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Abstract Patients undergoing knee replacement, which is mainly indicated in severe osteoarthritis, are frequently co-affected by osteoporosis and osteopenia. With a prevalence standing at around 20% in patients receiving knee arthroplasty, osteoporosis could lead to poor outcomes postoperatively. Some of these complications include periprosthetic fractures and an increased revision rate. Antiresorptive medications have been shown to be beneficial postoperatively. However, no studies have been conducted on whether they had any benefits if given preoperatively. Surgical management may also be beneficial, but this area remains full of controversy.

Abstract Functional assessment is a key element in evaluating adult spinal deformity (ASD) patients. The multitude of 3D kinematic parameters provided by movement analysis can be confusing for spine surgeons. The aim was to investigate movement patterns of ASD based on key kinematic parameters. 115 primary ASD and 36 controls underwent biplanar radiographs and 3D movement analysis during walking, sit-to-stand and stair ascent to calculate joint and segment kinematics. Principal component analysis was applied to identify the most relevant kinematic parameters that define movement strategies adopted by ASD. Pelvis and head relative to pelvis kinematics were the most relevant parameters. ASD patients adopted four different movement strategies. Class 1: normative head and pelvis kinematics. Class 2: persistent pelvic backward tilt. Class 3: persistent forward shift of the head. Class 4: both pelvic backward tilt and forward shift of the head. Patients in class 3 and 4 presented sagittal malalignment on static radiographs with increased pelvic tilt, pelvic incidence-lumbar lordosis mismatch and sagittal vertical axis. Surprisingly, patients in class 3 had normal pelvic kinematics during movement, showing the importance of functional evaluation. In addition to being key segments in maintaining static global posture, head and pelvis were found to define movement patterns.

Background: Adults with spinal deformity (ASD) are known to have spinal malalignment, which can impact their quality of life and their autonomy in daily life activities. Among these tasks, ascending and descending stairs is a common activity of daily life that might be affected. Research question: What are the main kinematic alterations in ASD during stair ascent and descent? Methods: 112 primary ASD patients and 34 controls filled HRQoL questionnaires and underwent biplanar X-from which spino-pelvic radiographic parameters were calculated. Patients were divided into 3 groups: 44 with sagittal malalignment (ASD-Sag: PT > 25°, SVA>5 cm or PI-LL>10°), 42 with isolated thoracic hyperkyphosis (ASD-HyperTK: TK > 60°), 26 with isolated frontal spine deformity (ASD-Front: Cobb>20°). All participants underwent 3D motion analysis of the whole body while ascending and descending a stair step from which kinematic waveforms were extracted. Results: During stair ascent, ASD-Sag exhibited an increased thorax flexion (20 vs 5°), a decreased lumbar lordosis L1L3-L3L5 (7 vs 14°), and an increased ROM of lumbo-pelvic joint (15 vs 10°, all p

Introduction: Radiographic analysis is necessary for the assessment and the surgical planning in adults with spinal deformity (ASD). Restoration of global alignment is key to improving patient's quality of life. However, the large number of existing global alignment parameters can be confusing for surgeons. Research question: To determine the most clinically and functionally relevant global alignment parameters in ASD. Material and methods: ASD and controls underwent full body biplanar X-ray to calculate global alignment parameters: odontoid to hip axis angle (OD-HA), global sagittal angle (GSA), global tilt (GT), SVA, center of auditory meatus to hip axis (CAM-HA), SSA, T1-tilt and T9-tilt. All subjects filled HRQoL questionnaires: ODI, SF-36, VAS for pain and BDI (Beck's Depression Inventory). 3D gait analysis was performed to calculate kinematic and spatio-temporal parameters. A machine learning model predicted gait parameters and HRQoL scores from global alignment parameters. Results: 124 primary ASD and 47 controls were enrolled. T9 tilt predicted the most BDI (31%), hip flexion/extension during gait (36%), and double support time (39%). GSA predicted the most ODI (26%), thorax flexion/extension during gait (33%), and cadence (36%). Discussion and conclusion: Among all global alignment parameters, GSA, evaluating both trunk shift and knee flexion, and T9 tilt, evaluating the shift of the center of mass, were the best predictors for most of HRQoL scores and gait kinematics. Therefore, we recommend using GSA and T9 tilt in clinical practice when evaluating ASD because they represent the most quality of life and functional kinematic of these patients.

Aim: Bone tumors are rare and have an uneven geographic distribution. Methods: 730 patients diagnosed with bone tumors were included in this retrospective analysis. Results: With a 64% rate of malignancy, the most common tumors were metastasis (40%) mostly in the axial skeleton, Osteosarcoma (9%) mostly in the femur, Osteochondroma (8%) mostly in the femur, giant cell tumors (7%) mostly in the knee, and Ewing's sarcoma (6%) mostly in the axial skeleton. Conclusion: Even though a some of the tumors have a predilection for certain localizations in the human body, they may differ in the middle-eastern population. One must also pay attention to the higher rates of malignancies as compared with other cohorts.

