Diabetes Risk Diagnosis and Management

NCT ID: NCT03949504

Last Updated: 2022-01-12

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 1500 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2019-01-09
• Study Completion Date: 2021-12-31

Brief Summary

Considering the multifactorial nature of the complications of Type 2 diabetes, such as cardiovascular and neurological complications and therefore the multiplicity of risk factors that contribute to their development, it is assumed that the use of a dedicated function of the MyStar Connect software (beta version), that allows the querying of the application through specific queries (presence of risk factors) and the calculation of specific risk scores in order to extract the patients most at risk of developing such complications, can provide support to the diabetologist to optimize management of the patient at risk and complicated through, for example, a more intensive visit program and this then translates into an improvement in the parameters related to these risk factors.

Detailed Description

The study aims are:

• To evaluate the percentage of subjects at risk of diabetes in the general population
• To evaluate the percentage of type 2 diabetics with and without complications in the identified population at risk
• To evaluate whether the new computer system is able to identify subjects at risk of developing complications or aggravation of complications already in progress (cardiovascular and neurological complications).

Through the IT platform made available within the framework of the project, the selected sample will be given the questionnaire to detect the risk of diabetic disease (FINDRISC adapted) and, in the case of a positive outcome, the subject at risk will be assessed with laboratory tests, to confirm or not the condition of prediabetes or diabetes. Therefore, all the subsequent phases of patient care and management will be followed, from the modification of lifestyles for prediabetics to the management of overt diabetic pathology and the complications associated with it, thus experimenting with all the modules of the software platform integrated.

Subjects who have a high diabetic risk score will be referred to the Neuromed laboratories for the analysis of fasting blood glucose and the glycemic load test. Consistent with the diagnostic protocol developed, the subjects will follow a triple address:

1. Subjects at risk with fasting blood glucose or normal glycemic load

2. Subjects with prediabetes

3. Subjects with diabetes Patients in whom a vascular or neurological complication is diagnosed will be managed by the Neuromed clinic work groups using dedicated modules developed within the project.

At time T0 for diabetic patients without or with cardiovascular and neurological complications who will come to visit as from normal clinical practice, the presence of risk / complication parameters will be checked and risk scores will be applied to ascertain the patient's condition. The patient will then be followed as per normal clinical practice and risk parameters and the derived scores will be re-evaluated.

Conditions

Diabetes Mellitus, Type 2

Study Design

• Observational Model Type: CASE_ONLY
• Study Time Perspective: CROSS_SECTIONAL

Study Groups

General population

Male and Female subjects (n=1000) over 34 years of age randomly recruited from the participants to the recall phase of the Moli-sani study

New Find-risk questionnaire software

Intervention Type: PROCEDURE

FINDrisk: software with 12 questions to define the risk of diabetes in the general population MyStar Connect: software to guide the diagnosis and the management of diabetes and its complications

Patients with type 2 Diabetes

Male and Female patients with type 2 diabetes (n=550) without (n=200) or with cardiovascular (n=200) or neurological (n=150) complications consecutively admitted to the IRCCS Neuromed

No interventions assigned to this group

Interventions

New Find-risk questionnaire software

FINDrisk: software with 12 questions to define the risk of diabetes in the general population MyStar Connect: software to guide the diagnosis and the management of diabetes and its complications

Intervention Type: PROCEDURE

Other Intervention Names

MyStar Connect software (version beta)

Eligibility Criteria

Inclusion Criteria

• Signature of informed consent;
• Subjects recruited consecutively during the recall phase of the Moli-sani project.
• Patients with type 2 diabetes mellitus and vascular or neurological complications attending the IRCCS Neuromed

Exclusion Criteria

• Inability to understand and to want
• Refusal to sign informed consent.
• Type 1 diabetes
• Gestational diabetes.
• For subjects of the general population, a previous diagnosis of diabetes.

• Minimum Eligible Age: 34 Years
• Maximum Eligible Age: 100 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Neuromed IRCCS

OTHER

Sponsor Role: lead

Responsible Party

Licia Iacoviello

MD, PhD

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Licia iacoviello, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

IRCCS Neuromed

Locations

IRCCS INM Neuromed, Department of Epidemiology and Prevention

Pozzilli, IS, Italy

Countries

Italy

References

Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, Nathan DM; Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002 Feb 7;346(6):393-403. doi: 10.1056/NEJMoa012512.

Reference Type: RESULT

PMID: 11832527 (View on PubMed)

Lindstrom J, Tuomilehto J. The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care. 2003 Mar;26(3):725-31. doi: 10.2337/diacare.26.3.725.

Reference Type: RESULT

PMID: 12610029 (View on PubMed)

Bergmann A, Li J, Wang L, Schulze J, Bornstein SR, Schwarz PE. A simplified Finnish diabetes risk score to predict type 2 diabetes risk and disease evolution in a German population. Horm Metab Res. 2007 Sep;39(9):677-82. doi: 10.1055/s-2007-985353.

Reference Type: RESULT

PMID: 17846976 (View on PubMed)

Li J, Bergmann A, Reimann M, Bornstein SR, Schwarz PE. A more simplified Finnish diabetes risk score for opportunistic screening of undiagnosed type 2 diabetes in a German population with a family history of the metabolic syndrome. Horm Metab Res. 2009 Feb;41(2):98-103. doi: 10.1055/s-0028-1087191. Epub 2008 Oct 29.

Reference Type: RESULT

PMID: 18975253 (View on PubMed)

American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010 Jan;33 Suppl 1(Suppl 1):S62-9. doi: 10.2337/dc10-S062. No abstract available.

Reference Type: RESULT

PMID: 20042775 (View on PubMed)

Other Identifiers

DEP3_2019

Identifier Type: -

Identifier Source: org_study_id