Use of the diabetes risk score for opportunistic screening of undiagnosed diabetes and impaired glucose tolerance: the IGLOO (Impaired Glucose Tolerance and Long-Term Outcomes Observational) study

Feasibility of a Type 2 Diabetes Prevention Program at Nationwide Level in General Practice: A Pilot Study in Italy

BACKGROUND

Lifestyle interventions halt the progression of prediabetes to frank type 2 diabetes (T2D). However, the feasibility of a diabetes prevention program promoting tailored interventions on a national scale and conducted by primary care physicians is unclear.

METHODS

General practitioners located in ten different regions throughout Italy enrolled random subjects without known metabolic diseases to identify individuals with prediabetes and prescribe them an intervention based on physical activity. Using a simple stepwise approach, people referring to their primary care physician for any reason were screened for their diabetes risk with a web-based app of the Findrisc questionnaire. Those at risk for T2D, i.e., with a Findrisc score >9, were invited to come back after overnight fasting to measure fasting glycaemia (FG). Those with 100 ≤ FG < 126 mg/dL were considered as people with prediabetes and compiled the Physical Activity Readiness Questionnaire (PAR-Q) to then receive a personalised prescription of physical activity.

RESULTS

Overall, 5928 people were enrolled and compiled the questionnaire. Of these, 2895 (48.8%) were at risk for T2D. Among these, FG was measured in 2168 subjects (participation rate 75%). The numbers of individuals with undetected prediabetes and T2D according to FG were 755 and 79 (34.8% and 3.6% of those assessing FG), respectively. Of the 755 subjects in the prediabetes range, 739 compiled the PAR-Q and started a personalised program of physical activity (participation rate 97%). Physicians involved in the study reported a mean of 6 min to perform the screening.

CONCLUSIONS

Overall, these data suggest the feasibility of a national diabetes prevention program developed by general practitioners using a simple stepwise approach starting from a web app to intercept individuals with prediabetes.

Risk of Type 2 Diabetes in University Students at the University of Extremadura: A Cross-Sectional Study

The prevalence of type 2 diabetes is increasing worldwide. The aim of our study was to detect people susceptible to DM among a university population aged 18 to 45 years and analyze the existence of modifiable risk factors in order to implement prevention programs, in addition to analyzing BMI data related to the variables under study. We proposed a descriptive, cross-sectional study following the recommendations of cross-sectional studies (STROBE), with a sample of 341 subjects, students enrolled at the University of Extremadura, carried out by two researchers. The research protocol was approved by the Bioethics Committee of the University of Extremadura (165/2021). The study considered the Findrisk questionnaire in Spanish, validated by the Blackboard Study, a stadiometer to measure height, a bioimpedance meter to evaluate weight and body composition parameters, and a blood pressure monitor to measure blood pressure. The results indicated that the participants had a low risk of suffering T2DM. The highest Findrisk test scores were found in those with a BMI value above 25, lower physical activity, poor dietary intake of fruits and vegetables, and increased fat mass. Our future research will be the implementation of T2DM prevention programs, acting on modifiable factors.

Comparisons of the prediction models for undiagnosed diabetes between machine learning versus traditional statistical methods

We compared the prediction performance of machine learning-based undiagnosed diabetes prediction models with that of traditional statistics-based prediction models. We used the 2014-2020 Korean National Health and Nutrition Examination Survey (KNHANES) (N = 32,827). The KNHANES 2014-2018 data were used as training and internal validation sets and the 2019-2020 data as external validation sets. The receiver operating characteristic curve area under the curve (AUC) was used to compare the prediction performance of the machine learning-based and the traditional statistics-based prediction models. Using sex, age, resting heart rate, and waist circumference as features, the machine learning-based model showed a higher AUC (0.788 vs. 0.740) than that of the traditional statistical-based prediction model. Using sex, age, waist circumference, family history of diabetes, hypertension, alcohol consumption, and smoking status as features, the machine learning-based prediction model showed a higher AUC (0.802 vs. 0.759) than the traditional statistical-based prediction model. The machine learning-based prediction model using features for maximum prediction performance showed a higher AUC (0.819 vs. 0.765) than the traditional statistical-based prediction model. Machine learning-based prediction models using anthropometric and lifestyle measurements may outperform the traditional statistics-based prediction models in predicting undiagnosed diabetes.

Large scale application of the Finnish diabetes risk score in Latin American and Caribbean populations: a descriptive study

Background

The prevalence of type 2 diabetes (T2D) continues to increase in the Americas. Identifying people at risk for T2D is critical to the prevention of T2D complications, especially cardiovascular disease. This study gauges the ability to implement large population-based organized screening campaigns in 19 Latin American and Caribbean countries to detect people at risk for T2D using the Finnish Diabetes Risk Score (FINDRISC).

