Acute Crit Care.  2018 Nov;33(4):216-221. 10.4266/acc.2018.00178.

Performance of APACHE IV in Medical Intensive Care Unit Patients: Comparisons with APACHE II, SAPS 3, and MPMâ‚€ III

• Ko M
• Shim M
• Lee SM
• Kim Y
• Yoon S

• KMID: 2441238
• DOI: http://doi.org/10.4266/acc.2018.00178

Abstract

BACKGROUND
In this study, we analyze the performance of the Acute Physiology and Chronic Health Evaluation (APACHE) II, APACHE IV, Simplified Acute Physiology Score (SAPS) 3, and Mortality Probability Model (MPM)â‚€ III in order to determine which system best implements data related to the severity of medical intensive care unit (ICU) patients.
METHODS
The present study was a retrospective investigation analyzing the discrimination and calibration of APACHE II, APACHE IV, SAPS 3, and MPMâ‚€ III when used to evaluate medical ICU patients. Data were collected for 788 patients admitted to the ICU from January 1, 2015 to December 31, 2015. All patients were aged 18 years or older with ICU stays of at least 24 hours. The discrimination abilities of the three systems were evaluated using c-statistics, while calibration was evaluated by the Hosmer-Lemeshow test. A severity correction model was created using logistics regression analysis.
RESULTS
For the APACHE IV, SAPS 3, MPMâ‚€ III, and APACHE II systems, the area under the receiver operating characteristic curves was 0.745 for APACHE IV, resulting in the highest discrimination among all four scoring systems. The value was 0.729 for APACHE II, 0.700 for SAP 3, and 0.670 for MPMâ‚€ III. All severity scoring systems showed good calibrations: APACHE II (chi-square, 12.540; P=0.129), APACHE IV (chi-square, 6.959; P=0.541), SAPS 3 (chi-square, 9.290; P=0.318), and MPMâ‚€ III (chi-square, 11.128; P=0.133).
CONCLUSIONS
APACHE IV provided the best discrimination and calibration abilities and was useful for quality assessment and predicting mortality in medical ICU patients.

Keyword

APACHE; intensive care unit; Mortality Probability Model; severity of illness index; Simplified Acute Physiology Score

MeSH Terms

APACHE*
Calibration
Critical Care*
Discrimination (Psychology)
Humans
Intensive Care Units*
Mortality
Organization and Administration
Physiology
Retrospective Studies
ROC Curve
Severity of Illness Index

Figure

• 

  Figure 1. Comparison of the receiver operating characteristic curves for prediction of hospital death by APACHE II, APACHE IV, SAPS 3, and MPM0 III. APACHE: Acute Physiology and Chronic Health Evaluation; SAPS: Simplified Acute Physiology Score; MPM: Mortality Probability Model.

Reference

1. Kwon Y. Health care outcome measurement and risk adjustment. J Korean Soc Qual Assur Health Care. 2007; 13:59–67.

2. Keegan MT, Gajic O, Afessa B. Comparison of APACHE III, APACHE IV, SAPS 3, and MPM0III and influence of resuscitation status on model performance. Chest. 2012; 142:851–8.

3. Knaus WA, Wagner DP, Draper EA, Zimmerman JE, Bergner M, Bastos PG, et al. The APACHE III prognostic system: risk prediction of hospital mortality for critically ill hospitalized adults. Chest. 1991; 100:1619–36.

4. Lee H, Shon YJ, Kim H, Paik H, Park HP. Validation of the APACHE IV model and its comparison with the APACHE II, SAPS 3, and Korean SAPS 3 models for the prediction of hospital mortality in a Korean surgical intensive care unit. Korean J Anesthesiol. 2014; 67:115–22.

5. Pappachan JV, Millar B, Bennett ED, Smith GB. Comparison of outcome from intensive care admission after adjustment for case mix by the APACHE III prognostic system. Chest. 1999; 115:802–10.

6. Kim EK, Kwon YD, Hwang JH. Comparing the performance of three severity scoring systems for ICU patients: APACHE III, SAPS II, MPM II. J Prev Med Public Health. 2005; 38:276–82.

7. Lee JH, Baek KJ, Han SB, Ahn ST, Shin DW, Kim AJ, et al. Mortality analysis of intensive care units patients using Mortality Probability Models (MPM II). J Korean Soc Traumatol. 2001; 14:101–7.

8. Carson SS, Bach PB. Predicting mortality in patients suffering from prolonged critical illness: an assessment of four severity-of-illness measures. Chest. 2001; 120:928–33.

9. Schellongowski P, Benesch M, Lang T, Traunmüller F, Zauner C, Laczika K, et al. Comparison of three severity scores for critically ill cancer patients. Intensive Care Med. 2004; 30:430–6.

10. Kang CH, Kim YI, Lee EJ, Park K, Lee JS, Kim Y. The variation in risk adjusted mortality of intensive care units. Korean J Anesthesiol. 2009; 57:698–703.

11. Groeger JS, Lemeshow S, Price K, Nierman DM, White P Jr, Klar J, et al. Multicenter outcome study of cancer patients admitted to the intensive care unit: a probability of mortality model. J Clin Oncol. 1998; 16:761–70.

12. Zimmerman JE, Kramer AA, McNair DS, Malila FM. Acute Physiology and Chronic Health Evaluation (APACHE) IV: hospital mortality assessment for today’s critically ill patients. Crit Care Med. 2006; 34:1297–310.

13. Metnitz PG, Moreno RP, Almeida E, Jordan B, Bauer P, Campos RA, et al. SAPS 3: from evaluation of the patient to evaluation of the intensive care unit. Part 1: objectives, methods and cohort description. Intensive Care Med. 2005; 31:1336–44.

14. 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.

15. Carmel S, Rowan K. Variation in intensive care unit outcomes: a search for the evidence on organizational factors. Curr Opin Crit Care. 2001; 7:284–96.

16. Peelen L, de Keizer NF, Peek N, Scheffer GJ, van der Voort PH, de Jonge E. The influence of volume and intensive care unit organization on hospital mortality in patients admitted with severe sepsis: a retrospective multicentre cohort study. Crit Care. 2007; 11:R40.

17. Frick S, Uehlinger DE, Zuercher Zenklusen RM. Medical futility: predicting outcome of intensive care unit patients by nurses and doctors: a prospective comparative study. Crit Care Med. 2003; 31:456–61.