Evidence map›Paper›PMID 42220852›Full record

ArticleCureus2026

Predictors of Pacemaker Implantation Among Patients Hospitalized With Syncope: An Analysis of the National Inpatient Sample (2016-2020).

Emmanuel Kokori, Samuel Osei, Nirajan Kandel, Zuhaib Khokar, Abdullah Ahmad, Muhammad Daniyal, Syed Hasham Ali

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Article in Cureus, 2026. 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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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

7 authors.

Emmanuel KokoriDepartment of Internal Medicine, Cape Fear Valley Health, Fayetteville, USA.
Samuel OseiDepartment of Internal Medicine, Cape Fear Valley Health, Fayetteville, USA.
Nirajan KandelDepartment of Internal Medicine, Cape Fear Valley Health, Fayetteville, USA.
Zuhaib KhokarDepartment of Internal Medicine, Cape Fear Valley Health, Fayetteville, USA.
Abdullah AhmadDepartment of Internal Medicine, Hameed Latif Teaching Hospital, Lahore, PAK.
Muhammad DaniyalDepartment of Internal Medicine, Montefiore Medical Center, Bronx, USA.
Syed Hasham AliDepartment of Internal Medicine, Dow Medical College, Karachi, PAK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSyncope is a frequent cause of hospitalization with etiologies ranging from benign to life-threatening. Identifying which patients will ultimately require permanent pacemaker implantation (PPI) remains a clinical challenge. We aimed to characterize the independent predictors of PPI using a nationally representative inpatient dataset to optimize clinical risk stratification and guide targeted diagnostic workups.

methodsWe analyzed the National Inpatient Sample (NIS) from 2016 to 2020, identifying adult patients hospitalized with a primary diagnosis of syncope (ICD-10-CM: R55). PPI was identified using ICD-10-PCS codes (0JH604Z, 0JH606Z, 0JH605Z). Univariate and multivariate logistic regression were performed to identify independent predictors of PPI, adjusting for patient demographics, hospital characteristics, and clinical comorbidities. Survey weights were applied throughout to generate nationally representative estimates.

resultsOf 2,046,185 weighted syncope hospitalizations, 50,060 (2.4%) underwent PPI. Conduction disorders were the strongest independent predictor (adjusted odds ratio (aOR) 14.82; 95% CI 14.53-15.11), followed by age ≥65 years (aOR 4.10), atrial fibrillation (aOR 1.78), obesity (aOR 1.17), and hypertension (aOR 1.10). Factors such as Black race, Hispanic ethnicity, and Medicaid or self-pay status were associated with lower odds of PPI. Additionally, comorbid sepsis, malignancy, electrolyte imbalance, history of prior stroke, anemia, and chronic pulmonary disease were also independently associated with lower odds of PPI. Notably, diabetes mellitus (DM), congestive heart failure (CHF), chronic kidney disease (CKD), and coronary artery disease (CAD), each positive on univariate analysis, became significant negative predictors after multivariate adjustment.

conclusionsConduction abnormalities and older age above 65 years remain the dominant drivers of PPI in hospitalized syncope patients. The reversal of several common comorbidities to negative predictors after adjustment suggests they signal non-bradycardic etiologies and should prompt a more comprehensive evaluation before pacing is pursued. Significant racial and socioeconomic disparities in PPI highlight the need for targeted quality and equity initiatives.

Indexed as

bradyarrhythmiacardiac conduction defectsnational inpatient sample (nis)pacemakersyncope

Identifiers

PMID42220852
PMCPMC13218641

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