Kun Jiang

Alessandro Victorino

Ali Charara

Estimation and prediction of vehicle dynamics states based on fusion of OpenStreetMap and vehicle dynamics models*

This paper presents a novel approach for estimation and prediction of vehicle dynamics states by incorporating digital road map and vehicle dynamics models. Precise information about vehicle dynamics states is essential for the safety and stability of vehicle. In particular, the tire-road contact forces and vehicle side slip angle are the most important parameters for evaluating the safety of vehicle. Nevertheless, these dynamics states are immeasurable with low cost sensors. Therefore, different observers, or the so-called virtual sensors are developed to estimate vehicle dynamics states. However, the existing observers are only capable in estimating vehicle dynamics states at a current instant but not to predict the potential dangers in a future instant. In order to make time for correcting drive behaviors, especially when driving at high speed, it seems very appealing for us to predict an impending dangerous event and react before the danger occurs. In this paper, the estimation of vehicle dynamics states is based on the fusion of information from inertial sensors, GPS and OpenStreetMap. The geometry of the upcoming path ahead of vehicle is provided by the digital map and is employed to predict the future dynamics states.

I. INTRODUCTION

The development of an active safety system that can prevent the potential accidents is a critical research topic. Nowadays many safety assistance systems are already equipped on modern vehicles, such as anti-block brake system (ABS) and electronic stability program (ESP). We can classify all these safety system according to its trigger time, as shown in Figure 1. According to the report of U.S Department of Transportation [START_REF] Liu | Run-Off-Road Crashes: An On-Scene Perspective[END_REF], for the vehicles equipped with both ABS and ESC, 7.5 percent ran off the road, while for the vehicles equipped with neither ABS nor ESC, 14.6 percent ran off the road. It is clear that these active safety system has enhanced the road safety. However, these systems typically react to an event that has already occurred. In some dangerous situation, it is too late or too complicated to avoid the accidents when the signs of dangers have already occurred. In order to reduce the driver performance errors, a better strategy is to warn the driver about the potential dangers much earlier and prevent the vehicle from arriving at such high speed in the beginning.

In order to preview the potential accidents, two tasks have to be accomplished: 1, estimation of the current vehicle dynamics states; 2, prediction of the future vehicle dynamics *This work was carried out in the framework of the Labex MS2T, which was funded by the French Government, through the program "Investments for the future" managed by the National Agency for Research (Reference ANR-11-IDEX-0004-02) 1 The authors are with Sorbonne universités, Université de technologie de Compiègne, CNRS UMR 7253, Heudiasyc, 60205, France. Email: kun.jiang@hds.utc.fr, acorreau@hds.utc.fr, acharara@hds.utc.fr Fig. 1. Classification of vehicle safety system according to its trigger time states in the coming path. Today, the task of estimating vehicle dynamics states is still challenging due to economical and technical reasons. Many observers based on low-cost sensors have been proposed in the literature. Most of these research is based on Kalman filter. The Extended Kalman filter is implemented in [START_REF] Chen | Sideslip angle estimation using extended Kalman filter[END_REF] to estimate tire/road forces and side slip angle and steering stiffness. The common objective of these estimators is to detect and correct the errors of inertial sensor measurement. The accuracy of these estimators depends on the quality of inertial sensors. In this paper, we propose to incorporate the information from digital map to improve the current estimation and furthermore provide prediction of the future states. The digital map we used is a free editable map, the OpenStreetMap. The road bank angle and road friction coefficient are important for vehicle dynamics but are difficult for vehicle to measure. However it is possible to obtain these information by using a digital map. Furthermore, digital map can be used to predict future road geometry or road surface condition,such as the sudden change of road condition (e.g. icy road, sharp turn). We propose to synthesize all vehicle dynamics information to provide an risk assessment of vehicle's safety. In the literature, various methods are presented to develop risk assessments. In [START_REF] Bouton | A rollover indicator based on the prediction of the load transfer in presence of sliding: application to an All Terrain Vehicle[END_REF], a rollover indicator is proposed to predict the vehicle rollover phenomenon of light all terrain vehicles. Some other vehicle rollover prediction method can be equally found in [START_REF] Imine | Rollover risk prediction of heavy vehicle in interaction with infrastructure[END_REF] for heavy vehicles. [START_REF] Sentouh | Advanced vehicle infrastructure-driver speed profile for road departure accident prevention[END_REF] proposes a algorithm for the curve speed prediction which addresses control loss due to excessive speed in curves. [START_REF] Jiang | Adaptive estimation of vehicle dynamics through RLS and Kalman filter approaches[END_REF] proposes a vehicle full-state estimation system to describe overall vehicle dynamics.

The main contribution of this paper is to incorporate the digital-map and inertial sensors to estimate and predict the safety of vehicle. The method of how to get the road information through OSM is presented in Section II. Then section III describes the vehicle dynamics models and the risk assessment index. In Section IV, the whole estimation algorithm is presented. The results of experimental validation is illustrated is in Section V. Finally, concluding remarks and future perspectives are given in Section VI.

II. ROAD GEOMETRY ESTIMATION

OSM is a platform capable of describing a variety of information about roads. Typically, the OSM data is stored in a xml file. The OSM data model consists of three basic geometric elements: 1,N ode, which defines points in space. Each node comprises at least an id number and a pair of coordinates. 2,W ay, which represents linear features and area boundaries and is defined by an ordered list of nodes. 3, Relation, which is used to explain how other elements work together. Each element can be attributed to multiple tags to represent different road information.

A. Road geometry description

The first problem we encountered is how to describe the road geometry with OSM. Note that the original database of OpenStreetMap doesn't contain the accurate information we need (curvature, friction, etc). Therefore, we created new database with our own measurement. In OSM, a road is represented by intensive and consecutive way points. It is unpractical to attribute geometry information to each point, due to the huge amount of work needed. In the publication of Victorino et al. [START_REF] Victorino | Safe navigation for indoor mobile robots,partii: Exploration, self-localization and map building[END_REF], a topological representation of the robot path is proposed. Inspired by this work, the vehicle path in this paper is represented by corridors and the nodes of their intersections. The nodes of intersections were called as Critical Points (CP). The corridors are the roads between two CPs, without any other direction to go. The CPs are the locations where the vehicle dynamics states will change a lot (roundabout, slippery region or traffic light stop). Comparison with way points, the CPs can be defined sparsely and are attributed with many properties to describe the geometry of nearby road. The list of tags we attributed to each CP is illustrated in the Table 1.

Then the corridors can be obtained by connecting two CPs, as illustrated in Table 2. It is noted that the connections between two CPs can be straight lines or curves. In order to simplify the representation of corridor, the CPs should be selected carefully and the following assumption is made.

