Appropriatezza d'impiego dei tiazolidindioni nell'Azienda Ospedaliera di Ferrara
Bibliographic record
Abstract
Introduction. The risk-benefit profile of thiazolidinediones (TZDs), oral hypoglycaemic agents has been recently widely discussed in literature. As second-line treatment of type 2 diabetes their reimbursement has been associated in the ER Region to a treatment plans (TP), whose data allow the assessment of appropriateness, effectiveness, safety. Methods. The \nTP data were analyzed on the following parameters: age and sex of\npatients, TZD prescribed, other antidiabetic drugs, Hb1Ac and BMI values in first prescription, Hb1Ac value in following prescriptions, any major complications. Results. The investigation has been conducted on 788 PT, for 448 patients(mean age 65.7 yrs, 59% men), from April 2008 to November 2009. Up to 78.8% of first prescriptions were for pioglitazone, and 67.2% for metformin and sulphonylurea. The Hb1Ac and BMI values, in the first prescription, were respectively > 7% in 71.4% and ≥25 kg/m2 in\n79% patients. Only in 1⁄4 of the 49.3% of patients follow-up measures, HB1/Ac decreased. Complications were reported in 10.5% of pts, with a prevalence of cardiovascular events (3.2% for rosiglitazone, 2.7% for pioglitazone). Conclusion. The results show an adherence to the international guidelines criterias and to the labelled therapeutic indications for glitazones' prescription. Glitazones therapy seems to be effective in a quarter of patients and seems to be relatively safe; TPs provide an useful tool to monitor therapy safety, and effectiveness in diabetic patients.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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".