摘要
目的:探讨长期卧床老年病人发生坠积性肺炎的影响因素,并构建Nomogram模型。方法:选取2018年1月—2022年1月我院收治的130例长期卧床老年病人作为研究对象,采用自制的一般资料调查问卷对病人进行调查,采用Logistic回归方程筛选长期卧床老年病人发生坠积性肺炎的影响因素,并构建Nomogram模型。结果:长期卧床老年病人坠积性肺炎发生率为17.97%,Logistic回归分析结果显示,卧床时间、白细胞计数、中性粒细胞比率、意识障碍发生情况、预防性使用抗菌药物情况、吞咽障碍发生情况是长期卧床老年病人坠积性肺炎发生的影响因素(P<0.05)。基于以上影响因素构建的Nomogram模型内部验证平均绝对误差为0.002,其在高风险阈值范围时具有临床实用价值,病人净获益高。结论:长期卧床老年病人坠积性肺炎发生风险预测模型具有较好临床实用性。
Objective:To explore the influencing factors of hypostatic pneumonia in long-term bedridden elderly patients,and to construct Nomogram model.Methods:A total of 130 long-term bedridden elderly patients with hypostatic pneumonia in our hospital were selected as research subjects from January 2018 to January 2022.A self-made general data survey questionnaire was used to investigate the patients.Logistic regression equation was used to screen for the influencing factors of hypostatic pneumonia in long-term bedridden elderly patients,and Nomogram model was constructed.Results:The incidence of hypostatic pneumonia in long-term bedridden elderly patients was 17.97%.Logistic regression analysis showed that bedtime,white blood cell count,neutrophil ratio,occurrence of consciousness disorders,prophylactic use of antibiotics,and swallowing disorders were the influencing factors for the occurrence of hypostatic pneumonia in long-term bedridden elderly patients(P<0.05).The average absolute error of internal validation of Nomogram model based on the above influencing factors was 0.002.The model had clinical practical value in the high risk threshold range,and the net benefit of patients was high.Conclusions:The risk prediction model for the occurrence of hypostatic pneumonia in long-term bedridden elderly patients has good clinical utility.
作者
张紫薇
郭丝雨
赵天雪
ZHANG Ziwei;GUO Siyu;ZHAO Tianxue(Beijing Friendship Hospital,Capital Medical University,Beijing 100050 China)
出处
《护理研究》
北大核心
2023年第18期3242-3247,共6页
Chinese Nursing Research
基金
北京市卫生科技发展专项基金项目,编号:2019-2-120。