• Hypothesis 1: The CPs are pre-calculated so that each corridor is represented by a straight line or a clothoid;

Idway Rcurve = {0, 1} Rstop = {0, 1}
• Hypothesis 2: The length of each corridor is known;

• Hypothesis 3: The change rates of road friction and road inclination angle can be approximately regarded as constant in each corridor. The road geometry information vector listed in Table 1 is noted as State = [x y h µ κ θ ϕ x ρ ψ r ]. Based on Hypothesis 3, when the corridor is a straight road. the properties of each point in the straight corridor can be easily obtained by the Equation [START_REF] Schindler | Vehicle self-localization with high-precision digital maps[END_REF].

Statecurrent = (1 -L Lcorr )State CP 0 + L Lcorr State CP n (1)
where the index "current" means the geometry of current point, "CP 0 " represents the beginning point of the corridor and "CP n " corresponds to the ending point, L is the distance between the current position and CP 0 .

When the corridor is a curve, the properties of a CP in a curve corridor can be also obtained by Equation (1), except for the position. According to the fundamentals of road design [START_REF] Kühn | Fundamentals of Road Design[END_REF], the clothoid is widely used for urban road construction. They are defined by their begin curvature κ 0 and a constant curvature change rate κ 1 and their total length l. The current curvature of a clothoid after length l c can be obtained by Equation [START_REF] Hentschel | Autonomous robot navigation based on openstreetmap geodata[END_REF].

κ(l c ) = κ 0 + κ 1 • l c (2)
The variation of tangent angle after length l c can be computed by integration of Equation (2) over l c .

ψ = κ 0 + κ(l c ) 2 l c (3)
The position of a point [x, y] in a curve corridor is given as Equation (4).

x y = x y CP 0 + 2lc ψ sin ψ 2 cos(ψ + 1 2 ψ) sin(ψ + 1 2 ψ) (4)

B. Vehicle localization

The vehicle location is measured by a differential GPS sensor. However, the GPS has the problem of signal lost. Therefore, the Kalman filter algorithm is employed to combine the direct measurement and the integration of speed.

As the kinematic model is non-linear, an Extended Kalman filter is applied to minimize the estimation errors. The continuous state equations and measurement models are given by Equation [START_REF] Victorino | Safe navigation for indoor mobile robots,partii: Exploration, self-localization and map building[END_REF].

      Ẋ Ẏ vx ψ ψ       =      sin(ψ) • vx cos(ψ) • vx ax -g sin θ ψ 0      + noise measurement :        Xgps Ygps vgps ψgps v wheel ψgyro        =        1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 1             X Y vx ψ ψ      + noise (5)
where X gps , Y gps , v gps , v whell , ψ gps , ψgyro are the measurement of GPS receiver and inertial units, ψ is the clockwise angle between the north and the vehicle direction. In this equation, we suppose the lateral speed is negligible in the calculation of displacement.

The estimated vehicle location is used to identify the corresponding point in the OSM. The searching process can be divided into two steps: firstly searching for the corresponding corridor and secondly locating the relative position in the corridor. Supposing the initial position is already known, the total distance (l total ) between current position and initial position is the sum of length of the passed corridors. Then the criterion for matching the corridor of number n is given by Equation [START_REF] Wang | Real-Time Experimental Validation of Nonlinear Observer for Vehicle Dynamics Parameters Estimation : A Laboratory Vehicle Description[END_REF].

n-1 i=1 L corr, i < l total < n i=1 L corr, i l total, t = l total, t-1 + vx • t (6)
After the current corridor is identified, the vehicle position can be calculated with the two CPs of the corridor, as shown by Equation ( 1) or (4) depending on the corridor is straight or curve. As a result, we have two additional measurement about the location which could be used to improve the Kalman filter in Equation [START_REF] Victorino | Safe navigation for indoor mobile robots,partii: Exploration, self-localization and map building[END_REF].

Xosm Yosm = 1 0 0 0 0 0 1 0 0 0      X Y vx ψ ψ      + noise (7)
To eliminate the accumulated errors in the calculation of l total , when the vehicle passed the ending point of the N th corridor, the l total will be calibrated by Equation [START_REF] Dherbomez | véhicule expérimental pour la Dynamique du Véhicule[END_REF].

l total = n i=1 L corr, i (8)

III. DIAGNOSIS OF VEHICLE DYNAMIC BEHAVIORS

A. Evaluation of safety

In order to evaluate vehicle's safety, we employ three risk assessment indexes: load transfer ratio (LT R) and lateral skid ratio (LSR), and the stopping distance (SD) [START_REF] Imine | Rollover risk prediction of heavy vehicle in interaction with infrastructure[END_REF]. The lateral load transfer ratio LT R is defined by using four wheel vertical forces as in Equation [START_REF] Liu | Run-Off-Road Crashes: An On-Scene Perspective[END_REF]. The estimation method of vertical forces at each tire is introduced in our previous work [START_REF] Jiang | Adaptive estimation of vehicle dynamics through RLS and Kalman filter approaches[END_REF].

LT R = Fz11 -Fz12 + Fz21 -Fz22 Fz11 + Fz12 + Fz21 + Fz22 (9)
The lateral skid ratio LSR represents the loss of adhesion resulting in the lateral drift. The lateral skid ratio is defined by road friction coefficient and tire forces, as in Equation [START_REF] Jiang | Adaptive estimation of vehicle dynamics through RLS and Kalman filter approaches[END_REF]. The estimation of lateral tire forces and slip angle is introduced in next subsection. The µ max is the threshold of safe friction, it should be smaller than the real friction coefficient.

LSR ij = 1 - µmax-µ ij µmax µ ij = F yij F zij (10)
The stopping distance (SD) refers to the distance needed to stop the vehicle. We assume that during the stopping process, the braking acceleration is a constant value a xmax . The a xmax is defined as to ensure the comfort of passengers. The stopping distance can be obtained by Equation [START_REF] Bouton | A rollover indicator based on the prediction of the load transfer in presence of sliding: application to an All Terrain Vehicle[END_REF].

SD = 1 2axmax v 2 x (11)

B. Vehicle dynamics models

The yaw rate, steering angle and accelerations are important parameters for vehicle dynamics estimation. In the literature, all these parameters are usually measured by inertial sensors. However, the unpredictable sensor failure may happen during driving. In this paper, we propose to employ data from digital map to provide redundant information about these basic dynamics parameters. Supposing that the vehicle successfully followed the the road curve, these vehicle dynamics parameters can be approximated by applying the kinematic relationship, as shown in Equation [START_REF] Imine | Rollover risk prediction of heavy vehicle in interaction with infrastructure[END_REF]. The errors caused by the lane changing behavior can be viewed as the noises in the curvatureκ osm .

axosm = dvx/dt + g sin θosm ayosm = v 2 x κosm + g sin ϕosm azosm = v 2 x ρosm + g cos θosm cos ϕosm ψosm = vxκosm δosm = Lvκosm (12)
where θ osm and ϕ osm are the slope and bank angle of the road, ρ osm is the vertical curvature of the road, κ osm is the planar curvature, their value are obtained by Equation (1). When the κ osm is the curvature at current point, Equation (12) can be regarded as an redundant resource of current dynamics states. While κ osm is the curvature at future point, the computed accelerations and yaw rates can be employed to predict future dynamics states. The variance of κ osm is set as 0.03 2 .

