A Pan-European and Canadian Prospective Survey to Evaluate Patient Satisfaction with the SoloSTAR Insulin Injection Device in Type 1 and Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: This study evaluated patient satisfaction with SoloSTAR® (sanofi-aventis), a prefilled insulin pen device for injection of insulin glargine or insulin glulisine. METHODS: This was a 6-8-week multicenter (n = 652), observational, prospective Pan-European and Canadian registry study in patients with diabetes mellitus (n = 6542) who recently switched to or started treatment with insulin glargine and/or insulin glulisine using SoloSTAR or were insulin naïve. At the baseline visit, patients were asked to evaluate their satisfaction with their previous device, if applicable. After 6-8 weeks of SoloSTAR use, patients were asked to rate their satisfaction. RESULTS: Overall, 6481 patients (mean age 54 years, 48.7% male, 72% type 2 diabetes) were analyzed in this study. Of these, 4995 (77.1%) patients had used insulin before the study and 1641 (32.9%) and 3395 (68.0%) patients had previously used prefilled and/or reusable pens, respectively. During the study, SoloSTAR was used to administer insulin glargine and/or insulin glulisine by 97.3% and 36.0% of patients, respectively (both: 27.0%). Most patients rated SoloSTAR as "excellent/good" for ease of use (97.9%), learning to use (98.3%), selecting the dose (97.6%), and reading the dose (95.1%). Most patients rated ease of use (88.4%) and injecting a dose (84.5%) with SoloSTAR as "much easier/easier" versus their previous pen. Overall, 98% planned to continue using SoloSTAR. No safety concerns were reported. CONCLUSION: This European and Canadian survey shows that SoloSTAR was well accepted in this large patient population. Most patients preferred SoloSTAR to their previous pen and planned to continue SoloSTAR use.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".