Simona Bottani
email: simonabottani92@gmail.com

Elina Thibeau-Sutre

Aurélien Maire

Sebastian Ströer

Didier Dormont

Olivier Colliot

Ninon Burgos

Homogenization of brain MRI from a clinical data warehouse using contrast-enhanced to non-contrast-enhanced image translation with U-Net derived models

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INTRODUCTION

Clinical data warehouses, gathering hundreds of thousands of medical images from numerous hospitals, offer fantastic opportunities for computer-aided diagnosis for neurological diseases but also pose considerable challenges. One of these challenges is the heterogeneity of the images present in the data warehouse. Neurological diseases can result in a variety of brain lesions that are each studied with specific magnetic resonance imaging (MRI) sequences. For example, T1-weighted (T1w) brain MRI enhanced with a gadolinium-based contrast agent are used for the study of lesions such as tumors, and T1w images without gadolinium are used for the study of neurodegenerative diseases. To perform differential diagnosis using classification algorithms, homogeneous features must be extracted from the images, no matter the disease, otherwise a link could be established between MRI sequence and pathology, which would create bias. Software tools such as SPM, 1 ANTs 2 or FSL [START_REF] Mark | FSL[END_REF] have been widely used for feature extraction but they were largely validated using structural T1w MRI without gadolinium only, to the best of our knowledge, and their good performance on images with gadolinium is thus not guaranteed. A solution could then be to convert contrast-enhanced T1w (T1w-ce) into non-contrast-enhanced T1w (T1w-nce) brain MRI before using such tools.

Deep learning has been widely used in the image translation domain to enhance image quality, such as for denoising [START_REF] Hashimoto | Dynamic PET image denoising using deep convolutional neural networks without prior training datasets[END_REF][START_REF] Benou | Ensemble of expert deep neural networks for spatiotemporal denoising of contrast-enhanced MRI sequences[END_REF][START_REF] Jiang | Denoising of 3D magnetic resonance images with multi-channel residual learning of convolutional neural network[END_REF][START_REF] Yang | A robust deep neural network for denoising task-based fMRI data: An application to working memory and episodic memory[END_REF] or super-resolution, [START_REF] Chen | Efficient and accurate MRI super-resolution using a generative adversarial network and 3D multi-level densely connected network[END_REF][START_REF] Du | Brain mri super-resolution using 3d dilated convolutional encoder-decoder network[END_REF][START_REF] Kim | Improving resolution of MR images with an adversarial network incorporating images with different contrast[END_REF][START_REF] Pham | Brain MRI super-resolution using deep 3D convolutional networks[END_REF][START_REF] Zeng | Simultaneous single-and multi-contrast super-resolution for brain MRI images based on a convolutional neural network[END_REF] but also for image harmonization. [START_REF] Dewey | DeepHarmony: a deep learning approach to contrast harmonization across scanner changes[END_REF] Closer to our objective, 3D U-Net like models have been developed for the synthesis of images with gadolinium from images without gadolinium. [START_REF] Bône | Contrast-enhanced brain MRI synthesis with deep learning: key input modalities and asymptotic performance[END_REF][START_REF] Kleesiek | Can virtual contrast enhancement in brain MRI replace gadolinium?: a feasibility study[END_REF][START_REF] Sun | Substituting Gadolinium in Brain MRI Using DeepContrast[END_REF] Our objective in this work is to obtain a homogeneous dataset of T1w-nce images that will be later used for the differential diagnosis of neurological diseases in a clinical data warehouse. We propose two deep learning models, based on a 3D U-Net like structure that demonstrated good performance on similar tasks, [START_REF] Bône | Contrast-enhanced brain MRI synthesis with deep learning: key input modalities and asymptotic performance[END_REF][START_REF] Kleesiek | Can virtual contrast enhancement in brain MRI replace gadolinium?: a feasibility study[END_REF][START_REF] Sun | Substituting Gadolinium in Brain MRI Using DeepContrast[END_REF] to translate T1w-ce into T1w-nce images. We trained and tested our models using 307 pairs of T1w-nce and T1w-ce images. We first assessed synthesis accuracy by comparing real and synthetic T1w-nce images using standard metrics. We then compared the volumes of different tissues obtained by segmenting the real T1w-nce, real T1w-ce and synthetic T1w-nce images using SPM. [START_REF] Ashburner | Unified segmentation[END_REF]

MATERIALS AND METHODS

Dataset description

This work relies on a large clinical dataset containing all the T1w brain MR images of adult patients scanned in hospitals of the Greater Paris areas (Assistance Publique-Hôpitaux de Paris [AP-HP]). The data were made available by the AP-HP data warehouse and the study was approved by the Ethical and Scientific Board of the AP-HP. According to French regulation, consent was waived as these images were acquired as part of the routine clinical care of the patients. Images from this clinical data warreehouse are very heterogeneous: 18 they include images of patients with a wide range of ages and diseases, acquired with different scanners from 1980 up to now.

The dataset used in this work is composed of 307 pairs of T1w-ce and T1w-nce images that were extracted from a dataset composed of 9941 images made available by the AP-HP data warehouse. We first selected all the images of low, medium and good quality, excluding images that were not proper T1-weighted brain MRI, [START_REF] Bottani | Automatic quality control of brain T1-weighted magnetic resonance images for a clinical data warehouse[END_REF] resulting in 7397 images. This selection was based on manual quality control for 5500 images and on automatic quality control for the remaining 4441 images. [START_REF] Bottani | Automatic quality control of brain T1-weighted magnetic resonance images for a clinical data warehouse[END_REF] We then considered only patients having one T1w-ce and one T1w-nce at the same session, with a T1w-nce image of medium or good quality. Finally, we visually checked all the images and excluded 52 image pairs that were potential outliers because of extremely large lesions. Among the selected images we had 256 image pairs of medium and good quality, and 51 image pairs with a T1w-ce of low quality and a T1w-nce of good or medium quality.

Image preprocessing

All the images were organised using the Brain Imaging Data Structure (BIDS). [START_REF] Gorgolewski | The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments[END_REF] We applied the following pre-processing using the 't1-linear' pipeline of Clinica, [START_REF] Routier | Clinica: An Open-Source Software Platform for Reproducible Clinical Neuroscience Studies[END_REF] which is a wrapper of the ANTs software. [START_REF] Avants | The Insight ToolKit image registration framework[END_REF] Bias field correction was applied using the N4ITK method. [START_REF] Tustison | N4ITK: improved N3 bias correction[END_REF] An affine registration to MNI space was performed using the SyN algorithm. [START_REF] Avants | Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain[END_REF] The registered images were further rescaled based on the min and max intensity values, and cropped to remove background resulting in images of size 169×208×179, with 1 mm isotropic voxels. [START_REF] Wen | Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible Evaluation[END_REF] Finally all the images were resampled to have a size of 128×128×128 using trilinear interpolation.

Network architecture

We implemented two 3D U-Net like models: Res-U-Net with residual connections [START_REF] Bône | Contrast-enhanced brain MRI synthesis with deep learning: key input modalities and asymptotic performance[END_REF][START_REF] Milletari | V-net: Fully convolutional neural networks for volumetric medical image segmentation[END_REF] and Att-U-Net with attention mechanisms [START_REF] Oktay | Attention u-net: Learning where to look for the pancreas[END_REF] (Fig. 1). The U-Net structure allows preserving the original structure of the images thanks to the skip connections while the residual connections and the attention gates are both useful to make the model focus on the salient parts of the images. We used the ADAM optimizer, the L1 loss, a batch size of 2, and we trained the models for 300 epochs. We relied on Pytorch for the implementation.

Experiments and validation of the model

The experiments relied on 307 pairs of T1w-ce and T1w-nce images. We randomly selected 10% of the 256 image pairs of medium and good quality for testing (dataset called Test good ), the other 230 image pairs being used for training/validation. Only images of good and medium quality were used for training/validation to ensure that the model focuses on the differences related to the presence or absence of gadolinium, and not to other factors. The remaining 51 image pairs with a T1w-ce of low quality and a T1w-nce of good or medium quality were used only for testing (dataset called Test low ).

Synthesis accuracy

Image similarity was evaluated using the mean absolute error (MAE), peak signal-to-noise ratio (PNSR) and structural similarity (SSIM). [START_REF] Wang | Image quality assessment: from error visibility to structural similarity[END_REF] We calculated these metrics both between the real and synthetic T1w-nce images and between the real T1w-nce and T1w-ce (as reference). These metrics were calculated within the brain region obtained by skull-stripping the T1w-nce and T1w-ce [START_REF] Isensee | Automated brain extraction of multisequence MRI using artificial neural networks[END_REF] and computing the union of the two resulting brain masks.

Segmentation fidelity

Our goal is to obtain gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) segmentations from T1w-ce images using widely-used software tools that are consistent with segmentations obtained from T1w-nce images. We thus assessed segmentation consistency by analyzing the tissue volumes resulting from the segmentations, which are important features when studying atrophy in the context of neurodegenerative diseases.

