Anest. intenziv. Med. 2023;34(3):120-124 | DOI: 10.36290/aim.2023.043

Prognostic scores in the ICUReview Article

Harazim M.
Interní gastroenterologická klinika Fakultní nemocnice Brno
Lékařská fakulta Masarykovy univerzity, Brno

Prognostic scoring systems are employed in the intensive care unit to predict the outcome of our treatments, to characterize the severity of disease or organ dysfunction, or for comparisons in scientific research. This review article outlines the history and introduction of frequently utilized scoring systems in intensive care units. It aims to demonstrate performance and future directions, emphasizing the significance of prognostic models not only in publications but also for enhancing resource usage and improving the provided care.

Keywords: Intensive Care, APACHE, prognosis, SOFA, scoring systems.

Received: August 1, 2023; Revised: September 24, 2023; Accepted: October 2, 2023; Prepublished online: October 25, 2023; Published: October 31, 2023  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Harazim M. Prognostic scores in the ICU. Anest. intenziv. Med. 2023;34(3):120-124. doi: 10.36290/aim.2023.043.
Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. Falcão ALE, Barros AGA, Bezerra AAM, Ferreira NL, Logato CM, Silva FP, et al. The prognostic accuracy evaluation of SAPS 3, SOFA and APACHE II scores for mortality prediction in the surgical ICU: an external validation study and decision­‑making analysis. Ann Intensive Care. 2019 Jan 30;9(1):18. doi: 10.1186/s13613-019-0488-9. PMID: 30701392; PMCID: PMC6353976. Go to original source... Go to PubMed...
    2. Haniffa R, Isaam I, De Silva AP, Dondorp AM, De Keizer NF. Performance of critical care prognostic scoring systems in low and middle­‑income countries: a systematic review. Crit Care. 2018 Jan 26;22(1):18. doi: 10.1186/s13054-017-1930-8. PMID: 29373996; PMCID: PMC5787236. Go to original source... Go to PubMed...
    3. Ko RE, Cho J, Shin MK, Oh SW, Seong Y, Jeon J, et al. Machine Learning­‑Based Mortality Prediction Model for Critically Ill Cancer Patients Admitted to the Intensive Care Unit (CanICU). Cancers (Basel). 2023 Jan 17;15(3):569. doi: 10.3390/cancers15030569. PMID: 36765528; PMCID: PMC9913129. Go to original source... Go to PubMed...
    4. Choi MH, Kim D, Choi EJ, Jung YJ, Choi YJ, Cho JH, et al. Mortality prediction of patients in intensive care units using machine learning algorithms based on electronic health records. Sci Rep. 2022 May 3;12(1):7180. doi: 10.1038/s41598-022-11226-4. PMID: 35505048; PMCID: PMC9065110. Go to original source... Go to PubMed...
    5. Subudhi S, Verma A, Patel AB, Hardin CC, Khandekar MJ, Lee H, et al. Comparing machine learning algorithms for predicting ICU admission and mortality in COVID-19. NPJ Digit Med. 2021 May 21;4(1):87. doi: 10.1038/s41746-021-00456-x. PMID: 34021235; PMCID: PMC8140139. Go to original source... Go to PubMed...
    6. Yeh TS, Pollack MM, Holbrook PR, Fields AI, Ruttiman U. Assessment of pediatric intensive care--application of the Therapeutic Intervention Scoring System. Crit Care Med. 1982 Aug;10(8):497-500. doi: 10.1097/00003246-198208000-00002. PMID: 7094595. Go to original source... Go to PubMed...
    7. Keene AR, Cullen DJ. Therapeutic Intervention Scoring System: update 1983. Crit Care Med. 1983 Jan;11(1):1-3. doi: 10.1097/00003246-198301000-00001. PMID: 6848305. Go to original source... Go to PubMed...
    8. Knaus WA. APACHE 1978-2001: the development of a quality assurance system based on prognosis: milestones and personal reflections. Arch Surg. 2002 Jan;137(1):37-41. doi: 10.1001/archsurg.137. 1. 37. PMID: 11772212. Go to original source...
    9. 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 Nov 24;270(20):2478-86. PMID: 8230626. Go to original source...
    10. Le Gall JR, Loirat P, Alperovitch A, Glaser P, Granthil C, Mathieu D, et al. A simplified acute physiology score for ICU patients. Crit Care Med. 1984 Nov;12(11):975-7. doi: 10.1097/00003246-198411000-00012. PMID: 6499483. Go to original source... Go to PubMed...