Methods

This cross-sectional descriptive analysis uses data collected in a sample of men and women 18 years of age or older who completed FINDRISC via eHealth during a Guinness World Record attempt campaign between October 25 and November 1, 2021. FINDRISC is a non-invasive screening tool based on age, body mass index, waist circumference, physical activity, daily intake of fruits and vegetables, history of hyperglycemia, history of antihypertensive drug treatment, and family history of T2D, assigning a score ranging from 0 to 26 points. A cut-off point of ≥ 12 points was considered as high risk for T2D.

Results

The final sample size consisted of 29,662 women (63%) and 17,605 men (27%). In total, 35% of subjects were at risk of T2D. The highest frequency rates (FINDRISC ≥ 12) were observed in Chile (39%), Central America (36.4%), and Peru (36.1%). Chile also had the highest proportion of people having a FINDRISC ≥15 points (25%), whereas the lowest was observed in Colombia (11.3%).

Conclusions

FINDRISC can be easily implemented via eHealth technology over social networks in Latin American and Caribbean populations to detect people with high risk for T2D. Primary healthcare strategies are needed to perform T2D organized screening to deliver early, accessible, culturally sensitive, and sustainable interventions to prevent sequelae of T2D, and reduce the clinical and economic burden of cardiometabolic-based chronic disease.

Prevalence and predictive modeling of undiagnosed diabetes and impaired fasting glucose in Taiwan: a Taiwan Biobank study

INTRODUCTION

We investigated the prevalence of undiagnosed diabetes and impaired fasting glucose (IFG) in individuals without known diabetes in Taiwan and developed a risk prediction model for identifying undiagnosed diabetes and IFG.

RESEARCH DESIGN AND METHODS

Using data from a large population-based Taiwan Biobank study linked with the National Health Insurance Research Database, we estimated the standardized prevalence of undiagnosed diabetes and IFG between 2012 and 2020. We used the forward continuation ratio model with the Lasso penalty, modeling undiagnosed diabetes, IFG, and healthy reference group (individuals without diabetes or IFG) as three ordinal outcomes, to identify the risk factors and construct the prediction model. Two models were created: Model 1 predicts undiagnosed diabetes, IFG_110 (ie, fasting glucose between 110 mg/dL and 125 mg/dL), and the healthy reference group, while Model 2 predicts undiagnosed diabetes, IFG_100 (ie, fasting glucose between 100 mg/dL and 125 mg/dL), and the healthy reference group.

RESULTS

The standardized prevalence of undiagnosed diabetes for 2012-2014, 2015-2016, 2017-2018, and 2019-2020 was 1.11%, 0.99%, 1.16%, and 0.99%, respectively. For these periods, the standardized prevalence of IFG_110 and IFG_100 was 4.49%, 3.73%, 4.30%, and 4.66% and 21.0%, 18.26%, 20.16%, and 21.08%, respectively. Significant risk prediction factors were age, body mass index, waist to hip ratio, education level, personal monthly income, betel nut chewing, self-reported hypertension, and family history of diabetes. The area under the curve (AUC) for predicting undiagnosed diabetes in Models 1 and 2 was 80.39% and 77.87%, respectively. The AUC for predicting undiagnosed diabetes or IFG in Models 1 and 2 was 78.25% and 74.39%, respectively.

CONCLUSIONS

Our results showed the changes in the prevalence of undiagnosed diabetes and IFG. The identified risk factors and the prediction models could be helpful in identifying individuals with undiagnosed diabetes or individuals with a high risk of developing diabetes in Taiwan.

Improving screening of prediabetes and undiagnosed diabetes

BACKGROUND

Type II diabetes mellitus is a chronic medical condition affecting societies worldwide. The duration of hyperglycemia is a strong predictor of adverse outcomes and imposes immense clinical and public health concerns. The best way to prevent complications and reduce the economic burden is by capturing asymptomatic individuals early in the disease process.

LOCAL PROBLEM

Patients at a large urban academic medical center were not consistently identified as having a high risk of hyperglycemia.

METHODS

The project used a pretest-posttest design. Retrospective data on new-onset hyperglycemia incidence were compared for all individuals seeking primary care services 6 weeks before and after the intervention.

INTERVENTION

Patients without a known hyperglycemia history were provided the screening tool to determine risk status. Additional screening measures were implemented for patients identified as high risk on the initial screening.

RESULTS

A total of 52 (61.6%) of the 84 individuals who met inclusion criteria during the intervention period were diagnosed with new-onset chronic hyperglycemia. In contrast, 20 (22.5%) of the 89 individuals identified during the retrospective period resulted in a statistically significant difference ( p < .001) in the frequency and accuracy of patients diagnosed with hyperglycemia between groups.

CONCLUSION

A diabetes risk assessment tool is quick and reliable in capturing high-risk individuals who would benefit from additional screening measures.

Developing a risk assessment tool for insulin resistance in European adolescents: the HELENA-IR score

OBJECTIVES

To develop and validate an easy-to-use screening tool for identifying adolescents at high-risk for insulin resistance (IR).

