American journal of translational research · 2026
Differential impact of hemiplegia severity stratification on post-hemiarthroplasty dislocation in elderly intertrochanteric fracture patients.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
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Ошибки и ограничения
История · было → стало
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Gao Xinxing, Qu Lijuan, Duan Yonghong
Аннотация
OBJECTIVES: To investigate the impact of hemiplegia due to cerebral infarction sequelae on postoperative dislocation after hemiarthroplasty (HHA) in elderly patients with intertrochanteric fractures, identify associated risk factors, and compare dislocation risks between moderate-to-severe and mild hemiplegia.
METHODS: We retrospectively analyzed 305 patients aged ≥70 years with intertrochanteric fractures who underwent HHA from January 2020 to May 2023. Inclusion criteria required confirmed cerebral infarction with hemiplegia, Evans-Jensen Type III/IV fracture, and ≥1-year follow-up. Postoperative dislocation was diagnosed radiographically, and preoperative motor dysfunction was assessed by the Fugl-Meyer Scale (mild ≥22, moderate-to-severe <22). Statistical analyses included chi-square and t-tests, Lasso regression, and logistic regression. A risk prediction model was developed and its discriminative capacity assessed by ROC analysis.
RESULTS: Dislocation occurred in 81 patients (26.6%). Significant factors included age ≥75 years, disease duration ≥6 months, fall-related injury, preoperative motor dysfunction, Evans-Jensen Type IV, diabetes mellitus, adverse lifestyle habits, inadequate nursing care, and posterolateral approach (all P<0.05). Multivariate analysis identified age (OR=3.164), preoperative motor dysfunction (OR=2.695), diabetes (OR=2.501), adverse lifestyle (OR=2.181), inadequate nursing care (OR=4.276), and posterolateral approach (OR=3.216) as independent predictors. In moderate-to-severe hemiplegia, age and diabetes were risk factors, whereas in mild hemiplegia, fall-related injury and diabetes predominated. The prediction model showed good performance (AUC=0.811; sensitivity 77.8%, specificity 71.9%).
CONCLUSIONS: Hemiplegia from cerebral infarction sequelae significantly increases dislocation risk after HHA in elderly intertrochanteric fracture patients. Independent risk factors vary by hemiplegia severity, and the proposed risk model may aid preoperative risk stratification and clinical decision-making.
METHODS: We retrospectively analyzed 305 patients aged ≥70 years with intertrochanteric fractures who underwent HHA from January 2020 to May 2023. Inclusion criteria required confirmed cerebral infarction with hemiplegia, Evans-Jensen Type III/IV fracture, and ≥1-year follow-up. Postoperative dislocation was diagnosed radiographically, and preoperative motor dysfunction was assessed by the Fugl-Meyer Scale (mild ≥22, moderate-to-severe <22). Statistical analyses included chi-square and t-tests, Lasso regression, and logistic regression. A risk prediction model was developed and its discriminative capacity assessed by ROC analysis.
RESULTS: Dislocation occurred in 81 patients (26.6%). Significant factors included age ≥75 years, disease duration ≥6 months, fall-related injury, preoperative motor dysfunction, Evans-Jensen Type IV, diabetes mellitus, adverse lifestyle habits, inadequate nursing care, and posterolateral approach (all P<0.05). Multivariate analysis identified age (OR=3.164), preoperative motor dysfunction (OR=2.695), diabetes (OR=2.501), adverse lifestyle (OR=2.181), inadequate nursing care (OR=4.276), and posterolateral approach (OR=3.216) as independent predictors. In moderate-to-severe hemiplegia, age and diabetes were risk factors, whereas in mild hemiplegia, fall-related injury and diabetes predominated. The prediction model showed good performance (AUC=0.811; sensitivity 77.8%, specificity 71.9%).
CONCLUSIONS: Hemiplegia from cerebral infarction sequelae significantly increases dislocation risk after HHA in elderly intertrochanteric fracture patients. Independent risk factors vary by hemiplegia severity, and the proposed risk model may aid preoperative risk stratification and clinical decision-making.