Bibliographic record
Abstract
La troglitazone est capable de favoriser la differenciation adipocytaire in vitro et d'augmenter la sensibilite a l'insuline in vivo. La troglitazone pourrait donc etre interessante chez les patients presentant un diabete lipoatrophique, cette forme exceptionnelle de diabete marquee par des troubles de la repartition des graisses et une insulinoresistance majeure. Dans une etude prospective ouverte menee aux Etats-Unis et au Canada, 20 patients presentant differents syndromes associant une lipoatrophie, une lipodystrophie et un diabete, ont ete traites pendant 6 mois avec 200 a 600 mg par jour de troglitazone. Chez les 13 patients diabetiques, l'hemoglobine A1c a diminue en moyenne de 2,8 %. Chez 19 des patients, les concentrations de triglycerides a jeun ont diminue de 2,6 mmol/l (2,30 g/l) et les acides gras libres ont diminue. La troglitazone agit en augmentant l'oxydation des graisses puisque le quotient respiratoire a diminue en moyenne de 0,12. La masse grasse a augmente de 2,4 % et l'IRM a mis en evidence une augmentation du tissu adipeux sous-cutane mais non de la graisse viscerale. Un patient a presente une hepatotoxicite qui est rentree dans l'ordre trois mois apres l'arret du traitement. Le traitement par troglitazone semble donc ameliorer le controle metabolique et augmenter le tissu adipeux chez les patients presentant un diabete lipoatrophique. Le risque d'hepatotoxicite doit cependant etre mis en balance.Arioglu E., et al. 2000. Efficacy and safety of troglitazone in the treatment of lipodystrophy syndromes. Ann Intern Med 133 : 263-274.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".