To simplify the estimation, the linear tire model and bicycle model are used to estimate the sideslip angle, as shown in Equation [START_REF] Sentouh | Advanced vehicle infrastructure-driver speed profile for road departure accident prevention[END_REF]. With this observer, we can also obtain the lateral force per axle. To obtain the lateral force at each tire, the double track model and Dugoff model are employed, as explained in our previous work [START_REF] Wang | Real-Time Experimental Validation of Nonlinear Observer for Vehicle Dynamics Parameters Estimation : A Laboratory Vehicle Description[END_REF][START_REF] Jiang | Adaptive estimation of vehicle dynamics through RLS and Kalman filter approaches[END_REF].

[ ψ βcog F xf F yf F yr ] T =        - L 2 1 C f +L 2 2 Cr Iz vx L 2 Cr -L 1 C f Iz -1 + L 2 Cr -L 1 C f mv v 2 x - C f +Cr mv vx O 2×3 O 3×2 O 3×3             ψ βcog F xf F yf F yr      + L 1 C f Iz C f mv vx δ + cov(noise)    ψIz mvay mvax 0    =     L 1 sin δ L 1 cos δ -L 2 0 0 sin δ cos δ 1 0 0 cos δ sin δ 0 0 0 L 2 vx -1 0 0 1 Cr          ψ βcog F xf F yf F yr      +cov(noise) ( 13
)
where C f , C r are side slip stiffness of front tires and rear tires. L 1 , L 2 are the distances from COG to front and rear axle. δ is steering angle. I z is vehicle yaw inertia. F yf and F yr are lateral forces at front and rear axle respectively, F xf is the longitudinal tire forces at front axle.

IV. PREDICTION ALGORITHM

The overall prediction process can be expressed by the Figure 4. The sensor measurement is used to locate the vehicle's position and identify the corresponding corridors and CPs. Then CPs can provide information about road friction coefficient which can greatly improve the the estimation of current states. Moreover, by extracting the upcoming CPs, the estimator could predict the potential variation of dynamics states. Then the dynamics states of current instant and future instant will be evaluated by three indicators of safety, introduced in the above section. To simplify the prediction process, the vehicle speed is regarded as constant and equals to the current speed during the preview time. The prediction system will perform the risk assessment for the coming 300m road. If a potential danger is detected, the system will warn the driver to slow down. The predicted dynamics states can also be used to control the stabilization system. However, in order to improve the accuracy of prediction, a more accurate model about the variation of speed is needed. Sensor based measurement and map geometry based prediction provides two independent approaches for the observation of the vehicle dynamics. The Kalman filter algorithm could combine the two observation to minimize the variance of final estimation result.

V. EXPERIMENTAL VALIDATION

The experimental vehicle DYNA is instrumented by our laboratory, as shown in Figure 6. This experimental platform is dedicated to validate the algorithm of estimating vehicle dynamics. The details about these sensors are introduced in our previous work [START_REF] Wang | Real-Time Experimental Validation of Nonlinear Observer for Vehicle Dynamics Parameters Estimation : A Laboratory Vehicle Description[END_REF][START_REF] Jiang | Adaptive estimation of vehicle dynamics through RLS and Kalman filter approaches[END_REF]. A remarkable point about our vehicle DYNA is the ability to directly measure the vertical and lateral tire forces, which were used as the ground truth to validate the estimation results. The observers were validated in an off-line algorithm. The trajectory of the vehicle during the test is illustrated in Figure 7. In total, 53 critical points and 52 corridors were defined to describe the trajectory. More CPs were defined around the sharp turning and lane changing point in order to better describe the road. Some examples of CPs and corridors are demonstrated in Table 3. A segmentation of data (150 < t < 200s) is selected due to the successive turning behaviors in this period. The maneuver time history are presented by red lines in Figure 8. The average speed is about 50 km/h. The curvature at each critical point is illustrated by red spots in Figure 7. The curvature between two critical points were computed by Equation (1), which is a linear interpolation of the two neighboring critical points. As we can see in Figure 7, the interpolation method (represented by red lines) was a simplification of real road geometry and was not always accurate. However, it effectively represented the main characteristic of the road. Then the obtained curvature was used to compute the value of accelerations and yaw rate with Equation [START_REF] Imine | Rollover risk prediction of heavy vehicle in interaction with infrastructure[END_REF]. The comparison between inertial sensor measurement and digital map based (OSM) estimation was illustrated in Figure 8. Then two data are incorporated to provide a robust estimation about the basic dynamics parameters, as represented by green lines. The estimation results of tire forces are compared with the measurement of force transducer in Figure 9. The red lines are the measurement data. The green lines represented the estimation result based on inertial sensors. The blue lines corresponded to the estimation result based on the Open-StreetMap. The accuracy of the OSM method depends on the intensity of critical points and map quality. Moreover, it is also based on the assumption that the vehicle successfully followed the planned path. At t = 175s, the driver did a lane changing behavior, which was not in the planning and caused some errors. As demonstrated by the experimental result, the inertial sensor based method can better follow the vertical force variation, while, the OSM based estimation method is accurate when the vehicle is following the curve. Fusion of these two estmation provides a better estimation of vertical force, as expressed by solid black lines in the Figure 9.a). The similar situation can be found in the estimation of lateral force. Note that the shift in the estimation of F y at front tires is caused by the Ackermann steering geometry. The steering angles at left tire and right tire are different, while we regarded as identical in this paper. The advantage of OSM is obvious in the estimation of sideslip angle. We configured the slip stiffness C r as two times of the correct value. Therefore, the estimated sideslip angle is obvious smaller than measurement. The OSM method could get the correct C r from the digital map, as we suppose C r ∝ µ. It is clear that the combined method provided a better estimation of sideslip angle. Note that due to the position of the optic sensor, the direct measurement is actually the sideslip angle at rear axle β r . The transformation between β r and β cog is given by β cog = β r + L2 ψ vx . The curvature at each point is a function of the traveled distance, as shown in Figure 7. Then it is able to predict the curvature of following 300 meters ahead of the vehicle's current postion. The vehicle's safety could be evaluated with the index introduced by Equation (9, 10, 11). Figure 10 illustrated the prediction of vehicle's safety situation in the following 300 meters at instant t = 160 s and t = 180 s.

