OBJECTIVE: Investigators in France have developed a risk score to predict death or poor neurologic outcome after out-of-hospital cardiac arrest. The aim of this study is to externally validate this score in an independent patient population in the United States. DESIGN: Retrospective, observational, cohort study. PATIENTS: Patients being admitted to the intensive care unit after out-of-hospital cardiac arrest. SETTING: Two geographically distinct tertiary care hospitals in the United States. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The primary end point was poor outcome, defined as either death or a Cerebral Performance Category score of 3-5. The secondary end point was all-cause mortality. Calibration was assessed by comparing the number of expected outcomes based on the logistic model of the French study with observed outcomes within this study using Hosmer-Lemeshow C test (goodness-of-fit). Discrimination was assessed by calculation of the area under the receiver operating characteristic curve. Of a total of 128 patients, 99 (77%) had a poor outcome, including 91 nonsurvivors (71%). The probability of poor neurologic outcome and mortality increased stepwise with increasing out-of-hospital cardiac arrest score. Graphic display of observed against predicted outcomes and goodness-of-fit test indicated good calibration of the score (p = .4). The score showed good discrimination for poor outcome (area under the receiving operating characteristic curve, 0.85; 95% confidence interval, 0.79-0.92) and for mortality (area under the receiving operating characteristic curve, 0.85; 95% confidence interval, 0.78-0.91). In patients with an out-of-hospital cardiac arrest score >40 points and >60 points, the positive predictive value for poor outcome was 97% and 100%, respectively. CONCLUSIONS: This study found good calibration and high discrimination of the out-of-hospital cardiac arrest score in two geographically distinct patient populations in the United States. Particularly, this score had a high positive predictive value and performed well in identifying high-risk patients for poor outcomes.
OBJECTIVE: Investigators in France have developed a risk score to predict death or poor neurologic outcome after out-of-hospital cardiac arrest. The aim of this study is to externally validate this score in an independent patient population in the United States. DESIGN: Retrospective, observational, cohort study. PATIENTS: Patients being admitted to the intensive care unit after out-of-hospital cardiac arrest. SETTING: Two geographically distinct tertiary care hospitals in the United States. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The primary end point was poor outcome, defined as either death or a Cerebral Performance Category score of 3-5. The secondary end point was all-cause mortality. Calibration was assessed by comparing the number of expected outcomes based on the logistic model of the French study with observed outcomes within this study using Hosmer-Lemeshow C test (goodness-of-fit). Discrimination was assessed by calculation of the area under the receiver operating characteristic curve. Of a total of 128 patients, 99 (77%) had a poor outcome, including 91 nonsurvivors (71%). The probability of poor neurologic outcome and mortality increased stepwise with increasing out-of-hospital cardiac arrest score. Graphic display of observed against predicted outcomes and goodness-of-fit test indicated good calibration of the score (p = .4). The score showed good discrimination for poor outcome (area under the receiving operating characteristic curve, 0.85; 95% confidence interval, 0.79-0.92) and for mortality (area under the receiving operating characteristic curve, 0.85; 95% confidence interval, 0.78-0.91). In patients with an out-of-hospital cardiac arrest score >40 points and >60 points, the positive predictive value for poor outcome was 97% and 100%, respectively. CONCLUSIONS: This study found good calibration and high discrimination of the out-of-hospital cardiac arrest score in two geographically distinct patient populations in the United States. Particularly, this score had a high positive predictive value and performed well in identifying high-risk patients for poor outcomes.
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Authors: N Yoshimi; T Futamura; S E Bergen; Y Iwayama; T Ishima; C Sellgren; C J Ekman; J Jakobsson; E Pålsson; K Kakumoto; Y Ohgi; T Yoshikawa; M Landén; K Hashimoto Journal: Mol Psychiatry Date: 2016-01-19 Impact factor: 15.992
Authors: Hans Kirkegaard; Asger Roer Pedersen; Ville Pettilä; Jakob Hjort; Bodil Steen Rasmussen; Inge de Haas; Jørgen Feldbæk Nielsen; Susanne Ilkjær; Anne Kaltoft; Anni Nørgaard Jeppesen; Anders Morten Grejs; Christophe Henri Valdemar Duez; Alf Inge Larsen; Valdo Toome; Urmet Arus; Fabio Silvio Taccone; Christian Storm; Timo Laitio; Markus B Skrifvars; Eldar Søreide Journal: Scand J Trauma Resusc Emerg Med Date: 2016-11-28 Impact factor: 2.953
Authors: Noriko Yoshimi; Takashi Futamura; Keiji Kakumoto; Alireza M Salehi; Carl M Sellgren; Jessica Holmén-Larsson; Joel Jakobsson; Erik Pålsson; Mikael Landén; Kenji Hashimoto Journal: BBA Clin Date: 2016-04-03