Long-Term Efficacy of Insulin Pump Therapy on Glycemic Control in Adults with Type 1 Diabetes Mellitus
Bibliographic record
Abstract
OBJECTIVE: Continuous subcutaneous insulin infusion (CSII) is an effective method of intensive therapy for patients with type 1 diabetes; however, most studies have not examined long-term glycemic control. We evaluated the long-term efficacy of CSII in a cohort of adult patients with type 1 diabetes. SUBJECTS AND METHODS: This was a retrospective observational study of 200 patients with type 1 diabetes who initiated CSII at a single outpatient clinic in Kingston, ON, Canada between January 1998 and December 2012. Data were collected from 3 months prior to and up to 15 years after initiation of CSII and included glycated hemoglobin (HbA1c) level and demographic factors potentially associated with glycemic control. RESULTS: Mean age and duration of diabetes at CSII initiation were 35.4 years and 22.4 years, respectively. Mean duration of CSII at the time of analysis was 6 years. Mean HbA1c at initiation of CSII was 8.7% and decreased to a nadir of 7.5% 6 months post-initiation (SD = 1.0) (P < 0.001). This increased over time (range, 7.8-8.2%) but remained lower than the pre-CSII HbA1c (P < 0.001). Shorter duration of diabetes prior to CSII initiation, history of missed appointments, mental illness, and active smoking were predictors of higher HbA1c on CSII. Pre-CSII HbA1c predicted long-term HbA1c on CSII. CONCLUSIONS: The data demonstrate that in a clinic setting, patients on CSII maintain lower HbA1c values over a 1-10-year period compared with pre-CSII values. Poor pre-CSII HbA1c, history of missed appointments, mental illness, and active smoking are predictors of those less likely to achieve an HbA1c target of ≤ 7.0%.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".