Predictive Value of Lymphocyte-to-Monocyte Ratio in Patients with Atrial Fibrillation: A Propensity Score Matching Analysis
Year: 2021
Type: preprint
Study design: Observational Study
Abstract: Background Inflammation plays a key role in the initiation and progression of atrial fibrillation (AF). Lymphocyte-to-monocyte ratio (LMR) has been proved to be a reliable predictor of many inflammation-associated diseases, but little data are available on the relationship between LMR and AF. The present study aimed to evaluate the predictive value of LMR in predicting all-cause mortality among AF patients. Methods Data of patients diagnosed with AF were retrieved from the Medical Information Mart for Intensive Care-III (MIMIC-III) database. X-tile analysis was used to calculate the optimal cutoff value for LMR. The Cox proportional-hazards regression model was used to assess the association of LMR and 28-day, 90-day and 1-year mortality. Additionally, a propensity score matching (PSM) method was performed to minimize the impact of potential confounders. Results A total of 3,567 patients hospitalized with AF were enrolled in this study. The X-tile software indicated that the optimal cutoff value of LMR was 2.67. A total of 1,127 pairs were generated and all the covariates were well balanced after PSM. The Cox proportional-hazards model showed that patients with the low LMR (≤ 2.67) had a higher 1-year all-cause mortality than those with the high LMR (> 2.67) in the study cohort before PSM (HR = 1.640, 95% CI: 1.437–1.872, P < 0.001) and after PSM (HR = 1.279, 95% CI: 1.094–1.495, P = 0.002). The multivariable Cox regression analysis for 28-day and 90-day mortality yielded similar results. Conclusions The lower LMR (≤ 2.67) was associated with a higher risk of 28-day, 90-day, and 1-year all-cause mortality, which might serve as an independent prognostic predictor in AF patients.
Source: Research Square
Institutions: Shanghai Jiao Tong University, Ruijin Hospital, Tongji University
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W4200620469
