ReviewEuropean journal of pediatrics2026
Screening for diabetes mellitus type 1 in the pediatric general population: an ethical analysis.
Review in European journal of pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Reducing Diabetic Ketoacidosis in Pediatric Type 1 Diabetes: The Impact of Screening Programs and Early Disease-Modifying Treatment.Journal of clinical medicine · 2026Review
- Islet autoantibodies as predictors of type 1 diabetes development, a systematic review with public health implications for Africa.Diabetology & metabolic syndrome · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Autoantibodies can predict clinical type 1 diabetes, impacting early diagnosis, prevention, and management. While integrating antibody testing into routine practice is debated globally, ethical considerations are often overlooked. This paper explores these ethical concerns through qualitative analysis based on a literature review. A PubMed literature search provided the foundation for a qualitative ethical analysis. Arguments regarding type 1 diabetes screening were extracted from 92 eligible articles and categorized using Beauchamp and Childress's four ethical principles. A thematic and principle-oriented ethical analysis was conducted. Key ethical concerns include decision-making for children, risk determination, screening timepoints, psychological aspects, DKA rates, treatment options, and monetary and personnel aspects. Addressing these issues ensures general population screening aligns with autonomy, beneficence, nonmaleficence, and justice.Conclusions; General population antibody screening for type 1 diabetes presents ethical challenges requiring careful consideration. While early detection offers benefits, risks such as psychological distress, stigmatization, and resource diversion must be taken into consideration. Further research should assess feasibility, including human resource demands, parental and child anxiety, optimal screening timepoints, development of educational material, children's involvement in screening, and expanding options for prevention, including teplizumab approval in the EU. What is Known: • Autoantibodies can identify individuals at risk for Type 1 Diabetes before symptom onset, and population screening is increasingly discussed as a strategy to reduce complications such as diabetic ketoacidosis at diagnosis. What is New: • This study provides a structured ethical analysis of general population antibody screening for Type 1 Diabetes using the four-principle framework of Beauchamp and Childress (autonomy, beneficence, nonmaleficence, justice) • It identifies key ethical domains, including decision-making for children, psychological impact, screening timing, resource allocation, and emerging preventive options such as Teplizumab, that should guide future implementation and research on population screening programs.
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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.