Home telemonitoring of patients with diabetes: a systematic assessment of observed effects
Bibliographic record
Abstract
RATIONALE, AIMS AND OBJECTIVES: Diabetes represents a common chronic disease continuously growing worldwide. Unless closely monitored, it can be associated with serious complications and high expenditures. Telemonitoring is a patient management approach increasingly used with chronic illnesses. It supports timely transmission and remote interpretation of patients' data for follow-up and preventive interventions. No comprehensive review exists on all aspects of diabetes 'home telemonitoring' and its effects. The objective of this study is to provide a systematic review of this approach and its effect at the informational, clinical, behavioural, structural and economical levels. METHODS: A comprehensive literature review was conducted on Medline and Cochrane Library to identify relevant articles. The keywords used include diabetes, telemonitoring, home monitoring, telecare and telemedicine. RESULTS: Seventeen studies using diverse technologies and transmitting different clinical, medical and behavioural data were found. Significant impacts were observed namely at the behavioural, clinical and structural levels. Minimal technical problems and no cost-benefit and cost-effectiveness analyses were reported. CONCLUSION: Close management of diabetic patients through telemonitoring showed significant reduction in HbA(1c) and complications, good receptiveness by patients and patient empowerment and education. Yet, the magnitude of its effects remains debatable, especially with the variation in patients' characteristics (e.g. background, ability for self-management, medical condition), samples selection and approach for treatment of control groups. Further investigation of telemonitoring efficacy and cost-effectiveness over longer periods of time, and larger samples is needed. Assessment of the attitude of providers is also important in light of their heavy workload and issues of reimbursement.
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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 | 0.018 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".