The results showed at instant t=180s, the algorithm detected potential dangers in the upcoming path.

VI. CONCLUSIONS AND PROSPECTS

This paper presented a novel method to estimate and predict vehicle dynamic states based on the fusion of Open-StreetMap and inertial sensors. The current and future road information was obtained from the digital map after the localization process. Then the vehicles models and map data are combined to evaluate the safety of the vehicle. Experimental results validated the proposed algorithm. The future work will focus on the improvement of map quality and localization accuracy.

Fig. 2 .

 2 Fig. 2. Geometry of a roundabout in OpenStreetMap

Fig. 3 .

 3 Fig. 3. Double track model

Fig. 4 . 5 .Fig. 5 .

 455 Fig. 4. Overall structure of vehicle safety prediction system

Fig. 6 .

 6 Fig. 6. Experimental vehicle: DYNA

Fig. 7 .

 7 Fig. 7. Vehicle's trajectory and curvature value at each critical point

Fig. 8 .

 8 Fig. 8. Comparison of lateral dynamics states estimated by inertial sensors and OSM

Fig. 9 .

 9 Fig. 9. a) Estimation of of vertical forces at each tire; b) Estimation of lateral forces at each tire: comparison between sensor measurement and estimation

Fig. 10 .

 10 Fig. 10. Prediction of vehicle safety in the following 300 meters road

TABLE III THE

 III CONSTRUCTION OF CRITICAL POINTS AND CORRIDORS


MD Jean-Pierre Estebe
email: jean-pierre.estebe@chu-rennes.fr

Cécile Degryse

Gilles Rezzadori
email: rezzadori.g@chu-nice.fr

Florin Dimache
email: florin.dimache@chru-strasbourg.fr

Georges Daccache
email: daccache-g@chu-caen.fr

Alain Le Naoures

Anissa Belbachir
email: anissa.belbachir@cch.aphp.fr

Pierre Schoeffler
email: pschoeffler@chu-clermontferrand.fr

Anne-Laure Sérandour
email: al.serandour@slbpharma.com

PhD Alain Lenaoures
email: alain.lenaoures@chu-rennes.fr

MD Cecile Degryse
email: cecile.degryse@chu-bordeaux.fr

Pierre Schoeffer

Tolerance and efficacy of a polyamine-deficient diet for the treatment of perioperative pain

Keywords: Polyamine-deficient diet polyamines, diet, pain, perioperative pain, spine surgery, NMDA receptors

Suppression of polyamines from the diet offers a nutrition-based treatment option for perioperative pain reduction.

Results: Compliance (preoperatively: 100% in group 1 and 83% in group 2; postoperatively: 83% in group 1 and 71% in group 2) and tolerance were good. After seven days of the diet before surgery, a trend of decrease on pain was observed in group 1 whereas no effect was observed in group 2 (P = 0.144). This analgesic effect became significant in group 1 in the subgroup of patients with initial high levels of pain (NS ≥ 4) at rest (P = 0.03). and on motion (P = 0.011). Quality of life was significantly improved in group 1 (P = 0.0465). In the postoperative period, pain was significantly decreased in group 1 compared to group 2 at rest (P = 0.022). and on motion (P = 0.029). The effect was significantly better on patients with higher initial pain both at rest (P = 0.013) and on motion (P = 0.005) in group 1 compared to group 2.

Conclusion:

Suppression of polyamines from the diet offers a nutrition-based treatment option for perioperative pain reduction independent of and complementary to typical analgesic approaches.

M A N U S C R I P T A C C E P T E D

Introduction:

Lower back pain, with or without leg pain, is a notably common problem that effects up to 85% of adults and has a negative impact on work productivity and quality of life [START_REF] Freburger | The rising prevalence of chronic low back pain[END_REF][START_REF] Taylor | Low back pain hopitalization. Recent United States trends and regional variations[END_REF] . It may lead to a history of pain sensitization and long-term use of pain medication. Lumbar spinal stenosis surgery (LSS) is a perfect surgical example of the complex situation when nociceptive (i.e., low back pain), inflammatory (i.e., articular hypertrophy), and neuropathic pain (i.e., neurogenic pain) combine to result in substantial psychological and/or social consequences [START_REF] Gerbershagen | Pain intensity on the first day after surgery: A prospective cohort study comparing 179 surgical procedures[END_REF] . In this case, the postoperative outcomes remain partially satisfactory (i.e., persistent chronic postoperative pain) [START_REF] Robinson | Instrumentation in lumbar fusion improves back pain but not quality of life 2 years after surgery[END_REF] .

Excitation of N-methyl-D-aspartate (NMDA) receptors was considered a straightforward process that evolved to maximize the rate of neuronal communication. It was recently reported that NMDA receptors might play an important role in pain and/or hyperalgesia phenomena, particularly in pain memorization and pain sensitization. In a recent review, it was reported that ketamine has an opioid sparing effect, particularly in painful procedures [START_REF] Laskowski | A systematic review of intravenous ketamine for postoperative analgesia[END_REF] , that is mainly due to the inhibition of NMDA receptors [START_REF] Weinbroum | Non-opioid IV adjuvants in the perioperative period: pharmacological and clinical aspects of ketamine and gabapentinoids[END_REF] . Many different NMDA receptor subtypes coexist in the central nervous system [START_REF] Paoletti | NMDA receptor subunit diversity: impact on receptor properties, synaptic plasticity and disease[END_REF] . Usually localized in postsynaptic sites, they are mobile with various levels of conductance channels modulated by protons, polyamines (PA), and magnesium. PA (putrescine, spermidine, and spermine) are ubiquitous small cationic organic molecules [START_REF] Minois | Polyamines in aging and disease[END_REF] . They contribute to the control of neuronal excitability. PA act on tyrosine phosphorylation of NMDA receptor subtype-2B as a scaffolding element of neuroplasticity [START_REF] Paoletti | NMDA receptor subunit diversity: impact on receptor properties, synaptic plasticity and disease[END_REF] .