We processed the images using the 't1-volume-tissue-segmentation' pipeline of Clinica. [START_REF] Routier | Clinica: An Open-Source Software Platform for Reproducible Clinical Neuroscience Studies[END_REF][START_REF] Samper-González | Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data[END_REF] This wrapper of the Unified Segmentation procedure implemented in SPM [START_REF] Ashburner | Unified segmentation[END_REF] simultaneously performs tissue segmentation, bias correction and spatial normalization. The probability maps were then binarized to derive tissue volumes. We calculated the volume difference for each tissue between the T1w-nce and the synthetic T1w-nce or T1w-ce. We multiplied the difference with the average total intracranial volume computed across the two test sets. To assess whether the tissue volumes presented a statistically significant difference depending on the images they were obtained from, we performed paired t-tests correcting for multiple comparisons using the Bonferroni method.

RESULTS

We report results of the proposed 3D U-Net like models trained on 230 image pairs and tested on Test good and Test low obtained from a clinical multisite dataset (examples in Fig 2). We note the absence of contrast agent in the synthetic T1w-nce, while it is clearly visible in the sagittal slice of the T1w-ce, and that the anatomical Table 1. MAE, PSNR and SSIM obtained on the two independent test sets with various image quality. For each metric, we report the average and standard deviation across the corresponding test set. We compute the metrics for both T1w-ce and synthetic T1w-nce in relation to the real T1w-nce, and so within the brain region. structures are preserved between the synthetic and real T1w-nce. We also note that for the patient from Test low the contrast between gray and white matter seems improved in the synthetic compared with the real T1w-ce.

Synthesis accuracy

Table 1 reports the image similarity metrics obtained for the two test sets within the brain region. We computed these metrics to assess the similarity between real and synthetic T1w-nce images, but also between T1w-nce and T1w-ce images to set a baseline. We observe that for both models, the similarity is higher between real and synthetic T1w-nce images than between T1w-nce and T1w-ce images according to all three metrics on both test sets. Att-U-Net performed slightly but systematically better than Res-U-Net and was thus kept in the following.

Segmentation fidelity

Absolute volume differences obtained between T1w-nce and T1w-ce images and between T1w-nce and synthetic T1w-nce images are reported in Table 2. For both test sets and all tissues, the absolute volume differences are smaller between real and synthetic T1w-nce images than between T1w-nce and T1w-ce images. The differences between T1-nce/synthetic T1w-nce and T1w-nce/T1w-ce are statistically significant (corrected p-value <10e-3) for GM and CSF when considering Test good , and for all tissues when considering Test low .

DISCUSSION AND CONCLUSION

The use of clinical images for the validation of computer-aided diagnosis (CAD) systems is still largely unexplored. One of the obstacles lies in the heterogeneity of the data acquired in the context of routine clinical practice. Homogenization of the dataset, and consequently of the features extracted from it, is an important step for the development of reliable CAD systems in a clinical setting. To homogenize such dataset, we proposed U-Net like structures to synthesize T1w-nce from T1w-ce images and we trained the models using images from a clinical data warehouse. To the best of our knowledge, this is the first work to propose such approach in this context. We first showed using MAE, PSNR and SSIM that the similarity between real and synthetic T1w-nce images was higher than the similarity between real T1w-nce and T1w-ce images, no matter the U-Net model. The synthesis accuracy was of the same order as that of recent works, [START_REF] Bône | Contrast-enhanced brain MRI synthesis with deep learning: key input modalities and asymptotic performance[END_REF][START_REF] Kleesiek | Can virtual contrast enhancement in brain MRI replace gadolinium?: a feasibility study[END_REF] but slightly better performance was reached with the Att-U-Net model, which was thus further evaluated. In the second step of the validation, we showed that the absolute volume differences of GM, WM and CSF were larger between real T1w-nce and Tw-ce images than between real and synthetic T1w-nce images (statistically significant difference most of the times). This confirms the hypothesis that gadolinium-based contrast agent may alter the contrast between the different brain tissues, making features extracted from such images with standard segmentation tools, here SPM, 1 unreliable. At the same time, we validated the suitability of the synthetic images since their segmentation was consistent with those obtained from real T1w-nce images as the volume differences were small. Finally, our results show that the proposed model performs well, no matter the quality of the input T1w-ce image, even though more accurate results are reached for images of good/medium quality.

Several steps remain to be performed before using synthetic T1-nce images for the differential diagnosis of neurological diseases. For example, the performance of CAD systems trained with a mix of real T1w-nce and T1w-ce images should be compared with that of CAD systems trained with a mix of real and synthetic T1wnce images. Future work could also involve implementing and evaluating other approaches, such as generative adversarial networks, to further improve the quality of the synthetic images, in particular their sharpness.

Figure 1 .

 1 Figure1. Architectures of the proposed 3D U-Net models. The models take as input the real T1w-nce image of size 128×128×128 and generate the synthetic T1w-nce of size 128×128×128. Res-U-Net (left): images pass through five descending blocks, each one followed by a residual module, and then through four ascending blocks and one final layer. Att-U-Net (right): images pass through five descending blocks and then through four ascending blocks and one final layer. One of the input of each ascending block is the results of the attention gate composed of convolutional blocks, ReLU and sigmoid layers. All the parameters such as kernel size, stride, padding, size of each feature map (N) are reported.

Figure 2 .

 2 Figure 2. Examples of real T1w-nce, synthetic T1w-nce (obtained with the Att-U-Net model) and real T1w-ce images for two patients (at the top from Test good and at the bottom from Test low ) in the sagittal and axial planes. Table1. MAE, PSNR and SSIM obtained on the two independent test sets with various image quality. For each metric, we report the average and standard deviation across the corresponding test set. We compute the metrics for both T1w-ce and synthetic T1w-nce in relation to the real T1w-nce, and so within the brain region.

  / T1w-ce -4.14 ± 1.59 23.03 ± 2.83 0.90 ± 0.05 T1w-nce / Synthetic T1w-nce Att-U-Net 2.73 ± 1.69 29.07 ± 4.53 0.96 ± 0.05 Res-U-Net 3.06 ± 1.50 26.89 ± 4.30 0.95 ± 0.04 Test low T1w-nce / T1w-ce -3.71 ± 1.99 24.20 ± 3.85 0.91 ± 0.06 T1w-nce / Synthetic T1w-nce Att-U-Net 2.89 ± 1.85 27.15 ± 4.57 0.95 ± 0.05 Res-U-Net 2.93 ± 1.77 26.71 ± 4.32 0.95 ± 0.05

Table 2 .

 2 Absolute volume difference (mean ± standard deviation in cm 3 ) between T1w-nce and T1w-ce images and between T1w-nce and synthetic T1w-nce images (obtained with the Att-U-Net model) for GM, WM and CSF. The corresponding corrected p-values were obtained with paired t-tests corrected for multiple comparisons using the Bonferroni correction. ] P-value Absolute difference [cm 3 ] P-value Absolute difference [cm 3 ] P-value

	Test set Absolute difference [cm 3 Test good Gray matter Compared images T1w-nce / T1w-ce 26.68 ± 15.92 T1w-nce / Synthetic T1w-nce 10.36 ± 6.98	<10e-3	White matter 10.81 ± 3.71 7.79 ± 5.87	0.12	CSF 61.62 ± 34.61 13.37 ± 10.18	<10e-3
	Test low	T1w-nce / T1w-ce T1w-nce / Synthetic T1w-nce	49.63 ± 49.38 19.61 ± 29.54	<10e-3	25.36 ± 27.73 13.95 ± 24.74	<10e-3	69.55 ± 37.77 18.27 ± 17.20	<10e-3

ACKNOWLEDGMENTS

The research was done using the Clinical Data Warehouse of the Greater Paris University Hospitals. The authors are grateful to the members of the AP-HP WIND and URC teams, and in particular Stéphane Bréant, Florence Tubach, Jacques Ropers, Antoine Rozès, Camille Nevoret, Christel Daniel, Martin Hilka, Yannick Jacob, Julien Dubiel and Cyrina Saussol. They would also like to thank the "Collégiale de Radiologie of AP-HP" as well as, more generally, all the radiology departments from AP-HP hospitals. The research leading to these results has received funding from the Abeona Foundation (project Brain@Scale), from the French government under management of Agence Nationale de la Recherche as part of the "Investissements d'avenir" program, reference ANR-19-P3IA-0001 (PRAIRIE 3IA Institute) and reference ANR-10-IAIHU-06 (Agence Nationale de la Recherche-10-IA Institut Hospitalo-Universitaire-6).


MD Milan Nigam

MD c , Smaranda Leu-Semenescu

MD Isabelle Arnulf
email: isabelle.arnulf@aphp.fr

MD Pr Isabelle Arnulf

Successful treatment of drug-resistant cataplexy with the anticholinergic drug tropatepine

Keywords: narcolepsy, cataplexy, anticholinergic

Narcolepsy type 1 is characterized by excessive daytime sleepiness and cataplexy, as well as hypocretin deficiency.

