摘要
目的探讨脓毒症相关肝损伤患者健康相关生活质量(HRQOL)的影响因素,并构建和验证其风险预测的列线图模型。方法选取2018年1月~2022年4月杭州市临平区第一人民医院重症监护病房(ICU)616例脓毒症相关肝损伤患者,于出院后24个月时采用简明健康调查量表(SF-36)评分评估患者HRQOL。依据SF-36评分将患者分别纳入HRQOL较高组(SF-36评分>中位值)、HRQOL较低组(SF-36评分≤中位值)。统计两组患者基线资料差异并分析HRQOL的影响因素,利用列线图构建脓毒症相关肝损伤患者HRQOL的风险预测模型。结果616例患者中有2例中途主动退出,共614例患者完成随访调查。采用随机数字表法按7∶3比例将614例患者分为训练集(n=430)和验证集(n=184):训练集用于筛选HRQOL影响因素并构建列线图预测模型,验证集用于评估模型效能。614例患者SF-36评分范围42~90分,中位评分68分。训练集430例中HRQOL较低组216例,较高组214例;验证集184例中HRQOL较低组94例,较高组90例。训练集多因素Logistic回归显示,年龄≥60岁、确诊时急性生理学和慢性健康状况评估系统Ⅱ(APACHEⅡ)评分高、脓毒症后生理功能障碍种类≥2种和社会支持度低是HRQOL较低的独立危险因素(P<0.05)。构建的列线图风险预测模型显示,模型一致性指数(C-index)为0.976,区分度好;受试者工作特征(ROC)曲线下面积(AUC)为0.915(95%CI 0.888~0.942),敏感度0.837,特异度0.841;校准曲线显示,校准曲线和理想曲线贴合良好,模型精确度好。验证集ROC曲线下面积为0.904(95%CI 0.864~0.945),敏感度0.926,特异度0.748;校准曲线贴合良好;决策曲线分析显示,在阈值0.02~1.00区间,受益均>0,临床应用价值较好。结论年龄≥60岁、确诊时APACHEⅡ评分高、脓毒症后生理功能障碍种类≥2种和社会支持度低是脓毒症相关肝损伤患者HRQOL较低的危险因素;基于训练集构建并经验证集验证的列线图模型,区分度、校准度及临床实用性良好,可为临床评估脓毒症相关肝损伤患者HRQOL提供可靠工具。
Objective To identify the influencing factors of health-related quality of life(HRQOL)in patients with sepsis-related liver injury,construct and verify a nomogram model for risk prediction.Methods A total of 616 patients with sepsis-related liver injury in the hospital from January 2018 to April 2022 were selected,and their HRQOL was evaluated using the Short Form 36 Health Survey(SF-36)at 24 months after discharge.According to the SF-36 scores,the patients were divided into the high HRQOL group(SF-36 score>median value)and the low HRQOL group(SF-36 score≤median value).The differences in baseline data between the two groups were statistically analyzed,the influencing factors of patients′HRQOL were explored,and a nomogram was used to construct a risk model for HRQOL in patients with sepsis-related liver injury.Results Among the 616 patients,2 voluntarily withdrew midway,and a total of 614 patients completed the follow-up survey.Using the random number table method,614 patients were divided into a training set(n=430)and a validation set(n=184)at a ratio of 7∶3:the training set was used to screen the influencing factors of HRQOL and construct the nomogram model,while the validation set was used to evaluate the model performance.The SF-36 scores of 614 patients ranged from 42 to 90 points,with a median score of 68 points;in the training set of 430 cases,there were 216 cases in the low HRQOL group and 214 cases in the high HRQOL group;in the validation set of 184 cases,there were 94 cases in the low HRQOL group and 90 cases in the high HRQOL group.Multivariate Logistic regression in the training set showed that age≥60 years,high APACHEⅡscore at diagnosis,≥2 types of sepsis-induced physiological dysfunction,and low social support were independent risk factors of low HRQOL(P<0.05).The constructed nomogram risk model showed that the concordance index(C-index)of 0.976,indicating good discrimination;the area under the ROC curve was 0.915(95%CI 0.888-0.942),with a sensitivity of 0.837 and a specificity of 0.841;the calibration curve drawn showed that the calibration curve was in good agreement with the ideal curve,indicating good model accuracy.The area under the ROC curve of the validation set was 0.904(95%CI 0.864-0.945),with a sensitivity of 0.926 and a specificity of 0.748;the calibration curve was in good agreement,and decision curve analysis demonstrated net benefit>0 within the threshold probability rang of 0.02-1.00.Conclusions Age≥60 years,high APACHEⅡscore at diagnosis,≥2 types of physiological dysfunction after sepsis,and low social support level are risk factors for low HRQOL in patients with sepsis-related liver injury;the nomogram model constructed based on the training set and verified by the validation set has good discrimination,calibration,and clinical practicability,and can provide a reliable tool for clinical evaluation of patients′HRQOL.
作者
漆玉荣
陈芸
朱渊鑫
邢跃栊
Qi Yurong;Chen Yun;Zhu Yuanxin;Xing Yuelong(Intensive Care Unit of the First People′s Hospital,Linping District,Hangzhou 311100,China)
出处
《中国急救医学》
2026年第1期56-62,共7页
Chinese Journal of Critical Care Medicine
