scholarly journals Comparing non-invasive diabetes risk scores for detecting patients in clinical practice: a cross-sectional validation study

2021 ◽  
Vol 4 ◽  
pp. 70
Author(s):  
Sinéad Flynn ◽  
Seán Millar ◽  
Claire Buckley ◽  
Kate Junker ◽  
Catherine Phillips ◽  
...  
Keyword(s):  
Risk Score ◽  
Characteristic Curve ◽  
Diabetes Risk ◽  
Detection Methods ◽  
Risk Scores ◽  
Continuous Variables ◽  
Irish Population ◽  
Cross Sectional ◽  
Non Invasive ◽  
Diabetes Risk Score

Background: Type 2 diabetes (T2DM) is a significant cause of morbidity and mortality, thus early identification is of paramount importance. A high proportion of T2DM cases are undiagnosed highlighting the importance of effective detection methods such as non-invasive diabetes risk scores (DRSs). Thus far, no DRS has been validated in an Irish population. Therefore, the aim of this study was to compare the ability of nine DRSs to detect T2DM cases in an Irish population. Methods: This was a cross-sectional study of 1,990 men and women aged 46–73 years. Data on DRS components were collected from questionnaires and clinical examinations. T2DM was determined according to a fasting plasma glucose level ≥7.0 mmol/l or a glycated haemoglobin A1c level ≥6.5% (≥48 mmol/mol). Receiver operating characteristic curve analysis assessed the ability of DRSs and their components to discriminate T2DM cases. Results: Among the examined scores, area under the curve (AUC) values ranged from 0.71–0.78, with the Cambridge Diabetes Risk Score (AUC=0.78, 95% CI: 0.75–0.82), Leicester Diabetes Risk Score (AUC=0.78, 95% CI: 0.75–0.82), Rotterdam Predictive Model 2 (AUC=0.78, 95% CI: 0.74–0.82) and the U.S. Diabetes Risk Score (AUC=0.78, 95% CI: 0.74–0.81) demonstrating the largest AUC values as continuous variables and at optimal cut-offs. Regarding individual DRS components, anthropometric measures displayed the largest AUC values. Conclusions: The best performing DRSs were broadly similar in terms of their components; all incorporated variables for age, sex, BMI, hypertension and family diabetes history. The Cambridge Diabetes Risk Score, had the largest AUC value at an optimal cut-off, can be easily accessed online for use in a clinical setting and may be the most appropriate and cost-effective method for case-finding in an Irish population.

scholarly journals The Efficacy of New Chinese Diabetes Risk Score in Screening Undiagnosed Type 2 Diabetes and Prediabetes: A Community-Based Cross-Sectional Study in Eastern China

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Tao Mao ◽  
Jiayan Chen ◽  
Haijian Guo ◽  
Chen Qu ◽  
Chu He ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Risk Score ◽  
Eastern China ◽  
Cross Sectional Study ◽  
Diabetes Risk ◽  
Undiagnosed Diabetes ◽  
Cross Sectional ◽  
Community Residents ◽  
Diabetes Risk Score

The New Chinese Diabetes Risk Score (NCDRS) is one of the recommended tools for screening undiagnosed type 2 diabetes in China. However, its performance in detecting undiagnosed diabetes needs to be verified in different community populations. Also, it is unknown whether NCDRS can be used in detecting prediabetes. In the present study, we aimed to evaluate the performance of NCDRS in detecting undiagnosed diabetes and prediabetes among the community residents in eastern China. We applied NCDRS in 7675 community residents aged 18-65 years old in Jiangsu Province. The results showed that the participants with undiagnosed diabetes reported the highest NCDRS value, followed by those with prediabetes (P<0.001). The best cut-off points of NCDRS for detecting undiagnosed diabetes and prediabetes were 27 (with a sensitivity of 78.0% and a specificity of 57.7%) and 27 (with a sensitivity of 66.0% and a specificity of 62.9%). The AUCs of NCDRS for identifying undiagnosed diabetes and prediabetes were 0.749 (95% CI: 0.739~0.759) and 0.694 (95% CI: 0.683~0.705). These results demonstrate the excellent performance of NCDRS in screening undiagnosed diabetes in the community population in eastern China and further provide evidence for using NCDRS in detecting prediabetes.