Cataplexy (the loss of voluntary postural muscle tone, often in response to emotional stimuli), is one of the most disabling features, and is associated with significant social impairment and risk of injury. Cataplexy is usually alleviated by antidepressants, sodium oxybate and pitolisant. In this case report, we describe three patients with severe, drugresistant cataplexy, who experienced a dramatic improvement when treated with tropatepine, an anticholinergic muscarinic antagonist (which is commonly used to prevent neuroleptic-induced parkinsonism) after having failed usual treatments. The single side effect was mild mouth dryness. In addition to providing a new therapeutic option for resistant cataplexy, this benefit supports a role of cholinergic muscarinic transmission in REM sleep atonia.

INTRODUCTION

Narcolepsy type 1 (NT1) is a neurological disorder caused by the loss of hypocretin-1 neurons in the lateral hypothalamus. It is characterized by excessive daytime sleepiness, sleep attacks and cataplexy, as well as other variably present symptoms, including sleep paralysis, hypnagogic hallucinations, disturbed nighttime sleep, rapid eye movement (REM) sleep behavior disorder and weight gain. [START_REF] Bassetti | Narcolepsy -clinical spectrum, aetiopathophysiology, diagnosis and treatment[END_REF] Cataplexy corresponds to brief loss of bilateral postural voluntary muscle tone, usually triggered by emotional stimuli. It is conceptualized as the intrusion of REM sleep atonia into wakefulness. Attacks can be either partial (i.e., loss of facial tone, dysarthria) or complete, involving the whole body and resulting into falls. Both types of cataplexy are a source of significant social impairment, anxiety and potential injury. Current treatment options for cataplexy include antidepressants (such as venlafaxine, paroxetine, escitalopram, fluoxetine and clomipramine), sodium oxybate and pitolisant. [START_REF] Bassetti | Narcolepsy -clinical spectrum, aetiopathophysiology, diagnosis and treatment[END_REF][START_REF] Morgenthaler | Practice parameters for the treatment of narcolepsy and other hypersomnias of central origin[END_REF] Although these agents are usually efficacious, some patients report persistent cataplexy despite multiple drug trials. This report describes three such patients, who experienced dramatic improvement following treatment with tropatepine, an anticholinergic muscarinic antagonist, primarily used in France as a treatment for neuroleptic-induced parkinsonism. [START_REF] Lambert | A new synthetic antiparkinsonian drug, tropatepine hydrochloride in extrapyramidal syndromes induced by neuroleptics[END_REF] In addition to its practical therapeutic implication, the successful use of this treatment re-emphasizes the importance of cholinergic mechanisms in the neurobiology of cataplexy.

CASE REPORTS Patient #1

A 27-year-old man was diagnosed with NT1 at age ten following a typical history of rapid weight gain, followed by progressive onset of excessive daytime sleepiness and cataplexy. The hypocretin-1 level was undetectable (<40 mg/mL) in the CSF. He received intravenous immunoglobulins 5 months after cataplexy onset, which led to a decrease of total and partial cataplexy, which gradually reoccurred several months after the infusion. [START_REF] Lecendreux | Clinical efficacy of high-dose intravenous immunoglobulins near the onset of narcolepsy in a 10-year-old boy[END_REF] Over the subsequent years, the patient was treated with several wake-promoting agents with variable success, including modafinil, sodium oxybate and methylphenidate. The patient reported frequent, highly disabling partial cataplexy attacks characterized by loss of facial, neck and arm tone, provoked by laughter and lasting up to one minute. The attacks occurred dozens of times per day and were associated with significant social impairment and avoidance behaviours which had a profoundly negative impact on his quality of life. Previous trials of venlafaxine and sodium oxybate for cataplexy were inefficacious and the combination of pitolisant 36 mg and clomipramine 25 mg resulted in only a minor decrease in frequency of attacks. Methylphenidate, though effective for somnolence, triggered a severe psychotic episode at age 18, which was successfully treated with cessation of methylphenidate and introduction of risperidone, which was tapered over a twoyear period. To prevent neuroleptic-induced parkinsonism, tropatepine (Lepticur®, a muscarinic anticholinergic) was introduced and titrated up to 10 mg daily. The dose was subsequently reduced to 5 mg because of dry mouth. Within days of the introduction of tropatepine, the patient reported a dramatic reduction in the severity and frequency of cataplexy, with only minor, non-disabling facial cataplexy occurring once per week. He had since been treated with pitolisant 36 mg, and reported remarkable efficacy for daytime sleepiness. After one year on tropatepine, the patient attempted a one-week tropatepine holiday (but still took pitolisant) which caused the cataplexy to return to its pretreatment severity, which remitted once again upon resumption of tropatepine. The patient had now been on tropatepine for seven years, and has enjoyed continued efficacy. Importantly, he also reported a significant reduction in social anxiety related to his cataplexy, which has allowed him to pursue fulfilling relationships and career opportunities previously impossible.

Patient #2

A 54-year-old man initially presented excessive daytime sleepiness in his early twenties, followed by facial cataplexy, which began near the age of thirty. The patient also exhibited occasional dream enactment behaviour compatible with REM sleep behaviour disorder (rarely, these had resulted in minor punches of his wife). At the age of 37, the patient sought out care and was diagnosed with NT1 following polysomnography and multiple sleep latency tests. He was treated with partial success with modafinil 500 mg daily in two doses and paroxetine 40 mg. Past trials of methylphenidate and sodium oxybate were not tolerated. The patient was referred to our centre at the age of 52 years old for progressive worsening in severity of cataplexy over the previous year. At that time, he reported partial cataplexy up to fifty times daily, which was characterized by jaw weakness and dysarthria with head dropping. Full cataplexy, often resulting in complete falls occurred several times per week and lasted for up to two minutes. Some of these episodes occurred in dangerous situations, including while swimming and while climbing a ladder. Typical triggers were laughing, anger and surprise. However, the episodes had begun to occur spontaneously, particularly if he was feeling fatigued. The patient reported that his cataplexy was by far the most invalidating symptom of his narcolepsy, with significant impairment in social and occupational functioning resulting in invalidity from his previous employment as a factory worker. At this time, the patient was also diagnosed with severe obstructive sleep apnea (apnea-hypopnea index: 54/hour) which was successfully treated with continuous airway pressure therapy. For his cataplexy, the patient was treated with clomipramine titrated up to 75 mg daily, replacing paroxetine. After several months of further worsening of cataplexy, paroxetine was re-introduced concomitantly with clomipramine. No improvement was noted over the following year. The patient reported frequent complete cataplexy episodes occurring multiple times daily with minor emotional triggers. At this point, tropatepine was introduced at 10 mg. The patient reported a rapid improvement in his cataplexy. At the most recent follow-up, 10 months after the introduction of tropatepine, he reported only occasional attacks of facial cataplexy, occurring up to three times per week. Interestingly, the patient's wife also reported a decrease in frequency of dream enactment behaviour, with only occasional somniloquy and no violent behaviours remaining. The patient did not report any modification in his daytime somnolence, which remained significant but was well managed with a programmed nap schedule. The treatment is well tolerated with the patient noting only mild mouth dryness.

Patient #3

A 78-year-old woman had been diagnosed with late-onset narcolepsy at age 53. She presented with a typical history of excessive daytime somnolence with irrepressible sleep attacks followed by onset of facial cataplexy triggered by laughing. She was otherwise known to have degenerative disk disease, osteoarthritis of the hip requiring hip replacement, hypertension and hypothyroidism. She lived alone and remained fully independent in activities of daily living, with no significant cognitive impairment. After having been satisfactorily treated with a combination of modafinil and escitalopram for several years, the patient was referred to our tertiary sleep unit at the age of 74 for worsening cataplexy. In recent years, she had begun experiencing complete cataplectic attacks more frequently. She reported that when playing tag with her young grand-daughter, she would run around the table laughing with her grand-daughter in pursuit, only to be caught lying on the ground as her cataplexy overwhelmed her. These attacks, precipitated by strong laughter occurred several times per month. They had resulted on at least one occasion in a minor occipital trauma and the patient and her family were increasingly concerned with her risk of injury. She also reported frequent, bothersome nightmares, often culminating in hypnopompic hallucinations. Escitalopram was discontinued and the patient was successively treated over the next four years with clomipramine, followed by combined paroxetine and pitolisant, the latter of which replaced her modafinil. None of these treatments proved more than modestly effective for her cataplexy, though 18 mg of pitolisant resulted in a significant improvement in her daytime sleepiness. Despite adherent use of pitolisant and paroxetine, the patient's cataplexy continued to worsen, and she reported multiple daily episodes of both partial and complete cataplexy. She also reported that the emotional threshold necessary to trigger cataplexy had become progressively lower, such that even mild bemusement could trigger attacks. Considering the significant risk for injury in this elderly patient, tropatepine was introduced at a dose of 5 mg. At last follow up, 2 months after the initiation of the treatment, the patient reported complete resolution of both complete and partial cataplexy within one week of treatment initiation. Interestingly, she also reported complete resolution of both nightmares and hypnopompic hallucinations. The patient, who continues to live independently, reported no significant cognitive side effects but did complain of mild dryness of her mouth.

