Scoring Systems in Assessing Survival of Critically Ill ICU Patients

Overview

Journal Med Sci Monit

Specialties General Medicine
Pathology

Date 2015 Sep 5

PMID 26336861

Citations 27

Authors

Ana D Sekulic

Sladjana V Trpkovic

Aleksandar P Pavlovic

Olivera M Marinkovic

Aleksandra N Ilic

Affiliations

Soon will be listed here.

Abstract

Background: The aim of this study was to determine which of the most commonly used scoring systems for evaluation of critically ill patients in the ICU is the best and simplest to use in our hospital.

Material And Methods: This prospective study included 60 critically ill patients. After admittance to the ICU, APACHE II, SAPS II, and MPM II0 were calculated. During further treatment in the ICU, SOFA and MPM II were calculated at 24 h, 48 h, and 72 h and 7 days after admittance using laboratory and radiological measures.

Results: In comparison with survivors, non-survivors were older (p<0.01) and spent significantly more days on mechanical ventilation (p<0.01). ARDS was significantly more common in patients who survived compared to those who did not (chi-square=7.02, p<0.01), which is not the case with sepsis (chi-square=0.388, p=0.53). AUROC SAPS II was 0.690, and is only slightly higher than the other 2 AUROC incipient scoring systems, MPM II and APACHE II (0.654 and 0.623). The APACHE II has the highest specificity (81.8%) and MPM II the highest sensitivity (85.2%). MPM II(7day) AUROC (1.0) shows the best discrimination between patients who survived and those who did not. MPM II(48) (0.836), SOFA(72) (0.821) and MPM II(72) (0.817) also had good discrimination scores.

Conclusions: APACHE II and SAPS II measured on admission to the ICU were significant predictors of complications. MPM II(7day) has the best discriminatory power, followed by SOFA(7day) and MPM II(48). MPM II(7day) has the best calibration followed by SOFA(7day) and APACHE II.

Citing Articles

The Influence of Prone Positioning on Energy and Protein Delivery in COVID-19 Patients Requiring ECMO Support.

Hintersteininger M, Haselwanter P, Maleczek M, Laxar D, Hermann M, Hermann A Nutrients. 2024; 16(20).

PMID: 39458527 PMC: 11510455. DOI: 10.3390/nu16203534.

Development and validation of novel interpretable survival prediction models based on drug exposures for severe heart failure during vulnerable period.

Guo Y, Yu F, Jiang F, Yin S, Jiang M, Li Y J Transl Med. 2024; 22(1):743.

PMID: 39107765 PMC: 11302109. DOI: 10.1186/s12967-024-05544-6.

A hybrid modeling framework for generalizable and interpretable predictions of ICU mortality across multiple hospitals.

E Samadi M, Guzman-Maldonado J, Nikulina K, Mirzaieazar H, Sharafutdinov K, Fritsch S Sci Rep. 2024; 14(1):5725.

PMID: 38459085 PMC: 10923850. DOI: 10.1038/s41598-024-55577-6.

Prognostic Performance of Sequential Organ Failure Assessment, Acute Physiology and Chronic Health Evaluation III, and Simplified Acute Physiology Score II Scores in Patients with Suspected Infection According to Intensive Care Unit Type.

Hwang S, Kim I, Jeong D, Park J, Lee G, Yoo J J Clin Med. 2023; 12(19).

PMID: 37835046 PMC: 10573563. DOI: 10.3390/jcm12196402.

Inadequate Energy Delivery Is Frequent among COVID-19 Patients Requiring ECMO Support and Associated with Increased ICU Mortality.

Schneeweiss-Gleixner M, Scheiner B, Semmler G, Maleczek M, Laxar D, Hintersteininger M Nutrients. 2023; 15(9).

PMID: 37432241 PMC: 10181417. DOI: 10.3390/nu15092098.

References

Rapsang A, Shyam D . Scoring systems in the intensive care unit: A compendium. Indian J Crit Care Med. 2014; 18(4):220-8. PMC: 4033855. DOI: 10.4103/0972-5229.130573. View

Breslow M, Badawi O . Severity scoring in the critically ill: part 1--interpretation and accuracy of outcome prediction scoring systems. Chest. 2012; 141(1):245-252. DOI: 10.1378/chest.11-0330. View

Vasilevskis E, Kuzniewicz M, Cason B, Lane R, Dean M, Clay T . Mortality probability model III and simplified acute physiology score II: assessing their value in predicting length of stay and comparison to APACHE IV. Chest. 2009; 136(1):89-101. PMC: 3198495. DOI: 10.1378/chest.08-2591. View