scholarly journals Prediction of risk of type 2 diabetes mellitus using Indian diabetes risk score: a cross sectional study in urban field practice area of a medical college, Bagalkot

2018 ◽  
Vol 5 (7) ◽  
pp. 2853
Author(s):  
Basavaraj S. Mannapur ◽  
Bhagyalaxmi S. Sidenur ◽  
Ashok S. Dorle
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Cross Sectional Study ◽  
Diabetes Risk ◽  
Risk Category ◽  
Cross Sectional ◽  
Medical College ◽  
High Risk Category ◽  
Field Practice ◽  
Diabetes Risk Score

Background: Diabetes is considered as a global emergency where a person dies from diabetes every 6 seconds and diabetes is seen on 1 in 11 adults. Identification of individuals who are at risk is very much necessary to prevent diabetes in India. IDRS could also help to detect people at risk of having prediabetes. The objective of the study were to estimate the prevalence of diabetes mellitus in the age group of >20 years in urban field practice area of S.N. Medical college, Bagalkot and to identify high risk subjects using Indian diabetes risk score (IDRS).Methods: A cross sectional study was done in urban field practice area of S.N. Medical College among adults >20 years of age with sample size of 207. Systematic random sampling was used to select the subjects. Data was collected using standardised questionnaire which included socio-demographic profile, standard glucometer was used to measure random blood glucose for all participants. IDRS was used to ascertain the risk of developing diabetes. Data was analysed using Pearson’s Chi square test and Fischer exact.Results: The overall prevalence of diabetes was 14.1%. Among 206 subjects, 4.8% were in low risk category. 39.6% and 55.1% were in moderate and high risk category respectively. Total of 11 subjects were newly diagnosed in our study. Among them 10 subjects were in the high risk category and 1 was in the low risk category. Sensitivity of IDRS was 90%, specificity 50%, positive predictive value 43.8% and negative predictive value 96.74%..Conclusions: This study estimates the usefulness of simplified Indian diabetes risk score for identifying high risk diabetic subjects in the community. It can be used routinely in commu­nity-based screening to find out high risk people for diabetes so that proper intervention can be done to reduce the burden of the disease. 

scholarly journals Diagnostic accuracy of the Finnish Diabetes Risk Score for the prediction of undiagnosed type 2 diabetes, prediabetes, and metabolic syndrome in the Lebanese University.

2020 ◽  
Author(s):  
Maher Abdallah ◽  
Safa SHARBAJI ◽  
Marwa SHARBAJI ◽  
Zeina DAHER ◽  
Tarek FAOUR ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Metabolic Syndrome ◽  
Risk Score ◽  
Diabetes Risk ◽  
Oral Glucose ◽  
Sample Population ◽  
Non Invasive ◽  
The Metabolic Syndrome ◽  
Diabetes Risk Score

Abstract Background: Risk scores were mainly proved to predict undiagnosed type 2 diabetes mellitus (UT2DM) in a non-invasive manner and to guide earlier clinical treatment. The objective of the present study was to assess the performance of the Finnish Diabetes Risk Score (FINDRISC) for detecting three outcomes: UT2DM, prediabetes, and the metabolic syndrome (MS).Methods: This was a prospective, cross-sectional study during which employees aged between 30 and 64, with no known diabetes and working within the faculties of the Lebanese University (LU) were conveniently recruited. Participants completed the FINDRISC questionnaire and their glucose levels were examined using both fasting blood glucose (FBG) and oral glucose tolerance tests (OGTT). Furthermore, they underwent lipid profile tests with anthropometry.Results: Of 713 subjects, 397 subjects (55.2% female; 44.8% male) completed the blood tests and thus were considered as the sample population. 7.6% had UT2DM, 22.9% prediabetes and 35.8% had MS, where men had higher prevalence than women for these 3 outcomes (P = 0.001, P = 0.003 and P = 0.001) respectively. The AUROC value with 95% Confidence Interval (CI) for detecting UT2DM was 0.795 (0.822 in men and 0.725 in women), 0.621(0.648 in men and 0.59 in women) for prediabetes and 0.710 (0.734 in men and 0.705 in women) for MS. The correspondent optimal cut-off point for UT2DM was 11.5 (sensitivity = 83.3% and specificity = 61.3%), 9.5 for prediabetes (sensitivity = 73.6% and specificity = 43.1%) and 10.5 (sensitivity = 69.7%; specificity = 56.5%) for MS.Conclusion: The FINDRISC can be considered a simple, quick, inexpensive, and non-invasive instrument to use in a Lebanese community of working people who are unaware of their health status and who usually report being extremely busy because of their daily hectic work for the screening of UT2DM and MS. However, it poorly screens for prediabetes in this context.

