Abstract:

Objective To develop and validate a risk prediction model for social dysfunction in middle-aged and elderly patients with ischemic stroke. Methods A non-matched case-control study was conducted among ischemic stroke patients admitted to the neurology department of a tertiary hospital in Tangshan between August 2022 and March 2023. Patients who developed social dysfunction within 3 months after discharge were assigned to a case group，while those without it were assigned to a control group. Multivariate logistic regression was used to identify significant predictors and construct a nomogram-based prediction model. The model’s discrimination and calibration were assessed using the area under the receiver operating characteristic curve（AUC） and the Hosmer-Lemeshow test. Internal validation was performed via bootstrap resampling，and clinical utility was evaluated using decision curve analysis. Results Logistic regression identified the following as significant risk factors for social dysfunction（P<0.05）：male gender，age ≥60 years，primary education or below，rural residence，income<3 000，cognitive impairment，low disability acceptance，poor self-management ability，suboptimal utilization of chronic disease resources，low future-oriented coping，and high cumulative ecological risk. The nomogram achieved an AUC of 0.874，with a sensitivity of 79.4% and specificity of 80.7%. The Hosmer-Lemeshow test indicated good calibration（χ²=3.631，P=0.88）. Conclusion The developed nomogram provides an effective tool for predicting the risk of social dysfunction in middle-aged and elderly ischemic stroke patients，facilitating early identification of high-risk individuals.

Key words: Middle-Aged and Elderly, Ischemic Stroke, Social Function, Prediction Model, Nursing Care

摘要：

目的 构建并验证中老年缺血性脑卒中患者社会功能障碍的风险预测模型，为医护人员早期识别中老年缺血性脑卒中患者的社会功能障碍提供参考。方法 采用非匹配病例对照研究设计，选取2022年8月—2023年3月唐山市某三级甲等医院神经内科收治的中老年缺血性脑卒中患者作为调查对象，将发病后出院3个月存在社会功能障碍的患者设为病例组，同期不存在社会功能障碍的患者设为对照组。采用多因素Logistic回归分析筛选变量，建立列线图预测模型。采用受试者操作特征曲线下面积、Hosmer-Lemeshow法评估模型的区分度和校准度；采用Bootstrap法进行模型验证，采用临床决策曲线评估模型的临床适用性。结果 Logisitic回归分析结果显示，男性、年龄≥60岁、文化程度为小学及以下、居住地在农村、家庭人均月收入<3 000元、认知功能障碍、低水平伤残接受度、低水平健康自我管理能力、慢性病资源利用不理想、低水平未来取向应对、高累积生态风险是中老年缺血性脑卒中患者社会功能障碍的危险因素（P<0.05）。该列线图预测模型受试者操作特征曲线下面积为0.874，灵敏度为79.4%，特异度为80.7%，Hosmer-Lemeshow检验显示，χ²=3.631（P=0.889）。结论 该研究构建的列线图模型可预测中老年缺血性脑卒中患者社会功能障碍的发生风险，有助于医护人员早期识别高危人群。

关键词: 中老年, 缺血性脑卒中, 社会功能, 预测模型, 护理