Knowledge and associated factors of healthcare professionals in detecting patient-ventilator asynchrony using waveform analysis at intensive care units of the federal public hospitals in Addis Ababa, Ethiopia, 2023

Autor: Habtamu Zelalem, Migbar Mekonnen Sibhat, Abate Yeshidinber, Habtamu Kehali
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: BMC Nursing, Vol 23, Iss 1, Pp 1-9 (2024)
Druh dokumentu: article
ISSN: 1472-6955
DOI: 10.1186/s12912-024-02068-8
Popis: 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
Databáze: Directory of Open Access Journals
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