Application of a cloud platform that identifies patient-ventilator asynchrony and enables continuous monitoring of mechanical ventilation in intensive care unit
机构:[1]Chinese Acad Med Sci & Peking Union Med Coll, Peking Union Med Coll Hosp, State Key Lab Complex Severe & Rare Dis, Dept Crit Care Med, 1st Shuaifuyuan, Beijing 100730, Peoples R China[2]Chinese Acad Med Sci & Peking Union Med Coll, Peking Union Med Coll Hosp, Dept Pulm & Crit Care Med, 1 Shuaifuyuan Wangfujing, Beijing, Peoples R China[3]Beijing Puren Hosp, Dept Crit Care Med, Beijing 100062, Peoples R China[4]Beijing Sixth Hosp, Dept Crit Care Med, Beijing 100007, Peoples R China[5]Beijing Univ Chinese Med, Dongzhimen Hosp, Intens Care Unit, Beijing 100700, Peoples R China[6]Beijing Hosp, Intens Care Unit, Beijing 100005, Peoples R China[7]Capital Med Univ, Beijing Hosp Tradit Chinese Med, Dept Crit Care Med, Beijing 100010, Peoples R China[8]Beijing Hepingli Hosp, Intens Care Unit, Beijing 100013, Peoples R China[9]Beijing Longfu Hosp, Intens Care Unit, Beijing 100010, Peoples R China[10]Capital Med Univ, Beijing Tongren Hosp, Intens Care Unit, Beijing 100730, Peoples R China首都医科大学附属北京同仁医院首都医科大学附属同仁医院[11]Peoples Liberat Army Gen Hosp, Med Ctr 7, Dept Crit Care Med, Beijing, Peoples R China
Background: Patient-ventilator asynchrony (PVA) frequently occurs in mechanically ventilated patients within the ICU and has the potential for harm. Depending solely on the health care team cannot accurately and promptly identify PVA. To address this issue, our team has developed a cloud-based platform for monitoring mechanical ventilation (MV), comprising the PVARemoteMonitor system and the 24-h MV analysis report. We conducted a survey to evaluate physicians' satisfaction and acceptance of the platform in 14 ICUs. Methods: Data from medical records, clinical information systems, and ventilators were uploaded to the cloud platform and underwent data processing. The data were analyzed to monitor PVA and displayed in the front-end. The 24-h analysis report for MV was generated for clinical reference. Critical care physicians in 14 hospitals' ICUs that involved in the platform participated in a questionnaire survey, among whom 10 physicians were interviewed to investigate physicians' acceptance and opinions of this system. Results: The PVA-RemoteMonitor system exhibited a high level of specificity in detecting flow insufficiency, premature cycle, delayed cycle, reverse trigger, auto trigger, and overshoot, with sensitivities of 90.31 %, 98.76 %, 99.75 %, 99.97 %, 100 %, and 99.69 %, respectively. The 24-h analysis report supplied essential data about PVA and respiratory mechanics. 86.2 % (75/87) of physicians supported the application of this platform. Conclusions: The PVA-RemoteMonitor system accurately identified PVA, and the MV analysis report provided guidance in controlling PVA. Our platform can effectively assist ICU physicians in the management of ventilated patients.
基金:
National High-Level Hospital Clinical Research Funding [2022-PUMCH-B-115, 2022-PUMCH-D-005]; CAMS Innovation Fund for Medical Sciences (CIFMS) [2023-I2M-CT-B-031]
第一作者机构:[1]Chinese Acad Med Sci & Peking Union Med Coll, Peking Union Med Coll Hosp, State Key Lab Complex Severe & Rare Dis, Dept Crit Care Med, 1st Shuaifuyuan, Beijing 100730, Peoples R China
通讯作者:
推荐引用方式(GB/T 7714):
Chen Xiangyu,Fan Junping,Zhao Wenxian,et al.Application of a cloud platform that identifies patient-ventilator asynchrony and enables continuous monitoring of mechanical ventilation in intensive care unit[J].HELIYON.2024,10(13):doi:10.1016/j.heliyon.2024.e33692.
APA:
Chen, Xiangyu,Fan, Junping,Zhao, Wenxian,Shi, Ruochun,Guo, Nan...&Long, Yun.(2024).Application of a cloud platform that identifies patient-ventilator asynchrony and enables continuous monitoring of mechanical ventilation in intensive care unit.HELIYON,10,(13)
MLA:
Chen, Xiangyu,et al."Application of a cloud platform that identifies patient-ventilator asynchrony and enables continuous monitoring of mechanical ventilation in intensive care unit".HELIYON 10..13(2024)