PDF(Pubmed)
Abstract：
BACKGROUND: The interaction between the patient and the ventilator is often disturbed, resulting in patient-ventilator asynchrony (PVA). Asynchrony can lead to respiratory failure, increased artificial ventilation time, prolonged hospitalization, and escalated healthcare costs. Professionals\' knowledge regarding waveform analysis has significant implications for improving patient outcomes and minimizing ventilation-related adverse events. Studies investigating the knowledge of healthcare professionals on patient-ventilator asynchrony and its associated factors in the Ethiopian context are limited. Therefore, this study aimed to assess the knowledge of healthcare professionals about using waveform analysis to detect asynchrony.
METHODS: A multicenter cross-sectional study was conducted on 237 healthcare professionals (HCPs) working in the intensive care units (ICUs) of federal public hospitals in Addis Ababa, Ethiopia, from December 2022 to May 2023. The data were collected using a structured and pretested interviewer-administered questionnaire. Then, the collected data were cleaned, coded, and entered into Epi data V-4.2.2 and exported to SPSS V-27 for analysis. After description, associations were analyzed using binary logistic regression. Variables with a P-value of < 0.25 in the bivariable analysis were transferred to the multivariable analysis. Statistical significance was declared using 95% confidence intervals, and the strengths of associations were reported using adjusted odds ratios (AORs).
RESULTS: A total of 237 HCPs participated in the study with a response rate of 100%. Half (49.8%) of the participants were females. The mean age of the participants was 29 years (SD = 3.57). Overall, 10.5% (95% CI: 6.9-15.2) of the participants had good knowledge of detecting PVA using waveform analysis. In the logistic regression, the number of MV-specific trainings and the training site had a statistically significant association with knowledge of HCPs. HCPs who attended more frequent MV training were more likely to have good knowledge than their counterparts [AOR = 6.88 (95% CI: 2.61-15.45)]. Additionally, the odds of good knowledge among professionals who attended offsite training were 2.6 times higher than those among professionals trained onsite [AOR = 2.63 (95% CI: 1.36-7.98)].
CONCLUSIONS: The knowledge of ICU healthcare professionals about the identification of PVA using waveform analysis is low. In addition, the study also showed that attending offsite MV training and repeated MV training sessions were independently associated with good knowledge. Consequently, the study findings magnify the relevance of providing frequent and specific training sessions focused on waveform analysis to boost the knowledge of HCPs.
METHODS: A multicenter cross-sectional study was conducted on 237 healthcare professionals (HCPs) working in the intensive care units (ICUs) of federal public hospitals in Addis Ababa, Ethiopia, from December 2022 to May 2023. The data were collected using a structured and pretested interviewer-administered questionnaire. Then, the collected data were cleaned, coded, and entered into Epi data V-4.2.2 and exported to SPSS V-27 for analysis. After description, associations were analyzed using binary logistic regression. Variables with a P-value of < 0.25 in the bivariable analysis were transferred to the multivariable analysis. Statistical significance was declared using 95% confidence intervals, and the strengths of associations were reported using adjusted odds ratios (AORs).
RESULTS: A total of 237 HCPs participated in the study with a response rate of 100%. Half (49.8%) of the participants were females. The mean age of the participants was 29 years (SD = 3.57). Overall, 10.5% (95% CI: 6.9-15.2) of the participants had good knowledge of detecting PVA using waveform analysis. In the logistic regression, the number of MV-specific trainings and the training site had a statistically significant association with knowledge of HCPs. HCPs who attended more frequent MV training were more likely to have good knowledge than their counterparts [AOR = 6.88 (95% CI: 2.61-15.45)]. Additionally, the odds of good knowledge among professionals who attended offsite training were 2.6 times higher than those among professionals trained onsite [AOR = 2.63 (95% CI: 1.36-7.98)].
