ArticleBMJ open2023
Have interventions aimed at assisting general practitioners in facilitating earlier diagnosis of type 1 diabetes in children been successful? A systematic review protocol.
Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it, 2 citations in OpenAlex.
- Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEarly diagnosis of type 1 diabetes in children is critical to prevent deterioration to diabetic ketoacidosis (DKA), a state where the body's insulin levels are critically low resulting in the use of fat for fuel and the accumulation of ketones. DKA is a life-threatening emergency where dehydration and cerebral oedema can quickly develop and lead to death. Despite treatment, DKA also has harmful impacts on cognition and brain development. Most children admitted to a hospital with DKA see their general practitioner in the week leading up to their admission. A delay in referral from general practice can result in delays in commencing lifesaving insulin therapy. Prior systematic reviews have explored publicity campaign interventions aimed at recognising type 1 diabetes earlier; however, no reviews have explored these interventions targeted at reducing the delay after presentation to the general practitioner. This systematic review aims to summarise interventions that target the diagnostic delay emerging from general practice and to evaluate their effectiveness in reducing DKA admissions.
methodsSix databases (Ovid (MEDLINE), Web of Science, EMBASE, CINAHL, Evidence-Based Medicine Reviews (EBMR) and Google Scholar) will be searched to identify studies exploring interventions to reduce diagnostic delay in children with type 1 diabetes, and hence DKA, in general practice. The primary outcome will be the number of DKA admissions to a hospital following a delay in general practice. The secondary outcome will be the behaviour of general practitioners with respect to urgent referral of children with type 1 diabetes. Title, abstract and full-text screening for exclusion and inclusion of publications will be completed by two independent reviewers. Any risks of bias within individual studies will be assessed by two independent reviewers, using the Risk Of Bias In Non-Randomized Studies of Interventions tool. Our confidence in the overall body of evidence will be assessed using the Grading of Recommendations, Assessment, Development and Evaluation. ETHICS AND DISSEMINATION: The systematic review will be disseminated via publication and potentially in conference presentations. Ethics is not required for a systematic review of secondary data. PROSPERO REGISTRATION NUMBER: CRD42023412504.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.