Key result
Second income quartile linked to ~52% higher in-hospital mortality after leadless pacemaker implantation versus lowest.
Why the study?
The relationship between neighborhood income and in-hospital outcomes after leadless pacemaker implantation is not well characterized.
Does neighborhood income affect in-hospital outcomes after leadless pacemaker implantation in adults?
Observational (n=41,985)
Yes
Does neighborhood income affect in-hospital outcomes after leadless pacemaker implantation in adults?
Odds Ratio: 1.517 (95% CI 1.115–2.064)
p-value: p=0.008
Neighborhood income is associated with endpoint-specific in-hospital outcomes after leadless pacemaker implantation, highlighting socioeconomic disparities that may inform peri-procedural counseling.
May support incorporating neighborhood income into peri-procedural risk counseling; leaves open whether the association is causal or modifiable.
BACKGROUND: Leadless pacemakers (LPMs) avoid transvenous leads and subcutaneous pockets and can reduce lead- and pocket-related complications. Whether neighborhood income relates to in-hospital outcomes after LPM implantation is not well characterized. OBJECTIVE: To evaluate the association between ZIP-code-based median household income and in-hospital outcomes after LPM implantation in the United States. METHODS: Using the National Inpatient Sample (2018-2022), we identified adult LPM implantations and applied discharge weights to estimate national totals. Admissions were stratified by income quartile (Q1 lowest to Q4 highest). Multivariable logistic regression estimated adjusted odds ratios (aORs) for in-hospital mortality, pericardial complications, bleeding, transfusion, venous thromboembolism, renal complications, and device removal or revision, adjusting for demographics, comorbidities, payer, and hospital region. RESULTS: We identified 41,985 weighted admissions (8397 unweighted). Q1 patients were younger (median 77.0 vs. 81.0 years; p < 0.001) and had more diabetes (44.9% vs. 33.8%) and end-stage renal disease (43.4% vs. 36.6%). Crude mortality was highest in Q1 (4.7%). After adjustment, Q2 had higher odds of in-hospital death versus Q1 (aOR 1.517; 95% confidence interval [CI], 1.115 to 2.064; p = 0.008). Pericardial complications increased with income (Q1 3.2% vs. Q4 4.1%); Q4 had higher adjusted odds versus Q1 (aOR 1.753; 95% CI, 1.244 to 2.469; p = 0.001). Q4 had lower adjusted odds of bleeding (aOR 0.788; 95% CI, 0.633 to 0.982; p = 0.034) and transfusion (aOR 0.645; 95% CI, 0.494 to 0.842; p = 0.001). Venous thromboembolism was more likely in Q2 and Q4 versus Q1. Median hospital charges (billed amounts) were highest in Q4, while median length of stay was longer in Q1 (6.0 vs. 5.0 days; p < 0.001). CONCLUSIONS: Neighborhood income showed endpoint-specific associations with in-hospital outcomes after LPM implantation. These patterns may inform peri-procedural counseling and institutional review.
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Sagoo et al. (2026) conducted an observational in Leadless pacemaker implantation (n=41,985). Neighborhood income vs. Lowest income quartile (Q1) was evaluated on In-hospital mortality (aOR 1.517, 95% CI 1.115 to 2.064, p=0.008). Compared to the lowest income quartile, the second quartile had higher adjusted odds of in-hospital death after leadless pacemaker implantation (aOR 1.517; 95% CI 1.115-2.064; p=0.008).
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