Evaluation of health care providers’ ability to identify patient-ventilator triggering asynchrony in intensive care unit: a translational observational study in China
Abstract Background Patient-ventilator asynchrony (PVA) can result in ventilator-induced lung injury (VILI), prolong mechanical ventilation, and ventilator withdrawal failure. The ability of healthcare providers in China to recognize patient-ventilator asynchrony is unknown. The aim of our study was...
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2025-02-01
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| Online Access: | https://doi.org/10.1186/s12909-025-06638-5 |
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| author | Shengjun Liu Zhangyi Zhao Xiangyu Chen Yi Chi Siyi Yuan Fuhong Cai Zhangwei Song Yue Ma Huaiwu He Longxiang Su Yun Long |
| author_facet | Shengjun Liu Zhangyi Zhao Xiangyu Chen Yi Chi Siyi Yuan Fuhong Cai Zhangwei Song Yue Ma Huaiwu He Longxiang Su Yun Long |
| author_sort | Shengjun Liu |
| collection | DOAJ |
| description | Abstract Background Patient-ventilator asynchrony (PVA) can result in ventilator-induced lung injury (VILI), prolong mechanical ventilation, and ventilator withdrawal failure. The ability of healthcare providers in China to recognize patient-ventilator asynchrony is unknown. The aim of our study was to evaluate the ability and potential influencing factors to correctly identify patient-ventilator triggering asynchrony in tertiary hospitals in China. Methods This was an observational study carried out in 53 tertiary hospitals in China. A total of 191 healthcare providers were asked to finish entry test and evaluation test sequentially. Entry test identified qualified professionals by matching concepts with its corresponding interpretations. Evaluation test assessed the ability in recognizing patient-ventilator asynchrony waveforms by matching asynchrony waveforms with corresponding concepts. A total of 109 qualified professionals were identified. Further analysis based on professional title, role in critical care team, years of experience in managing invasive mechanical ventilation, number of published articles in the field of clinical critical respiratory medicine and training in respiratory waveform/respiratory mechanics was carried out among qualified professionals. A self-innovate Remote-VentlateView platform was used to discriminate the patient-ventilator triggering asynchrony. Results Among 109 qualified professionals, the average recognition accuracy was 3.45 out of 8 sets. Inconsistency of concept cognition and waveform recognition of patient-ventilator asynchrony was found among all types of asynchronies. The accuracy of the trained professionals was greater than that of the nontrained professionals for ineffective trigger [76.7% vs. 59.2% (p = 0.009)], auto-trigger [26.7% vs. 12.2% (p = 0.014)] and reverse triggers [30.8% vs. 12.2% (p = 0.002)]. Professionals who published more than 2 articles in the field of critical respiratory performed better on auto-triggers [41.7% vs. 15.9% (p = 0.001)] and reverse triggers [38.9% vs. 19.2% (p = 0.018)]. Neither experience in managing invasive mechanical ventilation nor professional title was associated with the ability of healthcare providers to identify asynchrony. Conclusions Receiving training in mechanical ventilation and conducting critical respiratory clinical research may increase healthcare providers’ ability to identify patient-ventilator asynchrony by using waveform analysis. The Remote-VentlateView platform may assist in identifying patient-ventilator asynchronies. |
| format | Article |
| id | doaj-art-cadb7e6ff4a84145acfd2c862484d2c3 |
| institution | Kabale University |
| issn | 1472-6920 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | BMC |
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| series | BMC Medical Education |
| spelling | doaj-art-cadb7e6ff4a84145acfd2c862484d2c32025-02-09T12:42:34ZengBMCBMC Medical Education1472-69202025-02-012511910.1186/s12909-025-06638-5Evaluation of health care providers’ ability to identify patient-ventilator triggering asynchrony in intensive care unit: a translational observational study in ChinaShengjun Liu0Zhangyi Zhao1Xiangyu Chen2Yi Chi3Siyi Yuan4Fuhong Cai5Zhangwei Song6Yue Ma7Huaiwu He8Longxiang Su9Yun Long10Department of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical SciencesCollege of Basic Medical Sciences, Shanghai Jiao Tong University School of MedicineDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical SciencesDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical SciencesDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical SciencesShanghai Shumu Medical Technology Co., LtdShanghai Shumu Medical Technology Co., LtdShanghai