantitative calculation of fatty infiltration 3DML: three-dimensional muscle loss

  Results for each rotator cuff muscle are detailed in Table6. The 2D Goutallier score was significantly and highly correlated to the volume measurement of 3DFI and 3DML

	Goutallier 2 muscles, 20.7% ± 17.5 for Goutallier 3 muscles and 29.3% ± 23.4 for Goutallier
	4 muscles. Mean values of 3DML for all four rotator cuff muscles were 5.3% ± 17.4 for

Goutallier 0 muscles, 25.6% ± 22.3 for Goutallier 1 muscles, 49.5% ± 16.3 for Goutallier 2 muscles, 59.7% ± 13.9 for Goutallier 3 muscles and 70.2% ± 16.3 for Goutallier 4 muscles.

Table 1 .

 1 Patient demographics

Table 1 :

 1 Patient demographics

		Healthy Controls (46)	CTA (21)	IRCT (18)	OA (17)	All
	Mean Age	36	77	71	69	56
	± SD	± 16	± 8	± 8	± 8	± 22
	Mean age Females	46	78	73	69	67
	± SD	± 19	± 8	± 7	± 8	± 17
	Mean sage Males	33	73	68	70	46
	± SD	± 14	± 8	± 8	± 8	± 22
	Left / Right	25 / 21	9 / 12	4 / 14	9 / 8	47 / 55
	Females / Males	12/34	16/5	11/7	10/7	49/53

Table 2 :

 2 Normalized muscles fiber volume (NVfibers) for each condition.

				Healthy Controls	CTA		IRCT		OA
	Supraspinatus		M F	0.65 ± 0.1	0.67 ± 0.1 0.59 ± 0.1	0.24 ± 0.1	0.32 ± 0.1 0.21 ± 0.1	0.27 ± 0.1	0.31 ± 0.1 0.24 ± 0.1	0.37 ± 0.1	0.34 ± 0.1 0.39 ± 0.1
	Subscapularis		M F	1.89 ± 0.3	1.98 ± 0.3 1.63 ± 0.2	1.06 ± 0.3	1.04 ± 0.4 1.07 ± 0.3	1.03 ± 0 .2	1.05 ± 0.2 1.02 ± 0.3	1.04 ± 0.2	0.97 ± 0.2 1.09 ± 0.3
	Infraspinatus		M F	1.37 ± 0.2	1.40 ± 0.2 1.29 ± 0.2	0.65 ± 0.3	0.73 ± 0.3 0.62 ± 0.3	0.74 ± 0.2	0.88 ± 0.1 0.66 ± 0.2	0.92 ± 0.2	0.90 ± 0.2 0.93 ± 0.2
	Teres Minor	M	F	0.30 ± 0.1	0.32 ± 0.1 0.26 ± 0.1	0.21 ± 0.1	0.25 ± 0.1 0.20 ± 0.1	0.21 ± 0.1	0.20 ± 0.1 0.21 ± 0.1	0.19 ± 0.1	0.20 ± 0.1 0.19 ± 0.1

Table 3 :

 3 Inter-observer agreement for Goutallier classification (Fleiss' Kappa)

	Overall
	Fleiss Kappa	95% CI

Table 4 :

 4 Quantitative Three-Dimensional Fatty Infiltration (3D-FI). * represents values significantly different

		Healthy Controls	CTA	IRCT		OA	Kruskal-Wallis test
		2D Goutallier	3D-FI	2D Goutallier	3D-FI	2D Goutallier	3D-FI	2D Goutallier	3D-FI
	Supraspinatus	0.2 ±0.5	0.8% ±1.1%	2.3 ±0.9	15.9% * ±19% OA	2 ±0.7	11.7% * ±11% OA	1.4 ±0.7	CTA/MRCT 4.6% * ±4%	P<0.02
	Subscapularis	0 ±0	0.7% ±1.0%	1.2 ±0.6	8.9% ±10%	1.1 ±1.1	7.5% ±10%	0.4 ±0.5	3.9% ±%3
	Infraspinatus	0.2 ±0.4	0.6% ±0.9%	2.9 ±1.2	21% * ±19% OA	2.2 ±1.3	9.9% ±13%	1.2 ±0.8	CTA 3.3% * ±3%	P<0.001
	Teres Minor	0	0.7%	1.4	9%	0.9	4.4%	0.5	2.4%
		±0.1	±2.0%	±1.4	±22%	±1.1	±10%	±1	±4%

Table 5 :

 5 Three-dimensional muscle loss (3D-ML) * represents values significantly different

		Healthy Controls	CTA	IRCT		OA	ANOVA
		2D Goutallier	3D-ML	2D Goutallier	3D-ML	2D Goutallier	3D-ML	2D Goutallier	3D-ML
	Supraspinatus	0.2 ±0.5	0%	2.3 ±0.9	61% * ±13% OA	2 ±0.7	56% * ±16% OA	1.4 ±0.7	CTA/MRCT 39% * ±14%	P<0.001
	Subscapularis	0 ±0	0%	1.2 ±0.6	37% ±21%	1.1 ±1.1	41% ±14%	0.4 ±0.5	40% ±17%
	Infraspinatus	0.2 ±0.4	0%	2.9 ±1.2	51% * ±22% OA	2.2 ±1.3	44% ±16%	1.2 ±0.8	CTA 30% * ±15%	P<0.005
	Teres Minor	0 ±0.1	0%	1.4 ±1.4	22% ±36%	0.9 ±1.1	25% ±33%	0.5 ±1	30% ±44%

Table 6 :

 6 Correlation between the consensus Goutallier score and the quantitative 3D analysis of fatty infiltration (3D-FI) and muscle loss (3D ML) ± 17.4 25.6 ± 22.3 49.5 ± 16.3 59.7 ± 13.9 70.2± 16.3

		Goutallier	0	1	2	3	4	rho	p-value
		n	38	24	30	7	3
	Supraspinatus	3D-FI (%)	0.7 ± 1.2	2.2 ± 2.7	11.2 ± 10.2	25.3 ± 27	24.2 ± 13.9	0.79	<0.0001
		3D ML (%)	0.7 ± 0.5	25.6 ± 22.8	53.1 ± 15.2	72.7 ± 10.4	74.8 ± 4.0	0.87	<0.0001
		n	65	25	9	3	0		-
	Subscapularis	3D-FI (%)	1.2 ± 1.6	6.3 ± 7.3	13.7 ± 8.7	22.2 ± 14.1	N/A	0.69	<0.0001
		3D ML (%)	10 ± 16.9	37.6 ± 18.5	50.2 ± 17.5	58.4 ± 12.2	N/A	0.69	<0.0001
		n	43	26	9	12	12		-
	Infraspinatus	3D-FI (%)	0.6 ± 1.0	1.9 ± 2.2	7.5 ± 7.0	18.0 ± 14.1	29.7 ± 20.0	0.83	<0.0001
		3D ML (%)	2.3 ± 7.0	20.3 ± 18.6	36.5 ± 11.4	55.9 ± 10.5	62.6 ± 12.5	0.85	<0.0001
		n	71	20	4	2	5		-
	Teres Minor	3D-FI (%)	0.8 ± 1.8	1.0 ± 1.3	17.4 ± 15.3	21.0 ± 10.1	31.7 ± 36.8	0.45	<0.0001
		3D ML (%)	5.3 ± 24.3	17.6 ± 25.3	50 ± 21.3	31 ± 21.2	84.2 ± 19.5	0.46	<0.0001
		n	217	95	52	24	20
	All muscles	3D-FI (%)	0.9 ± 1.5	2.9 ± 4.6	11.4 ± 9.9 20.7 ± 17.6 29.3 ± 23.4	0.71	<0.0001

No funding was disclosed by the author(s). Conflicts of interest: Dr Werthel receives royalties for shoulder prosthesis design from FH Orthopedics. Dr Boux de Casson is an employee of Wright Medical. Dr Walch receives royalties for shoulder prosthesis design from Wright Medical. Dr Moroder receives royalties from Arthrex Inc. and NCS Lab for shoulder related products. Dr Sanchez-Sotelo receives royalties for shoulder prosthesis design from Wright Medical-Stryker. Prof


