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期刊来源：Nat Med

原文链接：https://doi.org/10.1038/s41591-024-02961-4

摘要内容如下：

早期识别脆弱患者具有改善预后的潜力，但在临床实践中存在重大挑战。在一项涉及39名医生和15，965名患者的多点随机对照试验中，该研究评估了人工智能（AI）支持的心电图（ECG）识别高死亡率住院患者的能力。AI-ECG警报干预包括AI报告和发送给医生的警告信息，标记预测为高死亡风险的患者。该试验达到了其主要结果，发现AI-ECG警报的实施与90天内全因死亡率的显著降低相关：干预组3.6%的患者在90天内死亡，而对照组为4.3%（4.3%）（风险比（HR）=0.83，95%置信区间（CI）=0.70-0.99）。一项预先指定的分析显示，与AI-ECG警报相关的全因死亡率的降低主要在高危ECG患者中观察到（HR=0.69，95%CI=0.53-0.90）。在次要转归分析中，与对照组相比，干预组的高危心电图患者接受了更高水平的重症监护；对于高危ECG组患者，AI-ECG警报的实施与心脏死亡风险的显著降低相关（干预组为0.2%，对照组为2.4%，HR=0.07，95%CI=0.01-0.56）。虽然AI-ECG警报的实施导致死亡率降低的确切方法有待充分阐明，但这些结果表明，这种实施有助于检测高危患者，促进及时的临床护理并降低死亡率。ClinicalTrials.gov注册：NCT05118035。

英文原文如下：

Abstracts

The early identification of vulnerable patients has the potential to improve outcomes but poses a substantial challenge in clinical practice. This study evaluated the ability of an artificial intelligence (AI)-enabled electrocardiogram (ECG) to identify hospitalized patients with a high risk of mortality in a multisite randomized controlled trial involving 39 physicians and 15,965 patients. The AI-ECG alert intervention included an AI report and warning messages delivered to the physicians, flagging patients predicted to be at high risk of mortality. The trial met its primary outcome, finding that implementation of the AI-ECG alert was associated with a significant reduction in all-cause mortality within 90 days: 3.6% patients in the intervention group died within 90 days, compared to 4.3% in the control group (4.3%) (hazard ratio (HR) = 0.83, 95% confidence interval (CI) = 0.70-0.99). A prespecified analysis showed that reduction in all-cause mortality associated with the AI-ECG alert was observed primarily in patients with high-risk ECGs (HR = 0.69, 95% CI = 0.53-0.90). In analyses of secondary outcomes, patients in the intervention group with high-risk ECGs received increased levels of intensive care compared to the control group; for the high-risk ECG group of patients, implementation of the AI-ECG alert was associated with a significant reduction in the risk of cardiac death (0.2% in the intervention arm versus 2.4% in the control arm, HR = 0.07, 95% CI = 0.01-0.56). While the precise means by which implementation of the AI-ECG alert led to decreased mortality are to be fully elucidated, these results indicate that such implementation assists in the detection of high-risk patients, prompting timely clinical care and reducing mortality. ClinicalTrials.gov registration: NCT05118035 .

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