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Background <p>The COVID-19 pandemic has placed unprecedented pressure on global healthcare systems, severely affecting the intensive care unit (ICU) capacity. Therefore, this study explored the association between prefecture-level ICU congestion and COVID-19 mortality in each prefecture of Japan.</p> Methods <p>This retrospective study analyzed data from the CRoss Icu Searchable Information System, covering all patients with COVID-19 who underwent mechanical ventilation with clearly documented initiation and cessation dates between January 1, 2020, and March 31, 2023. Prefecture-level ICU congestion was calculated as the total ventilator days over 2 weeks for severely ill patients with COVID-19, divided by the maximum potential ventilator days in the prefecture. Prefecture-level ICU congestion in each region was visualized by plotting time-series graphs capturing the temporal progression of congestion levels. Continuous variables were standardized, and missing data were imputed into 20 datasets by chained equations, assuming data missing at random. A mixed-effects logistic regression model was separately applied to each of the 20 multiply-imputed datasets generated during the imputation procedure to evaluate the association between prefecture-level ICU congestion and mortality. Estimates and standard errors from each model were pooled using Rubin’s rules to obtain final combined results. A sensitivity analysis was performed using the same mixed-effects model, replacing the continuous congestion level with a categorical variable.</p> Results <p>A total number of 10,427 patients were included in this study, and the mortality rate was 22.7% in the original cohort, with 226 (1.9%) cases having missing data. Congestion levels varied by time and prefecture, ranging from 0 to over 1.5, indicating a strain beyond capacity. Median congestion level (interquartile range [IQR]) at admission was 0.3 (0.1, 0.7), and increased congestion level was statistically associated with increased mortality (odds ratio: 1.14; 95% confidential interval: 1.07–1.22). Sensitivity analysis showed consistent results, indicating the robustness of our findings.</p> Conclusions <p>Increased prefecture-level ICU congestion may be associated with increased COVID-19 mortality, warranting further investigation.</p>

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Impact of prefecture-level intensive care unit congestion on mortality in severe COVID-19 patients: a retrospective observational study in Japan

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月28日

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  • Yudai Iwasaki,
  • Takayuki Ogura,
  • Hiroyuki Ohbe,
  • Satoru Hashimoto,
  • Shigeki Kushimoto,
  • Shinichiro Ohshimo,
  • Nobuaki Shime,
  • Shinhiro Takeda

摘要

Background

The COVID-19 pandemic has placed unprecedented pressure on global healthcare systems, severely affecting the intensive care unit (ICU) capacity. Therefore, this study explored the association between prefecture-level ICU congestion and COVID-19 mortality in each prefecture of Japan.

Methods

This retrospective study analyzed data from the CRoss Icu Searchable Information System, covering all patients with COVID-19 who underwent mechanical ventilation with clearly documented initiation and cessation dates between January 1, 2020, and March 31, 2023. Prefecture-level ICU congestion was calculated as the total ventilator days over 2 weeks for severely ill patients with COVID-19, divided by the maximum potential ventilator days in the prefecture. Prefecture-level ICU congestion in each region was visualized by plotting time-series graphs capturing the temporal progression of congestion levels. Continuous variables were standardized, and missing data were imputed into 20 datasets by chained equations, assuming data missing at random. A mixed-effects logistic regression model was separately applied to each of the 20 multiply-imputed datasets generated during the imputation procedure to evaluate the association between prefecture-level ICU congestion and mortality. Estimates and standard errors from each model were pooled using Rubin’s rules to obtain final combined results. A sensitivity analysis was performed using the same mixed-effects model, replacing the continuous congestion level with a categorical variable.

Results

A total number of 10,427 patients were included in this study, and the mortality rate was 22.7% in the original cohort, with 226 (1.9%) cases having missing data. Congestion levels varied by time and prefecture, ranging from 0 to over 1.5, indicating a strain beyond capacity. Median congestion level (interquartile range [IQR]) at admission was 0.3 (0.1, 0.7), and increased congestion level was statistically associated with increased mortality (odds ratio: 1.14; 95% confidential interval: 1.07–1.22). Sensitivity analysis showed consistent results, indicating the robustness of our findings.

Conclusions

Increased prefecture-level ICU congestion may be associated with increased COVID-19 mortality, warranting further investigation.