Bota D, Melot C, Ferreira F, Nguyen Ba V, Vincent J . The Multiple Organ Dysfunction Score (MODS) versus the Sequential Organ Failure Assessment (SOFA) score in outcome prediction. Intensive Care Med. 2002; 28(11):1619-24. DOI: 10.1007/s00134-002-1491-3. View

Boniatti M, Friedman G, Castilho R, Vieira S, Fialkow L . Characteristics of chronically critically ill patients: comparing two definitions. Clinics (Sao Paulo). 2011; 66(4):701-4. PMC: 3093802. DOI: 10.1590/s1807-59322011000400027. View

Minne L, Abu-Hanna A, de Jonge E . Evaluation of SOFA-based models for predicting mortality in the ICU: A systematic review. Crit Care. 2008; 12(6):R161. PMC: 2646326. DOI: 10.1186/cc7160. View

Park S, Chun H, Kim D, Im T, Hong H, Yi H . Acute Physiology and Chronic Health Evaluation II and Simplified Acute Physiology Score II in predicting hospital mortality of neurosurgical intensive care unit patients. J Korean Med Sci. 2009; 24(3):420-6. PMC: 2698186. DOI: 10.3346/jkms.2009.24.3.420. View

Bosscha K, Reijnders K, Hulstaert P, Algra A, van der Werken C . Prognostic scoring systems to predict outcome in peritonitis and intra-abdominal sepsis. Br J Surg. 1997; 84(11):1532-4. View

Zimmerman J, Kramer A, McNair D, Malila F . Acute Physiology and Chronic Health Evaluation (APACHE) IV: hospital mortality assessment for today's critically ill patients. Crit Care Med. 2006; 34(5):1297-310. DOI: 10.1097/01.CCM.0000215112.84523.F0. View

10.

Sawicka W, Owczuk R, Wujtewicz M, Wujtewicz M . The effectiveness of the APACHE II, SAPS II and SOFA prognostic scoring systems in patients with haematological malignancies in the intensive care unit. Anaesthesiol Intensive Ther. 2014; 46(3):166-70. DOI: 10.5603/AIT.2014.0030. View

11.

Salluh J, Soares M . ICU severity of illness scores: APACHE, SAPS and MPM. Curr Opin Crit Care. 2014; 20(5):557-65. DOI: 10.1097/MCC.0000000000000135. View

12.

Khwannimit B, Geater A . A comparison of APACHE II and SAPS II scoring systems in predicting hospital mortality in Thai adult intensive care units. J Med Assoc Thai. 2007; 90(4):643-52. View

13.

Arabi Y, Al Shirawi N, Memish Z, Venkatesh S, Al-Shimemeri A . Assessment of six mortality prediction models in patients admitted with severe sepsis and septic shock to the intensive care unit: a prospective cohort study. Crit Care. 2003; 7(5):R116-22. PMC: 270727. DOI: 10.1186/cc2373. View

14.

Hutchins R, Gunning M, Lucas D, Allen-Mersh T, Soni N . Relaparotomy for suspected intraperitoneal sepsis after abdominal surgery. World J Surg. 2004; 28(2):137-41. DOI: 10.1007/s00268-003-7067-8. View

15.

Janssens U, Graf C, Graf J, Radke P, Konigs B, Koch K . Evaluation of the SOFA score: a single-center experience of a medical intensive care unit in 303 consecutive patients with predominantly cardiovascular disorders. Sequential Organ Failure Assessment. Intensive Care Med. 2000; 26(8):1037-45. DOI: 10.1007/s001340051316. View

16.

Vincent J, Moreno R . Clinical review: scoring systems in the critically ill. Crit Care. 2010; 14(2):207. PMC: 2887099. DOI: 10.1186/cc8204. View

17.

Moseson E, Zhuo H, Chu J, Stein J, Matthay M, Kangelaris K . Intensive care unit scoring systems outperform emergency department scoring systems for mortality prediction in critically ill patients: a prospective cohort study. J Intensive Care. 2015; 2:40. PMC: 4424730. DOI: 10.1186/2052-0492-2-40. View

18.

Torer N, Yorganci K, Elker D, Sayek I . Prognostic factors of the mortality of postoperative intraabdominal infections. Infection. 2010; 38(4):255-60. DOI: 10.1007/s15010-010-0021-4. View

19.

Metnitz P, Moreno R, Almeida E, Jordan B, Bauer P, Abizanda Campos R . 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(10):1336-44. PMC: 1315314. DOI: 10.1007/s00134-005-2762-6. View

20.

Higgins T, Teres D, Copes W, Nathanson B, Stark M, Kramer A . Assessing contemporary intensive care unit outcome: an updated Mortality Probability Admission Model (MPM0-III). Crit Care Med. 2007; 35(3):827-35. DOI: 10.1097/01.CCM.0000257337.63529.9F. View