住院期间从PPG衍生的血流动力学特征预测中风
In-Hospital Stroke Risk-State Classification from PPG-Derived Hemodynamic Features
AI总结：
本文利用PPG数据，结合大型语言模型和ResNet-1D模型，实现了对住院期间中风的早期预测，展示了PPG在发病前数小时具有预测性，为临床主动监控提供了新方法。
摘要：
标准临床数据集中缺乏预住院生理数据从根本上限制了中风的早期预测，因为患者通常在中风发生后才出现，使得诸如光脉冲波形图（PPG）等连续监测信号的预测价值未被验证。在本工作中，我们通过关注一个罕见但临床关键的群体——住院期间发生中风且已处于连续监测的患者，从而实现了对预中风PPG波形的首次大规模分析，这些波形与已验证的发病时间对齐。使用MIMIC-III和MC-MED，我们开发了一个结合大型语言模型的数据挖掘流程，以从非结构化临床笔记中提取精确的住院中风发病时间戳，随后由医生验证，分别识别出176名（MIMIC）和158名（MC-MED）具有高质量同步发病前PPG数据的患者。然后我们从PPG中提取血流动力学特征，并使用ResNet-1D模型在多个早期预警时间范围内预测即将发生的中风。该模型在MIMIC-III上分别在发病前4、5和6小时达到F1分数0.7956、0.8759和0.9406，在不重新调整的情况下，在MC-MED上达到0.9256、0.9595和0.9888。这些结果提供了来自真实世界临床数据的首次实证证据，表明PPG在发病前数小时含有预测中风的特征，证明了被动获取的生理信号可以支持可靠的早期预警，支持从事件后中风识别向基于生理的主动监控的转变，可能在常规临床护理中显著改善患者预后。
英文摘要：
The scarcity of temporally aligned pre-event physiological data limits the study of stroke risk states before documented clinical recognition. We focus on patients who experienced stroke during hospitalization while undergoing continuous monitoring, enabling retrospective analysis of pre-anchor photoplethysmography (PPG). Using MIMIC-III and MC-MED, an LLM-assisted pipeline generated candidate stroke anchors from unstructured notes. All retained anchors underwent physician adjudication, and a stratified 100-case double-review audit showed 95.0% candidate-to-adjudicated agreement within +/-15 min. We identified 176 MIMIC-III patients and 154 MC-MED patients with eligible synchronized pre-anchor PPG. A fixed 17-channel hemodynamic representation and ResNet-1D classifier were evaluated using patient-level five-fold internal validation and frozen external testing. At validation-selected operating points, F1-scores were 0.7956, 0.8759, and 0.9406 for 4-, 5-, and 6-hour horizons in MIMIC-III and 0.9256, 0.9595, and 0.9888 in MC-MED; the corresponding threshold-free AUCs ranged from 0.6124 to 0.7079. The PPG model achieved higher F1 than four non-waveform clinical and structured-EHR comparators in all six cohort-horizon settings. On high-risk non-stroke controls, window-level false-positive rates ranged from 0.1371 to 0.2938 and decreased to 0.0183-0.1739 after persistence aggregation. These retrospective findings support measurable pre-anchor PPG structure, but do not establish biological stroke onset, a calibrated bedside alarm, or a clinically validated prediction lead time.
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