MD Gilles Lemesle
email: gilles_lemesle@yahoo.fr

MD Etienne Puymirat

MD Laurent Bonello

MD § ; Tabassome Simon

MD|| Philippe-Gabriel Steg

MD Jean Ferrières

MD François Schiele

MD Laurent Fauchier

MD Patrick Henry

MD ‡ ‡ Guillaume Schurtz

Pr Gilles

MD-PhD Lemesle

MD Sandro Ninni

MD § § Nicolas Lamblin

MD § § Christophe Bauters

MD Nicolas Danchin

Gilles Pr

Compared impact of diabetes on the risk of heart failure from acute myocardial infarction to chronic coronary artery disease

Keywords: Coronary artery disease, Diabetes mellitus, Heart failure, Myocardial infarction

niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

ABBREVIATIONS

INTRODUCTION

Diabetes mellitus (DM) is associated with an increased risk of heart failure (HF) both in terms of occurrence and severity [START_REF] Bauters | Influence of diabetes mellitus on heart failure risk and outcome[END_REF][START_REF] De Groote | Impact of diabetes mellitus on long-term survival in patients with congestive heart failure[END_REF]. In coronary artery disease (CAD) patients, DM is frequent and present in 20% to 30% [START_REF] Bauters | Prognosis of patients with stable coronary artery disease (from the CORONOR study)[END_REF][START_REF] Puymirat | Acute myocardial infarction: changes in patient characteristics, management, and 6-month outcomes over a period of 20 years in the FAST-MI Program (French Registry of Acute ST-Elevation or Non-ST-Elevation Myocardial Infarction) 1995 to 2015[END_REF]. In these patients with CAD and DM, progression towards HF is a critical issue in daily practice and is associated with subsequent poor prognosis [START_REF] Lamblin | First hospitalization for heart failure in outpatients with stable coronary artery disease: determinants, role of incident myocardial infarction, and prognosis[END_REF][START_REF] Das | Effects of diabetes mellitus and ischemic heart disease on the progression from asymptomatic left ventricular dysfunction to symptomatic heart failure: a retrospective analysis from the Studies of Left Ventricular Dysfunction (SOLVD) Prevention trial[END_REF][START_REF] Cavender | Impact of diabetes mellitus on hospitalization for heart failure, cardiovascular events, and death: outcomes at 4 years from the reduction of atherothrombosis for continued health (REACH) Registry[END_REF].

HF in DM patients may be related to multiple causes and mechanisms: larger myocardial infarction (MI) size related to more diffuse CAD and prothrombotic state [START_REF] Lemesle | Antithrombotic therapy in diabetic patients with coronary artery disease[END_REF], deleterious left ventricular remodelling after MI [START_REF] Singh | Dapagliflozin versus placebo on left ventricular remodeling in patients with diabetes and heart failure: The REFORM Trial[END_REF], myocardial fibrosis leading to diastolic HF and not well-understood diabetic cardiomyopathy itself [START_REF] Mordi | Microvascular disease and heart failure with reduced and preserved ejection fraction in type 2 diabetes[END_REF][START_REF] Maack | Heart failure and diabetes: metabolic alterations and therapeutic interventions: a state-of-the-art review from the Translational Research Committee of the Heart Failure Association-European Society of Cardiology[END_REF]. Some of these mechanisms are likely to be preponderant at the acute phase of the disease when others are more implicated at the chronic phase; some are mainly associated with systolic left ventricular dysfunction and others with diastolic dysfunction. Previous studies have focused on each of these mechanisms individually [START_REF] Bauters | Influence of diabetes mellitus on heart failure risk and outcome[END_REF][START_REF] Das | Effects of diabetes mellitus and ischemic heart disease on the progression from asymptomatic left ventricular dysfunction to symptomatic heart failure: a retrospective analysis from the Studies of Left Ventricular Dysfunction (SOLVD) Prevention trial[END_REF][START_REF] Cavender | Impact of diabetes mellitus on hospitalization for heart failure, cardiovascular events, and death: outcomes at 4 years from the reduction of atherothrombosis for continued health (REACH) Registry[END_REF][START_REF] Parizo | Diabetes and heart failure post-acute myocardial infarction: Important associations and need for evidence-based interventions[END_REF][START_REF] Ritsinger | Heart failure is a common complication after acute myocardial infarction in patients with diabetes: A nationwide study in the SWEDEHEART registry[END_REF][START_REF] Takeji | Diabetes mellitus and long-term risk for heart failure after coronary revascularization[END_REF][START_REF] Van Melle | Diabetes, glycemic control, and new-onset heart failure in patients with stable coronary artery disease: data from the heart and soul study[END_REF]. However, no study to our knowledge has tried to analyse the risk of HF development at the different clinical stages of CAD, and to determine whether the risk of developing HF is similarly increased whatever the clinical presentation of CAD.

In the present analysis, using two contemporary large multicentre cohorts, the FAST-MI (French registry of acute ST-elevation or non-ST-elevation myocardial infarction) [START_REF] Puymirat | Acute myocardial infarction: changes in patient characteristics, management, and 6-month outcomes over a period of 20 years in the FAST-MI Program (French Registry of Acute ST-Elevation or Non-ST-Elevation Myocardial Infarction) 1995 to 2015[END_REF][START_REF] Cambou | The French registry of Acute ST elevation or non-ST-elevation Myocardial Infarction (FAST-MI): study design and baseline characteristics[END_REF][START_REF] Hanssen | French registry on acute st-elevation and non st-elevation myocardial infarction 2010. FAST-MI 2010[END_REF][START_REF] Belle | French registry on acute st-elevation and non-st-elevation myocardial infarction 2015 (FAST-MI 2015). Design and baseline data[END_REF] and the CORONOR (Suivi d'une cohorte de patients COROnariens stables en région NORd-pas-de-Calais) registries [START_REF] Bauters | Prognosis of patients with stable coronary artery disease (from the CORONOR study)[END_REF], we analysed the risk of HF occurrence according to DM status in CAD patients during the acute phase of MI, during the subacute phase (i.e. within the first year following MI), and during the chronic, stable, phase of the disease.

MATERIAL AND METHODS

Study populations

For the purpose of this study, two populations emanating from real-life registries were used: the FAST-MI and the CORONOR cohorts. The FAST-MI cohort was used to analyse the impact of DM on HF occurrence during the acute phase and within the first year after MI.

The CORONOR cohort was used to analyse the impact of DM on HF occurrence in outpatients with stable chronic CAD (at chronological distance from any acute coronary event).

FAST-MI cohort:

Three nationwide French registries were conducted five years apart from 2005 to 2015: FAST-MI 2005 (NCT00673036) [START_REF] Cambou | The French registry of Acute ST elevation or non-ST-elevation Myocardial Infarction (FAST-MI): study design and baseline characteristics[END_REF], FAST-MI 2010 (NCT01237418) [START_REF] Hanssen | French registry on acute st-elevation and non st-elevation myocardial infarction 2010. FAST-MI 2010[END_REF] and FAST-MI 2015 (NCT02566200) [START_REF] Belle | French registry on acute st-elevation and non-st-elevation myocardial infarction 2015 (FAST-MI 2015). Design and baseline data[END_REF]. Methods used for these registries have been previously published [START_REF] Puymirat | Acute myocardial infarction: changes in patient characteristics, management, and 6-month outcomes over a period of 20 years in the FAST-MI Program (French Registry of Acute ST-Elevation or Non-ST-Elevation Myocardial Infarction) 1995 to 2015[END_REF]. Briefly, their primary objectives were to evaluate the characteristics, management, and outcomes of MI patients, as seen in routine clinical practice, on a countrywide scale. All three registries consecutively included patients with MI admitted to a coronary or intensive care unit within 48 hours of symptom onset during a 1-month period. MI was defined by increased levels of cardiac biomarkers (troponins, creatine kinase or creatine kinase myocardial band) together with either compatible symptoms or electrocardiogram (ECG) changes. Patients who died soon after admission and for whom cardiac markers were not measured were included if they had signs or symptoms associated with typical STsegment changes. Exclusion criteria were: i) refusal to participate; ii) iatrogenic MI, defined as occurring within 48 hours of any therapeutic procedure; and iii) MI diagnosis invalidated in favour of another diagnosis. ST-elevation MI (STEMI) was diagnosed when ST-elevation ≥1 mm was seen in at least two contiguous leads in any location on the index or qualifying ECG, or when presumed new left bundle branch block or documented new Q waves were observed. In the absence of ST-segment elevation, patients meeting the inclusion criteria were considered to have non-ST-elevation MI (NSTEMI). In the FAST-MI 2005 survey, recruitment was prolonged for one additional month, exclusively for DM patients (explaining the over-representation of DM patients in 2005, compared with the two subsequent surveys).

