Literature DB >> 10667495

Comparison of acute physiology and chronic health evaluations II and III and simplified acute physiology score II: a prospective cohort study evaluating these methods to predict outcome in a German interdisciplinary intensive care unit.

R Markgraf1, G Deutschinoff, L Pientka, T Scholten.   

Abstract

OBJECTIVE: To evaluate the ability of three scoring systems to predict hospital mortality in adult patients of an interdisciplinary intensive care unit in Germany.
DESIGN: A prospective cohort study.
SETTING: A mixed medical and surgical intensive care unit at a teaching hospital in Germany. PATIENTS: From a total of 3,108 patients, 2,795 patients (89.9%) for Acute Physiology and Chronic Health Evaluation (APACHE) II and 2,661 patients (85.6%) for APACHE III and Simplified Acute Physiology Score (SAPS) II could be enrolled to the study because of defined exclusion criteria.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: Probabilities of hospital death for patients were estimated by applying APACHE II and III and SAPS II and compared with observed outcomes. The overall goodness-of-fit of the three models was assessed. Hospital death rates were equivalent to those predicted by APACHE II but higher than those predicted by APACHE III and SAPS II. Calibration was good for APACHE II. For the other systems, it was insufficient, but better for SAPS II than for APACHE III. The overall correct classification rate, applying a decision criterion of 50%, was 84% for APACHE II and 85% for APACHE III and SAPS II. The areas under the receiver operating characteristic curve were 0.832 for APACHE II and 0.846 for APACHE III and SAPS II. Risk estimates for surgical and medical admissions differed between the three systems. For all systems, risk predictions for diagnostic categories did not fit uniformly across the spectrum of disease categories.
CONCLUSIONS: Our data more closely resemble those of the APACHE II database, demonstrating a higher degree of overall goodness-of-fit of APACHE II than APACHE III and SAPS II. Although discrimination was slightly better for the two new systems, calibration was good with a close fit for APACHE II only. Hospital mortality was higher than predicted for both new models but was underestimated to a greater degree by APACHE III. Both score systems demonstrated a considerable variation across the spectrum of diagnostic categories, which also differed between the two models.

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Year:  2000        PMID: 10667495     DOI: 10.1097/00003246-200001000-00005

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


  21 in total

1.  [Chronic critical disease--what does the long-term patient imply for intensive medicine].

Authors:  Jürgen Graf; Uwe Janssens
Journal:  Wien Klin Wochenschr       Date:  2006-07       Impact factor: 1.704

2.  External validation of the SAPS II, APACHE II and APACHE III prognostic models in South England: a multicentre study.

Authors:  Dieter H Beck; Gary B Smith; John V Pappachan; Brian Millar
Journal:  Intensive Care Med       Date:  2003-01-18       Impact factor: 17.440

3.  Prediction of mortality in an Indian intensive care unit. Comparison between APACHE II and artificial neural networks.

Authors:  Ashish Nimgaonkar; Dilip R Karnad; S Sudarshan; Lucila Ohno-Machado; Isaac Kohane
Journal:  Intensive Care Med       Date:  2004-01-15       Impact factor: 17.440

4.  Assessment of performance of four mortality prediction systems in a Saudi Arabian intensive care unit.

Authors:  Yaseen Arabi; Samir Haddad; Radoslaw Goraj; Abdullah Al-Shimemeri; Salim Al-Malik
Journal:  Crit Care       Date:  2002-03-13       Impact factor: 9.097

5.  Performance of the score systems Acute Physiology and Chronic Health Evaluation II and III at an interdisciplinary intensive care unit, after customization.

Authors:  R Markgraf; G Deutschinoff; L Pientka; T Scholten; C Lorenz
Journal:  Crit Care       Date:  2001-01-05       Impact factor: 9.097

6.  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

7.  Outcome after hepatectomy-delirium as an independent predictor for mortality.

Authors:  Dalila Veiga; Clara Luís; Daniela Parente; Fernando Abelha
Journal:  BMC Anesthesiol       Date:  2013-02-02       Impact factor: 2.217

8.  Modification of Acute Physiology and Chronic Health Evaluation II score through recalibration of risk prediction model in critical care patients of a respiratory disease referral center.

Authors:  Ali A Velayati; Yadollah Mehrabi; Golnar Radmand; Ali A Khadem Maboudi; Hamid R Jamaati; A Shahbazi; Seyed A Mohajerani; Seyed M R Hashemian
Journal:  Int J Crit Illn Inj Sci       Date:  2013-01

9.  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

Review 10.  Clinical review: mass casualty triage--pandemic influenza and critical care.

Authors:  Kirsty Challen; Andrew Bentley; John Bright; Darren Walter
Journal:  Crit Care       Date:  2007       Impact factor: 9.097

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