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Record W4409448695 · doi:10.2196/72513

Effect of a Mediterranean Diet Adapted to the Mexican Population on Indicators of Metabolic Risk in Patients With Obstructive Sleep Apnea: Protocol for a Randomized Controlled Trial

2025· article· en· W4409448695 on OpenAlexvenueno aff
Gittaim Pammela Torres San Miguel, María de la Luz Sevilla-González, Evelyn Ramirez, Lubia Velázquez–López

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsnot available
Fundersnot available
KeywordsPreprintObstructive sleep apneaRandomized controlled trialMedicineMediterranean dietPopulationSleep apneaPhysical therapyGerontologyEnvironmental healthInternal medicineComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Obstructive sleep apnea (OSA) is characterized by episodes of intermittent airway obstruction during deep sleep or REM (rapid eye movement). It is associated with cardiometabolic risk diseases. The base treatment is continuous positive airway pressure (CPAP), to which not all patients are able to adapt. The Mediterranean diet (MD) has proven to be effective in reducing cardiovascular risk markers; however, it must be adapted to different populations. Among patients with OSA, it can effectively reduce clinical entity and cardiometabolic risk, while improving quality of life and sleep. OBJECTIVE: We aimed to evaluate the effect of an MD adapted to the Mexican diet versus a standard nutritional treatment on metabolic risk indicators in patients with OSA. METHODS: A randomized, 2-arm clinical trial will be conducted with patients with OSA from the Hospital, Mexican Social Security Institute (Instituto Mexicano del Seguro Social) in Mexico. Patients will be randomly included in the group with MD adapted to Mexican foods. With a personalized diet plan adapted from the Mediterranean diet, prototype menus with Mexican foods adapted from the MD will be included for a higher consumption of fruit, vegetables, fiber-rich cereals, and reduction of red meat. In addition to an illustrative plate to improve adherence. The standard diet (SD) group will receive standardized nutritional counseling for patients with OSA. Fasting blood samples will be drawn after 6 and 12 months to identify glucose levels and lipid profiles. Anthropometric and body composition measurements will be taken, and adherence to diet will be recorded after 3, 6, and 12 months. Sleep quality, physical exercise, and life quality will be recorded basally and after 12 months. A multivariate logistic regression analysis will be performed, including the achievement of metabolic indicator control goals, sleep quality, and quality of life as outcome variables. This analysis will be adjusted for other variables that may be statistically significant in the bivariate analysis, such as sex, age, and comorbidities, among others. Statistically significant differences between groups will be considered when the value of P<.05. RESULTS: The protocol was authorized in 2024, and funding is being sought for patient follow-up. All 120 patients (60 per group) will be included in 2025; recruitment will begin in March 2025. The clinical trial is expected to be completed in April 2026. CONCLUSIONS: The results of this study will contribute to evaluate the effect of a nutritional intervention adapted to patients with OSA, seeking to reduce cardiovascular risk indicators in patients, improve their clinical condition, reduce OSA symptoms, and improve patients' quality of life. TRIAL REGISTRATION: ClinicalTrials.gov NCT06278571; https://clinicaltrials.gov/study/NCT06278571. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/72513.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.040
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.014
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0130.007
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0400.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.461
Teacher spread0.424 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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