Xu Lining, Wang Weiyu, Xu Yingying
Department of General Surgery, The Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
Zhongnan Hospital of Wuhan University, Institute of Hepatobiliary Diseases of Wuhan University, Transplant Center of Wuhan University, National Quality Control Center for Donated Organ Procurement, Hubei Key Laboratory of Medical Technology On Transplantation, Wuhan, 430071, China.
Perioper Med (Lond). 2024 Feb 26;13(1):10. doi: 10.1186/s13741-024-00366-y.
Owing to poor organ function reserve, older adults have a high risk of postoperative complications. However, there is no well-established system for assessing the risk of complications after hepatectomy in older adults.
This study aimed to design a risk assessment tool to predict the risk of complications after hepatectomy in adults older than 75 years. A total of 326 patients were identified. A logistic regression equation was used to create the Risk Assessment System of Hepatectomy in Adults (RASHA) for the prediction of complications (Clavien‒Dindo classification ≥ II).
Multivariate correlation analysis revealed that comorbidity (≥ 5 kinds of disease or < 5 kinds of disease, odds ratio [OR] = 5.552, P < 0.001), fatigue (yes or no, OR = 4.630, P = 0.009), Child‒Pugh (B or A, OR = 4.211, P = 0.004), number of liver segments to be removed (≥ 3 or ≤ 2, OR = 4.101, P = 0.001), and adjacent organ resection (yes or no, OR = 1.523, P = 0.010) were independent risk factors for postoperative complications after hepatectomy in older persons (aged ≥ 75 years). A binomial logistic regression model was established to evaluate the RASHA score (including the RASHA scale and RASHA formula). The area under the curve (AUC) for the RASHA scale was 0.916, and the cut-off value was 12.5. The AUC for the RASHA formula was 0.801, and the cut-off value was 0.2106.
RASHA can be used to effectively predict the postoperative complications of hepatectomy through perioperative variables in adults older than 75 years.
The Research Registry: researchregistry8531. https://www.researchregistry.com/browse-the-registry#home/registrationdetails/63901824ae49230021a5a0cf/ .
由于器官功能储备较差，老年人术后并发症风险较高。然而，目前尚无完善的系统来评估老年患者肝切除术后的并发症风险。
本研究旨在设计一种风险评估工具，以预测75岁以上成年人肝切除术后的并发症风险。共纳入326例患者。采用逻辑回归方程创建了成人肝切除风险评估系统（RASHA），用于预测并发症（Clavien-Dindo分级≥Ⅱ级）。
多因素相关性分析显示，合并症（≥5种疾病或<5种疾病，比值比[OR]=5.552，P<0.001）、乏力（是或否，OR=4.630，P=0.009）、Child-Pugh分级（B级或A级，OR=4.211，P=0.004）、拟切除肝段数量（≥3个或≤2个，OR=4.101，P=0.001）以及邻近器官切除（是或否，OR=1.523，P=0.010）是老年患者（年龄≥75岁）肝切除术后并发症的独立危险因素。建立了二项逻辑回归模型以评估RASHA评分（包括RASHA量表和RASHA公式）。RASHA量表的曲线下面积（AUC）为0.916，截断值为12.5。RASHA公式的AUC为0.801，截断值为0.2106。
RASHA可通过围手术期变量有效预测75岁以上成年人肝切除术后的并发症。
研究注册库：researchregistry8531。https://www.researchregistry.com/browse-the-registry#home/registrationdetails/63901824ae49230021a5a0cf/ 。