CONCLUSIONS: The knowledge of ICU healthcare professionals about the identification of PVA using waveform analysis is low. In addition, the study also showed that attending offsite MV training and repeated MV training sessions were independently associated with good knowledge. Consequently, the study findings magnify the relevance of providing frequent and specific training sessions focused on waveform analysis to boost the knowledge of HCPs.
摘要：
背景：患者与呼吸机之间的相互作用经常受到干扰，导致患者-呼吸机异步(PVA)。不同步会导致呼吸衰竭,增加人工通风时间，住院时间延长,和不断升级的医疗成本。专业人员关于波形分析的知识对于改善患者预后和减少通气相关不良事件具有重要意义。在埃塞俄比亚背景下，调查医疗保健专业人员对患者-呼吸机异步及其相关因素的知识的研究是有限的。因此,本研究旨在评估医疗保健专业人员使用波形分析检测异步性的知识。
方法：对在亚的斯亚贝巴联邦公立医院重症监护病房（ICU）工作的237名医疗保健专业人员（HCP）进行了一项多中心横断面研究，埃塞俄比亚,从2022年12月到2023年5月。数据是使用结构化和预先测试的面试官管理的问卷收集的。然后，收集的数据被清理，编码,并输入Epi数据V-4.2.2，并导出到SPSSV-27进行分析。在描述之后,使用二元逻辑回归分析关联。将双变量分析中P值<0.25的变量转移到多变量分析。使用95%置信区间声明统计显著性，并使用校正比值比(AORs)报告关联强度.
结果：共有237名HCP参与了该研究，反应率为100％。一半（49.8％）的参与者是女性。参与者的平均年龄为29岁（SD=3.57）。总的来说,10.5％（95％CI：6.9-15.2）的参与者具有使用波形分析检测PVA的良好知识。在逻辑回归中，MV特定培训的数量和培训地点与HCPs知识有统计学显著关联.参加更频繁的MV培训的HCP比他们的同行更有可能拥有良好的知识[AOR=6.88(95%CI:2.61-15.45)]。此外,参加非现场培训的专业人员获得良好知识的几率是现场培训的专业人员的2.6倍[AOR=2.63(95%CI:1.36-7.98)].
结论：ICU医疗专业人员使用波形分析识别PVA的知识较低。此外,该研究还表明，参加场外MV培训和重复MV培训课程与良好的知识独立相关。因此,研究结果放大了提供以波形分析为重点的频繁而具体的培训课程以提高HCP知识的相关性.
方法：对在亚的斯亚贝巴联邦公立医院重症监护病房（ICU）工作的237名医疗保健专业人员（HCP）进行了一项多中心横断面研究，埃塞俄比亚,从2022年12月到2023年5月。数据是使用结构化和预先测试的面试官管理的问卷收集的。然后，收集的数据被清理，编码,并输入Epi数据V-4.2.2，并导出到SPSSV-27进行分析。在描述之后,使用二元逻辑回归分析关联。将双变量分析中P值<0.25的变量转移到多变量分析。使用95%置信区间声明统计显著性，并使用校正比值比(AORs)报告关联强度.
结果：共有237名HCP参与了该研究，反应率为100％。一半（49.8％）的参与者是女性。参与者的平均年龄为29岁（SD=3.57）。总的来说,10.5％（95％CI：6.9-15.2）的参与者具有使用波形分析检测PVA的良好知识。在逻辑回归中，MV特定培训的数量和培训地点与HCPs知识有统计学显著关联.参加更频繁的MV培训的HCP比他们的同行更有可能拥有良好的知识[AOR=6.88(95%CI:2.61-15.45)]。此外,参加非现场培训的专业人员获得良好知识的几率是现场培训的专业人员的2.6倍[AOR=2.63(95%CI:1.36-7.98)].
结论：ICU医疗专业人员使用波形分析识别PVA的知识较低。此外,该研究还表明，参加场外MV培训和重复MV培训课程与良好的知识独立相关。因此,研究结果放大了提供以波形分析为重点的频繁而具体的培训课程以提高HCP知识的相关性.
