Aim of the study: Most survivors of an in-hospital cardiac arrest do not leave the hospital alive, and there is a need for a more patient-centered, holistic approach to the assessment of prognosis after an arrest. We sought to identify pre-, peri-, and post-arrest variables associated with in-hospital mortality amongst survivors of an in-hospital cardiac arrest.

Methods: This was a retrospective cohort study of patients ≥18 years of age who were resuscitated from an in-hospital arrest at our University Medical Center from January 1, 2013 to September 31, 2016. In-hospital mortality was chosen as a primary outcome and unfavorable discharge disposition (discharge disposition other than home or skilled nursing facility) as a secondary outcome.

Results: 925 patients comprised the in-hospital arrest cohort with 305 patients failing to survive the arrest and a further 349 patients surviving the initial arrest but dying prior to hospital discharge, resulting in an overall survival of 29%. 620 patients with a ROSC of greater than 20 min following the in-hospital arrest were included in the final analysis. In a stepwise multivariable regression analysis, recurrent cardiac arrest, increasing age, time to ROSC, higher serum creatinine levels, and a history of cancer were predictors of in-hospital mortality. A history of hypertension was found to exert a protective effect on outcomes. In the regression model including serum lactate, increasing lactate levels were associated with lower odds of survival.

Conclusion: Amongst survivors of in-hospital cardiac arrest, recurrent cardiac arrest was the strongest predictor of poor outcomes with age, time to ROSC, pre-existing malignancy, and serum creatinine levels linked with increased odds of in-hospital mortality.

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Notes/Citation Information

Published in Resuscitation Plus, v. 4, 100039.

© 2020 The Authors

This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).

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Funding Information

The project described was supported by the University of Kentucky Center for Health Services Research Data, Analytics, and Statistical Core.

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