Global Sagittal Angle and T9-tilt seem to be the most clinically and functionally relevant global alignment parameters in patients with Adult Spinal Deformity.

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.

Kinematic adaptations from self-selected to fast speed walking in patients with adult spinal deformity.

PURPOSE: To investigate kinematic adaptations from self-selected to fast speed walking in ASD patients. METHODS: 115 primary ASD and 66 controls underwent biplanar radiographic X-rays and 3D gait analysis to calculate trunk, segmental spine and lower limb kinematics during self-selected and fast speed walking. Kinematic adaptation was calculated as the difference (Δ) between fast and self-selected speed walking. ASD with 7 or more limited kinematic adaptation parameters were classified as ASD-limited-KA, while those with less than 7 limited kinematic adaptation parameters were classified as ASD-mild-KA. RESULTS: 25 patients were classified as ASD-limited-KA and 90 as ASD-mild-KA. ASD-limited-KA patients walked with a lesser increase of pelvic rotation (Δ = 1.7 vs 5.5°), sagittal hip movement (Δ = 3.1 vs 7.4°) and shoulder-pelvis axial rotation (Δ = 3.4 vs 6.4°) compared to controls (all p < 0.05). ASD-limited-KA had an increased SVA (60.6 vs - 5.7 mm), PT (23.7 vs 11.9°), PI-LL (9.7 vs - 11.7°), knee flexion (9.2 vs - 0.4°) and a decreased LL (44.0 vs 61.4°) compared to controls (all p < 0.05). Kinematic and radiographic alterations were less pronounced in ASD-mild-KA. The limited increase of walking speed was correlated to the deteriorated physical component summary score of SF-36 (r = 0.37). DISCUSSION: Kinematic limitations during adaptation from self-selected to fast speed walking highlight an alteration of a daily life activity in ASD patients. ASD with limited kinematic adaptations showed more severe sagittal malalignment with an increased SVA, PT, PI-LL, and knee flexion, a decreased LL and the most deteriorated quality of life. This highlights the importance of 3D movement analysis in the evaluation of ASD.

ASD with high pelvic retroversion develop changes in their acetabular orientation during walking.

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 â€‹< â€‹0.001). On static radiograph, ASD-highPT showed more severe postural malalignment than the other groups: ODHA â€‹= â€‹5°, L1L5 â€‹= â€‹17°, SVA â€‹= â€‹57.4 â€‹mm (vs 2°, 48° and 5 â€‹mm resp. in other groups,all p â€‹< â€‹0.001). During gait, ASD-highPT presented a higher dynamic pelvic retroversion of 30° (vs 15° in C-aged), along with a higher acetabular anteversion of 24° (vs 20°), external coverage of 38° (vs 29°) and a lower anterior coverage of 52° (vs 58°,all p â€‹< â€‹0.05). Conclusion: ASD patients with severe pelvic retroversion showed an increased acetabular anteversion, external coverage and lower anterior coverage during gait. These changes in acetabular orientation, computed during walking, were shown to be related to hip osteoarthritis.

Functional assessment using 3D movement analysis can better predict health-related quality of life outcomes in patients with adult spinal deformity: a machine learning approach.

Introduction: Adult 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. Methods: ASD 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. Results: In 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 < 0.05). Similar results were reported when the 3 simulations were tested on ASD after treatment. Discussion: This 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.

Impact of ABO and Rhesus blood groups on COVID-19 susceptibility and severity: A case-control study.

Early evidence from China suggested that blood groups may be involved in susceptibility to COVID-19. Several subsequent studies reported controversial results. We conducted a retrospective matched case-control study that aims to investigate the association between blood groups and the risk and/or severity of COVID-19. We compared the blood groups distribution of 474 patients admitted to the hospital for COVID-19 between March 2020 and March 2021, to that of a positive control group of outpatients infected with COVID-19 and matched them for sex and age, as well as to the distribution in the general population. Three hundred and eighteen HC+ pairs with available blood group information were matched. The proportion of group A Rh+ in hospitalized patients (HC+) was 39.9% (CI 35.2%-44.7%), compared to 44.8% (CI 39.8%-49.9%) and 32.3% in the positive outpatient controls (C+) and the general population (C-), respectively. Both COVID-19-positive groups (HC+ and C+) had significantly higher proportions of group A Rh+ compared to the general population (p = 0.0019 and p < 0.001, respectively), indicating that group A Rh+ increases susceptibility to COVID-19. Although blood group A Rh+ was more frequent in the outpatients C+ compared to the hospitalized group HC+, the association did not reach statistical significance, indicating that blood group A Rh+ is not associated with severity. There was no significant relationship between COVID-19 and other blood groups. Our findings indicate that blood group A Rh+ increases the susceptibility for COVID-19 but is not associated with higher disease severity.