Pre-resuscitation factors associated with mortality in 49,130 cases of in-hospital cardiac arrest: A report from the National Registry for Cardiopulmonary Resuscitation

Resuscitation

Volumn 81, Issue 3, 2010, Pages 302-311

  Larkin, Gregory Luke ^a   Copes, Wayne S ^a   Nathanson, Brian H ^a   Kaye, William ^a  

^a YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

In hospital cardiac arrest; Mortality; NRCPR; Pre resuscitation risk factors; Prediction

Indexed keywords

HYPERTENSIVE FACTOR;

ADULT; AGE; AGED; ARTICLE; ARTIFICIAL VENTILATION; CARDIOPULMONARY ARREST; CARDIORENAL SYNDROME; CARDIOVASCULAR SYSTEM EXAMINATION; DISEASE EXACERBATION; EMERGENCY WARD; FEMALE; GENETIC PREDISPOSITION; HOSPITALIZATION; HUMAN; IN HOSPITAL CARDIOPULMONARY ARREST; INJURY; LIVER FAILURE; MAJOR CLINICAL STUDY; MALE; MORTALITY; NEGRO; NEUROLOGIC DISEASE; PRIORITY JOURNAL; PULSE RATE; RESUSCITATION; RISK FACTOR; SEPTICEMIA; STROKE; SURVIVAL; TREATMENT PLANNING; ADOLESCENT; COHORT ANALYSIS; HEART ARREST; HOSPITAL PATIENT; MIDDLE AGED; MULTIVARIATE ANALYSIS; PATIENT CARE PLANNING; PREDICTION AND FORECASTING; REGISTER; STATISTICAL MODEL;

ADOLESCENT; ADULT; AGED; AGED, 80 AND OVER; CARDIOPULMONARY RESUSCITATION; COHORT STUDIES; FEMALE; HEART ARREST; HOSPITAL MORTALITY; HUMANS; INPATIENTS; LOGISTIC MODELS; MALE; MIDDLE AGED; MULTIVARIATE ANALYSIS; PATIENT CARE PLANNING; PREDICTIVE VALUE OF TESTS; REGISTRIES; RISK FACTORS; YOUNG ADULT;

EID: 77951931840     PISSN: 03009572     EISSN: 18731570     Source Type: Journal    
DOI: 10.1016/j.resuscitation.2009.11.021     Document Type: Article

References (35)