PA have been intensively investigated, and their link to several pathologies has been well established [START_REF] Minois | Polyamines in aging and disease[END_REF] . In addition to their well-known universal role in cell division and proliferation, PA are involved in additional biological processes, such as tumor growth [START_REF] Quemener | Polyamine deprivation: a new tool in cancer treatment[END_REF] and inflammatory processes [START_REF] Silva | Role of peripheral polyamines in the development of inflammatory pain[END_REF] . Interesting preliminary clinical results were recently described in the treatment of the prostate cancer [START_REF] Cipolla | Polyamine reduced diet (PRD) nutrition therapy in hormone refractory prostate cancer patients[END_REF][START_REF] Cipolla | Prostate cancer, a low polyamine diet and docetaxel[END_REF] . PA were recently shown to regulate the formation of mRNA stress granules [START_REF] Li | elF5A promotes translation elongation, polysome disassembly and stress granule assembly[END_REF] . Apart from being endogenously synthesized, an exogenous supply of PA by intestinal uptake is generally assumed to be the predominant PA transport pathway. PA intestinal absorption occurs through dietary sources (80%) and intestinal absorption from bacterial metabolism [START_REF] Bardocz | The importance of dietary polyamines in cell regeneration and growth[END_REF][START_REF] Larqué | Biological significance of dietary polyamines[END_REF] . Because intestinal absorption is a critical source of PA, an obvious link between food and PA concentration has been suggested. Based on recent animal studies, researchers have proposed that certain "Functional Foods" (defined as foods or food components that may provide health benefits beyond traditional nutrition) may represent a promising and safe strategy for improving the management of pain in combination with

M A N U S C R I P T A C C E P T E D

analgesic drugs classically used [START_REF] Bell | Food and pain: should we be more interested in what our patient eat?[END_REF] . However, establishing such a proof of concept in humans has never been specifically considered and in particular for perioperative pain. In a previous experimental model, it was reported that a polyamine-deficient diet (PDD) had preventive properties against pain hypersensitivity [START_REF] Rivat | Polyamine deficient diet to relieve pain hypersensitivity[END_REF] , oxaliplatine-induced sensory neuropathy [START_REF] Ferrier | A polyamine-deficient diet prevents oxaliplatin-induced acute sensory neuropathy in rats[END_REF] , and had a curative effect on heroin-induced hyperalgesia in a rat model [START_REF] Roy | A polyamine-deficient diet opposes hyperalgesia, tolerance and the increased anxiety-like behaviour associated with heroin withdrawal in rats[END_REF] .

To test the hypothesis that a PDD could have an effect on perioperative pain in humans, we designed a study by building on the experience gained in clinical trials on prostate cancer treatment [START_REF] Cipolla | Polyamine reduced diet (PRD) nutrition therapy in hormone refractory prostate cancer patients[END_REF][START_REF] Cipolla | Prostate cancer, a low polyamine diet and docetaxel[END_REF] . We planned a prospective, randomized, multicenter, and blinded phase II clinical trial following the intention-to-treat principle with the pain level as primary endpoint.

M A N U S C R I P T A C C E P T E D

Material and Methods:

Study design and patients:

The study design was built on previous clinical observations made with patients suffering from chronic non-malignant pain [START_REF] Moulinoux | Polyamine deficient diet against pain[END_REF] and in castrate-resistant prostate cancer [START_REF] Cipolla | Prostate cancer, a low polyamine diet and docetaxel[END_REF] . A significant decrease in the pain scores was observed when patients were under strict PDD, i.e., 80% of the food intake calories were provided by the food for special medical purposes, specifically Polydol TM , which is characterized by a low PA content. Conversely, no effect on pain was observed when patients were only under partial PDD. This lack of efficacy was probably due to an insufficient systemic depletion of PA. So, we consider that partial PDD could be used as control group. In the aim to obtain a blinded effect and to avoid some placebo effects, patients were informed that it was a dose-ranging study. So, in partial PDD group, patients could expect a significant analgesic effect with less inconvenient than in strict PDD group. This prospective, randomized, multicenter, blinded phase II study was designed to evaluate the dose-ranging effect of a low PA diet with respect to a total (less than 10 µmol of PA / day) or partial (approximately 370 µmol of PA / day) PA diet on perioperative pain. Eligible patients were aged 18 years or older and had chronic low back pain scheduled for spine surgery. The exclusion criteria were undernutrition, major medical problems, participation in another randomized trial, inability to use a patient controlled analgesia (PCA) morphine, or an inability to provide written informed consent. Patients using NSAIDs and steroids for other spine-related reasons, or nefopam were excluded. Pregnancy and diabetes with inadequate glycemic control were also exclusion criteria.

This study was conducted in accordance with the principles of the Declaration of Helsinki (59 th general assembly of the WMA, Seoul, South Korea, October 2008), the Directive 2001/20/EC of the European Parliament and of the Council and the French principles of good clinical practices. The study was approved by AFSSAPS and by the Regional French Ethics Committee (ID-RCB: 2009-A00504-53 August 2009). The design and description of the study adhered to the guidelines of the CONSORT (Figure 1). All patients provided written informed consent for trial participation.

Randomization:

Eligible patients were randomly assigned (1: 1) to group 1 or group 2 at least 10 days before spinal surgery. Block randomization of 16 patients was used to assign patients and was

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prepared and coordinated by an independent contract research organization (SLB Pharma, 28 bis rue du Thabor, 3500 Rennes France). The allocation sequence was computer-generated by the trial center. Only the physicians were aware of the treatment assignment.

Treatment: Diet:

Polydol™ is a food for special medical purposes according the European directive 1999/21/CE and was provided by Nutrialys Medical Nutrition SA. Each 250 ml drink contains a very low content of PA (less than 0.1 µmol of PA / drink). The nutritional information of Polydol TM is given in Table 1.

In the total PDD group (group 1), 6 drinks provided 1600 Kcal/day and additional 450 kcal were provided by a European breakfast (100 g of white bread, 100 ml of milk, 10 g of butter, and 10 g of sugar or jam). The patients could ingest additional drinks if they felt still hungry. In the partial PDD group (group 2), patients completed their normal diet with two drinks/day whenever necessary. The diet started 7 days before surgery and continued for 5 days after surgery. Nutrialys Medical Nutrition SA performed home and hospital pharmacy deliveries.

Surgery:

The surgical solution is to decompress the stenotic part of the lumbar spine. In cases of spine instability, one or more posterior lumbar interbody arthrodeses or fusions could be performed (restricted to four levels or less). Procedure-related complications such were recorded.

Anesthesia:

Before anesthesia, regular treatments were not modified. Regarding the intervention, each center was allowed to adopt its own anesthesia procedures, but due to the potential action on NMDA receptors, nitrous oxide, nefopam, and ketamine were contraindicated. To control postoperative pain, intravenous morphine PCA pumps were used by the patients according to a standardized protocol (i.e., bolus dose: 1 mg of morphine, lockout interval: 5 min; without maximal dose). Of course, usual multi modal analgesia protocol was systematically applied (paracetamol, NSAID) at the end of the surgery and during the postoperative period.

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Assessments and follow-up:

All parameters were recorded at each visit: i.e., at the inclusion time V0 (= preanesthesia visit) before diet, after 7 days of the diet just before surgery (V1), the day after surgery (V2), 5 days after surgery at the end of the diet (V3), and 1 and 6 months after the surgery (V4 and V5, respectively) (Figure 2).

