Evidence map›Paper›PMID 42139150›Full record

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Association between blood inflammatory biomarkers and mortality in individuals with self-reported obstructive sleep apnea symptoms: A nationwide population-based retrospective cohort study.

Anyuan Zhong, Yongjian Pei, Zengli Zhang, Rui Chen

Abstract read
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Article in Science progress. 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

4 authors.

Anyuan ZhongDepartment of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Soochow University, Suzhou, China.ORCID 0000-0003-0493-0064
Yongjian PeiDepartment of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Zengli ZhangDepartment of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Rui ChenDepartment of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Soochow University, Suzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ObjectiveTo investigate the associations of blood inflammatory biomarkers with all-cause and cardiovascular disease (CVD) mortality in individuals with self-reported obstructive sleep apnea (OSA) symptoms.MethodsThis retrospective cohort study included 10,230 adults aged ≥18 years with self-reported OSA symptoms from the NHANES database.Participants were followed from baseline through December 31, 2019. Kaplan-Meier analysis, multivariable Cox proportional hazards models, restricted cubic spline (RCS), segmented regression and sensitivity analyses were employed to evaluate the associations of inflammatory biomarkers, including red blood cell distribution width (RDW), RDW-to-albumin ratio (RAR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) with all-cause and CVD mortality.ResultsKaplan-Meier analysis showed that survival rates were significantly lower among individuals with self-reported OSA symptoms who had the highest levels of RDW, RAR, NLR, and MLR. In the fully adjusted Cox model, the highest quartile (Q4) of these biomarkers was associated with significantly increased risks of all-cause mortality compared with the lowest quartile (Q1): RDW (HR=3.70; 95% CI:2.14-6.42), RAR (HR=2.93; 95% CI:2.20-3.91), NLR (HR=1.65; 95% CI: 1.32-2.07), and MLR (HR=1.68; 95% CI:1.22-2.31). For CVD mortality, the corresponding HRs (Q4 vs. Q1) were: RDW (HR=3.07; 95% CI:1.61-5.85), RAR (HR=2.99; 95% CI:1.57-5.68), NLR (HR=2.66; 95% CI:1.51-4.68), and MLR (HR=1.87; 95% CI:1.07-3.29). RCS model demonstrated that there was a nonlinear association between RDW, RAR, NLR and the both mortality endpoints, while MLR did not show a significant nonlinear relationship with mortality. Segmented regression further identified data-driven statistical thresholds. These exploratory, data-driven thresholds have not been clinically validated and should not be directly applied to clinical decision-making. Sensitivity analyses yielded consistent results.ConclusionsBlood inflammatory biomarkers (RDW, RAR, NLR, MLR) are significantly associated with all-cause and CVD mortality in individuals with self-reported OSA symptoms. Given the observational design, these biomarkers should be regarded as associative rather than prognostic, pending future confirmation.

Indexed as

Cardiovascular DiseasesInflammationSleep Apnea, ObstructiveBiomarkersErythrocyte IndicesFemaleHumansMaleMiddle AgedNutrition SurveysRetrospective StudiesRiskSelf ReportSurvival RateBiomarkersinflammatory biomarkersmortalityNHANESpopulation-basedself-reported OSA symptoms

Identifiers

PMID42139150
PMCPMC13180234

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.