ArticleFrontiers in endocrinology2025
Non-HDL-C/HDL-C Ratio and N-Terminal Pro-B-Type Natriuretic Peptide in the general and hospital-based population: a cross-sectional validation study.
Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: As an innovative composite lipid assessment index, the Non-HDL-C/HDL-C Ratio (NHHR) offers a more holistic appraisal of lipid metabolic profile. This investigation seeks to elucidate the association between NHHR and elevated N-Terminal Pro-B-Type Natriuretic Peptide (NT-proBNP) levels in the general and hospital-based population. Methods: The research participants were drawn from the National Health and Nutrition Examination Survey (NHANES, 1999-2004, Group 1) and from hospital inpatients within the Cardiology Department of Jiangsu Province Traditional Chinese Medicine Hospital (JSHTCM, January to June 2025, Group 2). We preliminarily evaluated and adjusted for the original prevalence and age-standardized prevalence of NT-proBNP elevation in different populations. A stepwise inference generalized linear modeling approach was employed to explore the association between NHHR and NT-proBNP elevation, with a restrictive cubic spline (RCS) used to visualize the simulations, evaluated correlation trends through trend tests, observed inter-group differences through subgroup analyses, assessed overall population results robustness through interaction tests. Additionally, based on the non-linear associations, we further refined the analysis through threshold and saturation effects, as well as piecewise regression analysis. Results: In Group 1, females exhibited a higher age-standardized prevalence of NT-proBNP elevation than males (20.51% vs. 10.74%), which declined progressively as NHHR levels increased. Generalized linear models demonstrated a notable inverse link between NHHR and NT-proBNP elevation in both groups, and the results of the RCS plots are largely consistent with the findings from the generalized linear models. Additionally, further threshold and saturation effects analysis identified 4.3 as the NHHR inflection point in Group 1. Piecewise regression analysis indicated that below this threshold, higher NHHR corresponded to a reduced likelihood of NT-proBNP elevation. Specifically, for each standard unit increase in NHHR, the probability of elevated NT-proBNP decreased by 24% [HR (95% CI): 0.76 (0.68, 0.86), Conclusions: In the general and hospital-based population, a negative correlation was identified between the increase in NHHR and NT-proBNP elevation levels, corroborating the utility of NHHR as a simple composite lipid index for identifying changes in NT-proBNP.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.