Prearrest prediction of favourable neurological survival following in-hospital cardiac arrest: The Prediction of outcome for In-Hospital Cardiac Arrest (PIHCA) score.
Cardiopulmonary resuscitation
Clinical decision-making
Heart arrest
In-hospital cardiac arrest
Medical futility
Models-Statistical
Prognosis
Journal
Resuscitation
ISSN: 1873-1570
Titre abrégé: Resuscitation
Pays: Ireland
ID NLM: 0332173
Informations de publication
Date de publication:
10 2019
10 2019
Historique:
received:
22
01
2019
revised:
02
08
2019
accepted:
06
08
2019
pubmed:
15
8
2019
medline:
18
9
2020
entrez:
15
8
2019
Statut:
ppublish
Résumé
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. 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%). 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%). 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.
Sections du résumé
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.
Identifiants
pubmed: 31412292
pii: S0300-9572(19)30568-4
doi: 10.1016/j.resuscitation.2019.08.010
pii:
doi:
Types de publication
Journal Article
Multicenter Study
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
92-99Informations de copyright
Copyright © 2019 Elsevier B.V. All rights reserved.