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Record W4402234511 · doi:10.1080/17460913.2024.2391190

Combined bictegravir, emtricitabine and tenofovir alafenamide for treating people with HIV: a plain language summary of the BICSTaR study up to 1 year

2024· article· en· W4402234511 on OpenAlexaboutno aff
Stefan Eßer, Alexy Inciarte, Itzchak Levy, Antonella d’Arminio Monforte, John S. Lambert, Berend J. van Welzen, Katsuji Teruya, Marta Boffito, Chun-Eng Liu, Özlem Altuntaş Aydın, David Thorpe, Marion Heinzkill, Andrea Marongiu, Tali Cassidy, Richard Haubrich, Lisa D’Amato, Olivier Robineau

Bibliographic record

VenueFuture Microbiology · 2024
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsEmtricitabineTenofovir alafenamideHuman immunodeficiency virus (HIV)TenofovirMedicineVirologyAntiretroviral therapyViral load

Abstract

fetched live from OpenAlex

WHAT IS THIS SUMMARY ABOUT?: This is a summary of an article about an ongoing study called the BICSTaR study.The BICSTaR study includes people with HIV (human immunodeficiency virus) who are taking a medicine called bictegravir/emtricitabine/tenofovir alafenamide (shortened to B/F/TAF). B/F/TAF is a single tablet that contains 3 different drugs for the treatment of HIV. The drugs work together to reduce the levels of HIV so that the virus can no longer be detected by a blood test.People taking part in the study are adults with HIV living in Europe, Canada, Israel, Japan, South Korea, Singapore and Taiwan. People take 1 tablet of B/F/TAF once a day. They are either taking B/F/TAF as their first treatment for HIV, or they have switched to B/F/TAF from another HIV treatment.Researchers looked at how well B/F/TAF worked and how safe it was in people who took B/F/TAF for a year. WHAT ARE THE KEY TAKEAWAYS?: Researchers found that B/F/TAF worked well in almost all people in the study by reducing levels of HIV in the blood. The virus could not be found in the blood of more than 9 out of 10 (94%) people who were taking B/F/TAF as their first HIV medicine and more than 9 out of 10 people (97%) who had taken another HIV medicine before starting B/F/TAF. This is known as having an 'undetectable viral load' and is a major goal for HIV treatment success. Researchers did not find any evidence of HIV developing resistance to B/F/TAF, which might stop B/F/TAF from working properly.Around 1 out of 10 people (13%) had side effects (any unwanted sign or symptom that people have when taking a medicine that researchers think might be caused by the medicine) that might have been caused by B/F/TAF. Most of these side effects were not classified as serious. Less than 1 out of 100 (0.1%) people had serious side effects that might have been caused by B/F/TAF. Only 6 out of 100 people stopped taking B/F/TAF due to side effects caused by B/F/TAF. As a result, more than 9 out of 10 people (95%) took B/F/TAF for at least 1 year. WHAT WERE THE MAIN CONCLUSIONS REPORTED BY THE RESEARCHERS?: B/F/TAF worked well in people with HIV in this study. Most people (around 9 out of 10) did not have any side effects.

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)0.015
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0130.005

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 head0.004
GPT teacher head0.230
Teacher spread0.226 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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