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Record W2085641279 · doi:10.12688/f1000research.5995.1

Association between obesity and depression in patients with diabetes mellitus type 2; a study protocol

2015· preprint· en· W2085641279 on OpenAlexaboutno aff
Eduardo De la Cruz-Cano, Carlos Alfonso Tovilla‐Zárate, Emilio Reyes-Ramos, Thelma Beatriz González‐Castro, Isela Juarez-Castro, María Lilia López‐Narváez, Ana Fresán

Bibliographic record

VenueF1000Research · 2015
Typepreprint
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsnot available
Fundersnot available
KeywordsType 2 Diabetes MellitusDiabetes mellitusObesityMedicineDepression (economics)Body mass indexIncidence (geometry)PsychiatryInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: Diabetes mellitus and depression are highly prevalent conditions throughout the world and have significant impact on health outcomes. It has been estimated that diabetes mellitus type 2 affects about 246 million people in the world; nevertheless, incidence varies among countries. There is evidence that depression is associated with a poor metabolic control in patients with type 2 diabetes mellitus that present other health problems (such as hypertension and obesity). The aim of this study protocol is to determine if obesity increases the risk for depression in patient with diabetes type 2. METHODS: The analysis will be reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).The studies suitable for inclusion will be assessed by the Newcastle-Ottawa Scale (NOS) to determine their methodological quality. To identify the studies of interest, we will search on PubMed and EBSCO databases. We will use the following keyword combinations: "Diabetes Mellitus type 2 AND obesity AND depression", "depression AND Diabetes Mellitus type 2", "Diabetes Mellitus type 2 AND body mass index cross sectional study", "depression AND obesity cross-sectional study". Causes for exclusion will be publications that studied patients diagnosed with diabetes mellitus type 1; articles that focused on the treatment and complications of diabetes mellitus type 2; publications that have studied other clinical or psychiatric conditions (for instance, seizure disorder or history of schizophrenia, bipolar disorder, psychotic symptoms or dementia). CONCLUSION: The results of this study will form the basis for a better understanding of the association between obesity and depression in patients with diabetes mellitus type 2, and will allow development of prediction tools and better interventions. It is evident that several modifiable and non-modifiable risk factors play an important role in the pathogenesis of diabetes among population. Currently, evidence for the deleterious effects of diabetes mellitus type 2 are based on cross-sectional or other observational designs. Therefore, this study will have important implications for future research and public health guidance.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.047
GPT teacher head0.373
Teacher spread0.326 · 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 designObservational
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

Citations12
Published2015
Admission routes1
Has abstractyes

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