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开发和验证用于急性心力衰竭诊断的决策支持工具:系统评价、荟萃分析和建模研究。

Development and validation of a decision support tool for the diagnosis of acute heart failure: systematic review, meta-analysis, and modelling study.

机构信息

British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.

Contributed equally.

出版信息

BMJ. 2022 Jun 13;377:e068424. doi: 10.1136/bmj-2021-068424.

Abstract

OBJECTIVES

To evaluate the diagnostic performance of N-terminal pro-B-type natriuretic peptide (NT-proBNP) thresholds for acute heart failure and to develop and validate a decision support tool that combines NT-proBNP concentrations with clinical characteristics.

DESIGN

Individual patient level data meta-analysis and modelling study.

SETTING

Fourteen studies from 13 countries, including randomised controlled trials and prospective observational studies.

PARTICIPANTS

Individual patient level data for 10 369 patients with suspected acute heart failure were pooled for the meta-analysis to evaluate NT-proBNP thresholds. A decision support tool (Collaboration for the Diagnosis and Evaluation of Heart Failure (CoDE-HF)) that combines NT-proBNP with clinical variables to report the probability of acute heart failure for an individual patient was developed and validated.

MAIN OUTCOME MEASURE

Adjudicated diagnosis of acute heart failure.

RESULTS

Overall, 43.9% (4549/10 369) of patients had an adjudicated diagnosis of acute heart failure (73.3% (2286/3119) and 29.0% (1802/6208) in those with and without previous heart failure, respectively). The negative predictive value of the guideline recommended rule-out threshold of 300 pg/mL was 94.6% (95% confidence interval 91.9% to 96.4%); despite use of age specific rule-in thresholds, the positive predictive value varied at 61.0% (55.3% to 66.4%), 73.5% (62.3% to 82.3%), and 80.2% (70.9% to 87.1%), in patients aged <50 years, 50-75 years, and >75 years, respectively. Performance varied in most subgroups, particularly patients with obesity, renal impairment, or previous heart failure. CoDE-HF was well calibrated, with excellent discrimination in patients with and without previous heart failure (area under the receiver operator curve 0.846 (0.830 to 0.862) and 0.925 (0.919 to 0.932) and Brier scores of 0.130 and 0.099, respectively). In patients without previous heart failure, the diagnostic performance was consistent across all subgroups, with 40.3% (2502/6208) identified at low probability (negative predictive value of 98.6%, 97.8% to 99.1%) and 28.0% (1737/6208) at high probability (positive predictive value of 75.0%, 65.7% to 82.5%) of having acute heart failure.

CONCLUSIONS

In an international, collaborative evaluation of the diagnostic performance of NT-proBNP, guideline recommended thresholds to diagnose acute heart failure varied substantially in important patient subgroups. The CoDE-HF decision support tool incorporating NT-proBNP as a continuous measure and other clinical variables provides a more consistent, accurate, and individualised approach.

STUDY REGISTRATION

PROSPERO CRD42019159407.

摘要

目的

评估 N 末端脑利钠肽前体(NT-proBNP)诊断急性心力衰竭的性能,并开发和验证一种结合 NT-proBNP 浓度与临床特征的决策支持工具。

设计

个体患者水平数据的荟萃分析和建模研究。

设置

来自 13 个国家的 14 项研究,包括随机对照试验和前瞻性观察性研究。

参与者

纳入了 10369 名疑似急性心力衰竭患者的个体患者水平数据进行荟萃分析,以评估 NT-proBNP 阈值。开发并验证了一种决策支持工具(心力衰竭的诊断和评估协作(CoDE-HF)),该工具将 NT-proBNP 与临床变量相结合,为个体患者报告急性心力衰竭的概率。

主要观察指标

经裁决的急性心力衰竭诊断。

结果

总体而言,43.9%(10369 例中的 4549 例)患者经裁决诊断为急性心力衰竭(有和无既往心力衰竭的患者分别为 73.3%(2286/3119)和 29.0%(1802/6208))。指南推荐的排除阈值 300pg/ml 的阴性预测值为 94.6%(95%置信区间 91.9%至 96.4%);尽管使用了年龄特异性纳入阈值,但阳性预测值在年龄<50 岁、50-75 岁和>75 岁的患者中分别为 61.0%(55.3%至 66.4%)、73.5%(62.3%至 82.3%)和 80.2%(70.9%至 87.1%)。在大多数亚组中,尤其是肥胖、肾功能不全或有既往心力衰竭的患者中,其表现各不相同。CoDE-HF 具有良好的校准能力,在有和无既往心力衰竭的患者中均具有出色的区分度(有既往心力衰竭患者的受试者工作特征曲线下面积为 0.846(0.830 至 0.862),无既往心力衰竭患者的为 0.925(0.919 至 0.932),Brier 评分分别为 0.130 和 0.099)。在无既往心力衰竭的患者中,在所有亚组中,诊断性能均保持一致,40.3%(6208 例中的 2502 例)为低概率(阴性预测值为 98.6%,97.8%至 99.1%),28.0%(6208 例中的 1737 例)为高概率(阳性预测值为 75.0%,65.7%至 82.5%)。

结论

在对 NT-proBNP 诊断性能的国际协作评估中,指南推荐的诊断急性心力衰竭的阈值在重要的患者亚组中存在显著差异。结合 NT-proBNP 作为连续测量值和其他临床变量的 CoDE-HF 决策支持工具提供了更一致、准确和个体化的方法。

研究注册

PROSPERO CRD42019159407。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad06/9189738/5d0756bca244/leek068424.va.jpg

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