Discussion

To our knowledge, this is the first report of successful treatment of cataplexy with a specific anticholinergic drug.

Although this class of drug has not commonly been employed in the treatment of cataplexy, its use is rational when one considers the important role acetylcholine plays in the genesis of both REM sleep and muscle atonia.

The critical of role of acetylcholine in REM sleep has been demonstrated in animal models dating back to the era REM sleep discovery. Jouvet demonstrated in his seminal works in cats that the infusion of carbachol (a potent cholinergic, muscarinic agonist) in the mediodorsal pontine tegmentum produces both the clinical and electrophysiological features of REM sleep, a finding later replicated in several feline and murine models. [START_REF] Vanni-Mercier | Carbachol microinjections in the mediodorsal pontine tegmentum are unable to induce paradoxical sleep after caudal pontine and prebulbar transections in the cat[END_REF][START_REF] Grace | Evaluating the Evidence Surrounding Pontine Cholinergic Involvement in REM Sleep Generation[END_REF] Moreover, administration of anticholinergic agents have been shown, though less consistently, to reverse these physiological features. [START_REF] Grace | Evaluating the Evidence Surrounding Pontine Cholinergic Involvement in REM Sleep Generation[END_REF] Recently, a loss of function model in knockout mice demonstrated that specific muscarinic receptors, Chrm1 and Chrm3, are necessary to generate REM sleep and provides further evidence supporting the essential role of acetylcholine in REM sleep. [START_REF] Niwa | Muscarinic Acetylcholine Receptors Chrm1 and Chrm3 Are Essential for REM Sleep[END_REF] Cataplexy is thought to represent the intrusion of REM sleep atonia into wakefulness, resulting from the abnormal activation of the subcoeruleus nucleus (an equivalent of the peri-locus coeruleus alpha in the cat and of the sublaterodorsalis nucleus in the rat) by overactive limbic structures. [START_REF] Bassetti | Narcolepsy -clinical spectrum, aetiopathophysiology, diagnosis and treatment[END_REF][START_REF] Horner | Brain Circuitry Controlling Sleep and Wakefulness[END_REF] Data from canine studies suggest that this process is mediated in part by increased cholinergic tone. Mignot and colleagues have shown that injection of carbachol into the pontine reticular formation precipitates cataplexy in a dose dependant fashion in narcoleptic dogs. [START_REF] Nishino | Pharmacological aspects of human and canine narcolepsy[END_REF] A similar response can be observed in non-narcoleptic dogs, though significantly higher doses are required. Taken together, these findings suggest that cholinoceptive hypersensitivity in the pontine reticular formation which, via its reciprocal connections to limbic structures, facilitate the pathological recruitment of REM atonia generating circuits in response to salient emotional stimuli.

Considering the abundant evidence demonstrating the importance of acetylcholine in cataplexy and REM sleep, it is logical to attempt treatment of cataplexy with specific anticholinergic agents. Indeed, the dramatic and prompt therapeutic response to the muscarinic antagonist tropatepine in our report of three patients with severe and drug resistant cataplexy lends credence to this approach. Additionally, although tricyclic antidepressants are thought to exert their efficacy in the treatment of cataplexy primarily through their monoaminergic properties, it is reasonable to hypothesize their substantial anticholinergic activity is a contributing factor. Interestingly, two of our patients exhibited other signs of REM sleep dysfunction, including REM sleep behaviour disorder and nightmares with hypnagogic hallucinations, respectively. The observed improvement in these symptoms with tropatepine, may be related to the REM sleep suppressing properties of anticholinergics. Tropatepine has a long half-life (40 hours), which may be an advantage compared to venlafaxine short half-life, which can result in rebound cataplexy when a single dose is forgotten. [START_REF] Bun | Pharmacokinetics of Tropatepine in Healthy Volunteers[END_REF] Tropatepine is a common drug, marketed since 1975, which may induce atropinic side-effects (urine retention, constipation, blurred vision, rare confusion). The benefit to risk ratio was excellent in our patients, as side effect were limited to non-disturbing dry mouth. Although the specific drug tropatepine may not be widely available outside of France, we posit that it is reasonable to consider trials of other, more widely available, antimuscarinic agents commonly used in neurology, such as benztropine or trihexyphenidyl, in resistant cataplexy.

Conclusion

In this report of three narcoleptic patients, tropatepine was a potent treatment for severe, disabling and drug resistant cataplexy and may represent an efficacious and cost-effective treatment for drug resistant cataplexy, as well as other features of REM sleep dysfunction commonly observed in narcolepsy. The success of this treatment approach also reemphasizes the role of cholinergic mechanisms in the genesis of cataplexy, and may constitute a rationale for trials of other anticholinergic agents, such as benztropine or trihexyphenidyl, in countries where tropatepine is unavailable.

No specific financial support was allocated to this project. MN has received an educational grant from Paladin Labs pharmaceuticals. SLS has speaking engagements with UCB Pharma.

IA has received consultant fees from Idorsia Pharma, Ono Pharma, UCB Pharma.

Abbreviations

NT1: Narcolepsy type 1


Kleine-Levin Syndrome

MD PhD Isabelle Arnulf

MD Elisabeth Groos

MD Pauline Dodet

Isabelle Arnulf, MD, PhD, 1 , 2 Elisabeth Groos, MD [START_REF] Arnulf | Diagnosis, disease course, and management of patients with Kleine-Levin syndrome[END_REF] and Pauline Dodet, MD [START_REF] Arnulf | Diagnosis, disease course, and management of patients with Kleine-Levin syndrome[END_REF] 1 Sorbonne University, Paris, France [START_REF] Arnulf | Diagnosis, disease course, and management of patients with Kleine-Levin syndrome[END_REF] National Reference Center for Kleine-Levin syndrome, Sleep Disorders Unit, Pitie-Salpetriere Hospital, APHP-Sorbonne, Paris, France

DISCLOSURE STATEMENT

Funding sources for our researches on Kleine-Levin syndrome did not include any pharma or private company, but include patients associations and institutional founders, including the KLS foundation (Boston, USA) for research on brain imaging, the KLS-France patient association (Paris, France) for research on IV steroids, and recurrent grants from the French Health Ministry (PHRC 2007 and National Programs on Rare Diseases #2 and #3).

CONFLICT OF INTEREST STATEMENT

Dr Arnulf received consulting fees from IDORSIA pharma, ONO Pharma and ROCHE Pharma and speaker bureau fees from UCB Pharma in the last 24 months, none being related to any study in Keline-Levin syndrome. Dr Groos and Dr Dodet have no link of interest to disclose.

OFF-LABEL USE of DRUG

Off label use of IV steroids (prednisolone) and lithium therapy is mentioned here.

Place where the work was performed: National Reference Center for Kleine-Levin syndrome, Sleep Disorders Unit, Pitie-Salpetriere University Hospital (APHP-Sorbonne), Paris, France Click here to access/download;Manuscript;response.docx syndrome (KLS) results from an instability between GABA and glutamate transmissions during neurodevelopment. [START_REF] Ortega-Albás | GABA and glutamate[END_REF] Although interesting, this hypothesis is speculative, as it can hardly be tested, neglects some opposed evidences and may seem too holistic for such a rare disorder. Indeed, GABA and glutamate represent 80% of synaptic brain transmission. Consequently, they are not restricted to the functions (sleep, behavior, cognition, mood) specifically altered during KLS episodes, but are involved in hundreds of different functions, including for example synaptic stability (resulting in seizures, which are notably absent in KLS, when affected). Plus, it may seems oversimplistic to attribute the "positive" (hypersexuality, megaphagia, hallucinations or end-episode insomnia) KLS symptoms to increased glutamate stimulation (or impaired GABA inhibition) and the "negative" (apathy, derealization, hypersomnia, cognitive impairment) symptoms to increased GABA inhibition (or decreased glutamate inhibition), as double GABA inhibition results for example into stimulation. Eventually, benzodiazepines, which stimulates the GABA system have no efficacy in KLS. [START_REF] Arnulf | Diagnosis, disease course, and management of patients with Kleine-Levin syndrome[END_REF] The KLS mechanisms are still unknown, although genetics, inflammatory and autoimmune origins have been suspected. [START_REF] Arnulf | Diagnosis, disease course, and management of patients with Kleine-Levin syndrome[END_REF] Because KLS shares the remitting-relapsing course of multiple sclerosis, and may possibly be inflammatory (at least in neuropathological cases, although inflammatory markers are absent in the CSF), we tested lithium therapy (a potent anti-inflammatory drug) and IV steroids and found partial benefits in controlled observational cohorts. On the other hand, several complex neurologic and psychiatric syndromes are now recognized as autoimmune encephalitis caused by newly identified autoantibodies. Anti-NMDA receptors autoantibodies are interesting in the context of KLS, as they cause sleep and behavioral symptoms, [START_REF] Arino | Sleep disorders in anti-NMDAR encephalitis[END_REF] and have been found (with enzyme-linked immunosorbent assay but not cell-based assay) in a recent KLS case. [START_REF] Ortega-Albás | GABA and glutamate[END_REF] Unfortunately, this research field on autoimmunity has been disappointing in our experience, despite following 300 patients with KLS. Indeed, we could not find any association with human leucocyte antigen (HLA) genotypes in 228 patients with KLS, [START_REF] Arnulf | Diagnosis, disease course, and management of patients with Kleine-Levin syndrome[END_REF] and any positive CSF anti-NMDA autoantibodies in 5 symptomatic KLS patients. We found normal serum levels of anti-IA-2, anti-glutamate acid decarboxylase (GAD65) and anti-aquaporin 4 (AQP4) autoantibodies in more than 100 KLS sera tested (personal communication), despite a single KLS case with anti-GAD65 autoantibodies has been reported. KLS is a remitting-relapsing disorder, as diagnostic criteria stipulate that sleep, cognition, mood and behavior are normal between episodes. However, many other remitting-relapsing disorders (e.g., bipolar disorder, multiple sclerosis, chronic obstructive pulmonary disease) comprise mild inter-episodes symptoms and signs, interrupted by sudden exacerbations, often triggered by an identified external agent. Eventually, this 'iceberg model' also applies to KLS, as several recent studies indicate that a mild, attenuated symptomatology may persist or emerge during 'asymptomatic' periods in 20-25% patients, including memory and attention difficulties, [START_REF] Uguccioni | Long-term cognitive impairment in Kleine-Levin syndrome[END_REF] as well as mood and anxiety disorders, [START_REF] Groos | Emerging psychiatric disorders in Kleine-Levin syndrome[END_REF] whereas brain functional imaging often shows hypoperfusion and hypometabolism in associative and subcortical brain area during asymptomatic periods. [START_REF] Arnulf | Diagnosis, disease course, and management of patients with Kleine-Levin syndrome[END_REF] The mechanisms of KLS still remain to be determined in the future, thanks to large, national and international cohorts.

