Evidence map›Paper›PMID 42739273›Full record

ArticleDiagnostics (Basel, Switzerland)2026

Age, Sex, and Waist-to-Height Ratio Approach the Discrimination of Fifty-Four Model Inputs for Prevalent Hypertension: An Explainable Machine Learning Analysis of the Chilean National Health Survey.

Rodrigo Yáñez-Sepúlveda, Boryi A Becerra-Patiño, Felipe Montalva-Valenzuela, Rodrigo Olivares, Alejandra Uribe-Díaz, Eduardo Guzmán-Muñoz, Yeny Concha-Cisternas, Daniel Rojas-Valverde, José Francisco Tornero-Aguilera, Vicente Javier Clemente-Suárez and 1 more

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 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

11 authors.

Rodrigo Yáñez-SepúlvedaFaculty of Education and Humanities, Universidad Andrés Bello, Vina del Mar 2520000, Chile.ORCID 0000-0002-9311-6576
Boryi A Becerra-PatiñoFacultad de Educación Física, Universidad Pedagógica Nacional, Bogota 480100, Colombia.ORCID 0000-0002-9581-5071
Felipe Montalva-ValenzuelaEscuela de Entrenador en Actividad Física y Deporte, Facultad de Ciencias Humanas, Universidad Bernardo O'Higgins, Santiago 8370040, Chile.ORCID 0000-0003-0004-3089
Rodrigo OlivaresEscuela de Ingeniería Informática, Universidad de Valparaíso, Valparaiso 2340000, Chile.ORCID 0000-0003-0582-954X
Alejandra Uribe-DíazFaculty of Health Sciences, Universidad Tecnológica Atlántico Mediterráneo (UTAMED), 29590 Malaga, Spain.
Eduardo Guzmán-MuñozEscuela de Kinesiología, Facultad de Salud, Universidad Santo Tomás, Talca 3460000, Chile.ORCID 0000-0001-7001-9004
Yeny Concha-CisternasEscuela de Kinesiología, Facultad de Salud, Universidad Santo Tomás, Talca 3460000, Chile.ORCID 0000-0001-7013-3894
Daniel Rojas-ValverdeCentro de Investigación, Desarrollo e Innovación en Salud y Deporte (CIDISAD), Escuela Ciencias del Movimiento Humano y Calidad de Vida (CIEMHCAVI), Universidad Nacional de Costa Rica, Heredia 863000, Costa Rica.ORCID 0000-0002-0717-8827
José Francisco Tornero-AguileraDepartment of Sport Sciences, Faculty of Sport and Health Sciences, Fit Generation Research Institute, AD500 Andorra la Vella, Andorra.
Vicente Javier Clemente-SuárezDepartment of Sport Sciences, Faculty of Sport and Health Sciences, Fit Generation Research Institute, AD500 Andorra la Vella, Andorra.ORCID 0000-0002-2397-2801
José Francisco López-GilSchool of Medicine, Universidad Espíritu Santo, Samborondon 092301, Ecuador.ORCID 0000-0002-7412-7624

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Chilecomplex survey designexplainable artificial intelligencehealth surveyhypertensionmachine learningmodel parsimonyprediction modelSHapley Additive exPlanations

Identifiers

PMID42739273
PMCPMC13565000

What Socratic 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 Socratic graph.