In the FAST-MI 2010 and 2015 surveys, recruitment of all patients meeting the inclusion criteria could be prolonged for up to one additional month in voluntary centres.

For the purpose of this study, the three FAST-MI cohorts were pooled together (n=13,130 patients). As this study was dedicated to analyse new HF episodes in CAD patients, the analysis that focused on acute HF occurrence during the index MI hospitalisation was restricted to patients without history of HF before index MI (Study population 1: n=12,473) (Figure S1; see supplementary materials associated with this article on line). The analysis that focused on 1-year outcomes was restricted to patients who were discharged alive with no history of HF before index MI and no HF symptoms during the index MI hospitalisation (n=10,043); in addition, the population was further restricted to patients who had complete morbidity follow-up at one year (Study population 2: n=9,181; 91.4%) (Figure S1; see supplementary materials associated with this article on line).

CORONOR cohort:

As previously published [START_REF] Bauters | Prognosis of patients with stable coronary artery disease (from the CORONOR study)[END_REF], the CORONOR study was a multicentre registry that enrolled 4,184 consecutive outpatients with stable chronic CAD. Patients were enrolled by cardiologists from the French administrative district Nord-Pas-de-Calais during outpatient visits between February 2010 and April 2011 and were followed up to 5 years. Patients were eligible if they presented evidence of CAD defined by at least one of the following criteria: previous MI (>1 year ago), previous coronary revascularisation (>1 year ago), and/or obstruction of ≥50% of the luminal diameter of at least one native vessel on coronary angiography. The sole exclusion criterion was hospitalisation for MI or coronary revascularisation within the last year (exclusion of unstable patients).

As this study was dedicated to analyse the occurrence of a new hospitalisation for HF, we focused the present analysis on the 3,871 patients who had no history of hospitalisation for HF at inclusion. Among these patients, 5-year clinical follow-up data were available for 3,785 (98%) patients (Study population 3).

The CORONOR study was approved by the French medical data protection authority and authorised by the "Commission nationale de l'informatique et des libertés" for the treatment of personal health data. All patients consented to these studies after being informed in writing of their objectives, the use of their data, together with their right to object, rights of access, and mechanisms for redress. Both registries (FAST-MI and CORONOR) comply with the Declaration of Helsinki.

Definitions and Follow-up

Patients were defined as having DM when treated with oral hypoglycaemic drugs or insulin, or when they had a previous history of elevated (>126 mg/dL) fasting blood glucose on at least two separate occasions in conjunction with ongoing dietary measures in all cohorts.

HF occurrence during the index MI hospitalisation in the FAST-MI cohort was defined as all patients presenting with Killip-Kimball class ≥II at initial presentation or at any time during the hospital stay. HF after discharge was defined as any hospitalisation for HF during follow-up, which was systematically collected in both cohorts. After discharge in the FAST-MI cohort and in the CORONOR registry, hospitalisation for HF was defined as hospitalisation for symptoms of dyspnoea or oedema associated with bilateral rales, elevated venous pressure, or interstitial or alveolar oedema on chest X-ray, or the addition of intravenous diuretics or inotropic medications. Patients who were hospitalised for MI and who had symptoms of HF at admission or during hospitalisation were not adjudicated as hospitalisation for HF because the primary diagnosis was considered to be hospitalisation for MI.

For the FAST-MI cohort, 1-year follow-up was performed by dedicated research technicians who contacted both physicians and patients, after checking the vital status of patients in municipal registers. For all surveys, follow-up was centralised at the French Society of Cardiology, and reported clinical events were adjudicated by a 3-person committee (Nicolas Danchin, MD, Pascal Guéret, MD, Tabassome Simon, MD). One-year clinical follow-up data were available for >99% patients for mortality and for 91.4% of patients for morbid events (i.e. hospitalisation for HF).

For the CORONOR cohort, a 5-year follow-up was performed at outpatient visits with treating cardiologists using a standardised case record form to report clinical events. Five-year clinical follow-up data were available for 3,785 (98%) patients. Missing information was completed by contacting either general practitioners and/or patients themselves. All clinical events were centrally adjudicated, according to pre-specified definitions, by two investigators blinded to each other. A third investigator joined the adjudication in case of disagreement. For hospitalisations during the follow-up period, hospital records were reviewed for evidence of clinical events. The events reported by the patients were systematically confirmed from the medical reports.

For the present analysis, the primary endpoint was the occurrence of HF as defined above. In order to avoid biases in event reporting (especially missing HF events that led to early death), we also analysed the all-cause death or HF composite as a secondary endpoint.

Statistical analysis

Continuous variables were described as the mean ± standard deviation (SD) or as median with interquartile range (IQR) as appropriate. Categorical variables were presented as absolute numbers and percentages. Characteristics between the two groups (DM vs. not) were compared with the χ 2 or the Fisher test for categorical variables and with the Student t test for continuous variables as appropriate.

Rates of Killip-Kimball class ≥II and the all-cause death or HF composite during the index MI hospitalisation were compared using logistic regression. Unadjusted and adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for HF and the allcause death or HF composite.

Incidences of hospitalisation for HF and of the all-cause death or HF composite (after discharge for the FAST-MI cohort and in the CORONOR cohort) were estimated using the Kaplan-Meier method and compared using the log-rank test. Unadjusted and adjusted hazard ratios (HRs) and 95% CIs were calculated using Cox analyses for HF and the all-cause death or HF composite .

RESULTS

Study populations

Study population 1: The baseline characteristics of the FAST-MI cohort at admission are shown in Table S1 (see supplementary materials associated with this article on line). The proportion of patients with DM was 24.2%. Patients with DM were older than those without, 69.5 vs. 64.2 years, and there were more women among DM patients, 31.7% vs. 27.2% (P<0.001). DM patients presented less often with STEMI, 42.3% vs. 57.2%, and showed lower LVEF, 50.7% vs. 52.5% (P<0.001). Among the patients with DM, 26.7% received insulin therapy and the mean HbA1c was 7.51±1.54%.

Study population 2:

The baseline characteristics of the FAST-MI cohort at discharge are detailed in Table S2 (see supplementary materials associated with this article on line). The proportion of patients with DM was 22.1%. Patients with DM were older than those without 67.5 vs. 63.1 years and there were more women among DM patients, 27.4% vs. 25.4% (P<0.001). DM patients presented less often with STEMI, 43.4% vs. 57.8%, and showed lower LVEF, 53.4% vs. 54% (P<0.001). Patients with DM had less often percutaneous coronary intervention (PCI) during hospital stay, 74.8% vs. 80.3%, and more often coronary bypass surgery (CABG), 4.3% vs. 2.6% (P<0.001). There was a wide prescription of dual antiplatelet therapy, statins, ACEI/ARBs, and betablockers. At discharge, diuretics were used in 28% of the patients with DM and 14% of those without (P<0.001). Among patients with DM, 31.4% received insulin therapy at discharge and the mean HbA1c was 7.52±1.58%.

Study population 3: The baseline characteristics of the CORONOR population are shown in Table S3 (see supplementary materials associated with this article on line). The median time between CAD diagnosis and inclusion into the registry was 6 years (IQR 3 to 10). The proportion of patients with DM was 29.9%. There was no difference in age at inclusion between patients with and without DM, 66.9 vs. 66.4 years. The number of women was numerically higher in DM patients, 23.5% vs. 20.8% (P=0.058). A history of MI was documented in 58% of the DM patients vs. 64.1% in patients without DM (P<0.001). Most patients (86.4%) had at least one prior coronary revascularisation procedure prior to inclusion.

The mean LVEF was slightly but significantly lower in DM patients 58% vs. 59% (P=0.0003). There was a wide prescription of antiplatelet therapy, statins, ACEI/ARBs, and betablockers. Diuretics were used in 38.3% of the patients with DM vs. 22.6% of those without at inclusion (P<0.001). Among the patients with DM, 23.9% received insulin therapy at inclusion and the mean HbA1c was 7.25 ± 1.31%.