Counts


MD Milan Nigam

MSc Amandine Hippolyte

MD Pauline Dodet

MD Ana Gales

MD Jean-Baptiste Maranci

Saba Al-Youssef

MD Smaranda Leu-Semenescu

MD Isabelle Arnulf
email: isabelle.arnulf@aphp.fr

Sleeping through a Pandemic: Impact of COVID-19 Related Restrictions on Narcolepsy and Idiopathic Hypersomnia

Keywords: narcolepsy, hypersomnia, COVID-19, Sars-CoV-2, lockdown, confinement, teleworking

Study objectives: To assess the impact of COVID-19 related restrictions on narcolepsy type 1 (NT2), narcolepsy type 2 (NT2), and idiopathic hypersomnia (IH).

Methods: Participants with NT1, NT2 and IH followed in a university hospital completed an online 78-question survey assessing demographic, clinical and occupational features of the population during the first COVID-19 related lockdown.

Results:

The 219 /851 (25.7%) respondents of the survey reported a mean increase of 1.2±1.9 hours (P<.001) in night sleep time, and a mean decrease of 1.0±3.4 points (P<.001) on the Epworth sleepiness scale during lockdown. Bedtime was delayed by 46.1% of participants and wakeup time was delayed by 59.6%, driven primarily by participants with IH. Teleworkers (but not in-person workers) reported a mean increase of 0.9±1.2 hours in night sleep (P <.001) and a mean decrease in sleepiness score of 1.6± 3.1 (P <.001). Cataplexy improved in 54.1% of participants with NT1.

Sleepiness correlated with psychological wellness (R=0.3, P<.001). As many as 42.5% enjoyed the lockdown, thanks to reallocation of time usually spent commuting towards longer sleep time, hobbies and family time, and appreciated a freer napping schedule. Conversely, 13.2% disliked the lockdown, feeling isolation and psychological distress.

Conclusion:

Extended sleep time, circadian delay (in IH patients) and teleworking resulted in decreased symptoms of central hypersomnias. These findings suggest that people with IH, NT1 and NT2 may benefit from a decrease in social and professional constraints on sleep-wake habits, and support advocacy efforts aimed at facilitating workplace and schedule accommodations for this population.

Introduction

The COVID-19 worldwide pandemic has forced countries around the world to adopt stringent measures aimed at curbing the spread of the highly infectious SARS-CoV-2 virus. France was first put under such a lockdown from March 17 th to May 11 th, 2020. Specific measures put in place included prohibitions on travelling, outdoor activities, and in-person schooling and working.

Work-from-home (teleworking) was mandated for all but essential workers (e.g., healthcare workers, grocers and transportation workers). [START_REF]République Pdl[END_REF] Much interest has been generated within the sleep medicine community on the effects of the COVID-19 pandemic and associated lockdown measures on the sleep health of the general public and many have reported increased insomnia and circadian rhythm changes. [START_REF] Altena | Dealing with sleep problems during home confinement due to the COVID-19 outbreak: Practical recommendations from a task force of the European CBT-I Academy[END_REF][START_REF] Cellini | Changes in sleep pattern, sense of time and digital media use during COVID-19 lockdown in Italy[END_REF][START_REF] Gupta | COVID-Somnia: How the Pandemic Affects Sleep/Wake Regulation and How to Deal with it?[END_REF] The experience of people living with central hypersomnias during COVID-19 related restrictions is of particular interest. Narcolepsy is characterized by excessive daytime sleepiness, short and refreshing naps and REM sleep state dissociation. Narcolepsy type 1 (NT1) is further distinguished from narcolepsy type 2 (NT2) by cataplexy and hypocretin deficiency. Idiopathic hypersomnia (IH) is characterized by sleepiness despite normal or prolonged sleep time, long non-refreshing naps and sleep drunkenness. A key difficulty faced by this population lies in the reconciliation of their particular sleep needs (e.g., increased total sleep time or frequent napping) with their daytime obligations (e.g., work, schooling, etc.). This conflict accounts for a worsened quality of life, and may contribute to excessive daytime sleepiness. [START_REF] Vignatelli | Health-related quality of life in Italian patients with narcolepsy: the SF-36 health survey[END_REF][START_REF] Ervik | Health-related quality of life in narcolepsy[END_REF][START_REF] Dodel | Health-related quality of life in patients with narcolepsy[END_REF] We seized upon the opportunity of lockdown to understand how changes in social and professional constraints on sleep-wake habits affect people with central hypersomnias, using a survey sent to patients followed in our academic unit.

Methods

Participants

Eligible participants were patients diagnosed with NT1, NT2 or IH as per ICSD-3 criteria [START_REF] Sateia | International classification of sleep disorders-third edition: highlights and modifications[END_REF] and followed at the National Reference Centre for Narcolepsy and Rare Hypersomnias at Pitié-Salpétrière Hospital's Sleep Disorders Unit. Approximately 1600 such patients are followed at our centre, of whom approximately one half have given their e-mail address (at the time of this study) for participation in research projects. Participants who responded to an email containing the survey were included in the study. The sole exclusion criterion was non-completion of the survey. All participants gave consent for use of their responses in the present publication, in accordance with French research ethics laws.

Questionnaire

A 78-question survey was devised by a team of sleep medicine experts using the SurveyMonkey software (SurveyMonkey Inc, California, USA). The questionnaire assessed participants' demographic features, occupational status, COVID-19 status, sleep habits, hypersomnia symptoms, Epworth sleepiness scale (ESS), treatments and any changes to the above that occurred as a result of the COVID-19 related lockdown measures in France (See Appendix A1 for the complete questionnaire in original French and translated into English). Changes in sleepiness were assessed by asking participants to first complete an ESS questionnaire retrospectively assessing their pre-lockdown somnolence (ESS scores just preceding the lockdown were not available in most participants' charts), followed by an ESS questionnaire assessing current somnolence.

Similarly, participants were asked to first estimate their night sleep time prior to lockdown, followed by a report of their contemporary night sleep time. The majority of questions contained in the survey were closed, multiple choice or yes/no questions (e.g., "Was "x" increased, decreased or unchanged during lockdown?), assessing changes in sleep related symptoms and habits, psychological symptoms and general perceptions related to the lockdown. The questionnaire concluded with two open ended questions pertaining to participants global appreciation the lockdown: "If you liked/disliked the lockdown, why/why not?". The survey was sent to prospective participants one week prior to the end of the first COVID-19 related lockdown in May 2020 and was available for completion during a six-day window.

Statistical analysis

P-value significance was set below 0.05. All statistical analyses were computed using R version 4.0.3 (2020) from the R Foundation for Statistical Computing (Vienna, Austria). Three group comparisons of quantitative variables were performed using one-way analysis of variance (ANOVA). Three group comparisons of binary categorical variables were performed using Chisquare (presented as χ 2 , degree of freedom, P) or Fisher's exact test (presented as Odd Ratio, OR, 95%CI, P), depending on sample size. Ordinal categorical variables were assessed using ordinal logistic regression. Comparisons of teleworkers to in-person workers, and within group comparisons for measures assessed before and during lockdown were performed using Student's t-test. Correction for multiple testing was done using Bonferroni's adjustments (obtained P value were multiplied by the number of comparisons done for a given hypothesis test).

