Availability and access to pediatric diabetes care: a global descriptive study
Bibliographic record
Abstract
A decade since the discovery of insulin, the increasing prevalence of type 1 diabetes mellitus (T1DM) has underscored the prevailing inequalities in the provision of essential care for T1DM worldwide. However, the details on the availability of insulin types and associated medical devices remain unclear. A cross-sectional electronic survey was distributed across a global network of pediatric societies under the umbrella of the International Pediatric Association (IPA). Access to and availability of pediatric diabetes care were investigated using standardized questions. Responses from 25 of 132 pediatric societies across six regions were included. Pediatric endocrinologists typically manage T1DM together with pediatricians or adult endocrinologists. Nonetheless, 24% of the respondents reported pediatricians to be the sole healthcare professionals. According to the respondents, the patients were either partially or completely responsible for payments of insulin (40%), A1C (24%), C-peptide (28%), and antibody testing for diagnosis (28%). Government support is generally available for insulin, but this was merely 20% for insulin pumps and 12% for continuous glucose monitors. There are considerable disparities in the access, availability, and affordability of diabetes testing, medications, and support between countries with significant out-of-pocket payments for care. Country- and region-specific improvements to national programs are necessary to achieve optimal pediatric diabetes care globally.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".