» Articles » PMID: 39538084

Analysis of Six Consecutive Waves of ICU-admitted COVID-19 Patients: Key Findings and Insights from a Portuguese Population

Overview
Journal Geroscience
Specialty Geriatrics
Date 2024 Nov 13
PMID 39538084
Authors
Affiliations
Soon will be listed here.
Abstract

Identifying high-risk patients, particularly in intensive care units (ICUs), enhances treatment and reduces severe outcomes. Since the pandemic, numerous studies have examined COVID-19 patient profiles and factors linked to increased mortality. Despite six pandemic waves, to the best of our knowledge, there is no extensive comparative analysis of patients' characteristics across these waves in Portugal. Thus, we aimed to analyze the demographic and clinical features of 1041 COVID-19 patients admitted to an ICU and their relationship with the different SARS-Cov-2 variants in Portugal. Additionally, we conducted an in-depth examination of factors contributing to early and late mortality by analyzing clinical data and laboratory results from the first 72 h of ICU admission. Our findings revealed a notable decline in ICU admissions due to COVID-19, with the highest mortality rates observed during the second and third waves. Furthermore, immunization could have significantly contributed to the reduction in the median age of ICU-admitted patients and the severity of their conditions. The factors contributing to early and late mortality differed. Age, wave number, D-dimers, and procalcitonin were independently associated with the risk of early death. As a measure of discriminative power for the derived multivariable model, an AUC of 0.825 (p < 0.001; 95% CI, 0.719-0.931) was obtained. For late mortality, a model incorporating age, wave number, hematologic cancer, C-reactive protein, lactate dehydrogenase, and platelet counts resulted in an AUC of 0.795 (p < 0.001; 95% CI, 0.759-0.831). These findings underscore the importance of conducting comprehensive analyses across pandemic waves to better understand the dynamics of COVID-19.

Citing Articles

Early Mortality Prediction in Intensive Care Unit Patients Based on Serum Metabolomic Fingerprint.

Araujo R, Ramalhete L, Von Rekowski C, Fonseca T, Bento L, Calado C Int J Mol Sci. 2025; 25(24.

PMID: 39769370 PMC: 11677344. DOI: 10.3390/ijms252413609.

References
1.
Harapan H, Itoh N, Yufika A, Winardi W, Keam S, Te H . Coronavirus disease 2019 (COVID-19): A literature review. J Infect Public Health. 2020; 13(5):667-673. PMC: 7142680. DOI: 10.1016/j.jiph.2020.03.019. View

2.
Borges V, Isidro J, Cortes-Martins H, Duarte S, Vieira L, Leite R . Massive dissemination of a SARS-CoV-2 Spike Y839 variant in Portugal. Emerg Microbes Infect. 2020; 9(1):2488-2496. PMC: 7717510. DOI: 10.1080/22221751.2020.1844552. View

3.
Hodcroft E, Zuber M, Nadeau S, Vaughan T, Crawford K, Althaus C . Spread of a SARS-CoV-2 variant through Europe in the summer of 2020. Nature. 2021; 595(7869):707-712. DOI: 10.1038/s41586-021-03677-y. View

4.
Gowrisankar A, Priyanka T, Banerjee S . Omicron: a mysterious variant of concern. Eur Phys J Plus. 2022; 137(1):100. PMC: 8743750. DOI: 10.1140/epjp/s13360-021-02321-y. View

5.
Miller J, Tada M, Goto M, Chen H, Dang E, Mohr N . Prediction models for severe manifestations and mortality due to COVID-19: A systematic review. Acad Emerg Med. 2022; 29(2):206-216. DOI: 10.1111/acem.14447. View