DM and HF at the acute stage of MI (FAST-MI cohort, Study population 1)

Killip-Kimball class ≥II during the index hospitalisation for MI was present in 29% (n=876 events) of DM patients compared with 15.3% (n=1443 events) of non-DM patients (adjusted OR 1.60; 95% CI 1.43-1.79; P<0.001) (Figure 1 and Table I). Results were highly consistent in STEMI and NSTEMI patients (P for interaction = 0.138) and in the three FAST-MI cohorts: FAST-MI 2005, FAST-MI 2010 and FAST-MI 2015 (P for interaction = 0.150).

The all-cause death or HF composite during the index hospitalisation for MI was present in 30.4% of DM patients compared with 16% of non-DM patients (adjusted OR 1.64; 95% CI 1.47-1.83; P<0.001) (Figure 1 and Table II). Results were highly consistent in STEMI and NSTEMI patients (P for interaction = 0.134) and in the three FAST-MI cohorts: FAST-MI 2005, FAST-MI 2010 and FAST-MI 2015 (P for interaction = 0.198).

DM and 1-year HF occurrence after MI (FAST-MI cohort, Study population 2)

At 1 year, among the 9,181 patients discharged alive in the FAST-MI cohort, hospitalisation for HF occurred in 3.3% (n=66 events) of the patients with DM compared with 1.2% (n=84 events) of those without DM (adjusted HR 1.73; 95% CI 1.21-2.48, P=0.003) (Figure 2A and Table I). Results were highly consistent in STEMI and NSTEMI patients (P for interaction = 0.132) and in the three FAST-MI cohorts: FAST-MI 2005, FAST-MI 2010 and FAST-MI 2015 (P for interaction = 0.273).

The risk of the all-cause death and hospitalisation for HF composite occurred in 9.6% of the patients with DM compared with 4% of those without DM (adjusted HR 1.71; 95% CI 1.41-2.08, P<0.001) (Figure 2B and Table II). Results were highly consistent in STEMI and NSTEMI patients (P for interaction = 0.371) and in the three FAST-MI cohorts: FAST-MI 2005, FAST-MI 2010 and FAST-MI 2015 (P for interaction = 0.401).

DM and Incidence HF in patients with stable chronic CAD (CORONOR cohort, Study population 3)

Among the 3,785 patients included in the CORONOR registry without history of HF at inclusion, hospitalisation for HF occurred in 8.5% (n=96 events) of the patients with DM compared with 4.3% (n=115 events) of those without at 5 years (adjusted HR 1.70; 95% CI 1.25-2.29; P=0.001) (Figure 3A and Table I). Results were highly consistent in patients with history of MI and in those without (P for interaction = 0.546).

The risk of the all-cause death and hospitalisation for HF composite occurred in 22.1% of the patients with DM compared with 15% of those without DM (adjusted HR 1.53; 95% CI 1.28-1.82; P<0.001) (Figure 3B and Table II). Results were highly consistent in patients with history of MI and in those without (P for interaction = 0.386).

DISCUSSION

It is well established that occurrence of HF is associated with increased mortality over time, and this does also pertain to CAD patients [START_REF] Lamblin | First hospitalization for heart failure in outpatients with stable coronary artery disease: determinants, role of incident myocardial infarction, and prognosis[END_REF][START_REF] Parma | Incident heart failure in outpatients with chronic coronary syndrome: results from the international prospective CLARIFY registry[END_REF][START_REF] Ponikowski | ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC)Developed with the special contribution of the Heart Failure Association (HFA) of the ESC[END_REF][START_REF] Yancy | ACC/AHA/HFSA focused update of the 2013 ACCF/AHA guideline for the management of heart failure: a report of the American college of cardiology/American heart association task force on clinical practice guidelines and the heart failure society of America[END_REF][START_REF] Bahit | Post-Myocardial Infarction Heart Failure[END_REF]. In addition, is has been recently suggested that, even in CAD patients, HF has become the most common cause of cardiovascular death (i.e. before recurrent MI, stroke, or other atherosclerosis-related causes of death), because of improved management of atherosclerosis [START_REF] Bauters | Prognosis of patients with stable coronary artery disease (from the CORONOR study)[END_REF]. It is therefore critical to identify which CAD patients are at higher risk of HF and to better understand the pathogenesis of HF occurrence in these patients.

The present study from two large multicentre French cohorts [START_REF] Bauters | Prognosis of patients with stable coronary artery disease (from the CORONOR study)[END_REF][START_REF] Puymirat | Acute myocardial infarction: changes in patient characteristics, management, and 6-month outcomes over a period of 20 years in the FAST-MI Program (French Registry of Acute ST-Elevation or Non-ST-Elevation Myocardial Infarction) 1995 to 2015[END_REF][START_REF] Cambou | The French registry of Acute ST elevation or non-ST-elevation Myocardial Infarction (FAST-MI): study design and baseline characteristics[END_REF][START_REF] Hanssen | French registry on acute st-elevation and non st-elevation myocardial infarction 2010. FAST-MI 2010[END_REF][START_REF] Belle | French registry on acute st-elevation and non-st-elevation myocardial infarction 2015 (FAST-MI 2015). Design and baseline data[END_REF] confirms previous findings [START_REF] Bauters | Influence of diabetes mellitus on heart failure risk and outcome[END_REF][START_REF] Das | Effects of diabetes mellitus and ischemic heart disease on the progression from asymptomatic left ventricular dysfunction to symptomatic heart failure: a retrospective analysis from the Studies of Left Ventricular Dysfunction (SOLVD) Prevention trial[END_REF][START_REF] Cavender | Impact of diabetes mellitus on hospitalization for heart failure, cardiovascular events, and death: outcomes at 4 years from the reduction of atherothrombosis for continued health (REACH) Registry[END_REF][START_REF] Parizo | Diabetes and heart failure post-acute myocardial infarction: Important associations and need for evidence-based interventions[END_REF][START_REF] Ritsinger | Heart failure is a common complication after acute myocardial infarction in patients with diabetes: A nationwide study in the SWEDEHEART registry[END_REF][START_REF] Takeji | Diabetes mellitus and long-term risk for heart failure after coronary revascularization[END_REF][START_REF] Van Melle | Diabetes, glycemic control, and new-onset heart failure in patients with stable coronary artery disease: data from the heart and soul study[END_REF] and shows that, whatever the stage of CAD (acute phase of MI, early months following MI, or stable chronic phase), patients with DM have a constant 70% increased risk of developing HF compared with non-DM patients. In other words, no period showed a higher relative risk of HF occurrence as compared to another, although the absolute risk was higher at the acute stage. This risk was even higher in patients treated with insulin: a fact that may be more related to a longer duration of diabetes exposure, which is commonly observed in these patients, although a direct harmful effect of insulin by itself could not completely be excluded with our design. Therefore, it appears that the prevention of HF occurrence in CAD patients with DM is, first, critical in daily practice, and second, should be a constant life-long endeavour.

Although previous studies have shown an increased risk of developing HF in CAD patients with DM [START_REF] Bauters | Influence of diabetes mellitus on heart failure risk and outcome[END_REF][START_REF] Das | Effects of diabetes mellitus and ischemic heart disease on the progression from asymptomatic left ventricular dysfunction to symptomatic heart failure: a retrospective analysis from the Studies of Left Ventricular Dysfunction (SOLVD) Prevention trial[END_REF][START_REF] Cavender | Impact of diabetes mellitus on hospitalization for heart failure, cardiovascular events, and death: outcomes at 4 years from the reduction of atherothrombosis for continued health (REACH) Registry[END_REF][START_REF] Parizo | Diabetes and heart failure post-acute myocardial infarction: Important associations and need for evidence-based interventions[END_REF][START_REF] Ritsinger | Heart failure is a common complication after acute myocardial infarction in patients with diabetes: A nationwide study in the SWEDEHEART registry[END_REF][START_REF] Takeji | Diabetes mellitus and long-term risk for heart failure after coronary revascularization[END_REF][START_REF] Van Melle | Diabetes, glycemic control, and new-onset heart failure in patients with stable coronary artery disease: data from the heart and soul study[END_REF], to our knowledge, our study is the first to assess the temporality of HF occurrence, in order to apprehend the relative impact of DM on the different mechanisms of HF in CAD patients. This aspect may be of major interest when it comes to initiating or adapting treatments in these patients. Therefore, it may be relevant to identify whether DM impacts more one mechanism of HF over another in CAD patients. In previous studies, DM has been associated with a higher rate of HF at the acute phase of MI.

