Long-term mortality of patients discharged from the hospital after successful critical care in the ICU in Korea: a retrospective observational study in a single tertiary care teaching hospital

Three-year mortality, readmission, and medical expenses in critical care survivors: A population-based cohort study

BACKGROUND

Due to the increasing number of critical care survivors, population-based studies on the long-term outcomes after discharge are necessary to inform local decision-making.

OBJECTIVES

This study aimed to investigate mortality and its risk factors, readmissions, and medical expenses of intensive care unit survivors for 3 years after hospital discharge.

METHODS

This retrospective study analysed data from the National Health Insurance Service-National Sample Cohort in Korea. Of the 195,702 patients who survived and were discharged from hospital in 2012, 2693 intensive care unit patients were assigned to the case group for the study, and the remaining 193,009 were assigned to the comparison group. The primary outcome was all-cause mortality for 3 years after discharge. Secondary outcomes were all-cause hospital readmission and medical expenses in 3 years. We analysed risk factors for mortality using the Cox proportional hazard regression. The differences in hospital readmission and medical expenses between the case and comparison groups were analysed by multivariate logistic regression and independent t-tests.

RESULTS

The 1-year, 2-year, and 3-year cumulative mortality rates in the case group were 15.9%, 20.5%, and 24.4%, respectively, and older age, disability, medical admission, and longer hospital stay increased mortality. Almost 40% of intensive care unit survivors were readmitted to hospital within 6 months of discharge, and their odds of being readmitted were significantly higher than those of the comparison group. Medical expenses were also significantly higher in the case group, with the highest paid within 6 months.

CONCLUSIONS

Mortality, hospital readmission, and medical expenses for intensive care unit survivors were the worst within 6 months of discharge. In light of the long-term recovery trajectory of critical illness, it is necessary to investigate what factors may have contributed to the negative outcome during this period. Further research is needed to determine which services primarily contributed to the increase in medical expenses.

Transparency considerations for describing statistical analyses in research

Researchers who use the results of statistical analyses to draw conclusions about collected data must write a statistical analysis section in their manuscript. Describing statistical analyses in precise detail is as important as presenting the dosages of drugs and methodology of interventions. It is also essential for scientific accuracy and transparency in scientific research. We evaluated the quality of the statistical analysis sections of clinical research articles published in the Korean Journal of Anesthesiology between February 2020 and February 2021. Using a Likert scale where 1, 2, and 3 represented “not described at all,” “partially described,” and “fully described,” respectively, the following 6 items were assessed: 1) stating of the statistical analysis methods used, 2) rationale for and detailed description of the statistical analysis methods used, 3) parameters derived from the statistical analyses, 4) type and version of the statistical software package used, 5) significance level, and 6) sidedness of the test (one-sided vs. two-sided). The first 3 items evaluate issues directly related to the statistical analysis methods used and last 3 are indirectly related items. In all the included articles, the statistical analysis methods used were stated (score of 3). However, only 4 articles (12.9%) fully described the sidedness of the test (score of 3). Authors tend not to describe the sidedness of statistical analysis tests in the methodology section of clinical research articles. It is essential that the sidedness be described in research studies.