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急性呼吸窘迫综合征预测评分:推导与验证。

Acute Respiratory Distress Syndrome Prediction Score: Derivation and Validation.

机构信息

Lixue Huang is a clinician, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.

Man Song is a clinician, Department of Infectious Disease, Beijing Anzhen Hospital, Capital Medical University.

出版信息

Am J Crit Care. 2021 Jan 1;30(1):64-71. doi: 10.4037/ajcc2021753.

Abstract

BACKGROUND

Despite advances in treatment strategies, acute respiratory distress syndrome (ARDS) after cardiac surgery remains associated with high morbidity and mortality. A method of screening patients for risk of ARDS after cardiac surgery is needed.

OBJECTIVES

To develop and validate an ARDS prediction score designed to identify patients at high risk of ARDS after cardiac or aortic surgery.

METHODS

An ARDS prediction score was derived from a retrospective derivation cohort and validated in a prospective cohort. Discrimination and calibration of the score were assessed with area under the receiver operating characteristic curve and the Hosmer-Lemeshow goodness-of-fit test, respectively. A sensitivity analysis was conducted to assess model performance at different cutoff points.

RESULTS

The retrospective derivation cohort consisted of 201 patients with and 602 patients without ARDS who had undergone cardiac or aortic surgery. Nine routinely available clinical variables were included in the ARDS prediction score. In the derivation cohort, the score distinguished patients with versus without ARDS with area under the curve of 0.84 (95% CI, 0.81-0.88; Hosmer-Lemeshow P = .55). In the validation cohort, 46 of 1834 patients (2.5%) had ARDS develop within 7 days after cardiac or aortic surgery. Area under the curve was 0.78 (95% CI, 0.71-0.85), and the score was well calibrated (Hosmer-Lemeshow P = .53).

CONCLUSIONS

The ARDS prediction score can be used to identify high-risk patients from the first day after cardiac or aortic surgery. Patients with a score of 3 or greater should be closely monitored. The score requires external validation before clinical use.

摘要

背景

尽管治疗策略有所进步,但心脏手术后急性呼吸窘迫综合征(ARDS)仍然与高发病率和死亡率相关。需要有一种筛选心脏手术后 ARDS 风险的患者的方法。

目的

开发和验证一种 ARDS 预测评分,旨在识别心脏或主动脉手术后 ARDS 风险高的患者。

方法

ARDS 预测评分源自回顾性推导队列,并在前瞻性队列中进行验证。通过接收者操作特征曲线下面积和 Hosmer-Lemeshow 拟合优度检验分别评估评分的区分度和校准度。进行了敏感性分析,以评估在不同截断点下的模型性能。

结果

回顾性推导队列包括 201 例 ARDS 患者和 602 例无 ARDS 患者,他们接受了心脏或主动脉手术。ARDS 预测评分纳入了 9 个常规可用的临床变量。在推导队列中,评分区分了有 ARDS 和无 ARDS 的患者,曲线下面积为 0.84(95%置信区间,0.81-0.88;Hosmer-Lemeshow P=0.55)。在验证队列中,1834 例心脏或主动脉手术后 7 天内有 46 例(2.5%)发生 ARDS。曲线下面积为 0.78(95%置信区间,0.71-0.85),评分具有良好的校准度(Hosmer-Lemeshow P=0.53)。

结论

ARDS 预测评分可用于识别心脏或主动脉手术后第一天的高危患者。评分达到 3 分或更高的患者应密切监测。在临床应用之前,该评分需要进行外部验证。

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