Exploring the clinical benefit of ventilation therapy across various patient groups with COVID-19 using real-world data

Medientyp: E-Artikel

Titel: Exploring the clinical benefit of ventilation therapy across various patient groups with COVID-19 using real-world data

Beteiligte: Abbasi-Kangevari, Mohsen [VerfasserIn]; Ghanbari, Ali [VerfasserIn]; Malekpour, Mohammad-Reza [VerfasserIn]; Ghamari, Seyyed-Hadi [VerfasserIn]; Azadnajafabad, Sina [VerfasserIn]; Saeedi Moghaddam, Sahar [VerfasserIn]; Keykhaei, Mohammad [VerfasserIn]; Haghshenas, Rosa [VerfasserIn]; Golestani, Ali [VerfasserIn]; Rashidi, Mohammad-Mahdi [VerfasserIn]; Rezaei, Nazila [VerfasserIn]; Ghasemi, Erfan [VerfasserIn]; Rezaei, Negar [VerfasserIn]; Jamshidi, Hamid Reza [VerfasserIn]; Larijani, Bagher [VerfasserIn]

Erschienen: Berlin: Springer Nature, 2023

Sprache: Englisch

DOI: https://doi.org/10.1038/s41598-023-37912-5

ISSN: 2045-2322

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Beschreibung: Scarcity of ventilators during COVID-19 pandemic has urged public health authorities to develop prioritization recommendations and guidelines with the real-time decision-making process based on the resources and contexts. Nevertheless, patients with COVID-19 who will benefit the most from ventilation therapy have not been well-defined yet. Thus, the objective of this study was to investigate the benefit of ventilation therapy among various patient groups with COVID-19 admitted to hospitals, based on the real-world data of hospitalized adult patients. Data used in the longitudinal study included 599,340 records of hospitalized patients who were admitted from February 2020 to June 2021. All participants were categorized based on sex, age, city of residence, the hospitals' affiliated university, and their date of hospitalization. Age groups were defined as 18–39, 40–64, and more than 65-year-old participants. Two models were used in this study: in the first model, participants were assessed by their probability of receiving ventilation therapy during hospitalization based on demographic and clinical factors using mixed-effects logistic regression. In the second model, the clinical benefit of receiving ventilation therapy among various patient groups was quantified while considering the probability of receiving ventilation therapy during hospital admission, as estimated in the first model. The interaction coefficient in the second model indicated the difference in the slope of the logit probability of recovery for a one-unit increase in the probability of receiving ventilation therapy between the patients who received ventilation compared to those who did not while considering other factors constant. The interaction coefficient was used as an indicator to quantify the benefit of ventilation reception and possibly be used as a criterion for comparison among various patient groups. Among participants, 60,113 (10.0%) cases received ventilation therapy, 85,158 (14.2%) passed away due to COVID-19, and 514,182 (85.8%) ...

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