Literature DB >> 7650260

Evaluation of severity scoring systems in ICUs--translation, conversion and definition ambiguities as a source of inter-observer variability in Apache II, SAPS and OSF.

E Féry-Lemonnier1, P Landais, P Loirat, D Kleinknecht, F Brivet.   

Abstract

OBJECTIVE: To explore translation, conversion and definition ambiguities, when using severity scoring systems in patients admitted to intensive care units (ICUs).
DESIGN: A prospective study of the prognosis of acute renal failure in ICUs.
SETTING: The study was conducted in 20 French ICUs. PATIENTS: 360 patients presenting with severe acute renal failure were studied during their ICU stay. MEASUREMENTS AND
RESULTS: The inter-observer variability of Apache II (acute physiology and chronic health evaluation), SAPS (simplified acute physiology score), and OSF (organ-system failure) was considered. For Apache II, we explored the uncertainty of measurements arising from conversion into SI units, the rounding procedures used for the non-inclusive intervals defined for quantitative parameters such as age, mean arterial pressure (MAP) or serum creatinine, the absence of definition of acute renal failure (ARF) and its consequence on doubling serum creatinine values, and the absence of guidelines in the case of spontaneous ventilation when arterial blood gases (ABG) and forced inspiratory oxygen (FIO2) were not measured. The resulting variability was evaluated, calculating the lowest and the highest value of the scoring system for each patient. The mean difference by patient was greater than 1.5 (p < 0.0001). Other examples were presented and discussed for SAPS and OSF.
CONCLUSIONS: Translation, conversion and definition ambiguities are a source of inter-observer variability and increase the risk of classification and/or selection biases. This gives rise to particular concern in the design and analysis of multicenter trials of meta-analysis, and improvement of these scoring systems should be envisaged in the future.

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Year:  1995        PMID: 7650260     DOI: 10.1007/bf01705416

Source DB:  PubMed          Journal:  Intensive Care Med        ISSN: 0342-4642            Impact factor:   17.440


  10 in total

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2.  Individual outcome prediction models for intensive care units.

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Journal:  Lancet       Date:  1989-07-15       Impact factor: 79.321

3.  APACHE II: a severity of disease classification system.

Authors:  W A Knaus; E A Draper; D P Wagner; J E Zimmerman
Journal:  Crit Care Med       Date:  1985-10       Impact factor: 7.598

4.  A simplified acute physiology score for ICU patients.

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Journal:  Crit Care Med       Date:  1984-11       Impact factor: 7.598

5.  Influence of age, previous health status, and severity of acute illness on outcome from intensive care.

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Journal:  Crit Care Med       Date:  1982-09       Impact factor: 7.598

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Authors:  W A Knaus; E A Draper; D P Wagner; J E Zimmerman
Journal:  Ann Surg       Date:  1985-12       Impact factor: 12.969

7.  The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults.

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Journal:  Chest       Date:  1991-12       Impact factor: 9.410

8.  Identification of low-risk monitor patients within a medical-surgical intensive care unit.

Authors:  D P Wagner; W A Knaus; E A Draper; J E Zimmerman
Journal:  Med Care       Date:  1983-04       Impact factor: 2.983

9.  Factors related to outcome in intensive care: French multicenter study. The French Multicenter Group of ICU Research; The Inserm Unit 169 of Statistical and Epidemiological Studies.

Authors: 
Journal:  Crit Care Med       Date:  1989-04       Impact factor: 7.598

10.  Use of APACHE II severity of disease classification to identify intensive-care-unit patients who would not benefit from total parenteral nutrition.

Authors:  R W Chang; S Jacobs; B Lee
Journal:  Lancet       Date:  1986-06-28       Impact factor: 79.321

  10 in total
  18 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.  ICASP: an intensive-care acquisition and signal processing integrated framework.

Authors:  Eleftheria J Siachalou; Ilias K Kitsas; Konstantinos J Panoulas; Emmanouil Th Zadelis; Christos D Saragiotis; Yannis A Tolias; Leontios J Hadjileontiadis; Stavros M Panas
Journal:  J Med Syst       Date:  2005-12       Impact factor: 4.460

3.  The influence of missing components of the Acute Physiology Score of APACHE III on the measurement of ICU performance.

Authors:  Bekele Afessa; Mark T Keegan; Ognjen Gajic; Rolf D Hubmayr; Steve G Peters
Journal:  Intensive Care Med       Date:  2005-10-05       Impact factor: 17.440

4.  New advances and validation of knowledge management tools for critical care using classifier techniques.

Authors:  M Frize; L Wang; C M Ennett; B G Nickerson; F G Solven; M Stevenson
Journal:  Proc AMIA Symp       Date:  1998

5.  Mean Platelet Volume (MPV), Platelet Distribution Width (PDW), Platelet Count and Plateletcrit (PCT) as predictors of in-hospital paediatric mortality: a case-control Study.

Authors:  Zainab Mohammedi Golwala; Hardik Shah; Neeraj Gupta; V Sreenivas; Jacob M Puliyel
Journal:  Afr Health Sci       Date:  2016-06       Impact factor: 0.927

6.  Risk of death and the efficacy of eritoran tetrasodium (E5564): design considerations for clinical trials of anti-inflammatory agents in sepsis.

Authors:  Amisha V Barochia; Xizhong Cui; Charles Natanson; Peter Q Eichacker
Journal:  Crit Care Med       Date:  2010-01       Impact factor: 7.598

7.  The performance of SAPS II in a cohort of patients admitted to 99 Italian ICUs: results from GiViTI. Gruppo Italiano per la Valutazione degli interventi in Terapia Intensiva.

Authors:  G Apolone; G Bertolini; R D'Amico; G Iapichino; A Cattaneo; G De Salvo; R M Melotti
Journal:  Intensive Care Med       Date:  1996-12       Impact factor: 17.440

8.  Prognostic Values of Platelet Distribution Width and Platelet Distribution Width-to-Platelet Ratio in Severe Burns.

Authors:  Jian-Chang Lin; Guo-Hua Wu; Jian-Jun Zheng; Zhao-Hong Chen; Xiao-Dong Chen
Journal:  Shock       Date:  2022-04-01       Impact factor: 3.454

9.  SAPS 3--From evaluation of the patient to evaluation of the intensive care unit. Part 1: Objectives, methods and cohort description.

Authors:  Philipp G H Metnitz; Rui P Moreno; Eduardo Almeida; Barbara Jordan; Peter Bauer; Ricardo Abizanda Campos; Gaetano Iapichino; David Edbrooke; Maurizia Capuzzo; Jean-Roger Le Gall
Journal:  Intensive Care Med       Date:  2005-08-17       Impact factor: 17.440

10.  Autotaxin levels in serum and bronchoalveolar lavage fluid are associated with inflammatory and fibrotic biomarkers and the clinical outcome in patients with acute respiratory distress syndrome.

Authors:  Lijuan Gao; Xiaoou Li; Hao Wang; Yue Liao; Yongfang Zhou; Ke Wang; Jun Hu; Mengxin Cheng; Zijian Zeng; Tao Wang; Fuqiang Wen
Journal:  J Intensive Care       Date:  2021-06-15
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