A comparative study of insulin lispro and human regular insulin in patients with type 2 diabetes mellitus and secondary failure of oral hypoglycemic agents.
Bibliographic record
Abstract
OBJECTIVE: To compare the effects of insulin lispro (LP) and human regular insulin (HR) when given twice daily with NPH insulin on glycemic control (HbA1c), daily blood glucose profiles and rates of hypoglycemia in patients with type 2 diabetes mellitus after failure to respond to sulfonylurea drugs. RESEARCH DESIGN AND METHODS: A 5.5-month randomized, open-label, parallel study of 148 patients receiving either LP (n = 70) or HR (n = 78). Eight-point blood glucose profiles and HbA1c measurements were collected at baseline, 1.5, 3.5 and 5.5 months. RESULTS: Two-hour post-breakfast and 2-hour post-supper blood glucose levels (means [and standard errors]) were significantly lower for LP than for HR at the end point (9.5 [0.4] mmol/L v. 10.9 [0.4] mmol/L and 8.4 [0.4] mmol/L v. 9.7 [0.4] mmol/L, respectively, p = 0.02 in both cases). HbA1c improved from 10.5% (0.2%) (LP) and 10.3% (0.2%) (HR) to 8.0% (0.1%). Hypoglycemia rates were similar during the day; however, there was an overnight trend to reduced rates with LP (0.08 [0.03] episodes/30 d v. 0.16 [0.04] episodes/30 d, p = 0.057). Quality-of life assessment showed significant improvement (p < 0.05) in the diabetes-related worry scale for LP subjects whereas HR subjects slightly worsened. CONCLUSIONS: With traditional twice-daily insulin administration algorithms, LP improves 2-hour postprandial glucose levels, quality of life and overnight hypoglycemia rates while delivering an equivalent level of glycemic control (HbA1c) compared with HR to insulin-naïve patients with type 2 diabetes who require insulin.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".