Background: Adults with spinal deformity (ASD) are known to have postural malalignment affecting their quality of life. Classical evaluation and follow-up are usually based on full-body static radiographs and health related quality of life questionnaires. Despite being an essential daily life activity, formal gait assessment lacks in clinical practice.Research Question: What are the main alterations in gait kinematics of ASD and their radiological determinants? Methods: 52 ASD and 63 control subjects underwent full-body 3D gait analysis with calculation of joint kinematics and full-body biplanar X-rays with calculation of 3D postural parameters. Kinematics and postural parameters were compared between groups. Determinants of gait alterations among postural radiographic parameters were explored. Results: ASD had increased sagittal vertical axis (SVA:34 ± 59 vs − 5 ± 20 mm), pelvic tilt (PT:19 ± 13 vs 11 ± 6 • ) and frontal Cobb (25 ± 21 vs 4 ± 6 • ) compared to controls (all p < 0.001). ASD displayed decrease walking speed (0.9 ± 0.3 vs 1.2 ± 0.2 m/s), step length (0.58 ± 0.11 vs 0.64 ± 0.07 m) and increased single support (0.45 ± 0.05 vs 0.42 ± 0.04 s). ASD walked with decreased hip extension in stance (− 3 ± 10 vs − 7 ± 8 • ), increased knee flexion at initial contact and in stance (10 ± 11 vs 5 ± 10 • and 19 ± 7 vs 16 ± 8 • respectively), and decreased knee flexion/extension ROM (55 ± 9 vs 59 ± 7 • ). ASD had increased trunk flexion (12 ± 12 vs 6 ± 11 • ) and reduced dynamic lumbar lordosis (− 11 ± 12 vs − 15 ± 7 • , all p < 0.001). Sagittal knee ROM, walking speed and step length were negatively determined by SVA; lack of lumbar lordosis during gait was negatively determined by radiological lumbar lordosis. Significance: Static compensations in ASD persist during gait, where they exhibit a flexed attitude at the trunk, hips and knees, reduced hip and knee mobility and loss of dynamic lordosis. ASD walked at a slower pace with increased single and double support times that might contribute to their gait stability. These dynamic discrepancies were strongly related to static sagittal malalignment.

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Purpose To explore 3D hip orientation in standing position in subjects with adult spinal deformity (ASD) presenting with different levels of compensatory mechanisms. Methods Subjects with ASD (n = 159) and controls (n = 68) underwent full-body biplanar X-rays with the calculation of 3D spinopelvic, postural and hip parameters. ASD subjects were grouped as ASD with knee flexion (ASD-KF) if they compensated by flexing their knees (knee flexion ≥ 5°), and ASD with knee extension (ASD-KE) otherwise (knee flexion < 5°). Spinopelvic, postural and hip parameters were compared between the three groups. Univariate and multivariate analyses were then computed between spinopelvic and hip parameters. Results ASD-KF had higher SVA (67 ± 66 mm vs. 2 ± 33 mm and 11 ± 21 mm), PT (27 ± 14° vs. 18 ± 9° and 11 ± 7°) and PI-LL mismatch (20 ± 26° vs − 1 ± 18° and − 13 ± 10°) when compared to ASD-KE and controls (all p < 0.05). ASD-KF also had a more tilted (34 ± 11° vs. 28 ± 9° and 26 ± 7°), anteverted (24 ± 6° vs. 20 ± 5° and 18 ± 4°) and abducted (59 ± 6° vs. 57 ± 4° and 56 ± 4°) acetabulum, with a higher posterior coverage (100 ± 6° vs. 97 ± 7° for ASD-KE) when compared to ASD-KE and controls (all p < 0.05). The main determinants of acetabular tilt, acetabular abduction and anterior acetabular coverage were PT, SVA and LL (adjusted R 2 [0.12; 0.5]). Conclusions ASD subjects compensating with knee flexion have altered hip orientation, characterized by increased posterior coverage (acetabular anteversion, tilt and posterior coverage) and decreased anterior coverage which can together lead to posterior femoro-acetabular impingement, thus limiting pelvic retroversion. This underlying mechanism could be potentially involved in the hip-spine syndrome.