Compliance was recorded on each patient's block note and was considered good if the patient consumed more than 5 drinks/day in group 1 and more than 1.5 drink/day in group 2 (i.e., 80% of the total theoretical dose in each group). The tolerability was periodically evaluated based on the reporting of adverse effects (AEs) for all participants (i.e. nausea, vomiting, and diarrhea or constipation) considered as minor AEs if they do not require treatment, and major AEs if specific treatment was required.

The primary endpoint of the study was the pain level, evaluated by the numerical scale (NS) (zero to 10) at rest just after surgery (V2). But at each step pain at rest and at motion was

Statistical analysis:

All analyses followed the intention-to-treat (ITT) principle. On the ITT, a sample size of 64 patients (i.e., n = 32 in each group) had been determined to produce 80% power to detect a significance in the rate of pain at α = 0.05 (two-tailed), assuming that the pain decrease was 1 point (V0 Vs. V2). Due to the lack of preliminary data, we made the hypothesis that PDD, as MNDA antagonist, had a similar effect as another NMDA antagonist reported in the literature (ketamine) [START_REF] Remérand | The early and delayed analgesic effects of ketamine after total hip arthroplasty: a prospective, randomized, controlled, double-blind study[END_REF] . The description of the ITT population was based on the comparison of the means of quantitative variables or proportions of qualitative variables between 2 independent groups. All tests were two-tailed with significance at 5%. For quantitative variables, the results are expressed as the mean with standard deviation (SD), range and average. Conditions of validity when using parametric tests were checked systematically. Shapiro-Wilk test assessed whether variable distributions violated the assumption of normality. Student's test (T test) was used and was matched (T test) for

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comparison of means between two independent groups and matched data, respectively. For the comparison of means from more than two groups, repeated measures with ANOVA method, followed by multiple comparisons based on the contrast method were used. When conditions of validity were not verified, Wilcoxon and Mann-Whitney non-parametric tests were used. Chi 2 test or Fisher's exact test were used for comparison of proportions between two independent groups, and McNemar test was used for matched data. A post-hoc analysis with the level of preoperative pain (groups with or without numerical scale of pain > 4) was performed based on the hypothesis that high level of pain induced more hyperalgesia phenomenon.

Statistical analysis was accomplished using JMP software from SAS Institute (10.0 version for Windows XP). P < 0.05 is considered statistically significant. Data have been computed and double-checked by SLB Pharma, and decisions regarding exclusions of patients from the statistical analysis were made with the principal investigator.

Results:

Between September 2009 and September 2012, 64 patients recruited by seven participating hospitals were randomized. After the exclusion of 2 patients (one patient withdrew consent before treatment in group 1 and one withdrew for cancelled surgery due to cancer diagnosis in group 2), 60 patients were analyzed in ITT (one patient in each group was excluded from the ITT analysis because of the use of steroids) (Figure 1).

Preoperative period

1.a. Before diet (V0)
All characteristics of the patients were similar in group 1 and group 2 (Table 2). In each group, pain on motion was significantly higher than pain at rest (P < 0.0001). More than 80% of the patients were taking pain medication on a regular basis before surgery with no significant difference between both groups. More than 50% of these patients were taking step I pain medication according to the WHO-pain ladder (non-opioid medication). Twenty-six patients (52% vs. 46% for groups 1 and 2, respectively) received step II pain medication and 5 patients received step III pain medication. Despite the possible implication of the number of pain medications used on pain levels, there was no significant correlation in each group between the number of their medications and the level of pain (no treatment: n = 9 (at rest NS = 3.7 ± 2.6), one treatment: n = 21 (NS = 4.0 ± 2.3) and more than one treatment: n = 30 (NS = 4.7 ± 2.3)). There was only a slightly non-significant higher level of pain for patients on opioid medications (n = 5, NS = 5.2 ± 2.2 at rest, and 7.4 ± 1.3 on motion). There was no difference in neuropathic pain characteristics and in the results of quality of life questionnaires.

1.b. Preoperative effects of the PDD (V1).

The compliance was 100% in group 1 (n = 30/30) and 83% (n = 24/29) in group 2 (Table 3). The tolerance was good. A few minor AEs (not requiring treatment) were recorded in group 1 than in group 2 were reported (nausea 9 vs. 4; constipation 6 vs. 2, diarrhea 6 vs. 2;

for group 1 and 2, respectively). No additional drinks were used, and only 15% of patients required rice or bread at least once to be satiated in group 1.

In group 1, after seven days of PDD and without any change in analgesic treatment, there is a non-significant decreasing trend of their pain at rest (4.0 ± 2.7 to 3.5 ± 2.5 at V0 and V1, respectively) and on motion (6.7 ± 2.5 to 5.7 ± 2.8 for V0 and V1, respectively). No similar effect was observed in group 2. Based on previous clinical results showing that the

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patients who had higher levels of pain were experiencing more decreased pain after a PDD, the evolution of pain in patients with NS > 4 at V0 (n = 18 and 21 at rest, and n = 29 and 26 on motion, in group 1 and 2, respectively) was explored. In group 1, pain at rest decreased significantly from 5.9 ± 1.4 at V0 to 4.5 ± 2.6 at V1 (P = 0.03) and pain on motion decreased significantly from 7.2 ± 1.8 at V0 to 5.8 ± 2.8 at V1 (P = 0.011). In group 2, there was no difference in the pain levels for the patients with a NS > 4 (P = 0.75 at rest and P = 1 at motion).

The opioid treatment did not influence those results and no significant difference was observed when the patients (n = 5) with opioid medication were excluded from the statistical analysis.

After seven days of the diet, the quality of life according to the EFEIL questionnaire was significantly improved in the total PDD group 1 (P = 0.046).

Per-operative period (day 0).

Pre-operative characteristics were similar for all of the patients (see table 4). Five patients in group 1 (16%) and four patients in group 2 (14%) underwent unintended durotomy.

Despite their contraindication in the protocol, two patients in each group received an anti-NMDA drug (one patient received nitrous oxide administration and one received nefopam in group 1; two patients received ketamine administration in group 2). Multimodal pain treatment was almost used systematically and in the same way for all of the patients.

Anesthesia protocols were similar in the two groups.

Postoperative period

3.a. Immediate postoperative period (day 1 (V2) to day 5 (V3) after surgery)

Twenty-seven and twenty-six patients remained under protocol in groups 1 and 2, respectively at V2, and twenty-four and twenty-five patients at the end of the diet (V3).