METHODS

Α total of 1,053 adolescents (554 females), aged 12.5 to 17.5 years with complete data on glucose and insulin levels were included. Body mass index (BMI), fat mass index (FMI) and the homeostasis model assessment for insulin resistance (HOMA-IR) were calculated. VO₂max was predicted using 20 m multi-stage fitness test. The population was randomly separated into two cohorts for the development (n=702) and validation (n=351) of the index, respectively. Factors associated with high HOMA-IR were identified by Spearman correlation in the development cohort; multiple logistic regression was performed for all identified independent factors to develop a score index. Finally, receiver operating characteristic (ROC) analysis was performed in the validation cohort and was used to define the cut-off values that could identify adolescents above the 75th and the 95th percentile for HOMA-IR.

RESULTS

BMI and VO₂max significantly identified high HOMA-IR in males; and FMI, TV watching and VO₂max in females. The HELENA-IR index scores range from 0 to 29 for males and 0 to 43 for females. The Area Under the Curve, sensitivity and specificity for identifying males above the 75th and 95th of HOMA-IR percentiles were 0.635 (95%CI: 0.542-0.725), 0.513 and 0.735, and 0.714 (95%CI: 0.499-0.728), 0.625 and 0.905, respectively. For females, the corresponding values were 0.632 (95%CI: 0.538-0.725), 0.568 and 0.652, and 0.708 (95%CI: 0.559-0.725), 0.667 and 0.617, respectively. Simple algorithms were created using the index cut-off scores.

CONCLUSIONS

Paediatricians or physical education teachers can use easy-to-obtain and non-invasive measures to apply the HELENA-IR score and identify adolescents at high risk for IR, who should be referred for further tests.

Efficacy of an Online Educational Intervention in Reducing Body Weight in the Pre-Diabetic Population of 18-45 Years Old, a Randomized Trial Protocol

Aim: to analyze the efficacy of an educational online intervention focused on lifestyle changes in reducing body weight from baseline to 6 months in the pre-diabetic population of 18−45 years old in Extremadura (Spain). Methods: a single-blind, multicenter randomized parallel-comparison trial with two intervention groups in a 1:1 ratio will be carried out. Participants will be randomly assigned to intervention A or B with 37 cases in each group according to inclusion criteria of being enrolled or working at Extremadura University, scoring >7 points on the Findrisc test and not having diagnosed diabetes mellitus or physical disabilities. Intervention-A group will have access to online information about healthy diet and exercise. Intervention-B group will have access to a six-session educational program regarding behavioral changes in diet and exercise habits. They will complete follow-up activities and have a personal trainer and motivation. The primary outcome will be identifying changes in body weight from baseline to 1 and 6 months and between groups. The secondary outcomes will be accomplishing regular physical activity (>30 min/day or >4 h/week), decreasing sugary food intake or avoiding it altogether, increasing vegetable/fruit intake and lowering HbA1c levels to non-diabetic status when necessary.

Lower miR-21/ROS/HNE levels associate with lower glycemia after habit-intervention: DIAPASON study 1-year later

Background

The prevalence of prediabetes is increasing in the global population and its metabolic derangements may expose to a higher risk to develop type 2 diabetes (T2D) and its cardiovascular burden. Lifestyle modifications might have considerable benefits on ameliorating metabolic status. Alternative biomarkers, such as circulating miR-21, has been recently discovered associated with dysglycemia. Here we evaluated, in a longitudinal cohort of dysglycemic population the relation between the circulating miR-21/ROS/HNE levels and the habit-intervention (HI) after 1 year of follow-up.

Methods

1506 subjects from DIAPASON study were screened based on the Findrisc score. Of them, 531 subjects with Findrisc ≥ 9 were selected for dysglycemia (ADA criteria) and tested for circulating miR-21, ROS and HNE levels, as damaging-axis. 207 subjects with dysglycemia were re-evaluated after 1-year of habit intervention (HI). Repeated measures tests were used to evaluate changes from baseline to 1-year of follow-up. The associations between glycemic parameters and miR-21/ROS/HNE were implemented by linear regression and logistic regression models.

Results

After HI, we observed a significant reduction of miR-21/ROS/HNE axis in dysglycemic subjects, concomitantly with ameliorating of metabolic parameters, including insulin resistance, BMI, microalbuminuria, reactive hyperemia index and skin fluorescence. Significant positive interaction was observed between miR-21 axis with glycaemic parameters after HI. Lower miR-21 levels after HI, strongly associated with a reduction of glycemic damaging-axis, in particular, within-subjects with values of 2hPG < 200 mg/dL.

Conclusions

Our findings demonstrated that HI influenced the epigenetic changes related to miR-21 axis, and sustain the concept of reversibility from dysglycemia. These data support the usefulness of novel biological approaches for monitoring glycemia as well as provide a screening tool for preventive programmes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01465-0.

