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            "title": "Is There an Association Between the “Critical Shoulder Angle” and Clinical Outcome After Rotator Cuff Repair?",
            "creators": [
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                    "firstName": "Jacob M.",
                    "lastName": "Kirsch"
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                    "firstName": "Amit",
                    "lastName": "Nathani"
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                    "firstName": "Bruce S.",
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            "abstractNote": "Background:\n              Variations in scapular morphology have been associated with the development of atraumatic rotator cuff tears (RCTs). The critical shoulder angle (CSA) accounts for both glenoid inclination and lateral extension of the acromion. The impact of the CSA on outcomes after rotator cuff repair (RCR) has not been investigated previously.\n            \n            \n              Hypothesis:\n              Our hypothesis was that individuals with smaller CSAs will have better patient-reported outcome scores over time compared with those with larger CSAs. Theoretically, a smaller CSA minimizes the biomechanical forces favoring superior translation of the humeral head, which may be advantageous after RCR. This is the first study to examine the relationship between the CSA and clinical outcomes after RCR.\n            \n            \n              Study Design:\n              Cohort study; Level of evidence, 2.\n            \n            \n              Methods:\n              Fifty-three patients (mean age, 61 years) with atraumatic full-thickness RCTs who underwent arthroscopic RCR were prospectively evaluated. Demographic data as well as the Western Ontario Rotator Cuff Index (WORC) score, American Shoulder and Elbow Surgeons (ASES) score, and a visual analog scale (VAS) for pain were prospectively collected at various time points up to 24 months postoperatively. Statistical analysis included longitudinal multilevel regression modeling to investigate the association between the CSA and the WORC, ASES, and VAS scores.\n            \n            \n              Results:\n              The overall clinical outcome, as measured by the WORC, ASES, and VAS, improved significantly ( P < .0001). Controlling for demographic and clinical characteristics, a multilevel regression analysis demonstrated that the CSA was not a significant independent predictor for change in WORC ( P = .581), ASES ( P = .458), or VAS ( P = .859) scores at 24 months after arthroscopic RCR. Interobserver and intraobserver reliability for CSA measurements resulted in interclass correlation coefficients of 0.986 and 0.982, respectively ( P < .001), indicating excellent agreement.\n            \n            \n              Conclusion:\n              The CSA did not appear to be a significant predictor of patient-reported outcomes after arthroscopic repair of atraumatic full-thickness RCTs.",
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            "abstractNote": "Introduction:\n              Alpha angle (AA) is a widely used measure of hip shape that is commonly used to define cam morphology, a bulging of the lateral aspect of the femoral head. Cam morphology has shown strong associations with hip osteoarthritis (OA) making the AA a clinically relevant measure. In both clinical practice and research studies, AA tends to be measured manually which can be inconsistent and time-consuming.\n            \n            \n            \n              Objective:\n              We aimed to (i) develop an automated method of deriving AA from anterior-posterior dual-energy x-ray absorptiometry (DXA) scans; and (ii) validate this method against manual measures of AA.\n            \n            \n            \n              Methods:\n              6,807 individuals with left hip DXAs were selected from UK Biobank. Outline points were manually placed around the femoral head on 1,930 images before training a Random Forest-based algorithm to place the points on a further 4,877 images. An automatic method for calculating AA was written in Python 3 utilising these outline points. An iterative approach was taken to developing and validating the method, testing the automated measures against independent batches of manually measured images in sequential experiments.\n            \n            \n            \n              Results:\n              Over the course of six experimental stages the concordance correlation coefficient, when comparing the automatic AA to manual measures of AA, improved from 0.28 [95% confidence interval 0.13-0.43] for the initial version to 0.88 [0.84-0.92] for the final version. The inter-rater kappa statistic comparing automatic versus manual measures of cam morphology, defined as AA ³≥60°, improved from 0.43 [80% agreement] for the initial version to 0.86 [94% agreement] for the final version.\n            \n            \n            \n              Conclusions:\n              We have developed and validated an automated measure of AA from DXA scans, showing high agreement with manually measuring AA. The proposed method is available to the wider research community from\n              Zenodo\n              .",
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                    "firstName": "Brendan R.",
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