scholarly journals Validation of the Finnish diabetes risk score (FINDRISC) for the Caucasian population of Siberia

2016 ◽  
Vol 19 (2) ◽  
pp. 113-118 ◽  
Author(s):  
Svetlana V. Mustafina ◽  
Oksana D. Rymar ◽  
Olga V. Sazonova ◽  
Liliya V. Shcherbakova ◽  
Michail I. Voevoda
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Risk Score ◽  
Adult Population ◽  
Risk Groups ◽  
Diabetes Risk ◽  
Receiver Operating Curve ◽  
Siberian Population ◽  
Cross Sectional ◽  
Diabetes Risk Score

Aim. A validation of the Finnish diabetes risk score (FINDRISC) was conducted among the Siberian population. FINDRISC was used to study the prevalence of risk factors for type 2 diabetes mellitus (T2DM) and to estimate the incidence of T2DM in high-risk groups during a 10-year observation period. Materials and methods. A total of 9,360 subjects aged between 45 and 69 years were enrolled in this cross-sectional, population-based study. FINDRISC was used to group 8,050 people without diabetes according to their risk for T2DM. Statistical analysis was performed using SPSS. Results. When a cutoff point of 11 was used to identify those with diabetes, sensitivity was 76. 0% and specificity was 60. 2%. The area under the receiver operating curve for diabetes was 0. 73 (0. 73 for men and 0. 70 for women). More than one-third (31. 7%) of the adult population of Novosibirsk was estimated to have medium, high or very high risk of developing T2DM in the next 10 years. Cases of T2DM estimated to occur during the 10 years of follow-up had significantly higher incidence of risk factors such as BMI ≥30 kg/m2, waist circumference 102 cm in men and 88 cm in women and a family history of T2DM and were more likely to take drugs to lower blood pressure. Conclusion. FINDRISC provided good results in our sample, and we recommend its use in the Siberian population. 

scholarly journals Assessment of risk of type 2 diabetes mellitus among rural population in Karnataka by using Indian diabetes risk score

2017 ◽  
Vol 4 (4) ◽  
pp. 1056 ◽  
Author(s):  
Radha Ramaiah ◽  
Srividya Jayarama
Keyword(s):  
Physical Activity ◽  
Rural Area ◽  
Risk Score ◽  
Rural Areas ◽  
Lifestyle Modification ◽  
Public Health Problem ◽  
Diabetes Risk ◽  
Major Public Health Problem ◽  
Cross Sectional ◽  
Diabetes Risk Score

Background: Diabetes has emerged not only as a major public health problem, but also as a global societal catastrophe. Governments worldwide are struggling to meet the cost of the diabetic care. The proportion of people with diabetes is rapidly increasing in many countries, with the documented increase in low and middle income countries. With this background a study was planned with the objective of assessing the risk of diabetes among adults in a rural area using a simple diagnostic tool. Methods: A community based, cross-sectional study was done among 485 adults aged 20 years and above residing in a rural area of Karnataka. Data collection was done by household survey by direct interview using a pretested, structured questionnaire. The questionnaire had 2 parts with part one of socio-demographic variables and part two made up of Indian diabetes risk score (IDRS) questionnaire. IDRS was developed by Mohan et al and its parameters comprise of 2 modifiable (waist circumference, physical activity) and 2 non-modifiable risk factors (age, family history) for diabetes. Analysis was done with open Epi and Microsoft excel. Results: In the present study, according to IDRS, 14.84% of the study subjects had high risk of diabetes, 73.19% had moderate risk and 11.95% had no/low risk of diabetes. Conclusions: The risk of diabetes among adults is on rise in rural areas. Physical activity likes regular exercises, diet and lifestyle modification are some of the interventions that can reduce the risk of diabetes.

Sign in / Sign up

Export Citation Format

Share Document