Larger MI size related to more diffuse CAD at diagnosis, atypical chest pain or absence of pain leading to delayed management, and a specific prothrombotic state in DM patients may all increase the risk of HF occurrence in these circumstances [START_REF] Lemesle | Antithrombotic therapy in diabetic patients with coronary artery disease[END_REF]. In this context, early coronary revascularisation and intensive antithrombotic therapies using new P2Y12-receptor inhibitors have shown clinical benefit, in DM as in non-DM patients. Following MI, DM is also associated with a higher risk of improper left ventricular remodelling, which may also increase the risk of subsequent hospitalisation for HF [START_REF] Singh | Dapagliflozin versus placebo on left ventricular remodeling in patients with diabetes and heart failure: The REFORM Trial[END_REF]. Early initiation of specific HF treatments (betablockers, ACEi/ARB, mineralocorticoid receptor antagonists …) is likely to be of major importance particularly in this sub-population. These improvements in patient care, however, seem not to erase the excess risk of HF in patients with DM. As an example, DM was still associated with a 38% excess risk of cardiovascular death or hospitalisation for HF in the recent PARADIGM-HF trial [START_REF] Kristensen | Risk related to pre-diabetes mellitus and diabetes mellitus in heart failure with reduced ejection fraction: insights from prospective comparison of ARNI with ACEI to determine impact on global mortality and morbidity in heart failure trial[END_REF]. Finally, myocardial fibrosis and left ventricle rigidity have also been associated with diastolic HF [START_REF] Mordi | Microvascular disease and heart failure with reduced and preserved ejection fraction in type 2 diabetes[END_REF][START_REF] Maack | Heart failure and diabetes: metabolic alterations and therapeutic interventions: a state-of-the-art review from the Translational Research Committee of the Heart Failure Association-European Society of Cardiology[END_REF]. Whatever the underlying mechanisms leading to clinical HF, our results show that DM impacts HF occurrence to the same extent at all time points of the disease. Thus, prevention of HF in DM patients is of particular importance as it is a common complication of CAD at all stages, and carries a much poorer prognosis. Anti-diabetic medications may have different impacts on HF occurrence. Glitazones have shown to increase the risk of HF [START_REF] Gilbert | Heart failure in diabetes: effects of anti-hyperglycaemic drug therapy[END_REF]. The role of other anti-diabetic drugs such as metformin, insulin, DPP-4 inhibitors or glucagonlike peptide-1 (GLP-1) agonist, is unclear [START_REF] Cattadori | Glucose-lowering drugs and heart failure: implications of recent cardiovascular outcome trials in type 2 diabetes[END_REF], while sodium glucose co-transporter type 2 (SGLT-2) inhibitors prevent HF in DM as in non-DM patients [START_REF] Mcmurray | Dapagliflozin in patients with heart failure and reduced ejection fraction[END_REF][START_REF] Neal | Canagliflozin and cardiovascular and renal events in type 2 diabetes[END_REF][START_REF] Zinman | Empagliflozin, cardiovascular outcomes, and mortality in type 2 diabetes[END_REF].

The mechanism of action of SGLT-2 inhibitors remains however uncertain. SGLT-2 inhibitors might have a greater preventative impact during the chronic phase of CAD, rather than in acute situations. Recently, Singh et al. showed that dapagliflozin has no significant impact on left ventricular remodelling early after MI [START_REF] Singh | Dapagliflozin versus placebo on left ventricular remodeling in patients with diabetes and heart failure: The REFORM Trial[END_REF]. Of note, a clinical trial investigating initiation of empagliflozin immediately after MI with reduced LVEF is currently recruiting patients (the EMPACT-MI study NCT04509674) in order to assess this specific point. In addition, aside from considerations in HF prevention, GLP-1 agonists have shown to reduce atherosclerotic events in DM patients, which is also a critical point in CAD patients with DM. Thus, a combination of GLP-1 agonists and SGLT-2 inhibitors in CAD patients with DM may be a highly relevant combination in the near future.

Strengths and limitations

In order to assess the real impact of DM on HF development over time in CAD patients, we excluded at each time point of the study all patients with a history of previous HF. Our goal was indeed to assess the independent role of DM on new-onset HF. Some limitations have to be acknowledged. First, the lack of LVEF assessment at the time of HF occurrence limits the interpretation of the mechanism (systolic vs. diastolic) of left ventricular dysfunction. Second, our results emanate from two different multicentre French cohorts of patients and not from a single cohort. This, however, provided a unique opportunity to concomitantly analyse the entire spectrum of HF during the time course of CAD, including chronic stable CAD, which to the best of our knowledge, had not been done in the past.

CONCLUSIONS

In CAD patients, DM is associated with a remarkably constant 70% increase in the risk of developing HF, whatever the stage of the disease, from acute situations such as acute MI, to the post-MI subacute period, and up to the chronic phase of the disease. Avoiding HF occurrence should therefore be a permanent objective in everyday management of CAD patients with DM, with the optimal use of conventional therapy as well as new medications for HF prevention.

  ACEi/ARB: angiotensin-converting enzyme inhibitors and angiotensin receptor blockers CABG: coronary artery bypass grafting CAD: coronary artery disease CI: confidence interval DM: diabetes mellitus HF: heart failure HR: hazard ratio IQR: interquartile range LVEF: left ventricle ejection fraction MI: myocardial infarction NSTEMI: non-ST-elevation myocardial infarction OR: odds ratio STEMI: ST-elevation myocardial infarction

  The protocol of FAST-MI 2005 was reviewed by the Committee for the Protection of Human Subjects (CPP) in Biomedical Research of Saint Antoine University. The protocols of and FAST-MI 2010 and FAST-MI 2015 were reviewed and approved by the CPP of Saint Louis University Hospital Paris Ile-de-France IV. Data file collection and storage were approved by the "Commission Nationale Informatique et Liberte ́". All patients were informed of the nature and aims of the surveys and could request to be excluded; in addition, written consent was obtained for the 2005, 2010, and 2015 surveys.

  The different models were as follow: i) Adjustment for year of inclusion, age, sex, history of hypertension, current smoking, body mass index, type of MI (STEMI vs. NSTEMI), history of MI, history of percutaneous coronary intervention (PCI), history of coronary artery bypass grafting (CABG), history of peripheral artery disease (PAD), history of atrial fibrillation, history of stroke, estimated glomerular filtration rate (eGFR), left ventricle ejection fraction (LVEF), history of chronic obstructive pulmonary disease (COPD), history of cancer, treatment at admission (antiplatelet therapy, statins, betablockers, angiotensin-converting enzyme inhibitors and angiotensin receptor blockers (ACEI/ARB) and diuretics) for the risk of events during the index hospitalisation for MI (FAST-MI cohort, Study population 1); ii) Adjustment for year of inclusion, age, sex, history of hypertension, current smoking, body mass index, type of MI (STEMI vs. NSTEMI), history of MI, history of PCI, history of CABG, history of PAD, history of atrial fibrillation, history of stroke, eGFR, LVEF, history of COPD, history of cancer, PCI during the index MI hospitalisation, CABG during the index MI hospitalisation, treatment at discharge (dual antiplatelet therapy, statins, betablockers, ACEI/ARB and diuretics) for the risk of events within the first year after MI (FAST-MI cohort, Study population 2); iii) Adjustment for age, sex, history of hypertension, current smoking, history of MI, history of PCI, history of CABG, history of atrial fibrillation, history of stroke, history of PAD, LVEF, eGFR, treatment at inclusion (betablockers, ACEI/ARB and diuretics) for the risk of events during the chronic CAD phase (CORONOR cohort, Study population 3).All statistical analyses were performed using STATA 14.1 software (STATA Corporation, College Station, Texas, USA) and IBM-SPSS V25.0. Statistical significance was assumed at a P value <0.05.

