Dataset Information

Changes in characteristics and outcomes of critically ill COVID-19 patients in Tyrol (Austria) over 1 year.

ABSTRACT:

Background

Widely varying mortality rates of critically ill Coronavirus disease 19 (COVID-19) patients in the world highlighted the need for local surveillance of baseline characteristics, treatment strategies and outcome. We compared two periods of the COVID-19 pandemic to identify important differences in characteristics and therapeutic measures and their influence on the outcome of critically ill COVID-19 patients.

Methods

This multicenter prospective register study included all patients with a SARS-CoV‑2 infection confirmed by polymerase chain reaction, who were treated in 1 of the 12 intensive care units (ICU) from 8 hospitals in Tyrol, Austria during 2 defined periods (1 February 2020 until 17 July: first wave and 18 July 2020 until 22 February 2021: second wave) of the COVID-19 pandemic.

Results

Overall, 508 patients were analyzed. The majority (n = 401) presented during the second wave, where the median age was significantly higher (64 years, IQR 54-74 years vs. 72 years, IQR 62-78 years, p < 0.001). Invasive mechanical ventilation was less frequent during the second period (50.5% vs 67.3%, p = 0.003), as was the use of vasopressors (50.3% vs. 69.2%, p = 0.001) and renal replacement therapy (12.0% vs. 19.6%, p = 0.061), which resulted in shorter ICU length of stay (10 days, IQR 5-18 days vs. 18 days, IQR 5-31 days, p < 0.001). Nonetheless, ICU mortality did not change (28.9% vs. 21.5%, p = 0.159) and hospital mortality even increased (22.4% vs. 33.4%, p = 0.039) in the second period. Age, frailty and the number of comorbidities were significant predictors of hospital mortality in a multivariate logistic regression analysis of the overall cohort.

Conclusion

Advanced treatment strategies and learning effects over time resulted in reduced rates of mechanical ventilation and vasopressor use in the second wave associated with shorter ICU length of stay. Despite these improvements, age appears to be a dominant factor for hospital mortality in critically ill COVID-19 patients.

SUBMITTER: Mayerhofer T

PROVIDER: S-EPMC8521508 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Publications

Changes in characteristics and outcomes of critically ill COVID-19 patients in Tyrol (Austria) over 1 year.

Mayerhöfer Timo T Klein Sebastian J SJ Peer Andreas A Perschinka Fabian F Lehner Georg F GF Hasslacher Julia J Bellmann Romuald R Gasteiger Lukas L Mittermayr Markus M Eschertzhuber Stephan S Mathis Simon S Fiala Anna A Fries Dietmar D Kalenka Armin A Foidl Eva E Hasibeder Walter W Helbok Raimund R Kirchmair Lukas L Stögermüller Birgit B Krismer Christoph C Heiner Tatjana T Ladner Eugen E Thomé Claudius C Preuß-Hernandez Christian C Mayr Andreas A Pechlaner Agnes A Potocnik Miriam M Reitter Bruno B Brunner Jürgen J Zagitzer-Hofer Stefanie S Ribitsch Alexandra A Joannidis Michael M

Wiener klinische Wochenschrift 20211018 23-24

<h4>Background</h4>Widely varying mortality rates of critically ill Coronavirus disease 19 (COVID-19) patients in the world highlighted the need for local surveillance of baseline characteristics, treatment strategies and outcome. We compared two periods of the COVID-19 pandemic to identify important differences in characteristics and therapeutic measures and their influence on the outcome of critically ill COVID-19 patients.<h4>Methods</h4>This multicenter prospective register study included al ...[more]

PMID: 34661740

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Project description:BackgroundCoronavirus disease 2019 (COVID-19) has affected individuals worldwide, and patients with cancer are particularly vulnerable to COVID-19-related severe illness, respiratory failure, and mortality. The relationship between COVID-19 and cancer remains a critical concern, and a comprehensive investigation of the factors affecting survival among patients with cancer who develop COVID-19-related respiratory failure is warranted. We aim to compare the characteristics and outcomes of COVID-19-related acute respiratory failure in patients with and without underlying cancer, while analyzing factors affecting in-hospital survival among cancer patients.MethodsWe conducted a retrospective observational study at Taipei Veterans General Hospital in Taiwan from May to September 2022, a period during which the omicron variant of the severe acute respiratory syndrome coronavirus 2 was circulating. Eligible patients had COVID-19 and acute respiratory failure. Clinical data, demographic information, disease severity markers, treatment details, and outcomes were collected and analyzed.ResultsOf the 215 enrolled critically ill patients with COVID-19, 65 had cancer. The patients with cancer were younger and had lower absolute lymphocyte counts, higher ferritin and lactate dehydrogenase (LDH) concentrations, and increased vasopressor use compared with those without cancer. The patients with cancer also received more COVID-19 specific treatments but had higher in-hospital mortality rate (61.5% vs 36%, P = 0.002) and longer viral shedding (13 vs 10 days, P = 0.007) than those without cancer did. Smoking [odds ratio (OR): 5.804, 95% confidence interval (CI): 1.847-39.746], elevated LDH (OR: 1.004, 95% CI: 1.001-1.012), vasopressor use (OR: 5.437, 95% CI: 1.202-24.593), and new renal replacement therapy (OR: 3.523, 95% CI: 1.203-61.108) were independent predictors of in-hospital mortality among patients with cancer and respiratory failure.ConclusionCritically ill patients with cancer experiencing COVID-19-related acute respiratory failure present unique clinical features and worse clinical outcomes compared with those without cancer. Smoking, elevated LDH, vasopressor use, and new renal replacement therapy were risk factors for in-hospital mortality in these patients.

Dataset Information

Changes in characteristics and outcomes of critically ill COVID-19 patients in Tyrol (Austria) over 1 year.

Background

Methods

Results

Conclusion

Publications

Changes in characteristics and outcomes of critically ill COVID-19 patients in Tyrol (Austria) over 1 year.

Similar Datasets

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