Shumu Medical Technology Co., LtdDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical SciencesDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical SciencesDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical SciencesAbstract Background Patient-ventilator asynchrony (PVA) can result in ventilator-induced lung injury (VILI), prolong mechanical ventilation, and ventilator withdrawal failure. The ability of healthcare providers in China to recognize patient-ventilator asynchrony is unknown. The aim of our study was to evaluate the ability and potential influencing factors to correctly identify patient-ventilator triggering asynchrony in tertiary hospitals in China. Methods This was an observational study carried out in 53 tertiary hospitals in China. A total of 191 healthcare providers were asked to finish entry test and evaluation test sequentially. Entry test identified qualified professionals by matching concepts with its corresponding interpretations. Evaluation test assessed the ability in recognizing patient-ventilator asynchrony waveforms by matching asynchrony waveforms with corresponding concepts. A total of 109 qualified professionals were identified. Further analysis based on professional title, role in critical care team, years of experience in managing invasive mechanical ventilation, number of published articles in the field of clinical critical respiratory medicine and training in respiratory waveform/respiratory mechanics was carried out among qualified professionals. A self-innovate Remote-VentlateView platform was used to discriminate the patient-ventilator triggering asynchrony. Results Among 109 qualified professionals, the average recognition accuracy was 3.45 out of 8 sets. Inconsistency of concept cognition and waveform recognition of patient-ventilator asynchrony was found among all types of asynchronies. The accuracy of the trained professionals was greater than that of the nontrained professionals for ineffective trigger [76.7% vs. 59.2% (p = 0.009)], auto-trigger [26.7% vs. 12.2% (p = 0.014)] and reverse triggers [30.8% vs. 12.2% (p = 0.002)]. Professionals who published more than 2 articles in the field of critical respiratory performed better on auto-triggers [41.7% vs. 15.9% (p = 0.001)] and reverse triggers [38.9% vs. 19.2% (p = 0.018)]. Neither experience in managing invasive mechanical ventilation nor professional title was associated with the ability of healthcare providers to identify asynchrony. Conclusions Receiving training in mechanical ventilation and conducting critical respiratory clinical research may increase healthcare providers’ ability to identify patient-ventilator asynchrony by using waveform analysis. The Remote-VentlateView platform may assist in identifying patient-ventilator asynchronies.https://doi.org/10.1186/s12909-025-06638-5Critical careMechanical ventilationIntensive care unitPatient-ventilator asynchronyWaveformsRemote-VentlateView platform |
| spellingShingle | Shengjun Liu Zhangyi Zhao Xiangyu Chen Yi Chi Siyi Yuan Fuhong Cai Zhangwei Song Yue Ma Huaiwu He Longxiang Su Yun Long Evaluation of health care providers’ ability to identify patient-ventilator triggering asynchrony in intensive care unit: a translational observational study in China BMC Medical Education Critical care Mechanical ventilation Intensive care unit Patient-ventilator asynchrony Waveforms Remote-VentlateView platform |
| title | Evaluation of health care providers’ ability to identify patient-ventilator triggering asynchrony in intensive care unit: a translational observational study in China |
| title_full | Evaluation of health care providers’ ability to identify patient-ventilator triggering asynchrony in intensive care unit: a translational observational study in China |
| title_fullStr | Evaluation of health care providers’ ability to identify patient-ventilator triggering asynchrony in intensive care unit: a translational observational study in China |
| title_full_unstemmed | Evaluation of health care providers’ ability to identify patient-ventilator triggering asynchrony in intensive care unit: a translational observational study in China |
| title_short | Evaluation of health care providers’ ability to identify patient-ventilator triggering asynchrony in intensive care unit: a translational observational study in China |
| title_sort | evaluation of health care providers ability to identify patient ventilator triggering asynchrony in intensive care unit a translational observational study in china |
| topic | Critical care Mechanical ventilation Intensive care unit Patient-ventilator asynchrony Waveforms Remote-VentlateView platform |
| url | https://doi.org/10.1186/s12909-025-06638-5 |
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