Literature DB >> 17699456

Predictors of survival after cardiac arrest in outpatient hemodialysis clinics.

Patrick H Pun1, Ruediger W Lehrich, Stephen R Smith, John P Middleton.   

Abstract

Cardiac arrest (CA) is the most common cause of death in hemodialysis patients, and factors that improve survival after arrest are unknown. This study sought to identify modifiable factors that are associated with survival after CA in hemodialysis clinics. Patients who experienced in-center CA in the Gambro Healthcare System in the United States from 2002 to 2005 were identified. Patient characteristics at the time of arrest were compared between survivors and nonsurvivors at 24 h and 6 mo after CA. A total of 729 patients sustained in-clinic CA; 310 (42.5%) patients survived 24 h, and 80 (11%) patients survived 6 mo. Traditional risk factors, including cardiovascular comorbidities, diabetes, hemoglobin, and dialysis adequacy, did not predict survival at either time point. After adjustment for case-mix factors, presence of indwelling catheter, and concomitant medications, only use of beta blockers (BBL), calcium-channel blockers (CCB), and angiotensin-converting enzyme inhibitors (ACEI) and angiotensin receptor blockers (ARB) remained significantly associated with survival (BBL odds ratio [OR] 0.32 [95% confidence interval (CI) 0.17 to 0.61]; CCB OR 0.42 [95% CI 0.23 to 0.76]; ACEI/ARB OR 0.51 [95% CI 0.28 to 0.95]). The beneficial effect of ACEI/ARB and BBL on survival increased sequentially with higher medication dosages. Prescription of BBL at the time of the event was the only predictive variable of survival at 24 h. Therefore, traditional cardiovascular risk factors were not associated with survival after CA in this hemodialysis cohort. The benefits that are associated with BBL, CCB, and ACEI/ARB suggest that these medications may improve the chances of survival after CA.

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Year:  2007        PMID: 17699456     DOI: 10.2215/CJN.02360706

Source DB:  PubMed          Journal:  Clin J Am Soc Nephrol        ISSN: 1555-9041            Impact factor:   8.237


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