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&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

Introduction: It was hypothesized that pelvic retroversion in Adult Spinal Deformity (ASD) can be related to an increased hip loading explaining the occurrence of hip-spine syndrome. Research question: How pelvic retroversion can modify acetabular orientation in ASD during walking? Methods: 89 primary ASD and 37 controls underwent 3D gait analysis and full-body biplanar X-rays. Classic spinopelvic parameters were calculated from 3D skeletal reconstructions in addition to acetabular anteversion, abduction, tilt, and coverage. Then, 3D bones were registered on each gait frame to compute the dynamic value of the radiographic parameters during walking. ASD patients having a high PT were grouped as ASD-highPT, otherwise as ASD-normPT. Control group was divided in: C-aged and C-young, age matched to ASD-hightPT and ASD-normPT respectively. Results: 25/89 patients were classified as ASD-highPT having a radiographic PT of 31° (vs 12° in other groups, p ​

Background: COVID-19 is a health crisis that triggered the need to find a rapid and sensitive tool to screen populations with a high risk of complications. Lactate dehydrogenase (LDH) is an enzyme found in almost all body cells, particularly pneumocytes, and appears to be associated with worst outcome. Pneumomediastinum (PM), which results from ruptured alveoli, can occur in non-ventilated patients. Acute pneumocytes injury induces the release of serum LDH. Objective: This study evaluates the role of baseline serum LDH levels in predicting COVID-19 lung necrosis. Methods: This retrospective study was conducted among 524 COVID-19 patients admitted to Hôtel-Dieu de France university hospital, Lebanon, between March 2020 and March 2021. Baseline serum LDH was retrieved from patients’ medical records. Radiological severity outcomes were assessed at admission and during follow-up by non-contrast computed tomography (NCCT) of the chest. Results: The mean age of participants was 63 ± 16 years, with 359 males (68.5%) and median (IQR) LDH levels upon admission of 328 (248–430). LDH was correlated with lobar involvement at both admission and NCCT follow-up (Spearman’s rho 0.527 and 0.264, respectively) and the development of a PM (p = 0.035) in 3% of the patients. Using ROC analysis, a baseline LDH value higher than 395 U/L was associated with the presence of a PM on admission and follow-up chest CT, with a sensitivity of 75% and a specificity of 60.1%. Conclusion: Baseline LDH levels could serve as a tool for early diagnosis of severe pulmonary injury with poor radiological outcomes in hospitalized COVID-19 patients. Resumen: Fundamento: El COVID-19 es una crisis sanitaria que desencadenó la necesidad de encontrar una herramienta rápida y sensible para el cribado de poblaciones con alto riesgo de complicaciones. La lactato deshidrogenasa (LDH) es una enzima que se encuentra en casi todas las células del cuerpo, particularmente en los neumocitos, y parece estar asociada con el peor resultado. El neumomediastino (PM), que resulta de la ruptura de los alvéolos, puede ocurrir en pacientes no ventilados. La lesión aguda de neumocitos induce la liberación de LDH sérica. Objetivo: Este estudio evalúa el papel de los niveles séricos basales de LDH en la predicción de la necrosis pulmonar por COVID-19. Métodos: Este estudio retrospectivo se realizó entre 524 pacientes con COVID-19 ingresados en el hospital universitario Hôtel-Dieu de France, Líbano, entre marzo de 2020 y marzo de 2021. La LDH sérica basal se recuperó de los registros médicos de los pacientes. Los resultados de gravedad radiológica se evaluaron al ingreso y durante el seguimiento mediante tomografía computarizada (TCNC) sin contraste del tórax. Resultados: La edad media de los participantes fue de 63 ±16 años, con 359 varones (68,5%) y mediana (IQR) niveles de LDH al ingreso de 328 (248-430). La LDH se correlacionó con la afectación lobar tanto al ingreso como al seguimiento de la NCCT (rho de Spearman 0,527 y 0,264, respectivamente) y el desarrollo de un PM (p=0,035) en el 3% de los pacientes. Mediante el análisis ROC, se asoció un valor basal de LDH superior a 395 U/L con la presencia de un PM al ingreso y seguimiento de la TC de tórax, con una sensibilidad del 75% y una especificidad del 60,1%. Conclusión: Los niveles basales de LDH podrían servir como una herramienta para el diagnóstico precoz de lesión pulmonar grave con malos resultados radiológicos en pacientes hospitalizados con COVID-19.