High rates of undiagnosed diabetes mellitus among patients with active tuberculosis in Addis Ababa, Ethiopia

Background

Tuberculosis (TB) and diabetes mellitus (DM) have negative synergistic impact on each other. Global guidelines recommend collaborative efforts to address this synergy, but implementation has been slow. Part of the reason is lack of adequate evidence on the operational feasibility of existing tools and mechanisms of collaboration. The objective of this study was to assess the yield of DM screening among TB patients using risk scoring tools combined with blood tests as a feasible strategy for early detection to improve TB/DM treatment outcomes.

Methods

Between September 2020 and December 2021, we conducted a cross-sectional study among patients receiving TB treatment in public health facilities in Addis Ababa, Ethiopia. Trained health workers collected data on symptoms and risk scoring checklists before testing for random and fasting blood glucose levels. We used logistic regression analyses techniques to determine factors associated with increased DM detection. A receiver-operating characteristic curve was constructed to determine the performance of the risk scoring checklist.

Results

Of 2381 TB patients screened, 197 (8.3%) had DM of which 48.7% were newly diagnosed. Having a family history of DM predicted DM with Odds Ratio (OR) of 5.36 (95% Confidence Interval, [3.67, 7.83]) followed by age ≥ 45 years (OR = 4.64, [3.18, 6.76]). Having one or more “symptoms” of DM was a significant predictor (OR 2.88, 95% CI, 2.06–4.01). Combining risk scores with symptoms predicted DM diagnosis with sensitivity of 94.7%, but specificity was low at 29.4%. In patients with known treatment outcome status, death rate was high.

Conclusions

Almost a half of TB patients with DM did not know their status. A simple tool that combined risk factors with symptoms accurately predicted a subsequent diagnosis of DM. Such tools can help avoid high rates of death among TB patients suffering from DM through early detection.

Predictors of diabetes risk in urban and rural areas in Colombia

Background

Nutritional habits low in fruits and vegetables and sedentary lifestyle are associated with a higher risk of developing Type 2 Diabetes (T2D). However, it is important to assess differences between urban and rural areas. This study aimed to analyze the associations between the risk of developing T2D and setting in the Colombian north coast in 2017.

Methods

This cross-sectional study included 1,005 subjects. Data was collected by interviewing self-identified members of an urban community and a rural-indigenous population. The interaction terms were evaluated as well as the confounders. Then, adjusted binary logistic regressions were used to estimate the odds ratio (OR) and 95% Confidence Intervals (CI).

Results

subjects with a high risk of T2D are more likely to belong to the urban setting (OR = 1.908; 95%CI = 1.201–2.01) compared with those with lower T2D after adjusting for age, Body Mass Index (BMI), physical activity, history of high levels of glycemia, and diabetes in relatives.

Conclusions

Urban communities are more likely to have T2D compared with rural-indigenous populations. These populations have differences from the cultural context, including personal, and lifestyle factors.

Comparison of the Finnish Diabetes Risk Score Model With the Metabolic Syndrome in a Shanghai Population

AIMS

This study aimed to compare the diagnostic accuracy of the metabolic syndrome with the Finnish Diabetes Risk Score (FINDRISC) to screen for type 2 diabetes mellitus (T2DM) in a Shanghai population.

METHODS

Participants aged 25-64 years were recruited from a Shanghai population from July 2019 to March 2020. Each participant underwent a standard metabolic work-up, including clinical examination with anthropometry. Glucose status was tested using hemoglobin A1c (HbAlc), 2h-post-load glucose (2hPG), and fasting blood glucose (FBG). The FINDRISC questionnaire and the metabolic syndrome were examined. The performance of the FINDRISC was assessed using the area under the receiver operating characteristic curve (AUC-ROC).

RESULTS

Of the 713 subjects, 9.1% were diagnosed with prediabetes, whereas 5.2% were diagnosed with T2DM. A total of 172 subjects had the metabolic syndrome. A higher FINDRISC score was positively associated with the prevalence of T2DM and the metabolic syndrome. Multivariable linear regression analysis demonstrated that the FINDRISC had a linear regression relationship with 2hPG levels (b'= 036, p < 0.0001). The AUC-ROC of the FINDRISC to identify subjects with T2DM among the total population was 0.708 (95% CI 0.639-0.776), the sensitivity was 44.6%, and the specificity was 90.1%, with 11 as the cut-off point. After adding FBG or 2hPG to the FINDRISC, the AUC-ROC among the total population significantly increased to 0.785 (95% CI 0.671-0.899) and 0.731 (95% CI 0.619-0.843), respectively, while the AUC-ROC among the female group increased to 0.858 (95% CI 0.753-0.964) and 0.823 (95% CI 0.730-0.916), respectively (p < 0.001). The AUC-ROC of the metabolic syndrome to identify subjects with T2DM among the total and female population was 0.805 (95% CI 0.767-0.844) and 0.830 (95% CI 0.788-0.872), respectively, with seven as the cut-off point.

CONCLUSIONS

The metabolic syndrome performed better than the FINDRISC model. The metabolic syndrome and the FINDRISC with FBG or 2hPG in a two-step screening model are both efficacious clinical practices for predicting T2DM in a Shanghai population.

