Abstract
Objectives: To evaluate the association between early mechanical circulatory support (MCS) use and mortality in patients with cardiogenic shock (CS). Patients and Methods: We identified adults aged 18 years or older hospitalized from October 1, 2015, to June 30, 2023, with a diagnosis of CS. Patients receiving MCS within the first 2 days of admission were included in the study. Using inverse probability of treatment weighting, we assessed the association between receiving MCS on day 1 vs day 2 and in-hospital mortality. Results: Among 69,085 patients, 75.7% (n=52,307) and 24.3% (n=16,778) received MCS on day 1 and day 2, respectively. Devices included the intra-aortic balloon pump (62.9% [n=43,467]), percutaneous left ventricular assist device (25.0% [n=17,236]), and extracorporeal membrane oxygenation (22.0% [n=14,920]). The unadjusted mortality was 38.7% (n= 20,225 of 52,307) and 37.9% (n= 6,353 of 16,778) for MCS use on day 1 vs day 2, respectively (P=.06). After inverse probability of treatment weighting, MCS on day 1 was associated with a 7.4% (weighted mean; 95% CI, −8.4% to −6.4%; P<.001) reduction in mortality. Results persisted when each device was assessed separately and among patients presenting with acute myocardial infarction or heart failure as the shock etiology (all P<.001). When assessed by admission Society for Cardiovascular Angiography and Interventions shock stage, MCS on day 1 remained associated with lower mortality for each stage (stage C, −11.1%; 95% CI, −12.4 to −9.8%; stage D, −9.1%; 95% CI, −10.8% to −7.3%; stage E, −2.7%; 95% CI, −5.0% to −0.4%). Conclusion: For patients with CS, MCS on the first compared with the second day of admission was associated with a lower in-hospital mortality.
| Original language | English (US) |
|---|---|
| Journal | Mayo Clinic Proceedings |
| DOIs | |
| State | Accepted/In press - 2026 |
Bibliographical note
Publisher Copyright:© 2026 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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