Impact of Telemedicine Versus In-Person Pediatric Outpatient Type 1 Diabetes Visits on Immediate Glycemic Control: Retrospective Chart Review
Bibliographic record
Abstract
BACKGROUND Children, adolescents, and young adults with type 1 diabetes require frequent outpatient evaluation to assess glucose trends, modify insulin doses, and screen for complications. Continuous glucose monitoring (CGM) has become more prevalent in recent years and provides a detailed glycemic control assessment. Telemedicine has been increasingly utilized in lieu of in-person visits, especially since the onset of the COVID-19 pandemic. OBJECTIVE To investigate whether CGM profile parameters change in the periods immediately following an outpatient type 1 diabetes follow-up visit and to determine whether visits completed by telemedicine versus in-person impact these metrics, screening lab completion rates, or frequency of diabetic emergencies. METHODS A dual center retrospective chart review was conducted including outpatient type 1 diabetes follow-up visits for patients aged 5-21 years old utilizing Dexcom CGM during the 2021 calendar year. CGM profile change from baseline was assessed via Time in Range (TIR) and Glucose Management Indicator (GMI) comparing the 4-week period leading up to each outpatient visit to the 2-week and 4-week period immediately following. Completion of recommended screening labs collected prior to the next visit was determined. Diabetic emergencies were measured by frequency of glucagon use and/or diabetes-related ER visits or hospitalizations. RESULTS A total of 269 outpatient visits (41.2% telemedicine) among 135 patients were included across both study sites. Mean TIR increased by 1.63% and 1.35% during the 2-week and 4-week period after each visit, respectively (p = 0.003, 0.013). Mean GMI also improved, decreasing by 0.07% and 0.06% during the 2-week and 4-week period after each visit, respectively (p = 0.003, 0.021). There were no statistically relevant differences in TIR and GMI changes when comparing telemedicine versus in-person visits. However, patients seen by in-person visits were 2.69 times more likely to complete screening labs than those seen by telemedicine (p = 0.032). Diabetic emergencies occurred too infrequently to analyze. CONCLUSIONS Our study detected a small, but statistically significant improvement in CGM profile parameters that was similar between telemedicine and in-person follow-up visits. However, screening lab completion occurred more often in patients seen in-person, highlighting the importance of periodic face-to-face encounters. Since multiple visits over time are needed to sustain clinically relevant improvements in glycemic control, our findings suggest that telemedicine can be utilized to enhance diabetes care among children and adolescents. Future studies should examine how to best utilize a combination of telemedicine versus in-person visits to achieve diabetes care goals while providing flexibility for patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".