Health-related quality of life (HRQoL) in a population at risk of type 2 diabetes: a cross-sectional study in two Latin American cities

Purpose

The purpose of this study was to describe the health-related quality of life (HRQoL) characteristics in a population at risk of developing type 2 diabetes in Barranquilla and Bogotá, Colombia.

Methods

A cross-sectional study with 1135 participants older than 30 years-of-age recruited in Bogotá D.C., and Barranquilla by cluster sampling in 2018 to 2019. The Finnish Diabetes Risk Score (FINDRISC) was used to detect participants at risk of developing type 2 diabetes (T2D). HRQoL was assessed using the EQ-5D-3L questionnaire. Unadjusted and adjusted logistic regression models were used to calculate odds ratios (OR) and their corresponding 95% confidence intervals CI).

Results

Moderate or extreme problems appeared more frequently in the dimensions of Pain/Discomfort (60.8%) and Anxiety/Depression (30.8%). The mean score of the EQ-VAS was 74.3 (± 17.3), significantly larger in the state of complete health (11111) compared with those with problems in more than one of the quality-of-life dimensions. Being female and living in Bogota D.C., were associated with greater odds of reporting problems in the Pain (OR 1.6; 95% CI 1.2–2.2) and Discomfort dimensions (OR 1.6; 95% CI 1.2–2.0) respectively and Anxiety/Depression (OR 1.9; 95% CI 1.3–2.7), (OR 9.1; 95% CI 6.6–12.4), respectively.

Conclusions

As living place and sex were associated with dimensions of Pain/Discomfort and Anxiety/Depression in the HRQoL in people at risk of T2D, greater attention should be paid to these determinants of HRQoL to design and reorient strategies with a territorial and gender perspective to achieve better health outcomes.

Plain English summary

Diabetes is one of the four non-communicable diseases with increasing prevalence in the world, which has made it a serious public health problem. In Colombia, in 2019 diabetes affected 8.4% of the Colombian adult population and more than one million Colombian adults of this age group have hidden or undetected diabetes. This disease is not only characterized by increased premature mortality, loss of productivity, and economic impact, but it also involves a deterioration in the quality of life of people with diabetes with their respective families. However, very Little is known about health-related quality of life (HRQoL) in a population at risk or with prediabetes. This study has evaluated the quality of life in patients at risk of diabetes and their behavior with some variables as sociodemographic, lifestyle, history, and established their difference in two territories of the Colombian Caribbean. The results of this study indicate that the HRQoL of people at risk of type 2 diabetes is affected by factors such as gender, city, dysglycemia, medication for hypertension and education level. Therefore, greater attention should be paid to these determinants of HRQL to design and implement strategies that reduce this risk of developing type 2 diabetes, prevent prediabetes and improve the quality of life in prediabetic or diabetic patients.

A Fusion-Based Machine Learning Approach for the Prediction of the Onset of Diabetes

A growing portfolio of research has been reported on the use of machine learning-based architectures and models in the domain of healthcare. The development of data-driven applications and services for the diagnosis and classification of key illness conditions is challenging owing to issues of low volume, low-quality contextual data for the training, and validation of algorithms, which, in turn, compromises the accuracy of the resultant models. Here, a fusion machine learning approach is presented reporting an improvement in the accuracy of the identification of diabetes and the prediction of the onset of critical events for patients with diabetes (PwD). Globally, the cost of treating diabetes, a prevalent chronic illness condition characterized by high levels of sugar in the bloodstream over long periods, is placing severe demands on health providers and the proposed solution has the potential to support an increase in the rates of survival of PwD through informing on the optimum treatment on an individual patient basis. At the core of the proposed architecture is a fusion of machine learning classifiers (Support Vector Machine and Artificial Neural Network). Results indicate a classification accuracy of 94.67%, exceeding the performance of reported machine learning models for diabetes by ~1.8% over the best reported to date.

The Association Between Dietary Habits and Other Lifestyle Indicators and Dysglycemia in Saudi Adults Free of Previous Diagnosis of Diabetes

Objective:

Study the association of dietary habits and other indicators of lifestyle with dysglycemia in Saudi adults.

Methods:

In a cross-sectional design, data were obtained from 1403 Saudi adults (⩾20 years), not previously diagnosed with diabetes. Demographics, lifestyle variables and dietary habits were obtained using a predesigned questionnaire. Fasting plasma glucose, glycated hemoglobin and 1-hour oral glucose tolerance test were used to identify dysglycemia. Regression analysis was performed to determine the associations of dietary factors and other indicators of lifestyle with dysglycemia.

