Acute Crit Care.  2018 Aug;33(3):135-145. 10.4266/acc.2018.00164.

Changes in the Characteristics and Long-term Mortality Rates of Intensive Care Unit Patients from 2003 to 2010: A Nationwide Population-Based Cohort Study Performed in the Republic of Korea

• Heo J
• Hong Y
• Han SS
• Kim WJ
• Kwon JW
• Moon KW
• Jeong JH
• Kim YJ
• Lee SH
• Lee SJ

• KMID: 2436325
• DOI: http://doi.org/10.4266/acc.2018.00164

Abstract

BACKGROUND
There are few studies on intensive care unit (ICU) patients in the Republic of Korea. We analyzed the characteristics and mortality changes of all ICU patients over the last 8 years.
METHODS
This study used the cohort of the National Health Insurance Corporation, which provides medical care to all residents of the Republic of Korea. The cohort consists of patients aged 20 years or older between 2003 and 2010 with a history of ICU admission. We analyzed changes in sex, age, household income, number of hospital beds, emergency admissions, and reasons for admission using the Cochran-Armitage trend test. The adjusted hazard ratios (HRs) of mortality according to these variables and year of admission were calculated by Cox proportional hazards regression.
RESULTS
The proportion of patients aged ≥70 years increased over that period, as did their average age (by 3.6 years). During the 8-year study period, the 3-year mortality rate was 32.91%-35.83%. The overall mortality was higher in males and older patients, in those with a lower household income and higher Charlson Comorbidity Index (CCI) score, those admitted to a hospital with a smaller number of beds, and those admitted via the emergency room. There was no significant change in crude mortality rate over the 8-year study period; however, the adjusted HR showed a decreasing trend.
CONCLUSIONS
Patients admitted to the ICU were older and had higher CCI score. Nevertheless, there was a temporal trend toward a decrease in the HR of long-term mortality.

Keyword

cohort studies; intensive care unit; mortality

MeSH Terms

Cohort Studies*
Comorbidity
Critical Care*
Emergencies
Emergency Service, Hospital
Family Characteristics
Humans
Intensive Care Units*
Male
Mortality*
National Health Programs
Republic of Korea*

Figure

• 

  Figure 1. Flow chart of the study selection process. NHIS-NSC: National Health Insurance Service-National Sample Cohort; ICU: intensive care unit.

• 

  Figure 2. Forest plot of adjusted hazard ratio and 95% confidence interval in Cox models adjusted for sex, age, household income, Charlson Comorbidity Index, number of hospital beds, admission via the emergency room, and admission reason.

• 

  Figure 3. The adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of mortality and forest plots of HRs adjusted for sex, age, household income, Charlson comorbidity index, number of hospital beds, and admission via the emergency room in stratified Cox models by admission reason.

Reference

1. Bagshaw SM, Webb SA, Delaney A, George C, Pilcher D, Hart GK, et al. Very old patients admitted to intensive care in Australia and New Zealand: a multi-centre cohort analysis. Crit Care. 2009; 13:R45.

2. Kontis V, Bennett JE, Mathers CD, Li G, Foreman K, Ezzati M. Future life expectancy in 35 industrialised countries: projections with a Bayesian model ensemble. Lancet. 2017; 389:1323–35.

3. Milbrandt EB, Kersten A, Rahim MT, Dremsizov TT, Clermont G, Cooper LM, et al. Growth of intensive care unit resource use and its estimated cost in Medicare. Crit Care Med. 2008; 36:2504–10.

4. Molina JA, Seow E, Heng BH, Chong WF, Ho B. Outcomes of direct and indirect medical intensive care unit admissions from the emergency department of an acute care hospital: a retrospective cohort study. BMJ Open. 2014; 4:e005553.

5. Halpern NA, Pastores SM. Critical care medicine in the United States 2000-2005: an analysis of bed numbers, occupancy rates, payer mix, and costs. Crit Care Med. 2010; 38:65–71.

6. Halpern NA, Pastores SM, Greenstein RJ. Critical care medicine in the United States 1985-2000: an analysis of bed numbers, use, and costs. Crit Care Med. 2004; 32:1254–9.

7. Wallace DJ, Angus DC, Seymour CW, Barnato AE, Kahn JM. Critical care bed growth in the United States: a comparison of regional and national trends. Am J Respir Crit Care Med. 2015; 191:410–6.

8. Lee J, Lee JS, Park SH, Shin SA, Kim K. Cohort profile: The National Health Insurance Service-National Sample Cohort (NHISNSC), South Korea. Int J Epidemiol. 2017; 46:e15.

9. Kaukonen KM, Bailey M, Suzuki S, Pilcher D, Bellomo R. Mortality related to severe sepsis and septic shock among critically ill patients in Australia and New Zealand, 2000-2012. JAMA. 2014; 311:1308–16.

10. Zimmerman JE, Kramer AA, Knaus WA. Changes in hospital mortality for United States intensive care unit admissions from 1988 to 2012. Crit Care. 2013; 17:R81.

11. Mahmood K, Eldeirawi K, Wahidi MM. Association of gender with outcomes in critically ill patients. Crit Care. 2012; 16:R92.

12. Fuchs L, Chronaki CE, Park S, Novack V, Baumfeld Y, Scott D, et al. ICU admission characteristics and mortality rates among elderly and very elderly patients. Intensive Care Med. 2012; 38:1654–61.

13. Schnegelsberg A, Mackenhauer J, Nibro HL, Dreyer P, Koch K, Kirkegaard H. Impact of socioeconomic status on mortality and unplanned readmission in septic intensive care unit patients. Acta Anaesthesiol Scand. 2016; 60:465–75.

14. Christensen S, Johansen MB, Christiansen CF, Jensen R, Lemeshow S. Comparison of Charlson comorbidity index with SAPS and APACHE scores for prediction of mortality following intensive care. Clin Epidemiol. 2011; 3:203–11.

15. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987; 40:373–83.

16. Sjoding MW, Prescott HC, Wunsch H, Iwashyna TJ, Cooke CR. Longitudinal changes in ICU admissions among elderly patients in the United States. Crit Care Med. 2016; 44:1353–60.

17. Koch K, Nørgaard M, Schønheyder HC, Thomsen RW, Søgaard M; Danish Collaborative Bacteremia Network. Effect of socioeconomic status on mortality after bacteremia in workingage patients: a Danish population-based cohort study. PLoS One. 2013; 8:e70082.

18. Hutchings A, Raine R, Brady A, Wildman M, Rowan K. Socioeconomic status and outcome from intensive care in England and Wales. Med Care. 2004; 42:943–51.

19. Le Gall JR, Lemeshow S, Saulnier F. A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study. JAMA. 1993; 270:2957–63.

20. Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med. 1985; 13:818–29.

21. Lemeshow S, Teres D, Klar J, Avrunin JS, Gehlbach SH, Rapoport J. Mortality Probability Models (MPM II) based on an international cohort of intensive care unit patients. JAMA. 1993; 270:2478–86.

22. Ho KM, Knuiman M, Finn J, Webb SA. Estimating long-term survival of critically ill patients: the PREDICT model. PLoS One. 2008; 3:e3226.

23. Johnston JA, Wagner DP, Timmons S, Welsh D, Tsevat J, Render ML. Impact of different measures of comorbid disease on predicted mortality of intensive care unit patients. Med Care. 2002; 40:929–40.

24. Jhun HJ, Kim H, Cho SI. Time trend and age-period-cohort effects on acute myocardial infarction mortality in Korean adults from 1988 to 2007. J Korean Med Sci. 2011; 26:637–41.