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Record W6988100232

Weight and BMI Changes Following Initiation of Emtricitabine/Tenofovir Alafenamide Co-Formulated with Darunavir or Co-Administered with Dolutegravir in Overweight or Obese, ART-Naïve People Living with HIV-1

2023· other· en· W6988100232 on OpenAlexaboutno aff

Bibliographic record

VenueDove Medical Press (Taylor and Francis Group) · 2023
Typeother
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsnot available
FundersJanssen Scientific Affairs
KeywordsDolutegravirDarunavirBody mass indexIntegrase inhibitorOverweightIntegraseTenofovir alafenamidePropensity score matchingHuman immunodeficiency virus (HIV)
DOInot available

Abstract

fetched live from OpenAlex

Prina Donga,1 Bruno Emond,2 Carmine Rossi,2 Brahim K Bookhart,1 Johnnie Lee,1 Gabrielle Caron-Lapointe,2 Fangzhou Wei,3 Marie-Hélène Lafeuille2 1Janssen Scientific Affairs, LLC, Titusville, NJ, USA; 2Analysis Group, Inc, Montréal, QC, Canada; 3Analysis Group, Inc, Menlo Park, CA, USACorrespondence: Carmine Rossi, Analysis Group, Inc, 1190 Avenue des Canadiens-de-Montréal, Tour Deloitte, Suite 1500, Montréal, QC, H3B 0G7, Canada, Tel +1 514-871-4233, Email carmine.rossi@analysisgroup.comIntroduction: Integrase strand transfer inhibitor-based regimens (eg, containing dolutegravir [DTG]) are associated with weight/body mass index (BMI) increases among people living with HIV-1 (PLWH). Assessing antiretroviral therapy (ART)-related weight/BMI changes is challenging, as PLWH may experience return-to-health weight gain as a result of viral suppression. This retrospective, longitudinal real-world study compared weight/BMI outcomes among overweight/obese (BMI ≥ 25 kg/m2; thus excluding return-to-health weight/BMI changes), treatment-naïve PLWH who initiated darunavir (DRV)/cobicistat (c)/emtricitabine (FTC)/tenofovir alafenamide (TAF) or DTG + FTC/TAF.Methods: Treatment-naïve PLWH with BMI ≥ 25 kg/m2 who initiated DRV/c/FTC/TAF or DTG + FTC/TAF (index date) had ≥ 12 months of baseline observation and ≥ 1 weight/BMI measurement in baseline and post-index periods in the Symphony Health IDV® database (07/17/2017– 12/31/2021) were included. Inverse probability of treatment weighting (IPTW) was used to balance differences in baseline characteristics between cohorts. On-treatment time-to-weight/BMI increases ≥ 5% were compared between cohorts using weighted adjusted Cox models.Results: Post-IPTW, 76 overweight/obese DRV/c/FTC/TAF-treated (mean age = 51.2 years, 30.7% female, 35.6% Black, mean baseline BMI = 33.2 kg/m2) and 88 overweight/obese DTG + FTC/TAF-treated PLWH (mean age = 51.5 years, 31.4% female, 31.4% Black, mean baseline BMI = 32.7 kg/m2) were included. The median [interquartile range] time from ART initiation to weight/BMI increase ≥ 5% was shorter for the DTG + FTC/TAF cohort (21.8 [9.9, 32.3] months) than the DRV/c/FTC/TAF cohort (median and interquartile times not reached; Kaplan–Meier rate at 21.8 months = 20.8%). Over the entire follow-up, overweight/obese PLWH initiating DTG + FTC/TAF had a more than twofold greater risk of experiencing weight/BMI increase ≥ 5% compared to those initiating DRV/c/FTC/TAF (hazard ratio [95% confidence interval]=2.43 [1.02; 7.04]; p = 0.036).Conclusion: Overweight/obese PLWH who initiated DTG + FTC/TAF had significantly greater risk of weight/BMI increase ≥ 5% compared to similar PLWH who initiated DRV/c/FTC/TAF and had shorter time-to-weight/BMI increase ≥ 5%, suggesting a need for additional monitoring to assess the risk of weight gain-related cardiometabolic disease.Keywords: human immunodeficiency virus, weight gain, BMI, darunavir, dolutegravir, observational study

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.310
Teacher spread0.281 · 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 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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