Intensive Insulin Therapy With Insulin Lispro
Bibliographic record
Abstract
OBJECTIVE: To evaluate glycemic control, hypoglycemic events, and quality of life in patients treated with continuous subcutaneous insulin infusion (CSII) and multiple daily insulin injection (MDI), with insulin lispro as the principal insulin. RESEARCH DESIGN AND METHODS: This clinical trial enrolled 27 patients with type 1 diabetes. They were randomly assigned to CSII (n = 13) or MDI (n = 14) treatment regimens. Glycemic control (HbA(1c) level) was the primary outcome and was measured monthly for 9 months. Secondary outcomes were patient reports of hypoglycemic events (recorded monthly for 9 months) and quality of life assessed at 9 months using the Diabetes Quality of Life (DQOL) questionnaire. RESULTS: A significant decrease in HbA(1c) from baseline was shown for both groups. However, the overall treatment effect (CSII - MDI) for HbA(1c) was +0.08% (95% CI -0.23 to +0.39, P > 0.10). This was significantly less than the a priori limit of +/-0.5% (P = 0.004). The relative treatment effect ([CSII - MDI]/MDI) for the overall number of hypoglycemic events was +9% (95% CI -37 to +87, P > 0.10). There were no statistically significant differences between treatment groups for any of the DQOL subscales. CONCLUSIONS: No statistically significant differences in glycemic control, reported hypoglycemic events, or quality of life were found in this study. Furthermore, a clinically significant difference of more than +/-0.5% HbA(1c) between the two regimens can be confidently ruled out. We conclude that the choice of intensive insulin therapy should be a matter of patient preference, consistent with lifestyle.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".