JSES - 2026-06-01 - Journal Article
A preoperative decision algorithm for reverse shoulder arthroplasty in complex proximal humerus fractures in the elderly.
Lopiz Y, Bartrina A, Landero A, Checa-Betegón P, García-Fernandez C, Garríguez-Pérez D, Marco F
Topics
Key Takeaway
In patients ≥75 years undergoing rTSA for Neer 3- or 4-part proximal humerus fractures, ASA score was the only independent predictor of poor outcome (OR 0.36), with a decision algorithm achieving AUC 0.78.
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Summary
This study asked which preoperative patient-level factors predict poor functional outcome (Constant <45 or ASES <50) after rTSA for Neer 3- or 4-part PHFs in patients ≥75 years. Univariate analysis identified severe cognitive impairment, partial dependence (OR 3.6), lack of social support (OR 4.1), and Charlson Index >5 (OR 2.7) as significant predictors; multivariate analysis retained only ASA score as independently significant (OR 0.36, p=0.012). A decision algorithm derived from these variables demonstrated good discrimination with AUC 0.78 on internal validation.
Key Limitation
Single-center retrospective design with internal validation only limits the algorithm's external validity and introduces selection bias in who received rTSA versus alternative treatment.
Original Abstract
BACKGROUND
Reverse total shoulder arthroplasty (rTSA) has become the standard surgical option for managing complex proximal humerus fractures (PHFs) in elderly patients. Despite its widespread use, postoperative functional outcomes remain inconsistent, and patient selection criteria are not well defined.
METHODS
A retrospective cohort study was conducted including 117 patients ≥75 years who underwent rTSA for Neer 3- or 4-part PHFs between 2012 and 2023 at a single tertiary hospital. Preoperative clinical and epidemiological variables were recorded, including Charlson Comorbidity Index, American Society of Anesthesiologists (ASA) score, cognitive status, level of dependence, and availability of social support. Functional outcomes at 12 months were assessed using the Constant and American Shoulder and Elbow Surgeons (ASES) scores. Poor outcome was defined as Constant <45 or ASES <50. Univariate and multivariate logistic regression analyses were performed to identify predictors of poor outcome, and a therapeutic decision algorithm was developed and internally validated.
RESULTS
The mean age was 79 ± 7 years (range 75-92), and 80.2% were female. At 12-month follow-up the mean Constant and ASES scores were 55.85 ± 17.7 and 54.6 ± 13.2, respectively. Severe cognitive impairment was the strongest predictor of poor outcome (P < .001), followed by partial dependence (odds ratio [OR] 3.6; 95% confidence interval [CI]: 1.5-8.4; P = .004), lack of social support (OR 4.1; 95% CI: 1.2-13.6; P = .022), and Charlson Index >5 (OR 2.7; 95% CI: 1.1-6.3; P = .027). In multivariate analysis, ASA score remained the only statistically significant independent predictor (OR 0.36; 95% CI: 0.16-0.80; P = .012), while Charlson Comorbidity Index showed a near-significant trend (OR 1.34; 95% CI: 0.996-1.81; P = .053). The resulting predictive model showed good discrimination (area under the curve = 0.78).
CONCLUSION
Preoperative patient-related factors such as ASA score, cognitive status, comorbidity burden, and functional independence significantly influence functional outcomes after rTSA for PHFs in elderly patients. The proposed decision algorithm may enhance surgical decision-making and improve individualized patient care.