THE EFFECTS OF THIAZOLIDINEDIONE THERAPY ON NT-PROBNP LEVELS IN PATIENTS WITH TYPE 2 DIABETES
Bibliographic record
Abstract
: We sought to determine whether thiazolidinedione (TZD) therapy affects levels of serum N-terminal pro-brain natriuretic peptide (NT-proBNP) in patients with type 2 diabetes. Materials and Methods : This study population consisted of 76 patients with type 2 diabetes and no history of heart failure. Subjects had NTproBNP levels determined prior to initiating TZD therapy, and after 3 months of treatment. We compared within-person changes in NTproBNP over the 3 month duration. We determined if the magnitude of change in NTproBNP over the treatment period was correlated with baseline parameters or nature/dose of TZD medication. Results : The subjects were 42% female and 58% male, and the mean age and duration was 59.8±11.8 years old and 11.4±8.3 years respectively. The baseline mean A1C and BMI was 8.7±1.1% and 30.9±8.7 kg/m 2 respectively. We found that NT-proBNP levels did not vary significantly between baseline (mean±SD: 143.8±203.9 pg/mL) and 3 month follow-up (150.6±186.2 pg/mL). Conversely, A1C levels declined significantly (p<0.0001) and BMI increased significantly (p< 0.05). Conclusion : Adding TZD therapy to patients with type 2 diabetes and no history of heart failure does not have a significant effect on NTproBNP levels.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".