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建立一个预测 ICU 中因败血症引起的急性呼吸衰竭患者 30 天死亡率的列线图:一项回顾性队列研究。

Development of a prognostic nomogram for sepsis associated-acute respiratory failure patients on 30-day mortality in intensive care units: a retrospective cohort study.

机构信息

Southwest Jiaotong University of Medicine/Southwest Jiaotong University Affiliated Chengdu Third People's Hospital, Chengdu, 610031, Sichuan, China.

出版信息

BMC Pulm Med. 2023 Jan 30;23(1):43. doi: 10.1186/s12890-022-02302-6.

Abstract

BACKGROUND

Acute respiratory failure is a type of sepsis complicated by severe organ failure. We have developed a new nomogram for predicting the 30-day risk of death in patients through a retrospective study.

METHOD

Data was collected and extracted from MIMICIV, with 768 eligible cases randomly assigned to the primary cohort (540) and the validation cohort (228). The final six factors were included by Cox regression analysis to create the Nomogram, the accuracy of the Nomogram was assessed using the C-index and calibration curve, and finally, the clinical usefulness of the Nomogram was evaluated using DCA in.

RESULTS

Multivariate Cox regression analysis showed that age, DBP, lactate, PaO2, platelet, mechanical ventilation were independent factors for 30-day mortality of SA-ARF. The nomogram established based on the six factors. The C-index of nomogram in the primary cohort is 0.731 (95% CI 0.657-0.724) and 0.722 (95%CI 0.622-0.759) in the validation cohort. Besides, the decision curve analysis (DCA) confirmed the clinical usefulness of the nomogram.

CONCLUSION

The study developed and validated a risk prediction model for SA-ARF patients that can help clinicians reasonably determine disease risk and further confirm its clinical utility using internal validation.

摘要

背景

急性呼吸衰竭是一种伴有严重器官衰竭的败血症并发症。我们通过回顾性研究开发了一种新的列线图来预测患者 30 天的死亡风险。

方法

从 MIMICIV 中收集和提取数据,将 768 例符合条件的病例随机分配到主队列(540 例)和验证队列(228 例)。通过 Cox 回归分析纳入最终的 6 个因素来创建列线图,使用 C 指数和校准曲线评估列线图的准确性,并使用 DCA 在内部验证中评估列线图的临床实用性。

结果

多变量 Cox 回归分析表明,年龄、舒张压、乳酸、PaO2、血小板和机械通气是 SA-ARF 30 天死亡率的独立因素。基于这 6 个因素建立了列线图。主队列中列线图的 C 指数为 0.731(95%CI 0.657-0.724),验证队列中为 0.722(95%CI 0.622-0.759)。此外,决策曲线分析(DCA)证实了列线图的临床实用性。

结论

本研究开发并验证了一种用于预测 SA-ARF 患者风险的模型,该模型有助于临床医生合理判断疾病风险,并通过内部验证进一步确认其临床实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/722a/9885567/fa97efba8e4a/12890_2022_2302_Fig1_HTML.jpg

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