Une étude transversale, a été menée afin d’évaluer l’impact de la pandémie du coronavirus sur le niveau d’anxiété et la qualité du sommeil du personnel hospitalier d’un hôpital universitaire privé impliqué dans la réponse contre la pandémie au Liban, tout en identifiant les facteurs qui pourraient affecter ces symptômes. L’évaluation s’est effectuée à l’aide de questionnaires auto-administrés ; un auto-questionnaire qui inclut les données sociodémographiques, la nature du travail exercé à l’hôpital, des questions sur les facteurs affectant le niveau de stress, et des questions sur la consommation de substances. Des échelles d'auto-évaluation ont été utilisées ; l'Inventaire d'anxiété d'État-Trait (STAI) pour le dépistage des symptômes anxieux, et l'Indice de qualité du sommeil de Pittsburgh (PSQI) pour mesurer la qualité du sommeil. Un total de 628 personnels de santé a répondu au questionnaire. Parmi tous les participants, 503 (81,4 %) étaient des infirmiers/infirmières, 52 (8,4 %) des médecins et 63 (10,2 %) des internes. En ce qui concerne les caractéristiques des participants : 409 (66,2 %) avaient moins de 40 ans, 441 (71,4 %) étaient des femmes, 309 (55 %) étaient mariés, 333 (53,9 %) avaient un seul enfant, 428 (69,3 %) avaient un niveau universitaire, et 591 (95,6 %) ne présentaient pas une histoire psychiatrique. Les moyennes obtenues aux deux échelles étaient de 44,5 au STAI, et de 6,0 au PSQI. Parmi le total des participants, 61,5 % auront un score au STAI supérieur à 40, indiquant des symptômes anxieux modérés à sévères, et 48,4 % auront un score au PSQI supérieur à 5, indiquant une mauvaise qualité de sommeil. Les infirmiers/infirmières diplômés, les internes, les femmes et les participants plus jeunes présentent des scores significativement plus élevés au niveau des deux échelles que les autres catégories de participants. Les participants sans enfants, ceux ayant un niveau académique universitaire, et ceux ayant des antécédents psychiatriques présentent des scores significativement plus élevés uniquement en ce qui concerne la PSQI. Une proportion de 31,2 % de nos participants aura augmenté leur consommation d’alcool ou de substances (tabac, caféine, tranquillisants, cannabis ou autres). Parmi les facteurs liés à la COVID-19, le fait d'avoir des proches touchés par le virus (22,2 %), d'être excessivement exposé aux médias (12,9 %) et d'avoir augmenté la consommation de substances/alcool pendant la période de la pandémie (31,2 %) a été associé à des scores significativement plus élevés au niveau des deux échelles d’évaluation. Parmi les sources de stress liées à la pandémie rapportées, nous trouvons la peur d’être infecté ou d’infecter les autres dans 61,7 %, la peur que quelqu’un de leurs proches soit infecté des 45,6 %, la peur d’avoir un accès limité aux équipements médicaux dans 17 %, et la perte financière dans 16,3 %. Une analyse de régression logistique multivariée a permis d’identifier les facteurs suivants comme étant associés à un risque plus élevé de symptômes anxieux : sexe féminin, ...

IntroductionAdult spinal deformity (ASD) is classically evaluated by health-related quality of life (HRQoL) questionnaires and static radiographic spino-pelvic and global alignment parameters. Recently, 3D movement analysis (3DMA) was used for functional assessment of ASD to objectively quantify patient's independence during daily life activities. The aim of this study was to determine the role of both static and functional assessments in the prediction of HRQoL outcomes using machine learning methods.MethodsASD patients and controls underwent full-body biplanar low-dose x-rays with 3D reconstruction of skeletal segment as well as 3DMA of gait and filled HRQoL questionnaires: SF-36 physical and mental components (PCS&amp;MCS), Oswestry Disability Index (ODI), Beck's Depression Inventory (BDI), and visual analog scale (VAS) for pain. A random forest machine learning (ML) model was used to predict HRQoL outcomes based on three simulations: (1) radiographic, (2) kinematic, (3) both radiographic and kinematic parameters. Accuracy of prediction and RMSE of the model were evaluated using 10-fold cross validation in each simulation and compared between simulations. The model was also used to investigate the possibility of predicting HRQoL outcomes in ASD after treatment.ResultsIn total, 173 primary ASD and 57 controls were enrolled; 30 ASD were followed-up after surgical or medical treatment. The first ML simulation had a median accuracy of 83.4%. The second simulation had a median accuracy of 84.7%. The third simulation had a median accuracy of 87%. Simulations 2 and 3 had comparable accuracies of prediction for all HRQoL outcomes and higher predictions compared to Simulation 1 (i.e., accuracy for PCS = 85 ± 5 vs. 88.4 ± 4 and 89.7% ± 4%, for MCS = 83.7 ± 8.3 vs. 86.3 ± 5.6 and 87.7% ± 6.8% for simulations 1, 2 and 3 resp., p &lt; 0.05). Similar results were reported when the 3 simulations were tested on ASD after treatment.DiscussionThis study showed that kinematic parameters can better predict HRQoL outcomes than stand-alone classical radiographic parameters, not only for physical but also for mental scores. Moreover, 3DMA was shown to be a good predictive of HRQoL outcomes for ASD follow-up after medical or surgical treatment. Thus, the assessment of ASD patients should no longer rely on radiographs alone but on movement analysis as well.

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