Universal screening for early detection of chronic autoimmune, metabolic and cardiovascular diseases in the general population using capillary blood (UNISCREEN): low-risk interventional, single-centre, pilot study protocol.


Journal

BMJ open
ISSN: 2044-6055
Titre abrégé: BMJ Open
Pays: England
ID NLM: 101552874

Informations de publication

Date de publication:
05 Mar 2024
Historique:
medline: 8 3 2024
pubmed: 7 3 2024
entrez: 6 3 2024
Statut: epublish

Résumé

Chronic autoimmune (type 1 diabetes and coeliac disease) and metabolic/cardiovascular (type 2 diabetes, dyslipidaemia, hypertension) diseases are highly prevalent across all age ranges representing a major public health burden. Universal screening for prediction/early identification of these conditions is a potential tool for reducing their impact on the general population. The aim of this study is to assess whether universal screening using capillary blood sampling is feasible at a population-based level. This is a low-risk interventional, single-centre, pilot study for a population-based screening programme denominated UNISCREEN. Participants are volunteers aged 1-100 who reside in the town of Cantalupo (Milan, Italy) undergoing: (1) interview collecting demographics, anthropometrics and medical history; (2) capillary blood collection for measurement of type 1 diabetes and coeliac disease-specific autoantibodies and immediate measurement of glucose, glycated haemoglobin and lipid panel by point-of-care devices; (3) venous blood sampling to confirm autoantibody-positivity; (4) blood pressure measurement; (5) fulfilment of a feasibility and acceptability questionnaire. The outcomes are the assessment of feasibility and acceptability of capillary blood screening, the prevalence of presymptomatic type 1 diabetes and undiagnosed coeliac disease, distribution of glucose categories, lipid panel and estimate of cardiovascular risk in the study population. With approximately 3000 inhabitants, the screened population is expected to encompass at least half of its size, approaching nearly 1500 individuals. This protocol and the informed consent forms have been reviewed and approved by the San Raffaele Hospital Ethics Committee (approval number: 131/INT/2022). Written informed consent is obtained from all study participants or their parents if aged <18. Results will be published in scientific journals and presented at meetings. If proven feasible and acceptable, this universal screening model would pave the way for larger-scale programmes, providing an opportunity for the implementation of innovative public health programmes in the general population. NCT05841719.

Identifiants

pubmed: 38448070
pii: bmjopen-2023-078983
doi: 10.1136/bmjopen-2023-078983
pmc: PMC10916121
doi:

Substances chimiques

Autoantibodies 0
Glucose IY9XDZ35W2
Lipids 0

Banques de données

ClinicalTrials.gov
['NCT05841719']

Types de publication

Clinical Trial Protocol Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e078983

Informations de copyright

© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

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Auteurs

Aurora Merolla (A)

Vita-Salute San Raffaele University, Milano, Italy.

Rebecca De Lorenzo (R)

Vita-Salute San Raffaele University, Milano, Italy.

Giulia Ferrannini (G)

Karolinska Institute, Stockholm, Sweden.

Cristina Renzi (C)

Vita-Salute San Raffaele University, Milano, Italy.
Behavioural Science and Health, Institute of Epidemiology & Health Care, University College London, London, UK.

Francesca Ulivi (F)

Fondazione Italiana Diabete (FID), Milan, Italy.

Elena Bazzigaluppi (E)

Diabetes Research Institute, IRCCS San Raffaele Hospital, Milan, Italy.

Vito Lampasona (V)

Diabetes Research Institute, IRCCS San Raffaele Hospital, Milan, Italy.

Emanuele Bosi (E)

Vita-Salute San Raffaele University, Milano, Italy bosi.emanuele@hsr.it.
Diabetes Research Institute, IRCCS San Raffaele Hospital, Milan, Italy.

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Classifications MeSH