Using the "FactoMineR" package in R, multiple correspondence analysis (MCA) was performed as an exploratory technique to assess additional relationships between qualitive measures related to psychological wellbeing and sleep quality. MCA permits the representation of a large number of qualitative measures graphically in multidimensional space and identifies those dimensional axes that explain the largest variability within the dataset (percentage of inertia). Further assessment was performed to determine which qualitative measures were the principal determinants of the identified axes (measures with R 2 score larger than or equal to 0.3 were considered important). Finally, supplemental quantitative and qualitative variables expected to relate to these dimensions (telework, changes in sleep time, ESS, and others) were assessed for correlation to the principal dimensional axes.

Inductive thematic analysis

In order to extract meaningful information from participants' open-ended responses to the questions specified above, inductive thematic analysis was employed. This subtype of reflexive thematic analysis is a common methodology in qualitative research used to identify patterns of meaning across a dataset (i.e., open ended responses, texts, speeches). This is achieved through a structured process of data familiarization, coding of data extracts, development and naming of themes and revision. Inductive thematic analysis differs from deductive thematic analysis in that codes are induced based on the data, rather than pre-determined based on the author's research questions. In the present study, inductive thematic analysis was performed using the step-by-step framework set forth by Braun and Clarke. [START_REF] Braun | Using thematic analysis in psychology[END_REF] Data familiarization was first achieved by repetitive reading of participants' responses. Codes were then induced from the data extracts by recognizing patterns of semantic (explicit) and latent (implicit) meaning (see supplemental table S1 for examples of the coding process). Coding was done manually, without the use of specialized software. Using a conceptual map, codes were then grouped together into encompassing themes.

Themes were then reviewed and named during a group discussion with all co-authors until all were in agreement. Representative data extracts (participant citations) are presented to justify and support the identified themes. Participant responses were translated from French to English by the first author of this paper, a bilingual native English speaker.

Results

Participants

The questionnaire was sent to 851 participants with NT1, NT2 and IH. A total of 225 responded to the survey (return rate: 26.5%). Among IH participants, 77/88 (87.5%) had a form with long sleep time. The mean time to completion of the survey was 24 minutes and 11 seconds. Six participants were excluded for incomplete surveys and thus 219 participants were included in the final analysis. Table 1 summarizes the main clinical and demographic features of our participants grouped by hypersomnia type. Of the respondents, 73 had NT1, 58 had NT2 and 88 had IH. There were no between-group differences, with the exception of sex (women being more common in the IH group compared to NT1, but not NT2).

Impact of lockdown measures

The impact of lockdown measures on nighttime sleep habits and symptoms is displayed in Table 2. Night sleep time increased in all groups, and no difference was observed between hypersomnia subgroups. Insomnia was reported at some point during lockdown by 51.8% of participants.

Participants with NT1 were more likely to report insomnia than those with IH (χ 2 = 5.8, df = 1, P = 0.004), but not NT2 (χ 2 = 0.8, df = 1, P = 1). Overall, 46.1% of participants reported delaying bedtime and 59.6% reported delaying wakeup time. This trend towards sleep phase delay was driven by participants with IH, who were more likely to delay both bedtime and wakeup time compared to participants with NT1 (P<.01, P<.01 for bedtime and wakeup time, respectively) and NT2 (P <.001, P <.01).

Changes in daytime symptoms, fatigue, concentration, naps, sleep attacks, and stimulant dosages during the lockdown are shown in Table 3. Participants reported a mean decrease in ESS score of 1 ± 3.4 with no difference between hypersomnia subgroups (P = 0.6). Within-group comparisons showed that this ESS decrease was significant in IH and NT2 groups, and tended to be significant in the NT1 group (P = 0.08). Fifty-five (25.1%) participants reported a greater than 3 decrease in ESS. On average, 32% of participants reported less fatigue, 27.3% reported a better concentration, 30.1% reported a decrease in sleep attacks frequency, despite the fact that 35.7% had decreased their dosage stimulants. There were no further between-group differences in fatigue, concentration, number of naps per day, sleep attacks or stimulant dose adjustments.

Among the 61 participants with NT1 who typically had cataplexy pre-lockdown, 54.1% reported a decrease or disappearance of cataplexy, while 14.8% reported increased cataplexy and 31.1% reported no change. Sleep related hallucinations decreased in 35.0% of participants with NT1, increased in 10.7% and were unchanged in 54.3%. In participants with NT2, 34.5% experienced a decrease in sleep related hallucinations, 1.7% reported an increase and 63.8% reported no change.

In participants with IH, 71.6% reported difficulty getting out of bed, and 22.7% did not during lockdown. However, this percentage was not contrasted with pre-lockdown measures.

Measures of psychological wellness changes during lockdown are shown in supplemental table S2. Although mood, irritability, and stress worsened and improved similarly in participants, 42.5% of them appreciated the lockdown period, 13.2% disliked this period, and the remaining 44.3% had a neutral opinion. There were no further group differences in mood changes, stress level, irritability and overall appreciation of the lockdown.

Comparisons of teleworkers to in-person workers

At the beginning of the lockdown, 138 participants were employed on a full or part time basis. Of those, 74 (53.6 %) transitioned to teleworking, while 24 (17.4%) continued to work at their usual workplace (in-person workers) and the remaining 40 (29.0%) were placed on temporary paid leave as a result of pandemic related social assistance, protecting citizens from loss of employment. Table 4 summarizes the differences between teleworkers and in-person workers. Hypersomnia subtypes were present in similar proportions in each group. There were more white-collar workers among teleworkers (OR: 6.2; 95% CI [1.5-28.4]). As expected, commuting time (total duration per day) changed to 0 in teleworkers, and was probably unchanged in in-person workers (we only asked for usual commuting time). There was no difference for typical workday start time between teleworkers and in-person workers. Within-group testing revealed a prolongation of night sleep time and a decrease in ESS scores (on average -1.6) during lockdown among teleworkers, but not in-person workers. Between group comparison revealed a trend among teleworkers towards larger improvements in ESS scores and greater likelihood to report decreased fatigue (OR: 3.11, 95% CI [0.99 -11.74], P = 0.04).

Multiple correspondence analysis

MCA identified three principal dimensional axes, accounting collectively for 45.9% of the variability within the dataset (supplemental table S3). The name of each axis was based on the principal variables which determined them. Axis 1 was of most interest, accounting for 23.7% of the variance within the dataset. It was determined by variables associated with neuropsychological wellness (decreased stress and irritability, better mood, increased concentration, decreased fatigue and increased appreciation of the lockdown). Axis 2 accounting for 11.5% of variability was mainly explained by a decreased irritability and stress. Axis 3 accounting for 10.7% of variability was mainly explained by delayed sleep phase (delayed bedtime and wakeup time). Supplementary qualitative and quantitative variables hypothesized to be related to Axis 1 were identified and tested for correlation. Axis 1 was weakly associated with improving ESS score (R 2 = 0.3, p<.0001) and was not associated with age, night sleep time, number of naps per day, commuting time, hypersomnia type or teleworking status.

Thematic analysis of participants' overall assessment of the lockdown

Inductive thematic analysis of participants' responses to two open-ended questions assessing reasons why participants liked or disliked the lockdown. Seventeen codes were identified from those relating a positive experience of the lockdown and 11 codes from those relating a negative experience. These codes, were grouped into overarching themes (Figure 1): increased quality time and improved psychosocial wellbeing; worsened psychosocial wellbeing; and improved/worsened sleep-wake quality and hypersomnia symptoms. Representative data extracts are shown in Table 5. Among those who noted an improvement in the quality of sleep and alertness, many alluded to a pace of life more compatible with their sleep disorder, allowing increased time in bed and a freer napping schedule as a mitigating factor for somnolence during lockdown. Several participants also expressed relief at reduced exposure to social stigma in public settings related to their disorder.

Many participants reported that the lockdown measures allowed them to reallocate time (often spent commuting) towards increased quality time (more time with family and practicing hobbies) leading to improvement of their psychological and physical wellness. Among those who disliked the lockdown, several participants reported that the loss of regularly scheduled zeitgebers disrupted their circadian rhythm. Commonly, participants described feelings of isolation, loss of freedom, boredom and anxiety which often caused disturbances in sleep.

Discussion

Our participants reported increased night sleep time and decreased daytime sleepiness during lockdown, an effect more marked in teleworkers than in person-workers. A plurality of participants reported delaying their bedtime and wakeup time, which was driven by participants with IH. Half of participants with NT1 reported a decrease or disappearance of cataplexy. Stimulant dosage was decreased by nearly one third of participants. In contrast, half of all participants reported insomnia during lockdown. Neuropsychological wellness was associated with decreasing sleepiness scores.

