Prevalence of dermatitis including allergic contact dermatitis from medical devices used by children and adults with Type 1 diabetes mellitus: A systematic review and questionnaire study
Bibliographic record
Abstract
Use of medical devices (MDs), that is, glucose sensors and insulin pumps, in patients with Type 1 diabetes mellitus (T1D) has proven an enormous advantage for disease control. Adverse skin reactions from these MDs may however hamper compliance. The objective of this study was to systematically review and analyse studies assessing the prevalence and incidence of dermatitis, including allergic contact dermatitis (ACD) related to MDs used in patients with T1D and to compare referral routes and the clinical investigation routines between clinics being part of the European Environmental and Contact Dermatitis Research Group (EECDRG). A systematic search of PubMed, EMBASE, CINAHL and Cochrane databases of full-text studies reporting incidence and prevalence of dermatitis in persons with T1D using MDs was conducted until December 2021. The Newcastle-Ottawa Scale was used to assess study quality. The inventory performed at EECRDG clinics focused on referral routes, patient numbers and the diagnostic process. Among the 3145 screened abstracts, 39 studies fulfilled the inclusion criteria. Sixteen studies included data on children only, 14 studies were on adults and nine studies reported data on both children and adults. Participants were exposed to a broad range of devices. Skin reactions were rarely specified. It was found that both the diagnostic process and referral routes differ in different centres. Further data on the prevalence of skin reactions related to MDs in individuals with T1D is needed and particularly studies where the skin reactions are correctly diagnosed. A correct diagnosis is delayed or hampered by the fact that, at present, the actual substances within the MDs are not declared, are changed without notice and the commercially available test materials are not adequately updated. Within Europe, routines for referral should be made more standardized to improve the diagnostic procedure when investigating patients with possible ACD from MDs.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.013 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".