Results:

A total 1075 adults (596 men, and 479 women) had normoglycemia, and 328 (195 men, and 133 women) had dysglycemia. Following adjustment for age, BMI and waist circumference, in men the weekly intake of 5 portions or more of red meat and Turkish coffee were associated with decreased odds of having dysglycemia odds ratio (OR) 0.444 (95% CI: 0.223, 0.881; P = .02) and 0.387 (95% CI: 0.202, 0.74; P = .004), respectively. In women, the intake of fresh juice 1 to 4 portions per week and 5 portions or more were associated with OR 0.603 (95% CI: 0.369, 0.985; P = .043) and OR 0.511 (95% CI: 0.279, 0.935; P = .029) decreased odds of having dysglycemia, respectively compared with women who did not drink fresh juice. The intake of 5 times or more per week of hibiscus drink was associated with increased odds of having dysglycemia, OR 5.551 (95% CI: 1.576, 19.55, P = .008) compared with women not using such a drink. Other lifestyle factors were not associated with dysglycemia.

Conclusion:

Dietary practices by studied Saudis have some impact on risk of dysglycemia, with obvious sex differences.

Performance of the Finnish Diabetes Risk Score (FINDRISC) and Modified Asian FINDRISC (ModAsian FINDRISC) for screening of undiagnosed type 2 diabetes mellitus and dysglycaemia in primary care

AIMS

To evaluate the performance of FINDRISC and ModAsian FINDRISC for the screening of undiagnosed diabetes and dysglycaemia in primary care. To compare the performance of FINDRISC with the recommendations of the American Diabetes Association (ADA) and US Preventive Services Task Force (USPSTF) guidelines.

METHODS

This cross-sectional study was carried out on 293 patients without a prior history of diabetes at a primary care clinic in Malaysia. Questions on body mass index and waist circumference were modified based on the Asian standard in ModAsian FINDRISC. Haemoglobin A1c of ≥6.5% (48 mmol/mol) was used to diagnose diabetes. Areas under the receiver operating curve (ROC-AUC) for FINDRISC and ModAsian FINDRISC were analyzed.

RESULTS

The prevalence of undiagnosed diabetes was 7.5% and prediabetes was 32.8%. The ROC-AUC of FINDRISC was 0.76 (undiagnosed diabetes) and 0.79 (dysglycaemia). There was no statistical difference between FINDRISC and ModAsian FINDRISC. The recommended optimal FINDRISC cut-off point for undiagnosed diabetes was ≥11 (Sensitivity 86.4%, Specificity 48.7%). FINDRISC ≥11 point has higher sensitivity compared to USPSTF criteria (72.7%) and higher specificity compared to the ADA (9.6%).

CONCLUSIONS

FINDRISC is a useful diabetes screening tool to identify those at risk of diabetes in primary care in Malaysia.

One-hour plasma glucose combined with skin autofluorescence identifies subjects with pre-diabetes: the DIAPASON study

INTRODUCTION

The major challenge for diabetes prevention is early identification of individuals at risk to allow for implementation of measures to delay the onset of future disease. Measures such as fasting plasma glucose (FPG), 2-hour plasma glucose (2hPG), and glycosylated hemoglobin (HbA1c) are equally appropriate for identifying pre-diabetes and diabetes, but do not all identify the disease in the same individual. We tested the utility of a diagnostic method combining FPG, 2hPG and HbA1c for early evaluation and easy identification of pre-diabetes.

RESEARCH DESIGN AND METHODS

531 subjects underwent skin autofluorescence (SAF) and glycemia analyses. We created two classification groups based on the American Diabetes Association diagnosis guidelines: (1) based on 2hPG and (2) based on a new combination of three glycemia parameters (the three-criteria strategy (3-c)). Logistic regression modeling was used to estimate the associations.

RESULTS

SAF showed high associations for both 3-c definition and 2hPG definition alone. These associations appeared stronger in 3-c than those in 2hPG. The non-invasive SAF measurement outperformed 2hPG in the detection of dysglycemia or pre-diabetes. Stepwise selections identified 1-hour postload glucose (1hPG) as variable identifying pre-diabetes using the 2hPG criterion, and the model based on 1hPG plus SAF appeared to be the best association using the 3-c strategy.

CONCLUSIONS

1hPG coupled with SAF showed a strong association in the evaluation of pre-diabetes using the 3-c method.

The Association between Dyslipidemia, Dietary Habits and Other Lifestyle Indicators among Non-Diabetic Attendees of Primary Health Care Centers in Jeddah, Saudi Arabia

Diet and other lifestyle habits have been reported to contribute to the development of dyslipidemia in various populations. Therefore, this study investigated the association between dyslipidemia and dietary and other lifestyle practices among Saudi adults. Data were collected from adults (≥20 years) not previously diagnosed with diabetes in a cross-sectional design. Demographic, anthropometric, and clinical characteristics, as well as lifestyle and dietary habits were recorded using a predesigned questionnaire. Fasting blood samples were drawn to estimate the serum lipid profile. Out of 1385 people, 858 (62%) (491 men, 367 women) had dyslipidemia. After regression analysis to adjust for age, body mass index, and waist circumference, an intake of ≥5 cups/week of Turkish coffee, or carbonated drinks was associated with increased risk of dyslipidemia in men (OR (95% CI), 2.74 (1.53, 4.89) p = 0.001, and 1.53 (1.04, 2.26) p = 0.03 respectively), while the same intake of American coffee had a protective effect (0.53 (0.30, 0.92) p = 0.025). Sleep duration <6 h, and smoking were also associated with increased risk in men (1.573 (1.14, 2.18) p = 0.006, and 1.41 (1.00, 1.99) p = 0.043 respectively). In women, an increased intake of fresh vegetables was associated with increased risk (2.07 (1.09, 3.94) p = 0.026), which could be attributed to added salad dressing. Thus, there are sex differences in response to dietary and lifestyle practices.