During the postoperative period, compliance with the diet remained satisfactory until the end of the diet at day 5 (Table 3). As preoperatively, there were slightly more minor AEs in group 1 than in group 2. However, more patients needed a specific treatment in group 2 (4 vs. 7, in groups 1 and 2, respectively). At V2, one day after the surgery, pain at rest was significantly decreased in group 1 compared to group 2 (P = 0.022, Table 5) as expected in our statistical design. Regarding pain on motion, the decrease of pain between the two groups did not reach significance; but there

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Page 12 sur 28 was a significant decrease of pain in group 1 (6.7 ± 2.5 at V0 to 5.1 ± 2.9 at V2; P = 0.029), whereas no such effect was recorded in group 2.

When the evaluation was performed for the patients with higher pain at rest (NS > 4 at V0), the effect of group 1, in comparison with group 2, was more significant at rest (P = 0.013) as well as on motion (P = 0.005). The decrease of pain on motion was clearly significant in group 1 (P = 0.004), whereas no significant effect was observed in group 2 (P = 1). ANOVA analysis (V0 to V2) confirmed the interaction between the level of pain (NS< 4 or NS > 4 at V0) and the treatment (P = 0.001).

At the end of the nutritional program (V3) just before leaving the hospital and, likely because of the impact of the surgery, the level of pain was similar in both groups.

In terms of the quality of life and because of the difficulties in performing an evaluation on the first postoperative day, we only made a comparison at V3. Although significance was not reached, we found a trend of improvement in group 1 (P = 0.063) with the EFEIL questionnaire.

There was no difference in the postoperative opioid and non-opioid analgesic consumption (Table 6).

Long-term follow-up (at 1 (V4) and 6 months (V5))

There was no difference between the two groups in terms of postoperative hospital length of stay. One patient in each group had a new hospitalization between V3 and V4, one in group 1 for scar infection and one in group 2 for surgical complication, and during the six months following surgery (for new disc herniation). Despite of the positive effects of PDD in perioperative situation, there was no difference between the two groups in terms of long-term outcomes.

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Discussion:

We found that the PDD using Polydol™ had pain reduction effects on perioperative (i.e., pre and early postoperative) pain in the current clinical study. This is the very first randomized multicenter clinical trial confirming this new approach for the management of chronic pain. Our clinical data reinforce results from previously reported preliminary studies [START_REF] Cipolla | Prostate cancer, a low polyamine diet and docetaxel[END_REF][START_REF] Moulinoux | Polyamine deficient diet against pain[END_REF] . We choose to use a control group with partial PDD because we known that a partial PDD is not enough to induce a sufficient decrease of PA to allow a clinical effect. It was only reported an effect in chronic pain when a profound PA diet was previously induced.

A group eating just a regular diet could be disappointed and we could not extrapolate the placebo effect.

Despite the multicenter design study, the two groups were similar enough to provide a statistical evaluation. The mean duration of pain before surgery was approximately two years confirming the patient's status of chronic pain.

Covariate analysis, using ANOVA analysis, led to the observation that males had significantly less pain at rest than females (P = 0.014 at V0) so it was not surprising that the effect of the diet was more significant in the female group (P = 0.011 at V2 compared to V0) than in males (P = 0.06). These differences were not significant on motion. Note that the gender difference was previously reported with various explanations [see [START_REF] Mogil | Sex differences in pain and pain inhibition: multiple explanations of a controversial phenomenon[END_REF] ].

It is noteworthy that pain reduction induced by PDD was relatively quick with a significant effect reported during the preoperative period (7 days) despite any therapeutic modification. Interestingly, this PA deficient diet seems to be more effective for the higher levels of pain. If the statistical significance was not reached during the preoperative period, it is noteworthy that the decrease of pain was 0.5 points at rest and 1.0 point on motion in group 1, whereas no effect was recorded in group 2. If we evaluate patients with higher pain (NS ≥ 4 at rest) at V0, before surgery the effect of PDD led to a decrease 1.4 points at rest, and on motion. In other words and as an example, on motion if more than 90% of patients in the two groups had high levels of pain on motion (NS > 4) at V0, we observed a decrease at 70% before surgery to 54% just after surgery and 35% at the end of the nutritional program in group 1; whereas it remains at 90% at V1, 87.5% at V2 and 54% at V3 in group 2. In group 1, the pain reduction effect observed during the preoperative period was significantly increased just after surgery. On the one hand, it was reported in the literature that there was a clear correlation between the level of the preoperative pain and the level of postoperative pain [START_REF] Kalkman | Preoperative prediction of severe postoperative pain[END_REF] . On the other hand, the level of postoperative pain is predictive of chronic pain [START_REF] Robinson | Instrumentation in lumbar fusion improves back pain but not quality of life 2 years after surgery[END_REF] . Therefore, the

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efficacy of the PDD during the preoperative period could be very important. Quality of life was significantly improved during the preoperative diet treatment. Using the BPI questionnaire, we found no benefit; however, this may be because the questions refer to an assessment throughout this week of treatment. To see an effect of the treatment, BPI questions should have been asked just during the last two days.

The compliance with the PA deficient diet was very good, with no indication of significant food related AE. The relatively short duration of participation in the PDD (12 days) was accomplished by all our patients with a high frequency of compliance. The good tolerance could also be explained by prevention or treatment of anxiety, as previously described in a rat model [START_REF] Pain | Delayed aversive effects of high-dose fentanyl. Prevention by a polyamine-deficient diet[END_REF] and with other NMDA antagonists [START_REF] Bernudo-Soriano | New perspectives in glutamate and anxiety[END_REF][START_REF] Autry | MNDA receptor blockade at rest triggers rapid behavioral antidepressant responses[END_REF] . Preoperatively, the trend of decreased pain and the significant improvement of quality of life could also impact patient's psychology and may explain the better compliance observed in group 1. Due to the design of the study (dose-ranging study) we could most likely exclude a psychological effect between the two groups as usually observed if the patient information uses words such as placebo or control group. PDD, with appropriate composition of food, seems to have no AE on a postoperative period in terms of wound healing or risk of infection.

Due to the design of this clinical study, the number of patients included may have been too small to reach a level of significance with regard to long-term follow-up. Nevertheless, it was not surprising that no significant effects were recorded at 1 and 6 months. In previous clinical trials, the effects were more significantly prolonged when the duration of the total PDD was extended by more than 2 weeks. As described in prostate cancer publications and unpublished data on chronic pain treatment [START_REF] Cipolla | Prostate cancer, a low polyamine diet and docetaxel[END_REF][START_REF] Moulinoux | Polyamine deficient diet against pain[END_REF] , prolonged pain reduction effect has been maintained after 3 weeks of total PDD by the polyamine relative diet. Patients progressively modified the diet with foodstuff as a function of their PA content and decreased the number of drinks per day moving to a diet based on a list of foods with low PA content. Using a polyamine database, we could introduce diet variations based on the estimation of PA exposure [START_REF] Cipolla | Polyamine contents in current foods: a basis for polyamines reduced diet and a study of its long term observance and tolerance in prostate carcinoma patients[END_REF][START_REF] Soda | Food polyamine and cardiovascular disease: an epidemiological study[END_REF][START_REF] Zoumas-Morse | Development of a polyamine database for assessing dietary intake[END_REF] .