A minority of participants disliked the lockdown, while thrice as many enjoyed it. Many participants reported that the lockdown allowed the reallocation of time usually spent commuting towards sleep, hobbies and family time. Many also reported benefitting from a longer sleep time, a freer napping schedule and improved daytime vigilance daytime vigilance. By contrast, some expressed feelings of isolation and psychological distress during lockdown. Daytime sleepiness decreased in all disorders (although less in NT1 than in NT2 and IH) on average by 1 point of ESS. This modest but significant change was obtained despite unchanged or decreased dosage of stimulants in most participants. Decreased fatigue and better concentration were reported in one third of participants. The mechanisms of these improvements may be different across diseases, including increased nighttime sleep, sleep phase delay, free napping schedules, and a general psychological wellbeing (which correlated with improved sleepiness). People with narcolepsy generally have normal 24-hour total sleep time, but experience an ultradian rhythm, characterized by multiple sleep periods (including refreshing naps) rather than a single, consolidated sleep period. [START_REF] Bassetti | Narcolepsy -clinical spectrum, aetiopathophysiology, diagnosis and treatment[END_REF] In their open-ended statements, many participants reported that during lockdown, they were freer to nap as needed, improving their somnolence, though there was no quantitative assessment of changes in nap frequency. In addition, cataplexy mostly improved in our sample, possibly as a consequence of improved sleepiness and decreased social interaction (a primer of cataplexy attacks). Contrary to people with narcolepsy, people with IH often report long sleep times, evening chronotypy, [START_REF] Landzberg | Is Idiopathic Hypersomnia a Circadian Rhythm Disorder?[END_REF][START_REF] Vernet | Idiopathic Hypersomnia with and without Long Sleep Time: A Controlled Series of 75 Patients[END_REF] and long, unrefreshing naps. [START_REF] Trotti | Central Disorders of Hypersomnolence[END_REF] Participants slept one hour longer during than before lockdown, and this was more marked in IH, probably decreasing sleepiness and fatigue, as observed during vacation. A frequent sleep phase delay was found in our population (as in the general working population during COVID-19 pandemic [START_REF] Altena | Dealing with sleep problems during home confinement due to the COVID-19 outbreak: Practical recommendations from a task force of the European CBT-I Academy[END_REF][START_REF] Cellini | Changes in sleep pattern, sense of time and digital media use during COVID-19 lockdown in Italy[END_REF][START_REF] Gupta | COVID-Somnia: How the Pandemic Affects Sleep/Wake Regulation and How to Deal with it?[END_REF][START_REF] Franceschini | Poor Sleep Quality and Its Consequences on Mental Health During the COVID-19 Lockdown in Italy[END_REF] ), possibly reflecting a shift towards their innate chronotype absent the usual social constraints. A similar phase delay has been reported among patients with narcolepsy in Brazil during the COVID-19 pandemic (though in our sample, phase delay was driven by IH more than narcolepsy). [START_REF] Aguilar | The effects of the COVID-19 pandemic on patients with narcolepsy[END_REF] It is possible that under lockdown conditions, many people with narcolepsy and IH more easily adapted their sleep schedule in accordance with their biological needs.

Half of participants, however, experienced insomnia (more in NT1) at some point during the lockdown (though the survey did not assess baseline insomnia). In their open-ended statements, many participants who reported worsened sleep quality attributed this to increased anxiety and loss of their usual zeitgebers. In comparison, a large survey study among the general population in France during the same time as our study demonstrated a prevalence of 74% of troubled sleep during the pandemic (increased from 49% in a previous survey in 2017). [START_REF] Beck | Covid-19 health crisis and lockdown associated with high level of sleep complaints and hypnotic uptake at the population level[END_REF] Similar findings in the general population have been reported in a Canadian survey study, which further found that only 6% of the general population reported improved sleep during the pandemic. [START_REF] Robillard | Profiles of sleep changes during the COVID-19 pandemic: Demographic, behavioural and psychological factors[END_REF] The striking differences between our observations in people with hypersomnia and the reported data in the general population are likely a reflection of the fundamental neurobiological differences underlying different sleep needs between these populations. People with hypersomnia have been subject to the same factors posited to cause sleep disturbances during the pandemic as the general population (stress, increased screen time, etc.) and many participants did report disturbed sleep.

However, it appears that for most participants, the factors negatively impacting sleep were outweighed by the advantages associated with a less constrained sleeping schedule.

The COVID-19 pandemic has normalized telework globally on a large scale, which is likely to have a lasting impact beyond the pandemic. In our study, a decrease in sleepiness and fatigue as well as an increase in sleep time (reallocated from commuting time) were observed in teleworkers, but not in-person workers. Many of our participants also specifically evoked teleworking and its more adaptable schedule as a key factor in improving sleep-wake quality and work performance and related easing in social stigma and anxiety related to their hypersomnia symptoms. These findings support the data reported by Postiglione et al. showing that during the first COVID-19 related lockdown in Italy, 22 participants with NT1 who worked from home experienced increased sleep time and decreased ESS scores. [START_REF] Postiglione | Impact of COVID-19 pandemic lockdown on narcolepsy type 1 management[END_REF] Our results extend these findings to NT2 and IH participants. Rodrigues Aguilar et al did not report an association between changes in employment and narcolepsy symptoms, though they did not perform any direct comparisons between teleworkers and in-person workers. [START_REF] Aguilar | The effects of the COVID-19 pandemic on patients with narcolepsy[END_REF] Narcolepsy and IH impair work resulting in decreased healthrelated quality of life, [START_REF] Ervik | Health-related quality of life in narcolepsy[END_REF][START_REF] Dodel | Health-related quality of life in patients with narcolepsy[END_REF][START_REF] Broughton | Comparison of the psychosocial effects of epilepsy and narcolepsy/cataplexy: a controlled study[END_REF][START_REF] Daniels | Health-related quality of life in narcolepsy[END_REF][START_REF] Dodel | The socioeconomic impact of narcolepsy[END_REF][START_REF] Teixeira | Functional status in patients with narcolepsy[END_REF] and in loss or change in employment in 30.3% to 42.7%. [START_REF] Dodel | Health-related quality of life in patients with narcolepsy[END_REF][START_REF] Daniels | Health-related quality of life in narcolepsy[END_REF][START_REF] Ozaki | Quality of life in patients with narcolepsy with cataplexy, narcolepsy without cataplexy, and idiopathic hypersomnia without long sleep time: comparison between patients on psychostimulants, drug-naïve patients and the general Japanese population[END_REF] Patients report significant social stigma associated with sleepiness and cataplexy. Fear of being perceived as lazy is common, and people frequently adopt avoidance behaviours out of fear of precipitating cataplectic attacks in front of others. [START_REF] Kapella | Health-related stigma as a determinant of functioning in young adults with narcolepsy[END_REF][START_REF] Raggi | Health-Related Quality of Life in Patients With Narcolepsy: A Review of the Literature[END_REF] Ozaki and colleagues have reported that the autonomy to control one's job schedule (including nap opportunities) was associated with increased quality of life in people with NT1, NT2 or IH. [START_REF] Ozaki | Quality of life in patients with narcolepsy with cataplexy, narcolepsy without cataplexy, and idiopathic hypersomnia without long sleep time: comparison between patients on psychostimulants, drug-naïve patients and the general Japanese population[END_REF] Despite these compelling data, workplace and schedule adaptations may be underprovided, though the reasons are not clear. [START_REF] White | Academic and professional paths of narcoleptic patients: the Narcowork study[END_REF] Taken together, our results, combined with this existing literature, suggest that offering increased access to telework, or perhaps simply allowing work environment and scheduling adjustments to better accommodate the needs of people with hypersomnia, has the potential to improve sleepiness, work performance and quality of life.

Appreciation of the lockdown was clustered with measures of psychological wellbeing (including stress, mood, irritability, concentration and fatigue). Participants who enjoyed the lockdown commonly evoked that they had more time to spend for their loved ones, pursuing hobbies, introspection and physical activities. Many specifically mentioned gratitude at no longer having to squander time commuting to and from work. Furthermore, improved psychological wellness and decreased sleepiness correlated, although the direction of causality may be bidirectional. By contrast, many participants related decreased psychological wellbeing, related not only to anxiety concerning COVID-19, but also due to boredom, isolation and loss of freedom. Approximately one third of participants reported worsened mood, stress and irritability during the lockdown. This proportion is similar to those reported in the general population in systematic reviews and metaanalyses reporting prevalence between 30-40% for stress, and mood and anxiety disorders. [START_REF] Salari | Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: a systematic review and meta-analysis[END_REF][START_REF] Wu | Prevalence of mental health problems during the COVID-19 pandemic: A systematic review and meta-analysis[END_REF] One might have expected a higher proportion of our participants to experience psychological disturbances than what we observed, as people with hypersomnia are known to be at increased risk of anxiety and mood disorders. [START_REF] Dauvilliers | Psychological health in central hypersomnias: the French Harmony study[END_REF] This may be partly related to pandemic related social assistance programs in France guaranteeing salaries in the case of work leave caused by the pandemic, protecting citizens from loss of employment and mitigating financial burden compared to many other countries.

