Improved Glycemic Control Through the Use of a Telehomecare Program in Patients with Diabetes Treated with Insulin
Bibliographic record
Abstract
Background: With the drastic surge in the prevalence of diabetes, the use of medical resources for management of diabetic patients increased markedly. This study aimed to evaluate the impact of telehomecare (THC) use on clinical efficacy, nursing interventions, and medical visits compared with the standard care in insulin-treated diabetic patients. Materials and Methods: A prospective noninferiority clinical trial was designed. Participants were assigned to either an intervention group provided with a THC system during 3 months or to a control group. Main outcome was the difference in A1c at 3 months compared with baseline. Secondary outcomes were the difference in A1c at 6 months compared with baseline, the number of medical visits during the 6-month period of the study, and nursing interventions during the 3 months on THC. Results: A total of 92 participants completed the study. A significant decrease in A1c levels was observed in the THC group ( n = 45) compared with the control group ( n = 47) at 3 months (−0.61% vs. −0.06%, respectively, P = 0.048) and at 6 months (−0.37% vs. −0.10%, respectively, P = 0.036). The THC group had an average of 0.6 medical visit compared with 1.0 in the control group ( P < 0.001). An increase in nursing interventions (mainly e-mails) was noted in THC group ( n = 14.7) compared with control group ( n = 1.1). Conclusions: This THC program demonstrates improvement in glycemic control and a decrease in the number of medical visits. However, it is important to consider an additional burden in nursing interventions when implementing a THC program.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".