After the diabetes care trial ends, now what? A 1-year follow-up of the RxING study
Bibliographic record
Abstract
INTRODUCTION: There is strong evidence that pharmacist care improves patients' glycaemic control. However, the sustainability and durability of such interventions beyond the research period is not known. RxING was the first trial of pharmacist prescribing in diabetes and it showed an improvement in glycated haemoglobin (HbA1c) of 1.8% over 6 months. OBJECTIVE: 1° objective: To evaluate glycaemic control in the RxING study patients 12 months after the end of the formal study follow-up. 2° objective: To assess the patients' risk of cardiovascular events in the next 10 years. METHODS: We contacted the participating pharmacists to check if the patients who participated in the RxING study are still taking insulin, the dose of insulin they are taking, and their HbA1c. There were no mandated follow-up visits with the pharmacist after the study completion. RESULTS: A total of 100 patients with poorly controlled type 2 diabetes were enrolled in the original RxING study; 93 of them completed the study, while 83 participated in the 12-month follow-up. Seventy-five patients were still taking insulin, with the average dose increasing from 31.1 units (SD 18.4) at study completion to 37.4 units (SD 30.8) (95% CI -13.3 to 0.88, p=0.085). HbA1c was reduced from 9.1% (SD 1) at baseline to 7.3% (SD 0.9) at study completion (95% CI 1.4 to 2, p <0.001), and increased to 8.1% (SD 1.3) 12 months later (95% CI -1.1 to -0.5, p <0.001 vs study completion). CONCLUSIONS: Twelve months after completing the intervention, approximately half of the glycaemic control gains were lost. This highlights the importance of structured follow-up with the pharmacist in this patient population. TRIAL REGISTRATION NUMBER: clinicaltrials.gov; Identifier: NCT01335763.
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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 | 0.030 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".