Screening of diabetic patients in general practitioners offices

Česká verzia

Authors: Roman Mužik ¹; Veronika Knapčoková ¹; Katarína Nováková ¹; Ivan Tkáč ²
Authors place of work: DÔVERA zdravotná poisťovňa, a. s., Bratislava ¹; Excelentný tím pre výskum aterosklerózy (EXTASY), IV. interná klinika UPJŠ LF a UN LP Košice ²
Published in the journal: Forum Diab 2021; 10(2): 142-151
Category:

Summary

One of the most commonly used tools to improve the identification of individuals with diabetes is screening. Screening of healthy individuals could lead to early detection and treatment of diabetes, but this is not well supported by randomized trials to confirm these benefits. Therefore, screening is preferentially recommended for individuals at high risk. In this study, 589 diabetics (7.2% of those screened) and 322 prediabetics (4.0% of those screened) were identified out of a total of 8,151 individuals screened. Of the diagnosed prediabetics, 75.5% were at-risk individuals, and of the diabetics, at-risk individuals accounted for 80.5%. The success rate of identifying patients with diabetes was 2.75 times (95% CI 2.23–3.39) higher in the at-risk group than in the non-risk group. For prediabetic patients, the probability of identification was 1.98 times (95% CI 1.53–2.56) higher in the risk group. The study confirms the usefulness of screening performed on at-risk individuals, i.e., individuals with arterial hypertension, hypercholesterolemia, CHD, and other diseases associated with diabetes using health insurance company data.

Keywords:

diabetes – general medicine – glycemia – prediabetes – screening

Zdroje

1. [International Diabetes Federation]. IDF Diabetes Atlas. 9th ed. Intenational Diabetes Federation: Belgium 2019. Dostupné z WWW: <https://www.diabetesatlas.org/en>.

2. Mokáň M, Galajda P, Prídavková D et al. Prevalence of diabetes mellitus and metabolic syndrome in Slovakia. Diabetes Res Clin Pract 2008; 81(2): 238–242. Dostupné z DOI: <http://dx.doi.org/10.1016/j.diabres.2008.04.002>.

3. Interné údaje zdravotnej poisťovne Dôvera.

4. Lacka J, Ištokovičová P, Vraždová T et al. Prevalencia a mortalita pacientov s diabetes mellitus 2. typu v roku 2010 a 2015. Interná Medicína 2017; 17(4): 177–180.

5. [Národné centrum zdravotníckych informácií]. Dostupné z WWW: . [02–2021].<http://www.nczisk.sk/Statisticke_vystupy/Tematicke_statisticke_vystupy/Diabetologia/Pages/default.aspx>. [02–2021].

6. Brož J, Malinovská J, Nunes MA et al. Prevalence of diabetes and prediabetes and its risk factors in adults aged 25–64 in the Czech Republic: A cross-sectional study. Diabetes Res Clin Pract 2020; 170: 108470. Dostupné z DOI: <http://dx.doi.org/10.1016/j.diabres.2020.108470>. [04–2021].

7. [Česká diabetologická společnost ČLS JEP a Diabetická asociace ČR]. National diabetes programme 2012–2022. DMEV 2012; 15(3): 179– 199.

8. Schmutterer I, Delcour J, Griebler R. Österreichischer Diabetesbericht 2017. Bundesministerium für Gesundheit und Frauen: Wien 2017. ISBN 978–3-903099–37–1.

9. Simmons RK, Echouffo-Tcheugui JB, Sharp SJ et al. Screening for type 2 diabetes and population mortality over 10 years (ADDITION- Cambridge): a cluster-randomised controlled trial. Lancet 2012; 380(9855): 1741–1748. Dostupné z DOI: <http://dx.doi.org/10.1016/S0140–6736(12)61422–6>.

10. Peer N, Balakrishna Y, Durao S et al. Screening for type 2 diabetes mellitus. Cochrane Database Syst Rev 2020; 5(5): CD005266. Dostupné z DOI: <http://dx.doi.org/10.1002/14651858.CD005266.pub2>.

11. [World Health Organization]. Screening for Type 2 Diabetes, Report of a World Health Organization and International Diabetes Federation meeting. 2003. World Health Organization: Geneva 2003. Dostupné z WWW: <https://www.who.int/diabetes/publications/en/screening_mnc03.pdf>.

12. [Ludwig Boltzmann Institut. Health Technology Assessment]. Screening auf Diabetes mellitus. Leitlinien-Empfehlungen. Wien: 2019. LBI-HTA Projektbericht Nr. 118. ISSN 1992–0488. ISSN-online 1992– 0496. Dostupné z WWW: <https://eprints.aihta.at/1213/1/HTA-Projektbericht_Nr.118.pdf>.

