A Validated Prediction Tool for Initial Survivors of In-Hospital Cardiac Arrest

被引:136
作者
Chan, Paul S. [1 ,2 ]
Spertus, John A. [1 ,2 ]
Krumholz, Harlan M. [3 ,4 ,5 ,6 ]
Berg, Robert A. [7 ]
Li, Yan [1 ]
Sasson, Comilla [8 ]
Nallamothu, Brahmajee K. [9 ,10 ]
机构
[1] St Lukes Mid Amer Heart Inst, Kansas City, MO USA
[2] Univ Missouri, Dept Internal Med, Columbia, MO 65211 USA
[3] Yale Univ, Sch Med, Sect Cardiovasc Med, New Haven, CT USA
[4] Yale Univ, Sch Med, Dept Med, Robert Wood Johnson Clin Scholars Program, New Haven, CT 06510 USA
[5] Yale Univ, Sect Hlth Policy & Adm, Sch Publ Hlth, New Haven, CT USA
[6] Yale New Haven Hosp, Ctr Outcomes Res & Evaluat, New Haven, CT 06504 USA
[7] Childrens Hosp Philadelphia, Philadelphia, PA 19104 USA
[8] Univ Colorado, Denver, CO 80202 USA
[9] VA Ann Arbor Hlth Serv Res & Dev Ctr Excellence, Ann Arbor, MI USA
[10] Univ Michigan, Div Cardiovasc Med, Ann Arbor, MI 48109 USA
关键词
AUSTRALIAN RESUSCITATION COUNCIL; AMERICAN-HEART-ASSOCIATION; HEALTH-CARE PROFESSIONALS; CARDIOPULMONARY-RESUSCITATION; STROKE FOUNDATION; STATEMENT; CANADA;
D O I
10.1001/archinternmed.2012.2050
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: Accurate estimation of favorable neurological survival after in-hospital cardiac arrest could provide critical information for physicians, patients, and families. Methods: Within the Get With the Guidelines-Resuscitation registry, we identified 42 957 patients from 551 hospitals admitted between January 2000 and October 2009 who were successfully resuscitated from an in-hospital cardiac arrest. A simple prediction tool for favorable neurological survival in patients successfully resuscitated from an in-hospital cardiac arrest was developed using multivariate logistic regression, with two-thirds of the sample randomly selected as the derivation cohort and one-third as the validation cohort. Favorable neurological status was defined as the absence of severe neurological deficits (cerebral performance category score of <= 2). Results: Rates of favorable neurological survival were similar in the derivation cohort (7052 patients [24.6%]) and validation cohort (3510 patients [24.5%]). Eleven variables were associated with favorable neurological survival: younger age, initial cardiac arrest rhythm of ventricular fibrillation or pulseless ventricular tachycardia with a defibrillation time of 2 minutes or less, baseline neurological status without disability, arrest location in a monitored unit, shorter duration of resuscitation, and absence of mechanical ventilation, renal insufficiency, hepatic insufficiency, sepsis, malignant disease, and hypotension prior to the arrest. The model had excellent discrimination (C statistic of 0.80 for both the derivation and validation cohorts) and calibration. The prediction tool demonstrated the ability to identify patients across a wide range of rates of favorable neurological survival: patients in the top decile had a 70.7% probability of this outcome, whereas patients in the bottom decile had a 2.8% probability. Conclusions: Among successfully resuscitated patients with an in-hospital cardiac arrest, a simple, bedside prediction tool provides robust estimates of the probability of favorable neurological survival. This tool permits accurate prognostication after cardiac arrest for physicians, patients, and families.
引用
收藏
页码:947 / 953
页数:7
相关论文
共 17 条
[1]  
[Anonymous], 2002, IVEWARE IMPUTATION V
[2]  
Belsley D.A., 2005, REGRESSION DIAGNOSTI
[3]   Delayed time to defibrillation after in-hospital cardiac arrest [J].
Chan, Paul S. ;
Krumholz, Harlan M. ;
Nichol, Graham ;
Nallamothu, Brahmajee K. .
NEW ENGLAND JOURNAL OF MEDICINE, 2008, 358 (01) :9-17
[4]   Racial Differences in Survival After In-Hospital Cardiac Arrest [J].
Chan, Paul S. ;
Nichol, Graham ;
Krumholz, Harlan M. ;
Spertus, John A. ;
Jones, Philip G. ;
Peterson, Eric D. ;
Rathore, Saif S. ;
Nallamothu, Brahmajee K. .
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2009, 302 (11) :1195-1201
[5]   PREDICTING SURVIVAL FROM IN-HOSPITAL CPR - METAANALYSIS AND VALIDATION OF A PREDICTION MODEL [J].
COHN, EB ;
LEFEVRE, F ;
YARNOLD, PR ;
ARRON, MJ ;
MARTIN, GJ .
JOURNAL OF GENERAL INTERNAL MEDICINE, 1993, 8 (07) :347-353
[6]   A decade of in-hospital resuscitation: Outcomes and prediction of survival? [J].
Cooper, S ;
Janghorbani, M ;
Cooper, G .
RESUSCITATION, 2006, 68 (02) :231-237
[7]   Recommended guidelines for reviewing, reporting, and conducting research on in-hospital resuscitation: The In-Hospital 'Utstein style' - A statement for healthcare professionals from the American Heart Association, the European Resuscitation Council, the Heart and Stroke Foundation of Canada, the Australian Resuscitation Council, and the Resuscitation Councils of Southern Africa [J].
Cummins, RO ;
Chamberlain, D ;
Hazinski, MF ;
Nadkarni, V ;
Kloeck, W ;
Kramer, E ;
Becker, L ;
Robertson, C ;
Koster, R ;
Zaritsky, A ;
Bossart, L ;
Ornato, JP ;
Callanan, V ;
Allen, M ;
Steen, P ;
Connolly, B ;
Sanders, A ;
Idris, A ;
Cobbe, S .
CIRCULATION, 1997, 95 (08) :2213-2239
[8]   Is Hypothermia After Cardiac Arrest Effective in Both Shockable and Nonshockable Patients? Insights From a Large Registry [J].
Dumas, Florence ;
Grimaldi, David ;
Zuber, Benjamin ;
Fichet, Jerome ;
Charpentier, Julien ;
Pene, Frederic ;
Vivien, Benoit ;
Varenne, Olivier ;
Carli, Pierre ;
Jouven, Xavier ;
Empana, Jean-Philippe ;
Cariou, Alain .
CIRCULATION, 2011, 123 (08) :877-U95
[9]  
GEORGE AL, 1989, AM J MED, V87, P28
[10]  
Harrell FE., 2001, Regression Modeling Strategies: with Applications to Linear Models, Logistic Regression, and Survival Analysis, V608, DOI DOI 10.2147/