Sustained Improvement in Glycemic Control in Emerging Adults with Type 1 Diabetes 2 Years After the Start of the COVID-19 Pandemic
Bibliographic record
Abstract
Although there were initial concerns that the public health response to the COVID-19 pandemic would adversely affect glycemic control in people with type 1 diabetes, several early continuous glucose monitor (CGM) studies reported an unexpected slight improvement in glucose metrics. Early emerging adulthood (roughly spanning the ages of 18–24 years) is often a vulnerable time in the life of a person with type 1 diabetes. Here, we set out to determine how the care and glucose management of emerging adults with type 1 diabetes changed over a period of approximately 2 years from the start of the COVID-19 pandemic. This was a retrospective study of a tertiary referral, multidisciplinary young adult diabetes clinic, spanning before and after the 777-day state of emergency in the City of Toronto. Of 130 emerging adults with type 1 diabetes (80 male, 50 female; mean age 21.0 ± 2.1 years), baseline pre-pandemic HbA 1c values were available for 120 individuals. During 24.9 ± 5.4 months of follow-up before and after the start of the COVID-19 pandemic, HbA 1c fell from 8.5 ± 1.7% (69.3 ± 18.8 mmol/mol) to 8.1 ± 1.9% (65.2 ± 20.5 mmol/mol) ( P < 0.05), with change in HbA 1c from pre-lockdown levels being sustained throughout the second year of the pandemic. Over the same period, CGM use rose from 43% to 83%, primarily through increased uptake of intermittently scanned CGM, which is covered through the Ontario Drug Benefit program. Change in HbA 1c was most evident in Dexcom G6 real-time CGM users − 0.7 ± 1.2% (− 9.8 ± 17.1 mmol/mol) ( P < 0.01 vs. self-monitoring of blood glucose). Among emerging adults with type 1 diabetes attending a multidisciplinary clinic in a high-income country, glycated hemoglobin levels are on average 0.4% (4.1 mmol/mol) lower than they were before the pandemic. This reduction in HbA 1c is unlikely to be a consequence of early strict lockdowns given the length of time of follow-up. Rather, improved glycemic control coincided with increased utilization of wearable diabetes devices.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".