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Record W2042415768 · doi:10.2310/7750.2006.00034

Minocycline- and Tetracycline-Induced Hypertriglyceridemia in an HIV-Seropositive Patient Receiving Combination Antiretroviral Therapy

2006· article· en· W2042415768 on OpenAlexaff
Najwa Somani, Gregory P. Bondy, Richard I. Crawford

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2006
Typearticle
Languageen
FieldMedicine
TopicAcne and Rosacea Treatments and Effects
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMinocyclineHypertriglyceridemiaMedicineTetracyclineAcneAntiretroviral therapyHuman immunodeficiency virus (HIV)DermatologyInternal medicineViral loadImmunologyAntibioticsCholesterolTriglyceride

Abstract

fetched live from OpenAlex

BACKGROUND: Acne vulgaris may occur as part of immune reconstitution in human immunodeficiency virus (HIV)-seropositive patients on highly active antiretroviral therapy (HAART). Tetracyclines are a common acne treatment. Hypertriglyceridemia has not been reported as a side effect of this drug class. OBJECTIVE: We report a case of an HIV-seropositive man on HAART (CD4 count 450 cells/microL) who developed isolated hypertriglyceridemia (> 13 mmol/L) after three separate challenges with minocycline or tetracycline, improving each time therapy was discontinued. RESULTS: Based on a review of the literature, this is the first reported case of hypertriglyceridemia with minocycline or tetracycline therapy. No published reports have examined the safety of tetracyclines in the setting of HIV or HAART. CONCLUSION: A strong temporal association between tetracycline use and hypertriglyceridemia was found without an alternate explanation for the observed lipid profile. Given the common use of tetracyclines in dermatology, we feel that this is an important observation to report.

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)0.000
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.002
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 head0.023
GPT teacher head0.282
Teacher spread0.259 · 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 designCase report
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

Citations0
Published2006
Admission routes1
Has abstractyes

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Same venueJournal of Cutaneous Medicine and SurgerySame topicAcne and Rosacea Treatments and EffectsFrench-language works237,207