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Record W2598828884 · doi:10.1155/2017/1613657

Metabolic Syndrome in People Living with Human Immunodeficiency Virus: An Assessment of the Prevalence and the Agreement between Diagnostic Criteria

2017· article· en· W2598828884 on OpenAlexafffund
Kim Nguyen, Nasheeta Peer, Anniza de Villiers, Barbara Mukasa, Edward J. Mills, André Pascal Kengne

Bibliographic record

VenueInternational Journal of Endocrinology · 2017
Typearticle
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsCentre for Advancing Health Outcomes
FundersUniversity of Cape TownGrand Challenges CanadaCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsMedicineAlgorithmHuman immunodeficiency virus (HIV)Internal medicineMachine learningMathematicsFamily medicineComputer science

Abstract

fetched live from OpenAlex

Objectives. We determined metabolic syndrome (MetS) prevalence and assessed the agreement between different diagnostic criteria in HIV-infected South Africans. Method . A random sample included 748 HIV-infected adult patients (79% women) across 17 HIV healthcare facilities in the Western Cape Province. MetS was defined using the Joint Interim Statement (JIS 2009), International Diabetes Federation (IDF 2005), and Adult Treatment Panel III (ATPIII 2005) criteria. Results . Median values were 38 years (age), 5 years (diagnosed HIV duration), and 392 cells/mm 3 (CD4 count), and 93% of the participants were on antiretroviral therapy (ART). MetS prevalence was 28.2% (95%CI: 25–31.4), 26.5% (23.3–29.6), and 24.1% (21–27.1) by the JIS, IDF, and ATPIII 2005 criteria, respectively. Prevalence was always higher in women than in men (all <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn>0.001</mml:mn></mml:math>), in participants with longer duration of diagnosed HIV (all <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mi>p</mml:mi><mml:mo>≤</mml:mo><mml:mn>0.003</mml:mn></mml:math>), and in ART users not receiving 1st-line regimens (all <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mi>p</mml:mi><mml:mo>≤</mml:mo><mml:mn>0.039</mml:mn></mml:math>). The agreement among the three criteria was very good overall and in most subgroups (all <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M4"><mml:mi mathvariant="normal">k</mml:mi><mml:mi mathvariant="normal">a</mml:mi><mml:mi mathvariant="normal">p</mml:mi><mml:mi mathvariant="normal">p</mml:mi><mml:mi mathvariant="normal">a</mml:mi><mml:mo>≥</mml:mo><mml:mn>0.81</mml:mn></mml:math>). Conclusions . The three most popular diagnostic criteria yielded similarly high MetS prevalence in this relatively young population receiving care for HIV infection. Very good levels of agreement between criteria are unaffected by some HIV-specific features highlighting the likely comparable diagnostic utility of those criteria in routine HIV care settings.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004
Threshold uncertainty score0.164

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.393
Teacher spread0.367 · 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

Citations26
Published2017
Admission routes2
Has abstractyes

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