The Impact of Calcium on in-Hospital Cardiac Arrest

Document Type

Conference Proceeding

Publication Date

3-6-2026

Publication Title

Am J Health Syst Pharm

Keywords

calcium, hypertensive factor, sodium chloride, chi square distribution, cohort analysis, conference abstract, data analysis software, heart arrest, human, hypercalcemia, intensive care unit, length of stay, major clinical study, mortality, multicenter study, out of hospital cardiac arrest, propensity score, resuscitation, retrospective study, Sequential Organ Failure Assessment Score, survival rate, treatment outcome

Abstract

Purpose: In-hospital cardiac arrest (IHCA) is a critical event associated with high rates of mortality, with survival rates to discharge remaining poor. The role of intravenous push (IVP) calcium during resuscitation has evolved over time, and although its use has become increasingly common, high-quality evidence related to this practice is lacking. This multicenter, retrospective cohort study will evaluate the impact of calcium administration on patient outcomes post IHCA across 16 hospitals. Methods: The primary outcome will be sustained ROSC after cardiac arrest, defined as no chest compressions for ≥20 minutes. Secondary outcomes include time to ROSC, mortality, post-arrest SOFA score, vasopressor-free days, ICU length of stay, calcium-related adverse events (hypercalcemia or extravasation), and neurologic outcomes at discharge versus admission. Neurologic outcomes will be assessed by CPC, with CPC 1–2 classified as favorable and CPC 3–5 as unfavorable. In-hospital mortality will be defined as death or hospice admission before discharge or within 30 days of admission. Based on Vallentin et al., sustained ROSC occurred in 19% of calcium-treated versus 27% of saline-treated OHCA patients. To detect a 9% difference with 80% power and α=0.05, 838 patients (434/group) are required. Descriptive statistics will summarize populations. Continuous data will be analyzed with t-tests or Wilcoxon rank-sum tests; categorical data with chi-square tests. Kaplan-Meier and log-rank tests will assess time-to-event data. IPTW will adjust for treatment selection using logistic regression–derived propensity scores. Covariate balance will be evaluated with standardized differences (< 0.1 acceptable). Analyses will be performed in SPSS v.29 and SAS v.9.4, with p< 0.05 significant.

Volume

83

Issue

Supplement_2

First Page

S800

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