Literature DB >> 9107612

Failure of three decision rules to predict the outcome of in-hospital cardiopulmonary resuscitation.

M H Ebell1, J A Kruse, M Smith, J Novak, J Drader-Wilcox.   

Abstract

The objective of this study was to evaluate three decision-support tools (the Pre-Arrest Morbidity or PAM score, the Prognosis After Resuscitation or PAR score, and the Acute Physiology and Chronic Health Evaluation or APACHE III score) for their abilities to predict the outcomes of in-hospital cardiopulmonary resuscitation (CPR). The medical records of all 656 adult inpatients undergoing CPR during a two-to-three-year period in three large hospitals were retrospectively reviewed, and demographic and clinical variables were abstracted. Of 656 patients undergoing resuscitation, 248 (37.8%) survived the resuscitation attempt long enough to be stabilized (immediate survival), but only 35 (5.3%) survived to discharge. Only 11 patients had PAM scores higher than 8, none of whom survived to discharge; 131 patients had PAR scores above 8, of whom six survived to discharge. The PAR score and the APACHE III score had the greatest areas under the receiver operating characteristic curves (when predicting the outcome of survival to discharge), although no individual area for either outcome was greater than 0.6. None of the decision-support tools studied was able to effectively discriminate between survivors and non-survivors for the outcomes of immediate survival and survival to discharge following in-hospital CPR. This is consistent with previous work utilizing the APACHE II score, which did not identify a threshold above which patients did not benefit from CPR. The findings for the PAR score and the PAM score stand in contrast to previous studies that found them to be potentially useful decision rules. Further work is needed to develop a decision-support tool that better discriminates between survivors and non-survivors of in-hospital CPR.

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Year:  1997        PMID: 9107612     DOI: 10.1177/0272989X9701700207

Source DB:  PubMed          Journal:  Med Decis Making        ISSN: 0272-989X            Impact factor:   2.583


  8 in total

1.  Survival after in-hospital cardiopulmonary resuscitation. A meta-analysis.

Authors:  M H Ebell; L A Becker; H C Barry; M Hagen
Journal:  J Gen Intern Med       Date:  1998-12       Impact factor: 5.128

Review 2.  In-hospital cardiac arrest: incidence, prognosis and possible measures to improve survival.

Authors:  Claudio Sandroni; Jerry Nolan; Fabio Cavallaro; Massimo Antonelli
Journal:  Intensive Care Med       Date:  2006-09-22       Impact factor: 17.440

Review 3.  Using risk prediction tools in survivors of in-hospital cardiac arrest.

Authors:  Saket Girotra; Brahmajee K Nallamothu; Paul S Chan
Journal:  Curr Cardiol Rep       Date:  2014-03       Impact factor: 2.931

4.  APACHE II scores as predictors of cardio pulmonary resuscitation outcome: Evidence from a tertiary care institute in a low-income country.

Authors:  Muhammad Junaid Patel; Nadeem Ullah Khan; Muhammad Furqan; Safia Awan; Muhammad Shoaib Khan; Waqar Kashif; Ayesha L Sorathia; Syed Ather Hussain; Mohammed Umer Mir
Journal:  Saudi J Anaesth       Date:  2012-01

5.  Reexamination of the UN10 Rule to Discontinue Resuscitation During In-Hospital Cardiac Arrest.

Authors:  Bradley J Petek; Daniel N Bennett; Christian Ngo; Paul S Chan; Brahmajee K Nallamothu; Steven M Bradley; Yuanyuan Tang; Rodney A Hayward; Carl van Walraven; Zachary D Goldberger
Journal:  JAMA Netw Open       Date:  2019-05-03

6.  Pre-arrest and intra-arrest prognostic factors associated with survival after in-hospital cardiac arrest: systematic review and meta-analysis.

Authors:  Shannon M Fernando; Alexandre Tran; Wei Cheng; Bram Rochwerg; Monica Taljaard; Christian Vaillancourt; Kathryn M Rowan; David A Harrison; Jerry P Nolan; Kwadwo Kyeremanteng; Daniel I McIsaac; Gordon H Guyatt; Jeffrey J Perry
Journal:  BMJ       Date:  2019-12-04

7.  Predicting in-hospital mortality after an in-hospital cardiac arrest: A multivariate analysis.

Authors:  Talal Alnabelsi; Rahul Annabathula; Julie Shelton; Marc Paranzino; Sarah Price Faulkner; Matthew Cook; Adam J Dugan; Sethabhisha Nerusu; Susan S Smyth; Vedant A Gupta
Journal:  Resusc Plus       Date:  2020-11-07

8.  Clinical Predictive Models of Sudden Cardiac Arrest: A Survey of the Current Science and Analysis of Model Performances.

Authors:  Richard T Carrick; Jinny G Park; Hannah L McGinnes; Christine Lundquist; Kristen D Brown; W Adam Janes; Benjamin S Wessler; David M Kent
Journal:  J Am Heart Assoc       Date:  2020-08-13       Impact factor: 5.501

  8 in total

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