Diabetes mellitus risk among Jordanians in a dental setting: a cross-sectional study

BACKGROUND

Dental offices can be useful to screen and identify patients at risk of developing diabetes mellitus (DM) using risk prediction tools. The Finnish Diabetes Risk Score (FINDRISC) is a validated, questionnaire-based tool used to predict the 10-year risk of developing type II DM.

OBJECTIVES

To determine the 10-year DM risk among Jordanians using the FINDRISC questionnaire in a dental setting.

MATERIALS AND METHODS

Participants attending two university dental teaching centres between March 2017 and February 2018 were interviewed using an Arabic translated version of the FINDRISC questionnaire. Anthropometrics including weight, height, waist circumference (WC) and body mass index (BMI) were recorded. Random capillary blood glucose level was measured for each participant. Statistical analysis was done using Chi-square and independent t-tests.

RESULTS

A total of 1,247 (436 males and 811 females) participants were included. As defined by BMI, 1,012 (81.2%) participants were either overweight or obese. Abdominal adiposity as determined by WC was seen in 738 (59.2%) participants. The mean (± SD) FINDRISC score for females (11.3 ± 4.3) was significantly higher (P = 0.001) than males (10.4 ± 4.9). After age adjustment, more females were in the high-risk categories (FINDRISC ≥ 15) compared with males. This trend was seen among all age groups, but was statistically significant in the older age groups; 55-64 years (P = 0.037) and ≥ 65 years (P = 0.004).

CONCLUSION

In a developing Middle Eastern country such as Jordan, almost half of Jordanians attending university dental clinics are at a moderate to high risk of developing type II DM in 10 years. The risk of DM should be considered in dental patients, particularly older females.

Dysglycemia risk score in Saudi Arabia: A tool to identify people at high future risk of developing type 2 diabetes

AIMS/INTRODUCTION

To develop a non-invasive risk score to identify Saudis having prediabetes or undiagnosed type 2 diabetes.

METHODS

Adult Saudis without diabetes were recruited randomly using a stratified two-stage cluster sampling method. Demographic, dietary, lifestyle variables, personal and family medical history were collected using a questionnaire. Blood pressure and anthropometric measurements were taken. Body mass index was calculated. The 1-h oral glucose tolerance test was carried out. Glycated hemoglobin, fasting and 1-h plasma glucose were measured, and obtained values were used to define prediabetes and type 2 diabetes (dysglycemia). Logistic regression models were used for assessing the association between various factors and dysglycemia, and Hosmer-Lemeshow summary statistics were used to assess the goodness-of-fit.

RESULTS

A total of 791 men and 612 women were included, of whom 69 were found to have diabetes, and 259 had prediabetes. The prevalence of dysglycemia was 23%, increasing with age, reaching 71% in adults aged ≥65 years. In univariate analysis age, body mass index, waist circumference, use of antihypertensive medication, history of hyperglycemia, low physical activity, short sleep and family history of diabetes were statistically significant. The final model for the Saudi Diabetes Risk Score constituted sex, age, waist circumference, history of hyperglycemia and family history of diabetes, with the score ranging from 0 to 15. Its fit based on assessment using the receiver operating characteristic curve was good, with an area under the curve of 0.76 (95% confidence interval 0.73-0.79). The proposed cut-point for dysglycemia is 5 or 6, with sensitivity and specificity being approximately 0.7.

CONCLUSION

The Saudi Diabetes Risk Score is a simple tool that can effectively distinguish Saudis at high risk of dysglycemia.

Intelligent Machine Learning Approach for Effective Recognition of Diabetes in E-Healthcare Using Clinical Data

Significant attention has been paid to the accurate detection of diabetes. It is a big challenge for the research community to develop a diagnosis system to detect diabetes in a successful way in the e-healthcare environment. Machine learning techniques have an emerging role in healthcare services by delivering a system to analyze the medical data for diagnosis of diseases. The existing diagnosis systems have some drawbacks, such as high computation time, and low prediction accuracy. To handle these issues, we have proposed a diagnosis system using machine learning methods for the detection of diabetes. The proposed method has been tested on the diabetes data set which is a clinical dataset designed from patient's clinical history. Further, model validation methods, such as hold out, K-fold, leave one subject out and performance evaluation metrics, includes accuracy, specificity, sensitivity, F1-score, receiver operating characteristic curve, and execution time have been used to check the validity of the proposed system. We have proposed a filter method based on the Decision Tree (Iterative Dichotomiser 3) algorithm for highly important feature selection. Two ensemble learning algorithms, Ada Boost and Random Forest, are also used for feature selection and we also compared the classifier performance with wrapper based feature selection algorithms. Classifier Decision Tree has been used for the classification of healthy and diabetic subjects. The experimental results show that the proposed feature selection algorithm selected features improve the classification performance of the predictive model and achieved optimal accuracy. Additionally, the proposed system performance is high compared to the previous state-of-the-art methods. High performance of the proposed method is due to the different combinations of selected features set and Plasma glucose concentrations, Diabetes pedigree function, and Blood mass index are more significantly important features in the dataset for prediction of diabetes. Furthermore, the experimental results statistical analysis demonstrated that the proposed method would effectively detect diabetes and can be deployed in an e-healthcare environment.