Figure 1 .Figure 2 .Figure 3 .

 123 Figure 1. Risk of events in Study population 1 (during the index MI hospitalisation).

Table I .

 I Association between DM and the risk of HF occurrence in CAD patients.Relative risks (OR and HR) are presented as DM vs. non-DM patients. Adjusted for year of inclusion, age, sex, history of hypertension, current smoking, body mass index, type of MI (STEMI vs. NSTEMI), history of MI, history of PCI, history of CABG, history of PAD, history of atrial fibrillation, history of stroke, eGFR, LVEF, history of COPD, history of cancer, treatment at admission (antiplatelet therapy, statins, betablockers, ACEI/ARB and diuretics). Adjusted for year of inclusion, age, sex, history of hypertension, current smoking, body mass index, type of MI (STEMI vs. NSTEMI), history of MI, history of PCI, history of CABG, history of PAD, history of atrial fibrillation, history of stroke, eGFR, LVEF, history of COPD, history of cancer, PCI during the index MI hospitalization, CABG during the index MI hospitalization, treatment at discharge (dual antiplatelet therapy, statins, betablockers, ACEI/ARB and diuretics).

	Patients with diabetes	1.70 [1.25-2.29]	0.001
	Patients with diabetes without insulin therapy	1.52 [1.09-2.13]	0.014
	Patients with diabetes under insulin therapy	2.22 [1.43-3.44]	< 0.001
	Risk HF during the index MI OR = odds ratio; = hazard ratio; CI = confidence interval; HF = heart failure; MI = OR [95%CI] P value
	hospitalization myocardial infraction; CAD = coronary artery disease
	The FAST-MI cohort
	Unadjusted
	Patients without diabetes	Reference	-
	Patients with diabetes	2.26 [2.05-2.49]	< 0.001
	Patients with diabetes without insulin therapy	1.91 [1.71-2.14]	< 0.001
	Patients with diabetes under insulin therapy	3.37 [2.90-3.92]	< 0.001
	Adjusted a
	Patients without diabetes	Reference	-
	Patients with diabetes	1.60 [1.43-1.79]	< 0.001
	Patients with diabetes without insulin therapy	1.46 [1.29-1.65]	< 0.001
	Patients with diabetes under insulin therapy	2.05 [1.72-2.45]	< 0.001
	Risk of hospitalization for HF within the	HR [95%CI]	P value
	first year after MI
	The FAST-MI cohort
	Unadjusted
	Patients without diabetes	Reference	-
	Patients with diabetes	2.83 [2.05-3.92]	< 0.001
	Patients with diabetes without insulin therapy	1.68 [1.09-2.60]	0.019
	Patients with diabetes under insulin therapy	5.52 [3.76-8.10]	< 0.001
	Adjusted b
	Patients without diabetes	Reference	-
	Patients with diabetes	1.73 [1.21-2.48]	0.023
	Patients with diabetes without insulin therapy	1.14 [0.73 -1.77]	0.571
	Patients with diabetes under insulin therapy	2.56 [1.69-3.88]	< 0.001
	Risk of hospitalization for HF in stable CAD	HR [95%CI]	P value
	outpatients
	The CORONOR cohort
	Unadjusted
	Patients without diabetes	Reference	-
	Patients with diabetes	2.04 [1.56-2.68]	< 0.001
	Patients with diabetes without insulin therapy	1.78 [1.32-2.42]	< 0.001
	Patients with diabetes under insulin therapy	2.95 [1.98-4.38]	< 0.001
	Adjusted c
	Patients without diabetes	Reference	-

a b c Adjusted for age, sex, history of hypertension, current smoking, history of MI, history of PCI, history of CABG, history of atrial fibrillation, history of stroke, history of PAD, LVEF, eGFR, treatment at inclusion (betablockers, ACEI/ARB and diuretics).

Table II .

 II Association between DM and the risk of the composite of all-cause death or HF in CAD patients.Relative risks (OR and HR) are presented as DM vs. non-DM patients. year of inclusion, type of MI (STEMI vs. NSTEMI), age, sex, history of hypertension, current smoking, history of MI, history of PCI, history of CABG, history of atrial fibrillation, history of stroke, history of PAD, eGFR, previous use of betablockers, ACEI/ARB and diuretics. Adjusted for year of inclusion, type of MI (STEMI vs. NSTEMI), age, sex, history of hypertension, current smoking, history of MI, history of PCI, history of CABG, history of atrial fibrillation, history of stroke, history of PAD, LVEF, eGFR, previous use of betablockers, ACEI/ARB and diuretics, PCI during the index MI hospitalization, CABG during the index MI hospitalization. Adjusted for age, sex, history of hypertension, current smoking, history of MI, history of PCI, history of CABG, history of atrial fibrillation, history of stroke, history of PAD, LVEF, eGFR, previous use of betablockers, ACEI/ARB and diuretics.

	Adjusted c
	Patients without diabetes	Reference	-
	Patients with diabetes	1.53 [1.28-1.82]	< 0.001
	Patients with diabetes without insulin therapy	1.39 [1.14-1.69]	0.001
	Patients with diabetes under insulin therapy	1.97 [1.51-2.58]	< 0.001
	Risk of the composite death or HF during HF = heart failure; MI = myocardial infraction; CAD = coronary artery disease OR [95%CI] P value
	the index MI hospitalization
	The FAST-MI cohort
	Unadjusted
	Patients without diabetes	Reference	-
	Patients with diabetes	2.29 [2.09-2.52]	< 0.001
	Patients with diabetes without insulin therapy	1.94 [1.74-2.17]	< 0.001
	Patients with diabetes under insulin therapy	3.41 [2.93-3.96]	< 0.001
	Adjusted a
	Patients without diabetes	Reference	-
	Patients with diabetes	1.64 [1.47-1.83]	< 0.001
	Patients with diabetes without insulin therapy	1.51 [1.33-1.70]	< 0.001
	Patients with diabetes under insulin therapy	2.07 [1.73-2.47]	< 0.001
	Risk of the composite death or HF within	HR [95%CI]	P value
	the first year after MI
	The FAST-MI cohort
	Unadjusted
	Patients without diabetes	Reference	-
	Patients with diabetes	2.45 [2.04-2.93]	< 0.001
	Patients with diabetes without insulin therapy	1.76 [1.40-2.21]	< 0.001
	Patients with diabetes under insulin therapy	4.02 [3.20-5.07]	< 0.001
	Adjusted b
	Patients without diabetes	Reference	-
	Patients with diabetes	1.71 [1.41-2.08]	< 0.001
	Patients with diabetes without insulin therapy	1.39 [1.09-1.76]	0.007
	Patients with diabetes under insulin therapy	2.30 [1.79-2.96]	< 0.001
	Risk of the composite death or HF in stable	HR [95%CI]	P value
	CAD outpatients
	The CORONOR cohort
	Unadjusted
	Patients without diabetes	Reference	-
	Patients with diabetes	1.54 [1.31-1.80]	< 0.001
	Patients with diabetes without insulin therapy	1.38 [1.15-1.64]	< 0.001
	Patients with diabetes under insulin therapy	2.09 [1.64-2.67]	< 0.001

a b c

ACKNOWLEDGMENTS

None

FUNDING STATEMENTS

The French Society of Cardiology received grants for supporting the FAST-MI program from Amgen, AstraZeneca, Bayer, BMS, Boehringer-Ingelheim, Daiichi Sankyo, Eli Lilly, MSD, Pfizer, and Sanofi. None of the companies had a role in the design and conduct of the study, data collection and management. They were not involved in the analysis and interpretation of the data, nor in the preparation, review, or approval of the manuscript. The CORONOR study was supported by the Fédération Française de Cardiologie (Paris, France).

AUTHOR CONTRIBUTION

All authors have actively contributed to the manuscript as followed:

1) conception and design or analysis and interpretation of data, or both: GL, CB and ND 2) drafting of the manuscript or revising it critically for important intellectual content: EP, LB, TS, PGS, JF, FS, LF, PH, GS, SN, and NL 3) final approval of the manuscript submitted: GL, CB and ND.

CONFLICT OF INTEREST

None of the authors has any relationship with industry and financial associations that might pose a conflict of interest in direct connection with the submitted article.

