Evidence map›Paper›PMID 40786258›Full record

ArticleCureus2025

Impact of Hospital Volume on In-Hospital Cardiac Arrest Mortality: Trends Before and During the COVID-19 Pandemic.

Chau Doan Nguyen, Viet Nghi Tran, Sayma Yaqub, Huan Dat Pham, Thien Vo

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In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Chau Doan NguyenInternal Medicine, Texas Tech University Health Sciences Center, Amarillo, USA.
Viet Nghi TranInternal Medicine, Weiss Memorial Hospital, Chicago, USA.
Sayma YaqubInternal Medicine, Texas Tech University Health Sciences Center, Amarillo, USA.
Huan Dat PhamInternal Medicine, Conemaugh Memorial Medical Center, Johnstown, USA.
Thien VoPulmonology and Critical Care, Texas Tech University Health Sciences Center, Amarillo, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Hospital volume is frequently associated with clinical outcomes in patients with critical illnesses. This study aims to evaluate the impact of hospital volume on in-hospital mortality among patients with in-hospital cardiac arrest (IHCA) during the pre-pandemic period (2017-2019) and the COVID-19 pandemic era (2020-2021), using data from the Nationwide Inpatient Sample (NIS) database. Methods We conducted a retrospective analysis of 304,030 IHCA admissions (2017-2019) and 287,695 admissions (2020-2021) using the NIS database. Hospitals were categorized by annual IHCA volume into three groups: low (≤33rd percentile), medium (33rd-67th percentile), and high (≥67th percentile). Survey-weighted logistic regression was used to assess the association between hospital volume and in-hospital mortality, adjusting for demographics, comorbidities, hospital characteristics, and the Elixhauser index. Propensity score matching was used for pairwise comparisons across volume groups. Results During the pre-pandemic period (2017-2019), high-volume hospitals were associated with significantly higher in-hospital mortality than medium-volume hospitals before propensity score matching (adjusted odds ratio (OR): 1.100; 95% CI: 1.035-1.169; p = 0.02). After matching, this association persisted, with high-volume centers showing a modest but statistically significant increase in mortality (OR: 1.075; 95% CI: 1.001-1.154; p = 0.046). In the pandemic period (2020-2021), high-volume hospitals remained associated with higher IHCA mortality, with significantly elevated odds of death compared to both low-volume (OR: 1.239; 95% CI: 1.101-1.394; p < 0.001) and medium-volume hospitals (OR: 1.115; 95% CI: 1.026-1.211; p = 0.01) after matching. When stratified by COVID-19 status, high-volume hospitals in the non-COVID-19 subgroup continued to show significantly higher mortality rates than medium-volume hospitals after adjustment and matching (OR: 1.097; 95% CI: 1.009-1.192; p = 0.003). However, among COVID-19-positive patients, no statistically significant associations were found between hospital volume and in-hospital mortality after matching (medium vs. low: OR 1.125; 95% CI: 0.856-1.480; p=0.398; high vs. low: OR 1.387; 95% CI: 0.942-2.042; p = 0.098; high vs. medium: OR 1.116; 95% CI: 0.883-1.411; p=0.357). Conclusion Hospital volume was associated with in-hospital mortality, varying by pandemic period and patient subgroup. Before the pandemic, high-volume hospitals had a modestly higher mortality rate, a pattern that persisted among non-COVID-19 patients during the pandemic. No significant association emerged for COVID-positive patients, suggesting that system-level strain, rather than viral effects, was the primary driver. These findings highlight the need for surge-adaptive protocols to maintain IHCA care quality during periods of operational stress.

Indexed as

covid-19 pandemichospital volumein-hospital cardiac arrestmortality outcomespropensity score matching

Identifiers

PMID40786258
PMCPMC12335881

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.