Conflict-Adapted Hematological Thresholds for Cardiovascular Risk Prediction in Yemen and High-Malnutrition Settings: A Global Meta-Analysis

Naif Taleb Ali¹,², Radfan Saleh Abdullah¹,²

Keywords: Cardiovascular diseases, global health, resource-limited settings, conflict zones, neutrophil-lymphocyte ratio, health equity, sustainable development goals

DOI: 10.63475/yjm.v4i2.0182

DOI URL: https://doi.org/10.63475/yjm.v4i2.0182

Publish Date: 22-09-2025

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Pages: 436 - 453

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Author Affiliation:

1 Assistant Professor, Department of Medical Laboratory, Radfan University College, University of Lahej, Alhouta, Yemen
2 Assistant Professor, Department of Health Sciences, Faculty of Medicine and Health Sciences, University of Science and Technology, Aden, Yemen

Abstract

Background: Cardiovascular diseases (CVDs) disproportionately affect conflict zones like Yemen, where diagnostic limitations persist. This meta-analysis evaluated the global prognostic utility of the red cell distribution width (RDW) and the neutrophil-to-lymphocyte ratio (NLR) as predictors of CVD and aimed to establish region-specific thresholds for low-resource settings.

Methods: Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and MOOSE (Meta-analysis Of Observational Studies in Epidemiology) guidelines, we analyzed 75 prospective cohort studies (2014–2025) that included 201,604 adults from 142 countries. Random-effects models were used to pool hazard ratios (HRs) and the area under the curve (AUC).

Results: NLR > 3.0 (HR, 2.2 [95% CI, 1.8–2.7]) independently predicted an elevated CVD risk (p < 0.001). While RDW > 14% was associated with increased CVD risk in unadjusted analyses (HR, 2.3 [95% CI, 1.9–2.8]), this association became non-significant after adjusting for ferritin (HR, 1.02 [95% CI, 0.98–1.07]). This indicates that RDW primarily reflects iron status, emphasizing the need to measure ferritin before attributing high RDW to CVD risk. The combined RDW + NLR showed superior discriminative power (AUC, 0.82 vs. 0.71–0.74 for individual markers). Subgroup analyses revealed higher NLR cutoffs (>3.8) in HIV-endemic African populations (reflecting chronic immune activation). Sensitivity analyses revealed attenuated NLR effects in rural populations (HR, 1.9) and non-significant RDW-CVD associations when adjusting for ferritin (HR, 1.02), highlighting contextual limitations.

Conclusions: While NLR stands as an independent CVD predictor, RDW > 14% must be interpreted with concurrent ferritin measurement. This is crucial to avoid misattributing CVD risk in malnutrition-endemic regions, such as Yemen, where an RDW > 15% is common. The RDW primarily reflects iron status and requires iron-status validation, especially in these high-malnutrition areas. However, caution is warranted when generalizing findings to rural settings where the CVD burden is rising fastest, given the underrepresentation of rural populations (only 16% of included studies). We strongly recommend standardized automated hematology analyzers (k > 0.85).

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