Literature DB >> 9590314

Predictive value of severity scoring systems: comparison of four models in Tunisian adult intensive care units.

S Nouira1, M Belghith, S Elatrous, M Jaafoura, M Ellouzi, R Boujdaria, M Gahbiche, S Bouchoucha, F Abroug.   

Abstract

OBJECTIVES: To compare the performance of four severity scoring systems: the Acute Physiology and Chronic Health Evaluation (APACHE) II, the new versions of the Mortality Prediction Model (MPM0 and MPM24), and the Simplified Acute Physiology Score (SAPS) II.
DESIGN: A prospective cohort study.
SETTING: Three Tunisian intensive care units (ICUs). PATIENTS: Consecutive, unselected adult patients (n = 1325).
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: Overall, observed death rates were higher than predicted by all models except MPM0. All the evaluated scoring systems had good discrimination power as expressed by area under the receiver operating characteristics curve, but their calibration was less perfect when compared with original validation reports. There were no major differences between the models with regard either to discrimination or calibration performance.
CONCLUSION: Despite an overall good discrimination, APACHE II, MPM0, MPM24, and SAPS II showed a less satisfactory calibration in our Tunisian sample of ICU patients. Part of the models inaccuracy could be related to quality of care problems in our ICUs, but this issue needs further analysis.

Entities:  

Mesh:

Year:  1998        PMID: 9590314     DOI: 10.1097/00003246-199805000-00016

Source DB:  PubMed          Journal:  Crit Care Med        ISSN: 0090-3493            Impact factor:   7.598


  10 in total

Review 1.  The state of research on multipurpose severity of illness scoring systems: are we on target?

Authors:  G Apolone
Journal:  Intensive Care Med       Date:  2000-12       Impact factor: 17.440

2.  Predicting mortality in patients with systemic inflammatory response syndrome: an evaluation of two prognostic models, two soluble receptors, and a macrophage migration inhibitory factor.

Authors:  K Kofoed; J Eugen-Olsen; J Petersen; K Larsen; O Andersen
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2008-01-16       Impact factor: 3.267

3.  Determinants and outcomes associated with decisions to deny or to delay intensive care unit admission in Morocco.

Authors:  Maha Louriz; Khalid Abidi; Mostafa Akkaoui; Naoufel Madani; Kamal Chater; Jihane Belayachi; Tarek Dendane; Amine Ali Zeggwagh; Redouane Abouqal
Journal:  Intensive Care Med       Date:  2012-03-08       Impact factor: 17.440

4.  Associations with Perioperative Mortality Rate at a Major Referral Hospital in Rwanda.

Authors:  Jennifer L Rickard; Georges Ntakiyiruta; Kathryn M Chu
Journal:  World J Surg       Date:  2016-04       Impact factor: 3.352

5.  Probability of mortality of critically ill cancer patients at 72 h of intensive care unit (ICU) management.

Authors:  Jeffrey S Groeger; Jill Glassman; David M Nierman; Susannah Kish Wallace; Kristen Price; David Horak; David Landsberg
Journal:  Support Care Cancer       Date:  2003-08-05       Impact factor: 3.603

6.  External validation of the sepsis severity score.

Authors:  Marek Wełna; Barbara Adamik; Waldemar Goździk; Andrzej Kübler
Journal:  Int J Immunopathol Pharmacol       Date:  2020 Jan-Dec       Impact factor: 3.219

7.  Prognostic performance of the Simplified Acute Physiology Score II in major Croatian hospitals: a prospective multicenter study.

Authors:  Kristian Desa; Mladen Peric; Ino Husedzinovic; Alan Sustic; Andelko Korusic; Vjekoslav Karadza; Drazen Matlekovic; Branka Prstec-Veronek; Marta Zuvic-Butorac; Jadranko Sokolic; Mladen Siranovic; Danica Bosnjak; Jasna Spicek-Macan; Denis Gustin; Drazenka Ozeg-Jakopovic
Journal:  Croat Med J       Date:  2012-10       Impact factor: 1.351

8.  Can generic paediatric mortality scores calculated 4 hours after admission be used as inclusion criteria for clinical trials?

Authors:  Stéphane Leteurtre; Francis Leclerc; Jessica Wirth; Odile Noizet; Eric Magnenant; Ahmed Sadik; Catherine Fourier; Robin Cremer
Journal:  Crit Care       Date:  2004-05-21       Impact factor: 9.097

9.  Comparison of risk prediction scoring systems for ward patients: a retrospective nested case-control study.

Authors:  Shun Yu; Sharon Leung; Moonseong Heo; Graciela J Soto; Ronak T Shah; Sampath Gunda; Michelle Ng Gong
Journal:  Crit Care       Date:  2014-06-26       Impact factor: 9.097

Review 10.  Performance of critical care prognostic scoring systems in low and middle-income countries: a systematic review.

Authors:  Rashan Haniffa; Ilhaam Isaam; A Pubudu De Silva; Arjen M Dondorp; Nicolette F De Keizer
Journal:  Crit Care       Date:  2018-01-26       Impact factor: 9.097

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.