THE ASSOCIATION BETWEEN RATIO OF RED BLOOD CELL DISTRIBUTION WIDTH TO ALBUMIN LEVEL AND RISK OF ALL-CAUSE MORTALITY IN PATIENTS WITH HYPERTENSION: EVIDENCE FROM NHANES 1999-2008

Objective: The ratio of red blood cell distribution (RDW) width to albumin concentration (RAR) has emerged as a reliable prognostic marker for mortality in patients with various diseases. This study aims to explore whether RAR is associated with all-cause mortality in patients with hypertension. Design and method: The study included patients aged over 20 years from the NHANES database between 1999 and 2008. Included participants had complete data on serum albumin concentration, RDW. The NHANES data were linked to the National Death Index records through December 31, 2019.Kaplan-Meier survival curves were used to describe the time distribution of mortality across different groups, and log-rank tests were applied to compare changes between groups. Univariate and multivariate Cox regression analyses were conducted to determine the association between RAR and all-cause mortality. Results: A total of 15941 patients were included,6834 patients are with hypertension (median [IQR] age 56 [45,68] years; 3410 [49.9%] female) and their median (IQR) RAR was 2.98 (2.77,3.21). The datebase documented 3748 deaths over a median (IQR) follow-up of 162(135,193) months. In hypertension cohort, according to the multivariate Cox regression, after adjusting for common traditional risk factors, elevated RAR was significantly associated with higher risk of all-cause mortality (HR, 1.97, 95% CI:1.77-2.21). Additionally, we categorized the RAR levels into 4 quartiles and examined the associations between RAR groups and the risk of mortality. Compared with participants in the lowest quartile of RAR, those in higher quartiles experienced greater all-cause mortality (quartile 2: HR: 1.25, 95% CI:1.08-1.45;quartile 3: HR: 1.51, 95% CI:1.32-1.74;quartile 4: HR: 2.43, 95%CI:2.12-2.78).Kaplan-Meier survival plots revealed that participants in the higher RAR quartiles had greater cumulative all-cause mortality than those in the lowest quartiles (log-rank P < 0.001). In non-hypertension cohort, the association is only significant in quartile 3 (HR:1.31, 95% CI:1.02-1.69) and quartile 4 (HR:1.93, 95% CI:1.57-2.38). Furthermore, a nonlinear association was observed between RAR levels and all-cause mortality in hypertension cohort. Conclusions: In patients with hypertension, a higher baseline RAR was associated with an increased risk of all-cause mortality. These findings holds significant potential for identifying individuals at high risk of mortality in clinical practice.

Authors

Institutions

Publication Details

Journal
Journal of Hypertension
Published
2025-05-01
DOI
https://doi.org/10.1097/01.hjh.0001117536.63285.94
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

THE ASSOCIATION BETWEEN RATIO OF RED BLOOD CELL DISTRIBUTION WIDTH TO ALBUMIN LEVEL AND RISK OF ALL-CAUSE MORTALITY IN PATIENTS WITH HYPERTENSION: EVIDENCE FROM NHANES 1999-2008

Yanjun Gong, Bo Zheng, Yu Zhan
Journal of Hypertension
Inflammatory Biomarkers in Disease Prognosis
article

THE ASSOCIATION BETWEEN RATIO OF RED BLOOD CELL DISTRIBUTION WIDTH TO ALBUMIN LEVEL AND RISK OF ALL-CAUSE MORTALITY IN PATIENTS WITH HYPERTENSION: EVIDENCE FROM NHANES 1999-2008

Yanjun Gong, Bo Zheng, Yu Zhan
article en

Abstract

Objective: The ratio of red blood cell distribution (RDW) width to albumin concentration (RAR) has emerged as a reliable prognostic marker for mortality in patients with various diseases. This study aims to explore whether RAR is associated with all-cause mortality in patients with hypertension. Design and method: The study included patients aged over 20 years from the NHANES database between 1999 and 2008. Included participants had complete data on serum albumin concentration, RDW. The NHANES data were linked to the National Death Index records through December 31, 2019.Kaplan-Meier survival curves were used to describe the time distribution of mortality across different groups, and log-rank tests were applied to compare changes between groups. Univariate and multivariate Cox regression analyses were conducted to determine the association between RAR and all-cause mortality. Results: A total of 15941 patients were included,6834 patients are with hypertension (median [IQR] age 56 [45,68] years; 3410 [49.9%] female) and their median (IQR) RAR was 2.98 (2.77,3.21). The datebase documented 3748 deaths over a median (IQR) follow-up of 162(135,193) months. In hypertension cohort, according to the multivariate Cox regression, after adjusting for common traditional risk factors, elevated RAR was significantly associated with higher risk of all-cause mortality (HR, 1.97, 95% CI:1.77-2.21). Additionally, we categorized the RAR levels into 4 quartiles and examined the associations between RAR groups and the risk of mortality. Compared with participants in the lowest quartile of RAR, those in higher quartiles experienced greater all-cause mortality (quartile 2: HR: 1.25, 95% CI:1.08-1.45;quartile 3: HR: 1.51, 95% CI:1.32-1.74;quartile 4: HR: 2.43, 95%CI:2.12-2.78).Kaplan-Meier survival plots revealed that participants in the higher RAR quartiles had greater cumulative all-cause mortality than those in the lowest quartiles (log-rank P < 0.001). In non-hypertension cohort, the association is only significant in quartile 3 (HR:1.31, 95% CI:1.02-1.69) and quartile 4 (HR:1.93, 95% CI:1.57-2.38). Furthermore, a nonlinear association was observed between RAR levels and all-cause mortality in hypertension cohort. Conclusions: In patients with hypertension, a higher baseline RAR was associated with an increased risk of all-cause mortality. These findings holds significant potential for identifying individuals at high risk of mortality in clinical practice.

Journal of HypertensionVol. 43(Suppl 1)
Peking University (CN), Peking University First Hospital (CN)
Good health and well-being
Openalex Percentile: Top 83%
Inflammatory Biomarkers in Disease Prognosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.