13. Winkler G, Hídvégi T, Vándorfi G et al. Prevalence of undiagnosed abnormal glucose tolerance in adult patients cared for by gene ral practitioners in Hungary. Results of a risk-stratified screening based on FINDRISC questionnaire. Med Sci Monit 2013; 19: 67–72. Dostupné z DOI: <http://dx.doi.org/10.12659/msm.883747>.

14. Sieradzki J. Wilkins A, Szczepański M et al. SCREEN-POL 2 – active screening and early detection of type 2 diabetes in general practice in Poland. Results of multicentre, national screening survey. Diabetologia Praktyczna 2005; 6(3): 103–114.

15. Naumova NV, Makedonova YA, Mikhalchenko DV et al. The Outcomes of the Dental Patients’ Screening for Diabetes Mellitus. J Int Dent Med Res 2020; 13(3): 1071–1080.

16. Su N, Teeuw WJ, Loos BG et al. Development and validation of a screening model for diabetes mellitus in patients with periodontitis in dental settings. Clin Oral Investig 2020; 24(11): 4089–4100. Dostupné z DOI: <http://dx.doi.org/10.1007/s00784–020–03281-w>.

17. Schmalz G, Wolf C, Merle C et al. Evaluation of a questionnaire-based diabetes screening concept in German patients with Stage 3 or 4 periodontitis – A practice-based study. J Periodontol 2020. Dostupné z DOI: <http://dx.doi.org/10.1002/JPER.20–0297>.

18. [World Health Organization]. Cancer. Dostupné z WWW: https:// www.who.int/cancer/prevention/diagnosis-screening/screening/en/. [27–05–2020].

19. Sortsø C, Komkova A, Annelli Sandbæk A et al. Effect of screening for type 2 diabetes on healthcare costs: a register-based study among 139,075 individuals diagnosed with diabetes in Denmark between 2001 and 2009. Diabetologia 2018; 61(6): 1306–1314. Dostupné z DOI: <http://dx.doi.org/10.1007/s00125–018–4594–2>.

20. Glűmer C, Carstensen B, Sandbaek A et al. A Danish Diabetes Risk Score for Targeted Screening. Diabetes Care 2004; 27(3): 727–733. Dostupné z DOI: <http://dx.doi.org/10.2337/diacare.27.3.727>.

21. Köster IE, Huppertz, Hauner H et al. Costs of Diabetes Mellitus (CoDiM) in Germany, Direct Per-capita Costs of Managing Hyperglycaemia and Diabetes Complications in 2010 Compared to 2001. Exp Clin Endocrinol Diabetes 2014; 122(9): 510–516. Dostupné z DOI: <http://dx.doi.org/10.1055/s-0034–1375675>.

22. Zákon č. 577/2004 Z. z. Zákon o rozsahu zdravotnej starostlivosti uhrádzanej na základe verejného zdravotného poistenia a o úhradách za služby súvisiace s poskytovaním zdravotnej starostlivosti. Dostupné z WWW:<https://www.zakonypreludi.sk/zz/2004–577>. [02–2021].

23. Razavian N, Blecker S, Ann Marie Schmidt AM et al. Population-Level Prediction of Type 2 Diabetes from Claims Data and Analysis of Risk Factors. Big Data 2015; 3(4): 277–287. Dostupné z DOI:<http://dx.doi.org/10.1089/big.2015.0020>.

24. [International Diabetes Federation]. IDF Europe members. Dostupné z WWW: <https://www.idf.org/our-network/regions-members/europe/members>. [26–05–2020].

25. Tkáč I, Baldaufová L. Rizikový profil a očakávaný prínos farmakologickej liečby u novodiagnostikovaných diabetikov 2. typu. Interná Med 2005; 5(9): 473–477.

26. Mani S, Chen Y, Elasy T et al. Type 2 diabetes risk forecasting from EMR data using machine liearning. AMIA Annu Symp Proc 2012; 2012: 606–615.

27. McCoy GR, Nori VS, Smith SA et al. Development and Validation of HealthImpact: An Incident Diabetes Prediction Model Based on Administrative Data. Health Serv Res 2016; 51(5): 1896–1918. Dostupné z DOI: <http://dx.doi.org/10.1111/1475–6773.12461>.

28. Longato E, Fadini GP, Sparacino G et al. A Deep Learning Approach to Predict Diabetes Cardiovascular Complications from Administrative Claims. IEEE J Biomed Health Inform 2021; Dostupné z DOI: <http://dx.doi.org/10.1109/JBHI.2021.3065756>.

29. Ravaut M, Sadeghi H, Leung KK et al. Predicting adverse outcomes due to diabetes complications with machine learning using administrative health data. NPJ Digit Med 2021; 4(1): 24. Dostupné z DOI: <http://dx.doi.org/10.1038/s41746–021–00394–8>.