We acknowledge some limitations to our study. Firstly, our survey had a modest response rate (26.5%). Despite this, the sample was substantial and included participants with well-characterized disorders, diagnosed in a reference center, and included IH participants, a disorder less studied than narcolepsy. The response rate is likely attributable to the length of the survey (mean completion time 24 min), a high volume of spam mails and a single presentation of the study without reminders. Participants being asked to recall their pre-lockdown somnolence introduces the possibility of recall bias. This was necessary, however, as ESS scores shortly prior to lockdown were not available in most participant's charts. The questionnaire was designed "in-house" as a means to assess the real-world experience of our patients with hypersomnias. However, the inclusion of validated scales assessing the severity of narcolepsy and IH would have been informative and added to the robustness of our data. Some perspectives expressed by participants during this first lockdown in the first few months of the COVID-19 pandemic may not be reflective of their experience during subsequent lockdowns, as the pandemic has endured. Notably, use of online video communications technology (such as Zoom ® ) may have been less widespread during initial lockdown. Thus, participants may not yet have experienced so-called "Zoom-fatigue". [START_REF] Wiederhold | Connecting Through Technology During the Coronavirus Disease 2019 Pandemic: Avoiding "Zoom Fatigue[END_REF] Although our population was large, the group of in-person workers was relatively small, which may have limited statistical power for between-group comparisons.

In conclusion, we found that participants with IH, NT1 and NT2 experienced increased sleep time and decreased daytime somnolence during the first COVID-19 related lockdown. This may have been driven by decreased social and occupational constraints on sleep-wake habits, allowing an economy of commuting time, increased nighttime sleep, physiological circadian realignment and increased nap opportunities. We also noted that teleworking was associated with decreased fatigue and somnolence. These findings provide preliminary evidence suggesting that workplace adaptations for people with hypersomnia which ease social sleep constraints (including partial teleworking and protected nap time) may be beneficial. Because of its potential importance for patient advocacy efforts, this hypothesis warrants confirmation in future prospective studies.

Table 1 : Demographic, occupational and clinical features of participants with narcolepsy type 1 (NT1), narcolepsy type 2 (NT2) and idiopathic hypersomnia (IH)

 1 More women were present in the IH group compared to NT1 (P<0.008).

	Data displayed in % (n) unless otherwise indicated

*

Table 2 : Nighttime sleep habits and symptoms during lockdown

 2

		Total	NT1	NT2	IH	P B
	Mean night sleep time, hours (SD)
	Pre-lockdown	8.3 (1.4)	7.8 (1.7)	7.9 (1.7)	8.3 (1.4)
	Lockdown ∆ Sleep time	9.1 (2.1) 1.2 (1.9)	8.5 (1.8) 0.9 (0.7)	8.5 (2.4) 0.7 (1.7)	9.6 (2.1) 1.3 (1.9)	.3
	P A	<.001	.001	.004	<.001
	Insomnia during lockdown
	% Yes (n)	51.8 (113)	60.0 (45)	50.8 (30)	43.2 (38)	.04
	Change in bedtime during lockdown, %, (n)
	Later	47.6(101)	37.5 (27)	39.3 (22)	61.9 (52)
	No change	39.1 (83)	47.2 (34)	39.3 (22)	32.1 (27)	.002
	Earlier	13.2 (28)	15.3 (11)	21.4 (12)	59.5 (5)
	Change in wakeup time during lockdown, %, (n)
	Later	63.1 (130)	46.5 (33)	60.0 (33)	80.0 (64)
	No change	25.2 (52)	36.6 (26)	21.8 (12)	17.5 (14)	<.001
	Earlier	11.7 (24)	16.9 (12)	18.2 (10)	2.5 (2)
	Data displayed in % (n) unless otherwise indicated

A: Significance testing for within group comparison before and during lockdown B: Significance testing for between group comparisons

Table 3 : Daytime sleep habits and symptoms during lockdown

 3

		Total (219)	NT1 (73)	NT2 (58)	IH (88)
	Mean ESS (SD)
	Before lockdown	14.4 (4.8)	15.5 (4.8)	14.3 (4.9)	13.4 (4.5)
	During lockdown	13.4 (5.3)	14.7 (5.6)	12.9 (5.2)	12.5 (4.8)
	∆ ESS	-1.0 (3.4)	-0.8 (3.3)	-1.4 (3.8)	-0.9 (2.9)
	P A	<.001	.08	<.001	<.01
	Less fatigue, % (n)	32.0 (70)	37.0 (27)	25.9 (15)	31.8 (28)
	Better concentration, % (n)	27.3 (60)	23.3 (17)	24.1 (14)	33.0 (29)
	Naps per day (SD)	1.2 (1.0)	0.8 (1.1)	1.4 (1.0)	1.1 (0.6)
	Sleep attack frequency, % (n)
	Decreased	30.1 (66)	38.4 (28)	31.0 (18)	22.7 (20)
	Unchanged	54.3 (119)	42.5 (31)	62.1 (36)	59.1 (52)
	Increased	15.5 (34)	19.1 (14)	7.9 (4)	18.2 (16)
	Stimulant dose adjustments, % (n)
	Reduced dose	35.7 (66)	29.6 (21)	36.9 (24)	42.9 (21)
	Same dose	61.6 (114)	63.4 (45)	63.1 (41)	57.1 (28)
	Increased dose	2.7 (5)	7.0 (5)	0	0
	Data displayed in % (n) unless otherwise indicated

A: Significance testing for within group comparison before and during lockdown

Table 4 : Outcomes in teleworkers versus in-person workers

 4

		Teleworkers (74)	In-person workers (24)	P B
	Hypersomnia type
	NT1	28.4 (21)	33.3 (8)
	NT2	27.0 (20)	16.7 (4)	0.5
	IH	44.6 (33)	50.0 (12)
	Occupation
	White collar	91.9 (68)	62.5 (15)
				.005
	Blue collar	6.8 (5)	29.2 (7)
	Commuting time before and during lockdown, min (SD)
	Before	71.2 (48.9)	55.6 (51.8)	n/a
	During	0	55.6 (51.8)
	Workday start time, hh:mm (SD)	9:10 (1.1)	8:39 (1.8)	0.2
	Mean night sleep time before and during lockdown, h (SD)
	Before	7.9 (1.4)	8.0 (1.6)
	During ∆ Sleep time	8.8 (1.8) 0.9 (1.2)	8.5 (2.1) 0.6 (1.4)	.17
	P A	<.001	.3
	Mean ESS before and during lockdown (SD)
	Before	14.0 (4.2)	13.4 (3.7)
	During ∆ ESS	12.6 (5.1) -1.6 (3.1)	13.3 (4.4) -0.1 (3.7)	.08
	P A	<.001	.7
	Less fatigue	47.2 (35)	20.8 (5)	.04
	Insomnia	50.0 (37)	58.3 (14)	.63
	Naps per day (SD)	0.9 (0.8)	1.2 (0.9)	.22
	Data displayed in % (n) unless otherwise indicated
	A: Significance testing for within group comparison before and during lockdown
	B: Significance testing for between group comparisons
	*Commuting time during lockdown was deduced on the assumption that teleworkers reduced their commuting time to 0, with
	approximately unchanged commuting time in teleworkers.

Table 5 : Representative participant citations identified during inductive thematic analysis

 5 For once in my life, it was as if society was moving at my own pace (…) a less constrained schedule increased my joie de vivre." "I slept in one hour later and napped as needed in the afternoon, which allowed me to be more attentive during afternoon classes." "(…) My bed is always accessible with no obstacles to napping (…) This allows me a better sleep hygiene and improved work efficiency."

	Codes/Themes	Representative extracts
	a) Enjoyed lockdown
	Improved sleep schedule "Decreased social stigma "(…) I don't have to constantly hide my somnolence, fatigue, yawning and need to nap. Not being told 'you look tired!'" "(…I am less stressed by social interactions, as I no longer have to apologize for
	being tired."
	Quality time and improved
	psychological wellness

"Not having to commute to work allowed me to get up later and spend more time pursuing hobbies that I don't usually have time for." "Having less obligations and a freer schedule allows me to spend precious time with my child and husband." b) Disliked lockdown Perturbed schedule "The loss of structure and temporal cues was difficult. Although waking up early to get my children to school is difficult, it helps me to have a structured daily rhythm." "Staying at home is the worst thing possible for my sleep. I had great difficulty maintaining a regular schedule and sleep/wake times." Mood and sleep disturbance "I had a lot of difficulty dealing with solitude. The uncertainty and anxiety disturbed by sleep." "I was bored and felt imprisoned, which worsened my anxiety."

Acknowledgements:

MN would like to acknowledge the Department of Neurosciences at the University of Montreal for it's financial support in the form of an educational grant.

Financial support: PNMR3 (National Program for Rare Diseases) to IA MN has received an educational grant from Paladin Labs pharmaceuticals and from department of neurosciences at University of Montreal SLS has speaking engagements with UCB Pharma.

IA has received consultant fees from Idorsia Pharma, Ono Pharma, and speaker honoraria from UCB Pharma.

List of figures