Evidence map›Paper›PMID 42755914›Full record

ArticleFrontiers in endocrinology2026

Development and external validation of a risk prediction model for hypertension among individuals with established hypothyroidism.

Lan Lin, Liqing Chen, Kailing Yu, Qianwen Li, Junqian Huang, Ling Li, Yizhen Chen, Xiaoling Ke, Junping Wen, Jianbin You

Abstract readValidation Study
In one paragraph

Article in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Lan Lin *Center for Information Management, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China.
Liqing Chen *Department of Clinical Laboratory, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China.
Kailing YuCenter for Information Management, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China.
Qianwen LiCenter for Information Management, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China.
Junqian HuangCenter for Information Management, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China.
Ling LiDepartment of Clinical Laboratory, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China.
Yizhen ChenDepartment of Clinical Laboratory, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China.
Xiaoling KeDepartment of Clinical Laboratory, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China.
Junping WenShengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fujian Medical University, Fuzhou, China.
Jianbin YouDepartment of Clinical Laboratory, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hypothyroidism represents a multisystem endocrine disorder involving cardiovascular, renal, and metabolic alterations beyond thyroid hormone deficiency. However, validated tools for hypertension (HTN) risk stratification specifically designed for patients with hypothyroidism remain lacking. This study aimed to develop and externally validate a hypothyroidism-specific HTN prediction model incorporating routinely available clinical variables. Methods: This retrospective multicohort study included patients with hypothyroidism from a hospital-based cohort and an independent external population-based cohort. Eligible participants were identified according to predefined diagnostic criteria, and individuals with missing key clinical variables or incomplete outcome information were excluded. Candidate predictors were selected using regression-based approaches, and a multivariable prediction model was developed in the derivation cohort and subsequently evaluated in internal and external validation cohorts. An interpretable HTN risk profile was developed and evaluated using internal validation, external validation, and subgroup analyses. Results: Age, serum creatinine (SCr), anion gap (AG), and diabetes mellitus (DM) constituted a clinically interpretable risk profile reflecting vascular aging, renal vulnerability, and metabolic dysregulation. The model demonstrated robust discrimination, good calibration, and favorable clinical utility across training, testing, and external validation cohorts. Conclusions: A disease specific HTN risk profile was developed and externally validated in patients with hypothyroidism. This model provides a practical approach for individualized cardiovascular risk stratification and supports the application of precision endocrine medicine.

Indexed as

HypertensionHypothyroidismAgedFemaleHumansMaleMiddle AgedPrediction AlgorithmsRetrospective StudiesRisk AssessmentRisk Factorscardiovascular riskhypertensionhypothyroidismprecision endocrinologyprediction modelrisk stratification

Identifiers

PMID42755914
PMCPMC13581942

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.