Appendix supplementary material

Supplementary materials (Fig. S1 and Tables S1-S2-S3) associated with this article can be found at http://www.scincedirect.com at doi . . .


Augustin Schaefer

Martin Journaux

Haquima El Mourabit

Sarah Mouri

Dominique Wendum

Elisabeth Lasnier

Pierre-Olivier Couraud

Chantal Housset

Dominique Thabut

Marika Rudler

Augustin Schaeffer

Dr Nicolas Weiss
email: nicolas.weiss@aphp.fr

A systemic mechanism of increased transendothelial migration of leukocytes through the blood-brain barrier in hepatic encephalopathy

Keywords: transendothelial migration, leukocytes, cirrhosis, hepatic encephalopathy, systemic inflammation junctional adhesion molecules

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Hepatic encephalopathy (HE) is defined as the neurological or neuropsychological symptoms caused by liver failure, a chronic liver disease and/or a portosystemic shunt [START_REF] Vilstrup | Hepatic encephalopathy in chronic liver disease: 2014 Practice Guideline by the American Association for the Study of Liver Diseases and the European Association for the Study of the Liver[END_REF]. HE could be present at least in one half of cirrhotic patients in its overt form and in more than two third of patients when minimal HE is included. HE constitutes an independent risk factor of death. HE impairs the quality of life and it is associated with substantial costs related to hospitalization [START_REF] Bajaj | Minimal Hepatic Encephalopathy and Mild Cognitive Impairment Worsen Quality of Life in Elderly Patients With Cirrhosis[END_REF]. HE represents also a major burden for families/caregivers and health care systems [START_REF] Elsaid | The Health Care Burden of Hepatic Encephalopathy[END_REF]. Hepatic encephalopathy's pathophysiology is still debated. The synergic effect of hyperammonemia and systemic inflammation is now well admitted [START_REF] Shawcross | Systemic inflammatory response exacerbates the neuropsychological effects of induced hyperammonemia in cirrhosis[END_REF][START_REF] Shawcross | Role of ammonia and inflammation in minimal hepatic encephalopathy[END_REF]. Modifications of the gut microbiota have also been implicated and could explain both hyperammonemia and systemic inflammation [START_REF] Ahluwalia | Impaired Gut-Liver-Brain Axis in Patients with Cirrhosis[END_REF]. Recently, we showed that the blood-brain barrier (BBB) permeability to solutes and xenobiotics was increased in cirrhotic patients with HE [START_REF] Weiss | Modification in CSF specific gravity in acutely decompensated cirrhosis and acute on chronic liver failure independent of encephalopathy, evidences for an early blood-CSF barrier dysfunction in cirrhosis[END_REF].

The BBB is a unique organization of cerebral microvessels in which endothelial cells (EC) expressing tight junction proteins (claudin-5, occludin and junctional adhesion molecules (JAMs)) lay on a basal lamina made of type-IV collagen [START_REF] Weiss | The blood-brain barrier in brain homeostasis and neurological diseases[END_REF][START_REF] Wolburg | Tight junctions of the blood-brain barrier: Development, composition and regulation[END_REF]. Pericytes embedded in the basal lamina could be largely implicated in the cerebral vasoregulation [START_REF] Daneman | Pericytes are required for blood-brain barrier integrity during embryogenesis[END_REF]. Astrocytic endfeet cover the entire microvessels providing what is called the glial limitans. This special organization confers a particularly low permeability to solutes and circulating cells explaining that specific transport systems (receptors and transporters) are needed to fuel the brain with nutrients and allow exclusion of its waste products. EC are sensitive to inflammatory stimuli. They express Toll-Like receptor 4 (TLR-4) and receptors of cytokines including TNF-alpha and IL-1beta (CD120a and IL-1R respectively), that are elevated in the circulation of cirrhotic patients with HE (4). In patients with other neurological disorders such as multiple sclerosis [START_REF] Larochelle | How do immune cells overcome the bloodbrain barrier in multiple sclerosis?[END_REF], stroke [START_REF] Jin | Inflammatory mechanisms in ischemic stroke: role of inflammatory cells[END_REF], or Parkinson disease [START_REF] Brochard | Infiltration of CD4+ lymphocytes into the brain contributes to neurodegeneration in a mouse model of Parkinson disease[END_REF], systemic inflammation is associated with an increased transendothelial migration (TEM) of leukocytes through the BBB [START_REF] Weiss | The blood-brain barrier in brain homeostasis and neurological diseases[END_REF][START_REF] Jin | Inflammatory mechanisms in ischemic stroke: role of inflammatory cells[END_REF][START_REF] Brochard | Infiltration of CD4+ lymphocytes into the brain contributes to neurodegeneration in a mouse model of Parkinson disease[END_REF]. Within the brain, leukocytes cause an increase in the amount of matrix metalloproteinase -2 and -9 (MMP-2 and MMP-9) that will alter cerebral microvessels' basal lamina and thus BBB permeability.

We hypothesized that leukocytes TEM through the BBB is possible in HE cirrhotic patients due to the systemic inflammation and that this could exacerbate altered BBB permeability. We took advantage of the unique human hCMEC/D3 cell line that resumes human BBB characteristics [START_REF] Weksler | Blood-brain barrier-specific properties of a human adult brain endothelial cell line[END_REF], to test this hypothesis in vitro.

Materiel and methods

Patients

This study was approved by local ethic's committee of La Pitié-Salpêtrière Hospital. All participants were recruited in the Intensive Care Unit of Hepatology in La Pitié-Salpêtrière University Hospital, Paris, France and they all gave written informed consent. Inclusion criteria were: 1) cirrhosis, defined by clinical biological and/or morphological parameters and 2) age between 18 and 70 years. Exclusion criteria were: 1) a past history of neurological disease; 2) current evolutive neurological disease; 3) hepatocellular carcinoma; 4) expected survival of less that 3 months; 5) refusal to participate. HE was evaluated with the West Haven score [START_REF] Atterbury | Neomycin-sorbitol and lactulose in the treatment of acute portal-systemic encephalopathy. A controlled, double-blind clinical trial[END_REF]. A score ≥2 defined overt HE. The cohort of cirrhotic patients was divided into 2 groups, i.e., with or without overt HE. A control group included subjects without any history of liver or neurological disease, who also gave their written informed consent.

Blood samples

Blood samples were collected on EDTA tube and placed on ice. Then, 2 centrifugations were performed (10 min, 800 g, 4°C) to obtain plasma that was immediately stored at -80°C. Biological analyses were performed using routine biochemical methods.

Human cerebral endothelial cells

We used the hCMEC/D3, a stable model of human EC and a largely validated in vitro BBB model [START_REF] Weksler | Blood-brain barrier-specific properties of a human adult brain endothelial cell line[END_REF].

EC were cultured in Petri dish coated with collagen I (Rat Tail Collagen I, RDS, France), and were seeded each 3 days, as previously described [START_REF] Weksler | Blood-brain barrier-specific properties of a human adult brain endothelial cell line[END_REF][START_REF] Rampon | Molecular mechanism of systemic delivery of neural precursor cells to the brain: assembly of brain endothelial apical cups and control of transmigration by CD44[END_REF].

Monocytic cell line U937

We used the U937 monocytic cell line, that resumes leukocytes property to cross the BBB by TEM [START_REF] Sundström | Establishment and characterization of a human histiocytic lymphoma cell line (U-937)[END_REF]. For all experiences of TEM, U937 monocytes were used and labeled with the tracer Deep-Red Dye (Molecular Probes, C34565, OR, USA). Monocytes were labeled on the day of TEM experience.

Transendothelial leukocytes migration experiments

hCMEC/D3 cells were cultured as a monolayer on 8µm porous Transwell inserts (Corning) previously coated with collagen IV. At Day 6, i.e., when hCMEC/D3 are confluent, monocytes (U937 cell-line) were added to the upper chamber in SVF-free RPMI 1640 medium (Molecular Probes) containing 1% of plasma from patients or healthy controls (Fig 1A ) and were incubated at 37° for 16h. In each experiment, 25 ng/mL of the CCL-2 chemokine was added to the lower chamber to create a chemotactic gradient. The confluence of hCMEC/D3 cells was controlled by the immunofluorescence of PECAM-1 (CD31) (Fig 1B). Patient's plasma samples were diluted (endoGRO 1% with U937 labeled): 10 6 monocytes in 100 µL of plasma were placed in the upper compartment. After 16 hours, TEM was stopped and the upper compartment was analyzed using flow cytometry.

