中国真菌学杂志2026，Vol.21Issue(2)：174-180,7.DOI:10.3969/j.issn.1673-3827.2026.02.010
基于智能辅助医疗保障系统构建肺孢子菌肺炎早期预警模型的研究
Development and clinical validation of an early warning model for Pneumocystis jirovecii pneumonia in immunocompromised hematology patients using an intelligent medical support system
张震玮 1王艳军 1李嘉隆 1廖云 1朱在雄 2赵冰冰2
作者信息
- 1. 中国融通医疗健康集团有限公司网络安全与信息化办公室,成都 610000
- 2. 上海四一一医院血液内科,上海 200080
- 折叠
摘要
Abstract
Objective To evaluate the clinical value of an early warning model for Pneumocystis jirovecii pneumonia(PJP)developed using an intelligent medical support system in immunocompromised hematology patients.Methods A retrospective study conducted involving 179 immunocompromised hematologic malignancy patients who presented with fever or respiratory symptoms and received treatment at the Department of Hematology,Shanghai 411 Hospital from January 2025 to February 2026.An early warning model was constructed using a smart medical support system that integrated multi-source data,including immune status,fungal serological markers,imaging features,and clinical text information.The model's efficacy was validated using metrics such as diagnostic accuracy.Results Among 36 patients confirmed with PJP by metagenomic next-generation sequencing,the prediction model identified 34 true positive cases out of 63 positive alerts.Notably,all true positive cases were diagnosed within 72 hours after symptom onset,which was significantly earlier than the clinical diagnosis group(30 true positives out of 44 clinically diagnosed cases,with only 30％(9/30)diagnosed within 72 hours).The prediction model demonstrated a sensitivity of 94.44％and a specificity of 79.72％for diagnosing PJP in immunocompromised patients with hematological diseases.Conclusion The intelligent medical support system significantly enhances early PJP diagnosis efficiency through multimodal data fusion and a dual-track knowledge base,establishing a new paradigm for fungal infection prevention and control in immunosuppressed patients.关键词
耶氏肺孢子菌肺炎/人工智能/智能辅助医疗保障系统/早期预警/免疫抑制/回顾性研究Key words
Pneumocystis jirovecii pneumonia/artificial intelligence/intelligent medical support system/early warning/immunosuppression/retrospective study引用本文复制引用
张震玮,王艳军,李嘉隆,廖云,朱在雄,赵冰冰..基于智能辅助医疗保障系统构建肺孢子菌肺炎早期预警模型的研究[J].中国真菌学杂志,2026,21(2):174-180,7.