    11. Vincent JL, Moreno R, Takala J, Willatts S, De Mendonça A, Bruining H, et al. The SOFA (Sepsis­‑related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis­‑Related Problems of the European Society of Intensive Care Medicine. Intensive Care Med. 1996 Jul;22(7):707-10. doi: 10.1007/BF01709751. PMID: 8844239. Go to original source... Go to PubMed...
    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 May;34(5):1297-310. doi: 10.1097/01.CCM.0000215112.84523.F0. PMID: 16540951. Go to original source... Go to PubMed...
    13. Harrison DA, Parry GJ, Carpenter JR, Short A, Rowan K. A new risk prediction model for critical care: the Intensive Care National Audit & Research Centre (ICNARC) model. Crit Care Med. 2007 Apr;35(4):1091-8. doi: 10.1097/01.CCM.0000259468.24532. 44. PMID: 17334248. Go to original source...
    14. Vincent JL, Moreno R. Clinical review: scoring systems in the critically ill. Crit Care. 2010;14(2):207. doi: 10.1186/cc8204. Epub 2010 Mar 26. PMID: 20392287; PMCID: PMC2887099. Go to original source... Go to PubMed...
    15. Moreno R, Rhodes A, Piquilloud L, Hernandez G, Takala J, Gershengorn HB, et al. The Sequential Organ Failure Assessment (SOFA) Score: has the time come for an update? Crit Care. 2023 Jan 13;27(1):15. doi: 10.1186/s13054-022-04290-9. PMID: 36639780; PMCID: PMC9837980. Go to original source... Go to PubMed...
    16. Bosman RJ, Oudemane van Straaten HM, Zandstra DF. The use of intensive care information systems alters outcome prediction. Intensive Care Med. 1998 Sep;24(9):953-8. doi: 10.1007/s001340050695. PMID: 9803332. Go to original source... Go to PubMed...
    17. Kuzniewicz MW, Vasilevskis EE, Lane R, Dean ML, Trivedi NG, Rennie DJ, et al. Variation in ICU risk­‑adjusted mortality: impact of methods of assessment and potential confounders. Chest. 2008 Jun;133(6):1319-1327. doi: 10.1378/chest.07-3061. Epub 2008 Apr 10. PMID: 18403657. Go to original source... Go to PubMed...
    18. Wu T, Wei Y, Wu J, Yi B, Li H. Logistic regression technique is comparable to complex machine learning algorithms in predicting cognitive impairment related to post intensive care syndrome. Sci Rep. 2023 Feb 11;13(1):2485. doi: 10.1038/s41598-023-28421-6. PMID: 36774378; PMCID: PMC9922285. Go to original source... Go to PubMed...
    19. Escher M, Ricou B, Nendaz M, Scherer F, Cullati S, Hudelson P, et al. ICU physicians' and internists' survival predictions for patients evaluated for admission to the intensive care unit. Ann Intensive Care. 2018 Nov 14;8(1):108. doi: 10.1186/s13613-018-0456-9. PMID: 30430269; PMCID: PMC6236006. Go to original source... Go to PubMed...
    20. Meyer A, Zverinski D, Pfahringer B, Kempfert J, Kuehne T, Sündermann SH, et al. Machine learning for real­‑time prediction of complications in critical care: a retrospective study. Lancet Respir Med. 2018 Dec;6(12):905-914. doi: 10.1016/S2213-2600(18)30300-X. Epub 2018 Sep 28. PMID: 30274956. Go to original source... Go to PubMed...
    21. NKÚ. Kontrolní závěr z kontrolní akce - Zdravotnické informační systémy ve správě organizačních složek resortu zdravotnictví. 2017.

    Return to the content


    Anesteziologie a intenzivní medicína

    Madam, Sir,
    please be aware that the website on which you intend to enter, not the general public because it contains technical information about medicines, including advertisements relating to medicinal products. This information and communication professionals are solely under §2 of the Act n.40/1995 Coll. Is active persons authorized to prescribe or supply (hereinafter expert).
    Take note that if you are not an expert, you run the risk of danger to their health or the health of other persons, if you the obtained information improperly understood or interpreted, and especially advertising which may be part of this site, or whether you used it for self-diagnosis or medical treatment, whether in relation to each other in person or in relation to others.

    I declare:

    1. that I have met the above instruction
    2. I'm an expert within the meaning of the Act n.40/1995 Coll. the regulation of advertising, as amended, and I am aware of the risks that would be a person other than the expert input to these sites exhibited

    No
    Yes

    If your statement is not true, please be aware
    that brings the risk of danger to their health or the health of others.