Cell counting by flow cytometry

Statistical analyses

Results were expressed in median and interquartile range for quantitative variables and in absolute value and percentage for each group. Qualitative variables were compared using Fisher exact test and quantitative variables with non-parametric tests Wilcoxon and Kruskal-Wallis. All analyses were performed with JMP 9.0 software (CA, United States).

Results

Patients' and healthy controls' characteristics

Twenty-eight cirrhotic patients and 7 healthy controls were included. Twelve patients had no HE and 16 displayed HE. Baseline characteristics of patients and controls are depicted in Table 1.

Transendothelial migration of U937 through the BBB in presence of sera of patients and controls

TEM of U937 cells was significantly different between the 3 groups (Figure 3A). TEM was higher in the presence of plasma of cirrhotic patients with HE compared to cirrhotic patients without HE (p=0.0448) and to healthy controls (p=0.0334) (Figure 3A). Despite the absence of statistical significance, a trend towards an increased TEM in cirrhotic patients without HE compared to healthy controls was observed. A correlation exists between the importance of TEM and West-Haven scores (p=0.0015) and ammonemia (p=0.0231) (Figure 3B&C). A similar trend was observed for PS100-Beta, a marker of BBB solute's permeability increase, but was not significant (p=0.0981) (Figure 3D).

Discussion

In this study, we show that the plasma of cirrhotic patients with HE enhances TEM of U937 monocytes across hCMEC/D3 BBB model compared to cirrhotic patients without HE. U937 TEM is correlated with the West-Haven score and with ammonemia and might also be correlated with PS-100Beta. This result suggests a new mechanism in the pathophysiology of HE in cirrhosis and could imply, if confirmed, new therapeutic strategies since specific blockers of TEM are already available. Systemic inflammation in cirrhosis and elevated pro inflammatory cytokines (TNF-alpha, IL-6) were found to be necessary in patients with cirrhosis to develop HE in the presence of hyperammonemia [START_REF] Shawcross | Systemic inflammatory response exacerbates the neuropsychological effects of induced hyperammonemia in cirrhosis[END_REF]. Systemic inflammation may facilitate recruitment and migration of leukocytes through endothelia in these patients. Indeed, it has been demonstrated that leukocytes and EC presented an activated state in cirrhosis [START_REF] Iwakiri | Endothelial dysfunction in the regulation of cirrhosis and portal hypertension[END_REF]. Pro-inflammatory cytokines such as TNF-alpha and IL-6 have an impact on BBB permeability in patients without cirrhosis [START_REF] Wang | Tumor necrosis factor-α affects blood-brain barrier permeability in acetaminophen-induced acute liver failure[END_REF]. Moreover, their concentration correlate with the severity of HE and may promote TEM of leukocytes.

Our results reinforce the possible role of systemic inflammation to precipitate HE in cirrhosis. Several hypotheses have been raised to explain this association including an increase in benzodiazepine-like substances induced by IL-1beta and TNF-alpha [START_REF] Oh | Interleukin 1ß and Tumor Necrosis Factor Alpha Increase Peripheral-Type Benzodiazepine Binding Sites in Cultured Polygonal Astrocytes[END_REF], and a decrease in cerebral brain blood flow in response of proinflammatory cytokines [START_REF] Møller | Cerebral blood flow and oxidative metabolism during human endotoxemia[END_REF]. Our work suggests another mechanism relying of the increase in TEM. This theory is of interest, since several therapeutic strategies aiming to decrease TEM of leukocytes have been developed in different neurological diseases such as multiple sclerosis (natalizumab).

Our study included a limited number of subjects, as 28 patients were included. Moreover, HE may vary over time. Some patients may have been evaluated during improvement of HE. Finally, our results suggest, despite a non-significant difference with healthy controls, that there was an increase in BBB permeability in patients with cirrhosis, even in the absence of HE [START_REF] Weiss | Modification in CSF specific gravity in acutely decompensated cirrhosis and acute on chronic liver failure independent of encephalopathy, evidences for an early blood-CSF barrier dysfunction in cirrhosis[END_REF]. One can thus infer that modifications of BBB may precede overt HE.

In conclusion, we suggest an increase in leukocytes BBB permeability in cirrhotic patients with HE.

Although we used a validated model of human BBB, further studies are needed in order to evaluate TEM of leukocytes in vivo and validate our assumption in animal models using drugs blocking TEM like natalizumab, or even by analyzing the brain of deceased patients with cirrhosis, with or without HE.

Table 1: Baseline characteristics of the cirrhotic patients and controls

Healthy controls n=7

No HE cirrhotic patients n=12

HE cirrhotic patients n=16

Age Significant differences between groups are marked as following: between healthy controls and HE patients: $; between healthy controls and cirrhotic patients without HE: #; between HE patients and cirrhotic without HE: *; p values are marked as following: $, #, *: p < 0.05; $$, ##, **: p < 0.01; $$$, ###, ***: p < 0.001.

  All U937 cells were marked before experiments with a fluorescent cell tracker (Deep-Red Dye, Molecular Probes). The content of the lower chamber was harvested and cell counting was directly performed by flow cytometry using counting beads (Gallios, Beckman Coulter). Counting beads (CountBright, Molecular Probes) were added to each sample immediately before assay. The concentration of beads was precisely known and enabled us to estimate the absolute number of U937 cells that had migrated. The beads were easily separated from cells during flow cytometry assays on the basis of their physical properties (FSC/SSC, Fig 2A) and their high fluorescence in each channel (Fig 2B). Doublets were eliminated through an FSC-A/FSC-H assay (Fig 2B and 2E). The cell-tracker on U937 cells was only fluorescent in the FL-6 channel (Fig 2C). The efficacy of the cell tracker was also checked, comparing the cytometric profile of dyed U937 (red histogram) with undyed U937 (black histogram) and undyed hCMEC/D3 cells (blue histogram) (Fig 2D). To confirm beads' identity, an analysis was performed in the FL-1 channel (Fig 2F). The accuracy of the counting beads was checked comparing a wide range of expected concentrations of cells that were obtained by serial dilutions and the calculated ones, showing excellent correlations (Fig 2G).

Figure 1 :

 1 Figure 1: Leukocytes transendothelial migration experiment across the BBB A, Outline of TME experiment on Transwell inserts; B, anti-PECAM-1 (CD31) immunostaining of hCMEC/D3 cells.

Figure 2 :

 2 Figure 2: Cell counting strategy by flow cytometry Counting beads (CountBright, Molecular Probes) were added to each sample immediately before assay. The concentration of these beads was precisely known and enabled us to estimate the absolute number of U937 cells that had migrated. These beads were easily separated from cells during flow cytometry assays on the basis of their physical properties (FSC/SSC, Fig 2A) and their high fluorescence in each channel (Fig 2B). Doublets were eliminated through a FSC-A/FSC-H assay (Fig 2B and 2E). The cell-tracker on U937 cells was only fluorescent in the FL-6 channel (Fig 2C). The efficiency of the cell tracker was also checked, comparing the cytometric profile of dyed U937 (red histogram) with undyed U937 (black histogram) and undyed hCMEC/D3 cells (blue histogram) (Fig 2D). To confirm beads' identity, an analysis was performed in the FL-1 channel (Fig 2F). The accuracy of the counting beads was checked comparing a wide range of expected concentrations of cells that were obtained by serial dilutions and the calculated ones, showing excellent correlations (Fig 2G).

Figure 3 :

 3 Figure 3: U937 leukocytes transendothelial migration across the BBB in presence of plasma of cirrhotic patients and healthy controls. A, U937 TEM across the hCMEC/D3 BBB model. Correlations between U937 TEM and B, West-Haven score; C, ammonia concentration in plasma; D, PS-100Beta concentration in plasma.

Acknowledgements:

The authors would like to thank the Fondation pour le Recherche Médicale for their support, FRM (EQU202003010517) and Dr Clarisse Berlioz-Torrent (Institut Cochin, Paris, France) for providing leukocytes cell line U937.