Literature DB >> 3816253

Validation of the mortality prediction model for ICU patients.

D Teres, S Lemeshow, J S Avrunin, H Pastides.   

Abstract

We tested recently developed admission and 24-h models of hospital mortality on 1,997 consecutive admissions to a general medical/surgical ICU. This study population was independent of the group used to develop the models. The admission prediction model estimated each patient's probability of hospital mortality based on seven routinely collected admission variables. The 24-h model utilized seven variables routinely available at 24 h in the ICU. The admission model accurately described the mortality experience of the new cohort, while the 24-h model did not. Advantages of the admission model are that it is evaluable at the time of ICU admission, is independent of ICU treatment, and can be used to stratify patients by severity of illness, thereby making ICU comparisons possible. Its excellent goodness-of-fit, correct classification rate, sensitivity, and specificity suggest that this model is now ready for multihospital testing.

Entities:  

Mesh:

Year:  1987        PMID: 3816253     DOI: 10.1097/00003246-198703000-00005

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


  17 in total

1.  A new scoring system for disease intensity in a surgical intensive care unit.

Authors:  P Lehmkuhl; S Jeck-Thole; I Pichlmayr
Journal:  World J Surg       Date:  1989 May-Jun       Impact factor: 3.352

Review 2.  Prognostic models for predicting mortality in elderly ICU patients: a systematic review.

Authors:  Lilian Minne; Jeroen Ludikhuize; Evert de Jonge; Sophia de Rooij; Ameen Abu-Hanna
Journal:  Intensive Care Med       Date:  2011-06-07       Impact factor: 17.440

3.  Validation of a severity of illness score (APACHE II) in a surgical intensive care unit.

Authors:  G Giangiuliani; A Mancini; D Gui
Journal:  Intensive Care Med       Date:  1989       Impact factor: 17.440

4.  An analysis of the utilisation of an intensive care unit.

Authors:  S Jacobs; R W Chang; B Lee; B Lee
Journal:  Intensive Care Med       Date:  1989       Impact factor: 17.440

5.  Validation of a quality of life questionnaire for critically ill patients.

Authors:  R R Fernandez; J J Cruz; G V Mata
Journal:  Intensive Care Med       Date:  1996-10       Impact factor: 17.440

6.  Quality of life: a tool for decision-making in the ICU. Spanish Group for the Epidemiological Analysis of Critical Patients (PAEEC)

Authors: 
Journal:  Intensive Care Med       Date:  1994       Impact factor: 17.440

7.  Scoring system for nosocomial pneumonia in ICUs.

Authors:  A Kropec; G Schulgen; H Just; K Geiger; M Schumacher; F Daschner
Journal:  Intensive Care Med       Date:  1996-11       Impact factor: 17.440

Review 8.  A review of risk scoring systems utilised in patients undergoing gastrointestinal surgery.

Authors:  Aninda Chandra; Sudhakar Mangam; Deya Marzouk
Journal:  J Gastrointest Surg       Date:  2009-03-25       Impact factor: 3.452

9.  Simultaneous Prediction of New Morbidity, Mortality, and Survival Without New Morbidity From Pediatric Intensive Care: A New Paradigm for Outcomes Assessment.

Authors:  Murray M Pollack; Richard Holubkov; Tomohiko Funai; John T Berger; Amy E Clark; Kathleen Meert; Robert A Berg; Joseph Carcillo; David L Wessel; Frank Moler; Heidi Dalton; Christopher J L Newth; Thomas Shanley; Rick E Harrison; Allan Doctor; Tammara L Jenkins; Robert Tamburro; J Michael Dean
Journal:  Crit Care Med       Date:  2015-08       Impact factor: 7.598

10.  Case mix, outcome and activity for patients with severe acute kidney injury during the first 24 hours after admission to an adult, general critical care unit: application of predictive models from a secondary analysis of the ICNARC Case Mix Programme database.

Authors:  Nitin V Kolhe; Paul E Stevens; Alex V Crowe; Graham W Lipkin; David A Harrison
Journal:  Crit Care       Date:  2008-10-13       Impact factor: 9.097

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.