COVID‐19 Mortality in Swedish Intensive Care Units: A Multicenter Survival Analysis

BACKGROUND: Mortality among critically ill COVID-19 patients has varied globally. In Sweden, geographic differences in mortality have also been observed. The current study aimed to determine whether mortality differences persist after adjusting for differences in case-mix, and to identify potential independent factors contributing to regional variations in mortality. METHODS: We conducted a multicenter cohort study including adult patients admitted to seven hospital ICUs across three Swedish healthcare counties between March 1, 2020 and July 31, 2021. These ICUs include one university hospital, three county hospitals and three local hospitals, and cover the intensive care infrastructure for approximately one million inhabitants. Patients were assigned to the hospital of initial ICU admission, even if transferred later during the course. Patient characteristics, disease severity, respiratory support, and treatments were registered. Primary outcome was 90-day mortality. A mixed-effects Cox proportional hazards model was used. RESULTS: Seven hundred and forty seven patients were included. The unadjusted 90-day mortality varied significantly, with the highest rate at 30%, and the lowest at 8.5% (p < 0.001). After adjustment for baseline confounders (Charlson comorbidity index, sex, SAPS3, age, smoking status, BMI), calendar time and healthcare county (random intercept), all hospitals were significantly associated with increased 90-day mortality compared with the lowest mortality hospital. Hazard ratios ranged from 2.38 to 5.06. CONCLUSION: Among patients admitted to ICU due to COVID-19, we observed a difference in mortality related to the hospital of first ICU admission. This difference persisted after adjustment for calendar time, baseline confounders, and healthcare county. Potential explanations are lacking within the current study. Future studies should focus on comprehensive evaluation of both organizational and contextual determinants of mortality. EDITORIAL COMMENT: This analysis from 3 Swedish counties (7 hospitals) for COVID ICU cases presents factors and relations to mortality risk, including factors for first admission to university-larger-, or smaller hospital. An association was observed for higher risk if the first ICU admission was in a smaller hospital, though recognizing that this is a dataset coming from a small set of hospitals.

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Journal
Acta Anaesthesiologica Scandinavica
Published
2026-06-14
DOI
https://doi.org/10.1111/aas.70279
Primary Topic
COVID-19 Clinical Research Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

COVID‐19 Mortality in Swedish Intensive Care Units: A Multicenter Survival Analysis

Andreas Ekman, Johan Berkius, Sören Berg, Håkan Johansson et al.
Acta Anaesthesiologica Scandinavica
COVID-19 Clinical Research Studies
article

COVID‐19 Mortality in Swedish Intensive Care Units: A Multicenter Survival Analysis

Andreas Ekman, Johan Berkius, Sören Berg, Håkan Johansson, Fredrik Hammarskjöld, Knut Taxbro, Jonna Idh, Louise Elander, Gustaf Forsberg, Åse Östholm, Katarina Niward
article en

Abstract

BACKGROUND: Mortality among critically ill COVID-19 patients has varied globally. In Sweden, geographic differences in mortality have also been observed. The current study aimed to determine whether mortality differences persist after adjusting for differences in case-mix, and to identify potential independent factors contributing to regional variations in mortality. METHODS: We conducted a multicenter cohort study including adult patients admitted to seven hospital ICUs across three Swedish healthcare counties between March 1, 2020 and July 31, 2021. These ICUs include one university hospital, three county hospitals and three local hospitals, and cover the intensive care infrastructure for approximately one million inhabitants. Patients were assigned to the hospital of initial ICU admission, even if transferred later during the course. Patient characteristics, disease severity, respiratory support, and treatments were registered. Primary outcome was 90-day mortality. A mixed-effects Cox proportional hazards model was used. RESULTS: Seven hundred and forty seven patients were included. The unadjusted 90-day mortality varied significantly, with the highest rate at 30%, and the lowest at 8.5% (p < 0.001). After adjustment for baseline confounders (Charlson comorbidity index, sex, SAPS3, age, smoking status, BMI), calendar time and healthcare county (random intercept), all hospitals were significantly associated with increased 90-day mortality compared with the lowest mortality hospital. Hazard ratios ranged from 2.38 to 5.06. CONCLUSION: Among patients admitted to ICU due to COVID-19, we observed a difference in mortality related to the hospital of first ICU admission. This difference persisted after adjustment for calendar time, baseline confounders, and healthcare county. Potential explanations are lacking within the current study. Future studies should focus on comprehensive evaluation of both organizational and contextual determinants of mortality. EDITORIAL COMMENT: This analysis from 3 Swedish counties (7 hospitals) for COVID ICU cases presents factors and relations to mortality risk, including factors for first admission to university-larger-, or smaller hospital. An association was observed for higher risk if the first ICU admission was in a smaller hospital, though recognizing that this is a dataset coming from a small set of hospitals.

Acta Anaesthesiologica ScandinavicaVol. 70(6)
Linköping University (SE), Lund University (SE), Karolinska Institutet (SE), Eskilstuna Municipality (SE), Ministry of Emergency Situations (KG), Ornsköldsvik Hospital (SE), Center for Clinical Research Dalarna (SE), Skåne University Hospital (SE), Landstinget i Kalmar län (SE), Eksjö Municipality (SE), Ryhov Hospital Jönköping (SE), Linköping University Hospital (SE), Norrköping Hospital (SE), Trelleborg (Sweden) (SE)
Forskningsrådet i Sydöstra Sverige, Region Östergötland
Good health and well-being
Openalex Percentile: Top 7%
COVID-19 Clinical Research Studies
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