1Division of Cardiovascular Medicine, West Virginia University Heart and Vascular Institute, Morgantown, WV, USA

1Division of Cardiovascular Medicine, West Virginia University Heart and Vascular Institute, Morgantown, WV, USA

1Division of Cardiovascular Medicine, West Virginia University Heart and Vascular Institute, Morgantown, WV, USA

1Division of Cardiovascular Medicine, West Virginia University Heart and Vascular Institute, Morgantown, WV, USA

1Division of Cardiovascular Medicine, West Virginia University Heart and Vascular Institute, Morgantown, WV, USA

1Division of Cardiovascular Medicine, West Virginia University Heart and Vascular Institute, Morgantown, WV, USA

1Division of Cardiovascular Medicine, West Virginia University Heart and Vascular Institute, Morgantown, WV, USA

1Division of Cardiovascular Medicine, West Virginia University Heart and Vascular Institute, Morgantown, WV, USA

1Division of Cardiovascular Medicine, West Virginia University Heart and Vascular Institute, Morgantown, WV, USA

2Section of Electrophysiology, Division of Cardiovascular Medicine, Sulpizio Cardiovascular Center, University of California San Diego, 9452 Medical Center Dr., MC 7411, La Jolla, CA 92037, USA

The data that support the finding of this study are available from the corresponding author (MBM) upon reasonable request.

End-stage renal disease (ESRD) is a well-recognized risk factor for the development of sudden cardiac arrest (SCA). There is limited data on baseline characteristics and outcomes after an in-hospital SCA event in ESRD patients.

For the purpose of this study, data were obtained from the National Inpatient Sample from January 2007 to December 2017. In-hospital SCA was identified using the International Classification of Disease, 9th Revision, Clinical Modification and International Classification of Disease, 10th Revision, Clinical Modification codes of 99.60, 99.63, and 5A12012. ESRD patients were subsequently identified using codes of 585.6 and N18.6. Baseline characteristics and outcomes were compared among ESRD and non-ESRD patients in crude and propensity score (PS)–matched cohorts. Predictors of mortality in ESRD patients after an in-hospital SCA event were analyzed using a multivariate logistic regression model.

A total of 1,412,985 patients sustained in-hospital SCA during our study period. ESRD patients with in-hospital SCA were younger and had a higher burden of key co-morbidities. Mortality was similar in ESRD and non-ESRD patients in PS-matched cohort (70.4% vs. 70.7%, p = 0.45) with an overall downward trend over our study years. Advanced age, Black race, and key co-morbidities independently predicted increased mortality while prior implantable defibrillator was associated with decreased mortality in ESRD patients after an in-hospital SCA event.

In the context of in-hospital SCA, mortality is similar in ESRD and non-ESRD patients in adjusted analysis. Adequate risk factor modification could further mitigate the risk of in-hospital SCA among ESRD patients.

Sudden cardiac arrest (SCA) is a prevalent entity in patients with end-stage renal disease (ESRD) contributing to nearly one-quarter of deaths in this patient population [1]. The mortality rate after a SCA event exceeds 52% in ESRD patients [2]. ESRD patients are at risk of the development of SCA since majority of these patients have left ventricular hypertrophy (LVH) which provides an underlying substrate for SCA perpetuation in settings of rapid fluid and electrolyte fluctuations during dialysis sessions [3–6]. ESRD patients also require frequent hospitalizations due to associated co-morbid conditions [7]. Recent evidence points to improved outcomes in patients with in-hospital SCA over the past two decades [8]. Limited data, however, exist in the context of ESRD patients after in-hospital SCA, and whether these improved outcomes have also been witnessed in this patient population is currently unknown. In this paper, we aimed to study baseline characteristics, trends, and outcomes of ESRD patients after they sustained in-hospital SCA from a nationally representative contemporary cohort of US population.

Data from the National Inpatient Sample (NIS) were used for this study. NIS database has been made possible through sponsorship of the federal Agency for Healthcare Research and Quality (AHRQ). The main purpose of AHRQ is to enhance the quality, appropriateness, and effectiveness of health care services [9]. NIS is a publicly available all-payer administrative claims-based database. National estimates of the entire US hospitalized population were calculated using the Agency for Healthcare Research and Quality sampling and weighting method. Institutional review board approval was not required for this study, given the de-identified nature of the NIS and its public availability.

We analyzed the NIS data from January 2007 to December 2017 using the International Classification of Disease, 9th Revision, Clinical Modification (ICD-9-CM) and International Classification of Disease, 10th Revision, Clinical Modification (ICD-10-CM) codes. Patients who sustained in-hospital SCA were identified by applying ICD-9-CM and ICD-10-CM codes of 99.60, 99.63, and 5A12012, respectively, to any procedure field. These codes indicate utilization of cardiopulmonary resuscitation (CPR) and well representative of in-hospital SCA from administrative datasets as shown by the earlier studies [10–12]. ESRD patients were then subsequently identified using ICD-9-CM and ICD-10-CM codes of 585.6 and N18.6, respectively. Patients were excluded if they were less than 18 years of age or had acute kidney injury (AKI) and prior history of renal transplantation. Baseline characteristics and outcomes were compared in ESRD patients who sustained in-hospital SCA to non-ESRD patients with in-hospital SCA. Propensity score matching was also done to balance confounding variables, and outcomes were again assessed in both groups. Trends in in-patient mortality and length of stay (LOS) were also assessed. Predictors of in-patient mortality in ESRD patients after a SCA event were also analyzed.

Age, race, median income, urban/rural hospital, US region, and Elixhauser co-morbidities were selected for analysis. Descriptive statistics were presented as frequencies with percentages for categorical variables and as means with standard deviations or median with interquartile range as appropriate for continuous variables. Baseline characteristics were compared using Pearson’s chi-squared test for categorical variables and independent samples t test or non-parametric tests for continuous variables as appropriate. Median LOS, median cost of stay, and mortality were calculated. The median cost of stay was adjusted for inflation (in comparison to December 2017). Simple linear regression or chi-square test was used for trend analysis over the study years as appropriate. To mitigate the risk of confounding and selection bias, a nearest-neighbor 1:1 propensity score (PS) matching was done using a caliper width of 0.2. In this way, ESRD and non-ESRD patients were well matched with respect to demographic variables as shown in Table 1. Predictors of mortality in ESRD patients who sustained in-hospital SCA were analyzed using a logistic regression model. A forward stepwise entry model was used for this purpose. Initially, all variables, which were significantly associated with mortality with a p value of less than 0.05 in univariate analysis, were entered in the model from the baseline table. Subsequently, only those variables are retained in the model which were associated with mortality with a p value of less than 0.10 during forward entry. A type I error of less than 0.05 was considered statistically significant. All statistical analyses were performed using Statistical Package for the Social Sciences (SPSS) (version 26, IBM Corp) and R (version 3.5).

Unadjusted and adjusted baseline characteristics of the study population