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急诊普通外科手术后重症监护病房再入院及意外死亡情况

Intensive care unit readmission and unexpected death after emergency general surgery.

作者信息

Guo Ran, Cui Na

机构信息

Department of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, 100730, China.

出版信息

Heliyon. 2023 Mar 9;9(3):e14278. doi: 10.1016/j.heliyon.2023.e14278. eCollection 2023 Mar.

Abstract

BACKGROUND

Intensive care unit (ICU) readmission and unexpected death are closely associated with increased length of hospitalization and total mortality. However, data about readmission or unexpected death after discharge from ICU in patients who have undergone emergency general surgery (EGS) is very limited.

METHODS

In total, 1133 patients who underwent EGS were identified in the Multiparameter Intelligent Monitoring in Intensive Care IV (MIMIC-IV) database. Of these 1133 patients, 124 underwent readmission into the ICU or death unexpectedly after their initial discharge. The clinical characteristics of the patients were investigated. A logistic regression model was implemented for the analysis of the independent risk factors associated with ICU readmission or unexpected death. A nomogram model was established to predict the risk of ICU readmission or unexpected death within 72 h after EGS.

RESULTS

Peripheral vascular disease and atrial fibrillation, vasopressor requirement, a higher respiratory rate or heart rate, a lower pulse oxygen saturation or a platelet count of <150 K/μL and a relatively low Glasgow coma scale score in the last 24 h before ICU discharge were independent risk factors for ICU readmission or death within 72 h. The nomogram had moderate accuracy with an area under the curve of 0.852, which had a stronger prediction power than the Stability and Workload Index for Transfer (SWIFT) score, a classic prediction model for ICU readmission risk.

CONCLUSIONS

In critically ill patients who undergo EGS, ICU readmission or unexpected death within 72 h can be predicted using a nomogram model based on eight parameters including physiological and laboratory test values in the last 24 h before discharge and comorbidities. ICU physicians should prudently assess patients to make effective discharge decisions.

摘要

背景

重症监护病房(ICU)再入院和意外死亡与住院时间延长及总死亡率增加密切相关。然而,关于接受急诊普通外科手术(EGS)的患者从ICU出院后的再入院或意外死亡的数据非常有限。

方法

在多参数重症监护智能监测IV(MIMIC-IV)数据库中识别出总共1133例接受EGS的患者。在这1133例患者中,124例在首次出院后再次入住ICU或意外死亡。对患者的临床特征进行了调查。采用逻辑回归模型分析与ICU再入院或意外死亡相关的独立危险因素。建立了列线图模型以预测EGS后72小时内ICU再入院或意外死亡的风险。

结果

外周血管疾病和心房颤动、血管升压药的使用需求、较高的呼吸频率或心率、较低的脉搏血氧饱和度或血小板计数<150K/μL以及ICU出院前最后24小时相对较低的格拉斯哥昏迷量表评分是72小时内ICU再入院或死亡的独立危险因素。该列线图具有中等准确性,曲线下面积为0.852,其预测能力比用于预测ICU再入院风险的经典预测模型——转运稳定性和工作量指数(SWIFT)评分更强。

结论

对于接受EGS的危重症患者,可使用基于包括出院前最后24小时的生理和实验室检查值以及合并症在内的八个参数的列线图模型预测72小时内的ICU再入院或意外死亡。ICU医生应谨慎评估患者以做出有效的出院决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95b3/10023911/0ca3b799c2e8/gr1.jpg

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