Literature DB >> 31412292

Prearrest prediction of favourable neurological survival following in-hospital cardiac arrest: The Prediction of outcome for In-Hospital Cardiac Arrest (PIHCA) score.

Eva Piscator1, Katarina Göransson2, Sune Forsberg3, Matteo Bottai4, Mark Ebell5, Johan Herlitz6, Therese Djärv7.   

Abstract

BACKGROUND: A prearrest prediction tool can aid clinicians in consolidating objective findings with clinical judgement and in balance with the values of the patient be a part of the decision process for do-not-attempt-resuscitation (DNAR) orders. A previous prearrest prediction tool for in-hospital cardiac arrest (IHCA) have not performed satisfactory in external validation in a Swedish cohort. Therefore our aim was to develop a prediction model for the Swedish setting.
METHODS: Model development was based on previous external validation of The Good Outcome Following Attempted Resuscitation (GO-FAR) score, with 717 adult IHCAs. It included redefinition and reduction of predictors, and addition of chronic comorbidity, to create a full model of 9 predictors. Outcome was favourable neurological survival defined as Cerebral Performance Category score 1-2  at discharge. The likelihood of favourable neurological survival was categorised into very low (<1%), low (1-3%) and above low (>3%).
RESULTS: We called the model the Prediction of outcome for In-Hospital Cardiac Arrest (PIHCA) score. The AUROC was 0.808 (95% CI 0.807-0.810) and calibration was satisfactory. With a cutoff of 3% likelihood of favourable neurological survival sensitivity was 99.4% and specificity 8.4%. Although specificity was limited, predictive value for classification into ≤3% likelihood of favorable neurological survival was high (97.4%) and false classification into ≤3% likelihood of favourable neurological survival was low (0.6%).
CONCLUSION: The PIHCA score has the potential to be used as an objective tool in prearrest prediction of outcome after IHCA, as part of the decision process for a DNAR order.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Cardiopulmonary resuscitation; Clinical decision-making; Heart arrest; In-hospital cardiac arrest; Medical futility; Models-Statistical; Prognosis

Mesh:

Year:  2019        PMID: 31412292     DOI: 10.1016/j.resuscitation.2019.08.010

Source DB:  PubMed          Journal:  Resuscitation        ISSN: 0300-9572            Impact factor:   5.262


  4 in total

1.  Comparison of two strategies for managing in-hospital cardiac arrest.

Authors:  Jafer Haschemi; Ralf Erkens; Robert Orzech; Jean Marc Haurand; Christian Jung; Malte Kelm; Ralf Westenfeld; Patrick Horn
Journal:  Sci Rep       Date:  2021-11-18       Impact factor: 4.379

2.  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

3.  Mean arterial pressure is associated with the neurological function in patients who survived after cardiopulmonary resuscitation: A retrospective cohort study.

Authors:  Hai-Bo Ai; En-Li Jiang; Ji-Hua Yu; Lin-Bo Xiong; Qi Yang; Qi-Zu Jin; Wen-Yan Gong; Shuai Chen; Hong Zhang
Journal:  Clin Cardiol       Date:  2020-08-01       Impact factor: 2.882

4.  Low adherence to legislation regarding Do-Not-Attempt-Cardiopulmonary-Resuscitation orders in a Swedish University Hospital.

Authors:  Eva Piscator; Therese Djärv; Katarina Rakovic; Emil Boström; Sune Forsberg; Martin J Holzmann; Johan Herlitz; Katarina Göransson
Journal:  Resusc Plus       Date:  2021-04-29
  4 in total

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