[Establishing a prognostic prediction model for patients with septic shock based on the completion time of fluid resuscitation and the negative fluid balance volumes].

Q3 Medicine
Jiyin Qian, Jing Zhang
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引用次数: 0

Abstract

Objective: To explore the relationship between the completion time of fluid resuscitation as well as negative fluid balance volumes and the prognosis of patients with septic shock, and to try to construct a prediction model based on the completion time of fluid resuscitation and negative fluid balance volumes, and to verify the predictive efficacy of the model on the prognosis of patients with septic shock.

Methods: Patients with septic shock admitted to Wuxi People's Hospital from April 2020 to April 2023 were selected. The general data (gender, age, body mass index, infection site), pathological indicators on admission, the difference of acute physiology and chronic health evaluation II (APACHE II) and sequential organ failure assessment (SOFA) between admission and 24 hours after fluid resuscitation, the completion time of fluid resuscitation and negative fluid balance volume were recorded. Multivariate Logistic analysis was used to screen the influencing factors of the prognosis of patients with septic shock, and a nomogram model was established. Bootstrap method was used for internal validation of the model. The consistency index, calibration curve and receiver operator characteristic curve (ROC curve) were used to evaluate the accuracy and prediction efficiency of the model.

Results: A total of 96 patients with septic shock were enrolled, 38 patients died and 58 patients survived at 28 days. Compared with the survival group, the difference of APACHE II score, SOFA score, the proportion of fluid resuscitation completed within 1 to 3 hours, and the proportion of negative fluid balance volume -500 to -250 mL per day in the death group were lower, and the differences were statistically significant (all P < 0.05). Multivariate Logistic analysis showed that the completion time of fluid resuscitation was a risk factor for the prognosis of patients with septic shock [odds ratio (OR) = 26.285, 95% confidence interval (95%CI) was 9.984-76.902, P < 0.05]. The difference of APACHE II score (OR = 0.045, 95%CI was 0.015-0.131), SOFA score (OR = 0.056, 95%CI was 0.019-0.165) between admission and 24 hours after fluid resuscitation, and negative fluid balance volume (OR = 0.043, 95%CI was 0.015-0.127) were protective factors for the prognosis of patients with septic shock (all P < 0.05). The model validation results showed that the consistency index was 0.681 (95%CI was 0.596-0.924), indicating good discrimination. The calibration curve showed that the calibration curve fitted well with the ideal curve. The ROC curve showed that the sensitivity of the nomogram model for predicting the death of patients with septic shock was 83.7%, the specificity was 97.2%, and the area under the ROC curve (AUC) was 0.931 (95%CI was 0.846-0.985), indicating that the model had good prediction efficiency.

Conclusions: The completion time of fluid resuscitation and negative fluid balance volumes are related to the prognosis of septic shock patients, and the alignment diagram model improve the identification of the risk of death in septic shock patients.

[根据液体复苏完成时间和负液体平衡量建立脓毒性休克患者预后预测模型]。
目的探讨液体复苏完成时间及负性液体平衡量与脓毒性休克患者预后的关系,尝试构建基于液体复苏完成时间及负性液体平衡量的预测模型,并验证该模型对脓毒性休克患者预后的预测效果:方法:选取 2020 年 4 月至 2023 年 4 月无锡市人民医院收治的脓毒性休克患者。记录患者的一般资料(性别、年龄、体重指数、感染部位)、入院时的病理指标、入院时与液体复苏后 24 小时内急性生理学和慢性健康评估 II(APACHE II)与序贯器官衰竭评估(SOFA)的差异、液体复苏完成时间和液体负平衡量。采用多变量 Logistic 分析筛选脓毒性休克患者预后的影响因素,并建立提名图模型。采用 Bootstrap 方法对模型进行内部验证。采用一致性指数、校准曲线和接收者运算特征曲线(ROC曲线)评价模型的准确性和预测效率:共纳入 96 例脓毒性休克患者,其中 38 例患者死亡,58 例患者在 28 天后存活。与存活组相比,死亡组的APACHE II评分、SOFA评分、1至3小时内完成液体复苏的比例、每天液体负平衡量-500至-250毫升的比例均低于存活组,差异有统计学意义(P均<0.05)。多变量 Logistic 分析显示,液体复苏完成时间是脓毒性休克患者预后的危险因素[比值比(OR)=26.285,95% 置信区间(95%CI)为 9.984-76.902,P <0.05]。入院和液体复苏后24小时内APACHE II评分(OR=0.045,95%CI为0.015-0.131)、SOFA评分(OR=0.056,95%CI为0.019-0.165)和负液体平衡量(OR=0.043,95%CI为0.015-0.127)的差异是脓毒性休克患者预后的保护因素(所有P均<0.05)。模型验证结果表明,一致性指数为 0.681(95%CI 为 0.596-0.924),显示出良好的区分度。校准曲线显示,校准曲线与理想曲线拟合良好。ROC曲线显示,提名图模型预测脓毒性休克患者死亡的灵敏度为83.7%,特异度为97.2%,ROC曲线下面积(AUC)为0.931(95%CI为0.846-0.985),表明该模型具有良好的预测效率:液体复苏完成时间和负液体平衡量与脓毒性休克患者的预后有关,排列图模型提高了对脓毒性休克患者死亡风险的识别能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Zhonghua wei zhong bing ji jiu yi xue
Zhonghua wei zhong bing ji jiu yi xue Medicine-Critical Care and Intensive Care Medicine
CiteScore
1.00
自引率
0.00%
发文量
42
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