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Record W3092046481 · doi:10.1097/qad.0000000000002725

Changes in weight and BMI with first-line doravirine-based therapy

2020· article· en· W3092046481 on OpenAlexaff
Chloe Orkin, Richard Elion, Melanie Thompson, Juergen Rockstroh, Fernando Alvarez Bognar, Zhi Jin Xu, Carey Hwang, Peter Sklar, Elizabeth A. Martin

Bibliographic record

VenueAIDS · 2020
Typearticle
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsGlobal Affairs Canada
Fundersnot available
KeywordsMedicineInternal medicineOncology

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate changes in weight and BMI in adults with HIV-1 at 1 and 2 years after starting an antiretroviral regimen that included doravirine, ritonavir-boosted darunavir, or efavirenz. DESIGN: Post-hoc analysis of pooled data from three randomized controlled trials. METHODS: We evaluated weight change from baseline, weight gain at least 10%, and increase in BMI after 48 and 96 weeks of treatment with doravirine, ritonavir-boosted darunavir, or efavirenz-based regimens. Risk factors for weight gain and metabolic outcomes associated with weight gain were also examined. RESULTS: Mean (and median) weight changes were similar for doravirine [1.7 (1.0) kg] and ritonavir-boosted darunavir [1.4 (0.6) kg] and were lower for efavirenz [0.6 (0.0) kg] at week 48 but were similar across all treatment groups at week 96 [2.4 (1.5), 1.8 (0.7), and 1.6 (1.0) kg, respectively]. No significant differences between treatment groups were found in the proportion of participants with at least 10% weight gain or the proportion with BMI class increase at either time point. Low CD4 T-cell count and high HIV-1 RNA at baseline were associated with at least 10% weight gain and BMI class increase at both timepoints, but treatment group, age, sex, and race were not. CONCLUSION: Weight gains over 96 weeks were low in all treatment groups and were similar to the average yearly change in adults without HIV-1. Significant weight gain and BMI class increase were similar across the treatment groups and were predicted by low baseline CD4 T-cell count and high baseline HIV-1 RNA.

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 score0.128
Threshold uncertainty score0.205

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 head0.032
GPT teacher head0.295
Teacher spread0.263 · 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

Citations44
Published2020
Admission routes1
Has abstractyes

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