The CAHP (Cardiac Arrest Hospital Prognosis) score: a tool for risk stratification after out-of-hospital cardiac arrest

Maupain, Carole; Bougouin, Wulfran; Lamhaut, Lionel; Deye, Nicolas; Diehl, Jean Luc; Géri, Guillaume; Perier, Marie Cécile; Beganton, Frankie; Marijon, Éloi; Jouven, Xavier; Cariou, Alain; Dumas, Florence

doi:10.1093/eurheartj/ehv556

Cited by 271 publications

(237 citation statements)

References 28 publications

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“…The TTM risk score is divided into quartiles where the Youden’s J statistic cut-off (>13 points) coincides with second quartile upper limit (i.e., the median). The CAHP and OHCA risk scores are calculated and divided as described in their respective original publications [11, 12]. They were defined as high risk if >200 points and >32.5 points for the CAHP and OHCA risk scores, respectively…”

Section: Resultsmentioning

confidence: 99%

“…An assessment of the risk for a poor outcome would also be of great value for comparing populations and to define patient risk when assessing effects in interventional studies. Efforts to construct a prediction score based on the set of data available at hospital admission have yielded the OHCA score [11] and the Cardiac Arrest Hospital Prognosis (CAHP) score [12]. When applied prospectively, the OHCA score showed moderate predictive accuracy [13]; however, none of these scores has been validated for clinical use.…”

Section: Introductionmentioning

confidence: 99%

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Early predictors of poor outcome after out-of-hospital cardiac arrest

et al. 2017

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BackgroundEarly identification of predictors for a poor long-term outcome in patients who survive the initial phase of out-of-hospital cardiac arrest (OHCA) may facilitate future clinical research, the process of care and information provided to relatives. The aim of this study was to determine the association between variables available from the patient’s history and status at intensive care admission with outcome in unconscious survivors of OHCA.MethodsUsing the cohort of the Target Temperature Management trial, we performed a post hoc analysis of 933 unconscious patients with OHCA of presumed cardiac cause who had a complete 6-month follow-up. Outcomes were survival and neurological function as defined by the Cerebral Performance Category (CPC) scale at 6 months after OHCA. After multiple imputations to compensate for missing data, backward stepwise multivariable logistic regression was applied to identify factors independently predictive of a poor outcome (CPC 3–5). On the basis of these factors, a risk score for poor outcome was constructed.ResultsWe identified ten independent predictors of a poor outcome: older age, cardiac arrest occurring at home, initial rhythm other than ventricular fibrillation/tachycardia, longer duration of no flow, longer duration of low flow, administration of adrenaline, bilateral absence of corneal and pupillary reflexes, Glasgow Coma Scale motor response 1, lower pH and a partial pressure of carbon dioxide in arterial blood value lower than 4.5 kPa at hospital admission. A risk score based on the impact of each of these variables in the model yielded a median (range) AUC of 0.842 (0.840–0.845) and good calibration. Internal validation of the score using bootstrapping yielded a median (range) AUC corrected for optimism of 0.818 (0.816–0.821).ConclusionsAmong variables available at admission to intensive care, we identified ten independent predictors of a poor outcome at 6 months for initial survivors of OHCA. They reflected pre-hospital circumstances (six variables) and patient status on hospital admission (four variables). By using a simple and easy-to-use risk scoring system based on these variables, patients at high risk for a poor outcome after OHCA may be identified early.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Early predictors of poor outcome after out-of-hospital cardiac arrest

et al. 2017

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“…Currently available scores such as the OHCA score22 and Cardiac Arrest Hospital Prognosis score11 are useful but contain complex mathematical formulas and require biochemistry results which have a turn-around time; this may make the tool less widely in acute situations. On the other hand, simpler calculators like the Good Outcome Following Attempted Resuscitation (GO-FAR) score have been validated for in-hospital but not OHCA.…”

Section: Discussionmentioning

confidence: 99%

Influence of comorbidities and clinical prediction model on neurological prognostication post out-of-hospital cardiac arrest

et al. 2018

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In our derivation cohort of 129 patients, 30.23% survived with CPC 1-2. Significant factors associated with survival with good neurological outcomes were age-adjusted Charlson Comorbidity Index ≤5, time to first return of spontaneous circulation ≤40 min, the presence of immediate bystander cardiopulmonary resuscitation and shockable rhythms. We also developed a nomogram which showed good internal (ROC curve 0.84; 95% CI 0.77 to 0.91) and external validation (ROC curve 0.90; 95% CI 0.81 to 1.00).

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“…3,13 Cases in which the patients were alive at hospital admission were classified as ''short-term survival,'' whereas cases with good neurological recovery were classified as ''long-term survival'' (ie, patients with a cerebral performance category scale of 1, with a return to normal cerebral function and normal living, or a 2, with cerebral disability but sufficient functioning for the activities of daily life).…”

Section: Methodsmentioning

confidence: 99%