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Record W4210385137 · doi:10.25176/rfmh.v22i1.4354

Lifestyle intervention for the management of chronic noncommunicable diseases: hypertension, dyslipidemia, insulin resistance and overweight in a male patient. Case Report

2021· article· en· W4210385137 on OpenAlexaff
Natalia Delorenzo

Bibliographic record

VenueRevista de la Facultad de Medicina Humana · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Lifestyle Studies
Canadian institutionsOntario Council of University Libraries
Fundersnot available
KeywordsMedicineDyslipidemiaOverweightDiabetes mellitusInsulin resistanceIntensive care medicineObesityIntervention (counseling)DiseasePediatricsInternal medicineEndocrinologyPsychiatry

Abstract

fetched live from OpenAlex

Chronic noncommunicable diseases (NCDs) are defined as diseases of long duration, slow progression, that do not resolve spontaneously and that rarely achieve complete cure (1). Cardiovascular diseases (CVD), cancer, chronic respiratory diseases and diabetes stand out. NCDs cause 41 million deaths each year (71% of the world total). Cardiovascular disease accounts for the majority of these deaths (17.9 million per year) (2). In addition to causing premature deaths, these diseases lead to complications and disabilities, limit productivity, and drug treatments are expensive, so early detection and timely treatment should be a priority (2). Lifestyle medicine (MEV) has gained relevance in the prevention, treatment and reversal of most NCDs, directly addressing their causes (3). We will present the case of a young man with multiple risk factors and a diagnosis of arterial hypertension, dyslipidemia and insulin resistance. We carry out an intervention through the MEV to improve the patient's condition and health. At the 6-month follow-up, significant changes in habits and laboratory parameters were achieved.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.390
Teacher spread0.359 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2021
Admission routes1
Has abstractyes

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