If the major mechanism of action of PDD is most likely due to an inhibition of tyrosine phosphorylation of the NMDA receptors, we could not exclude other mechanisms of action. PA levels generally increase with inflammation. These higher levels and activity lead to the influx of pro-inflammatory macrophages into the central nervous system. We could not exclude a peripheral effect because experimental data have shown that peripheral PA are related to the induction of inflammation which is reduced with the inhibition of the PA biosynthesis enzyme [START_REF] Larqué | Biological significance of dietary polyamines[END_REF] . This is consistent with recent publications in the prevention of

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Page 15 sur 28 colorectal adenoma [START_REF] Raj | Role of dietery polyamnies in phase III clinical trial of difluoromethylornithine (DFMO) and sulindac for prevention of sporadic colorectal adenomas[END_REF][START_REF] Vargas | Dietary polyamine intake and risk of colorectal adenomatous polyps[END_REF] . In addition to NMDA receptors, PA may interact with different affinities with the voltage sensitive calcium channel, TRPV1, or AMPA. In the absence or decrease of extracellular PA, there may be a decrease of intercellular PA movement, which would decrease the stress response, or there is a more efficient intercellular PA migration producing a better coordinated response to stress and cell proliferation [START_REF] Li | elF5A promotes translation elongation, polysome disassembly and stress granule assembly[END_REF] . Nevertheless, the possible anti-inflammatory effect displays no significant adverse effects during the postoperative period. As previously mentioned, we did not observe any delay in wound healing or level of infection. Most likely, the PA deficiency is not substantial enough to depress the wound healing processes, which may be because quiescent cells have a significant lower PA content than active cells, quiescent cells are less sensitive to many stresses.

However, with various possible mechanisms of action, there is emerging evidence indicating a relationship between PA and pain or neural sensitization emphasizing the importance of PDD [START_REF] Rivat | Polyamine deficient diet to relieve pain hypersensitivity[END_REF][START_REF] Ferrier | A polyamine-deficient diet prevents oxaliplatin-induced acute sensory neuropathy in rats[END_REF][START_REF] Roy | A polyamine-deficient diet opposes hyperalgesia, tolerance and the increased anxiety-like behaviour associated with heroin withdrawal in rats[END_REF] . Some limitations of this study need to be addressed. We did not evaluate PA concentrations in the blood during the nutritional program. The development of an accurate biomarker of dietary PA exposure would improve the accuracy of PDD. We have previously reported a link between pain and the level of PA in the cerebrospinal fluid; but the biomarker

was not yet accurately validated [START_REF] Gentili | Cerebrospinal fluid polyamine levels in patients with colonic disease[END_REF] . Particularly in the partial PDD group, the caloric load was not strictly controlled. Perhaps we could not exclude that caloric and type of calories introduce some differences. A true control group, with the same number of blinded drinks, could be discussed, but the procedure was too expensive.

In conclusion, based on the current study, suppression of polyamines from the diet may be an important mechanism of preoperative and/or early postoperative (hyperalgesia) reduction independent of usual analgesic approaches. With good tolerance and compliance, a polyamine-deficient diet could be a new and safer technique for the treatment and/or the prevention of postoperative pain. Due to active patient participation, a polyamine diet could be part of the therapeutic education of chronic pain patients or be part of pre-habilitation strategy before surgery. This very first study confirms the concept proof the potential interest to use the polyamines diet as new analgesic strategy. Further studies must confirm the interest of such protocol for patients with high level of pain or for patients opioid-tolerant; comparison of the long-term benefits and costs will therefore require further studies.

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  recorded. The major secondary endpoint was the tolerance to the PDD. The other secondary endpoints were neuropathic pain evaluated by the DN4 questionnaire and Neuropathic Pain Symptom Inventory (NPSI) questionnaire. Quality of life was determined using the Brief Pain Inventory (BPI), EIFEL questionnaire (French version of Low Back Pain and Disability questionnaire), Short Form-12 (SF-12) acute questionnaire; sleep disorders were evaluated based on the NS of sleepiness (from 0 good sleep to 10 worst sleep disorder).

Figure 1 :Figure 2 :

 12 Figure 1: Flow-chart of the study

  Fig 2:

Table 1 :

 1 Nutritional information of POLYDOL TM

Table 2 :

 2 Preoperative characteristics and pain evaluation before the diet (V0) and after 7 days of the diet, before surgery (V1)

Table 3 :

 3 Compliance with the diet at after 7 days (V1) and after 12 days (V3)

Table 4 :

 4 Details of the surgery and anesthesia

Table 5 :

 5 Postoperative characteristics and pain evaluation 1 day (V2) and 5 days (V3) after surgery

Table 6 :

 6 Morphine consumption during and after surgery

Table 1 :

 1

	NUTRITION INFORMATION	250 ml
	Energy			265 kcal
	Proteins			10 g
	Carbohydrates			30 g
	Of which sugars			10 g
	Fats (total)			11•25 g
	Of which •saturated fatty acids (FA)	3 g
	• monounsaturated FA	3•3 g
	• polyunsaturated FA		2•5 g
	• omega 3 (total)		1•8 g
	Fibers			4•5 g
	VITAMINS	250 ml	MINERALS	250 ml
	A	135 µg Calcium	152 mg
	E	11 mg Potassium	281 mg
	D	1•8 µg Magnesium	31 mg
	C	94 mg Sodium	106 mg
	B1	1•1 mg Copper	0•25 mg
	B2	0•7 mg Iron	0•3 mg
	B6	2•1 mg Manganese	0•5 mg
	PP	4•2 mg Zinc	1 mg
	B5	2•2 mg Chlorides	265 mg
	H	42 µg Iodine	7 µg
	B9	111 µg Chromium	25 µg
	B12	0•1 µg Molybdenum	8•8 µg
	K1	4•3 µg Selenium	2•5 µg
		Phosphorus	112 mg
		Fluorine	0•5 mg

Table 2 :

 2

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Table 3 :

 3

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Table 4 :

 4

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Table 5 :

 5

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Table 6 :

 6

The study was supported by Nutrialys Medical Nutrition SA. The sponsor was not involved in the design of the study, data analysis, data interpretation, or the writing of the clinical report.

Designed the study and oversaw data collection and verification: JPE Enrolled patients and collected the data: CD, GR, FD, GD, AL, AB, PS, ALS Analyzed and interpreted the data and wrote the initial draft: ALS, JPE All authors critically ensured the accuracy of the data and analysis, reviewed the draft and approved the final version of the manuscript for submission.