1. Kouwenhoven W.B., Jude J.R., Knickerbocker G.G. Closed-chest cardiac massage. Jama 1960, 173:1064-1067.
2. Murphy D.J., Burrows D., Santilli S., et al. The influence of the probability of survival on patients' preferences regarding cardiopulmonary resuscitation. N Engl J Med 1994, 330:545-549.
3. Ebell M.H., Bergus G.R., Warbasse L., Bloomer R. The inability of physicians to predict the outcome of in-hospital resuscitation. J Gen Intern Med 1996, 11:16-22.
4. Brindley P.G., Markland D.M., Mayers I., Kutsogiannis D.J. Predictors of survival following in-hospital adult cardiopulmonary resuscitation. Cmaj 2002, 167:343-348.
5. Larkin G.L. End of life rituals: the beneficence of futile cardiopulmonary resuscitation. Turk Clin J Med Ethics, Law History 2004, 12:157-163.
6. Peberdy M.A., Kaye W., Ornato J.P., et al. Cardiopulmonary resuscitation of adults in the hospital: a report of 14720 cardiac arrests from the National Registry of Cardiopulmonary Resuscitation. Resuscitation 2003, 58:297-308.
7. van Walraven C., Forster A.J., Parish D.C., et al. Validation of a clinical decision aid to discontinue in-hospital cardiac arrest resuscitations. Jama 2001, 285:1602-1606.
8. Cummins R.O., Chamberlain D., Hazinski M.F., et al. Recommended guidelines for reviewing, reporting, and conducting research on in-hospital resuscitation: the in-hospital 'Utstein style'. Am Heart Assoc Circ 1997, 95:2213-2239.
9. Jacobs I., Nadkarni V., Bahr J., et al. Cardiac arrest and cardiopulmonary resuscitation outcome reports: update and simplification of the Utstein templates for resuscitation registries: a statement for healthcare professionals from a task force of the International Liaison Committee on Resuscitation (American Heart Association, European Resuscitation Council, Australian Resuscitation Council, New Zealand Resuscitation Council, Heart and Stroke Foundation of Canada, InterAmerican Heart Foundation, Resuscitation Councils of Southern Africa). Circulation 2004, 110:3385-3397.
10. Nadkarni V.M., Larkin G.L., Peberdy M.A., et al. First documented rhythm and clinical outcome from in-hospital cardiac arrest among children and adults. Jama 2006, 295:50-57.
11. Apache Medical Systems Inc. APACHE III. 2006.
12. Mander A., Clayton D. Hotdeck imputation. Stata Tech Bull 1999, 51:32-34.
13. Little R., Rubin D. Statistical analysis with missing data 1987, John Wiley & Sons, New York.
14. Royston P. Multiple imputation of missing values. Stata J 2004, 4:227-241.
15. Austin P., Tu J. Bootstrap methods for developing predictive models. Am Stat 2004, 58:131-137.
16. Hosmer D., Lemeshow S. Applied logistic regression 2000, John Wiley & Sons, New York.
17. Hanley J, McNeil B. A method of comparing the areas under receiver operating characteristic curves derived from the same cases.
18. Raftery A. Bayesian model selection in social research. Sociological methodology 1996, 111-163. Basil Blackwell, Oxford. P. Marsden (Ed.).
19. DeLong E.R., DeLong D.M., Clarke-Pearson D.L. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988, 44:837-845.
20. Teres D. Trends from the United States with end of life decisions in the intensive care unit. Intensive Care Med 1993, 19:316-322.
21. Lynn J., De Vries K.O., Arkes H.R., et al. Ineffectiveness of the SUPPORT intervention: review of explanations. J Am Geriatr Soc 2000, 48:S206-S213.
22. Cohn E.B., Lefevre F., Yarnold P.R., Arron M.J., Martin G.J. Predicting survival from in-hospital CPR: meta-analysis and validation of a prediction model. J Gen Intern Med 1993, 8:347-353.
23. Ebell M.H., Preston P.S. The effect of the APACHE II score and selected clinical variables on survival following cardiopulmonary resuscitation. Fam Med 1993, 25:191-196.
24. Ebell M.H., Kruse J.A., Smith M., Novak J., Drader-Wilcox J. Failure of three decision rules to predict the outcome of in-hospital cardiopulmonary resuscitation. Med Decis Making 1997, 17:171-177.
25. Marwick T.H., Case C.C., Siskind V., Woodhouse S.P. Prediction of survival from resuscitation: a prognostic index derived from multivariate logistic model analysis. Resuscitation 1991, 22:129-137.
26. Tunstall-Pedoe H., Bailey L., Chamberlain D.A., Marsden A.K., Ward M.E., Zideman D.A. Survey of 3765 cardiopulmonary resuscitations in British hospitals (the BRESUS Study): methods and overall results. Bmj 1992, 304:1347-1351.
27. Kaye W., Mancini M.E., Truitt T.L. When minutes count-the fallacy of accurate time documentation during in-hospital resuscitation. Resuscitation 2005, 65:285-290.
28. Ebell M.H., Becker L.A., Barry H.C., Hagen M. Survival after in-hospital cardiopulmonary resuscitation. A meta-analysis. J Gen Intern Med 1998, 13:805-816.
29. Malhotra S., Poole J., Davis H., et al. Effects of NOS3 Glu298Asp polymorphism on hemodynamic reactivity to stress: influences of ethnicity and obesity. Hypertension 2004, 44:866-871.
30. Zhu H., Wang X., Dong Y., Treiber F.A., Snieder H. Influence of the eNOS gene on development of blood pressure and left ventricular mass: longitudinal findings in multiethnic youth. Pharmacogenet Genom 2005, 15:669-675.
31. Ballew K.A., Philbrick J.T., Caven D.E., Schorling J.B. Predictors of survival following in-hospital cardiopulmonary resuscitation. A moving target. Arch Intern Med 1994, 154:2426-2432.
32. Borum M.L., Lynn J., Zhong Z. The effects of patient race on outcomes in seriously ill patients in SUPPORT: an overview of economic impact, medical intervention, and end-of-life decisions. Study to understand prognoses and preferences for outcomes and risks of treatments. J Am Geriatr Soc 2000, 48:S194-S198.
33. Greenlee R.T., Hill-Harmon M.B., Murray T., Thun M. Cancer statistics. CA Cancer J Clin 2001, 51:15-36.
34. Chandra K.M., Parish D.C., Dane F.C. Survival after the resuscitation. Arch Intern Med 2001, 161:1233-1234.
35. Rogers W.J., Canto J.G., Lambrew C.T., et al. Temporal trends in the treatment of over 1.5 million patients with myocardial infarction in the US from 1990 through 1999: the National Registry of Myocardial Infarction 1, 2 and 3. J Am Coll Cardiol 2000, 36:2056-2063.