Development and Validation of Two Self-Reported Tools for Insulin Resistance and Hypertension Risk Assessment in A European Cohort: The Feel4Diabetes-Study

Early identification of type 2 diabetes mellitus (T2DM) and hypertension (HTN) risk may improve prevention and promote public health. Implementation of self-reported scores for risk assessment provides an alternative cost-effective tool. The study aimed to develop and validate two easy-to-apply screening tools identifying high-risk individuals for insulin resistance (IR) and HTN in a European cohort. Sociodemographic, lifestyle, anthropometric and clinical data obtained from 1581 and 1350 adults (baseline data from the Feel4Diabetes-study) were used for the European IR and the European HTN risk assessment index respectively. Body mass index, waist circumference, sex, age, breakfast consumption, alcohol, legumes and sugary drinks intake, physical activity and sedentary behavior were significantly correlated with Homeostatic Model Assessment of IR (HOMA-IR) and/or HTN and incorporated in the two models. For the IR index, the Area Under the Curve (AUC), sensitivity and specificity for identifying individuals above the 75th and 95th of HOMA-IR percentiles were 0.768 (95%CI: 0.721-0.815), 0.720 and 0.691 and 0.828 (95%CI: 0.766-0.890), 0.696 and 0.778 respectively. For the HTN index, the AUC, sensitivity and specificity were 0.778 (95%CI: 0.680-0.876), 0.667 and 0.797. The developed risk assessment tools are easy-to-apply, valid, and low-cost, identifying European adults at high risk for developing T2DM or having HTN.

Opportunistic screening for type 2 diabetes in community pharmacies. Results from a region-wide experience in Italy

Background and aims

Given the paucity of symptoms in the early stages of type 2 diabetes, its diagnosis is often made when complications have already arisen. Although systematic population-based screening is not recommended, there is room to experience new strategies for improving early diagnosis of the disease in high risk subjects. We report the results of an opportunistic screening for diabetes, implemented in the setting of community pharmacies.

Methods and results

To identify people at high risk to develop diabetes, pharmacists were trained to administer FINDRISC questionnaire to overweight, diabetes-free customers aged 45 or more. Each interviewee was followed for 365 days, searching in the administrative database whether he/she had a glycaemic or HbA1c test, or a diabetologists consultation, and to detect any new diagnosis of diabetes defined by either a prescription of any anti-hyperglycaemic drug, or the enrolment in the register of patients, or a hospital discharge with a diagnosis of diabetes.

Out of 5977 interviewees, 53% were at risk of developing diabetes. An elevated FINDRISC score was associated with higher age, lower education, and living alone. Excluding the number of cases expected, based on the incidence rate of diabetes in the population, 51 new cases were identified, one every 117 interviews. FINDRISC score, being a male and living alone were significantly associated with the diagnosis.

Conclusions

The implementation of a community pharmacy-based screening programme can contribute to reduce the burden of the disease, particularly focusing on people at higher risk, such as the elderly and the socially vulnerable.

Two-stage, school and community-based population screening successfully identifies individuals and families at high-risk for type 2 diabetes: the Feel4Diabetes-study

BACKGROUND

The implementation of population screening and early prevention strategies targeting individuals at high-risk for type 2 diabetes (T2D) seems to be a public health priority. The current work aimed to describe the screening procedure applied in the Feel4Diabetes-study and examine its effectiveness in identifying individuals and families at high risk, primarily for T2D and secondarily for hypertension, among vulnerable populations in low to middle-income countries (LMICs) and high-income countries (HICs) across Europe.

METHODS

A two-stage screening procedure, using primary schools as the entry-point to the community, was applied in low socioeconomic status (SES) regions in LMICs (Bulgaria-Hungary), HICs (Belgium-Finland) and HICs under austerity measures (Greece-Spain). During the first-stage screening via the school-setting, a total of 20,501 parents (mothers and/or fathers) of schoolchildren from 11,396 families completed the Finnish Diabetes Risk Score (FINDRISC) questionnaire, while their children underwent anthropometric measurements in the school setting. Parents from the identified "high-risk families" (n = 4484) were invited to participate in the second-stage screening, including the measurement of fasting plasma glucose (FPG) and blood pressure (BP). In total, 3153 parents participated in the second-stage screening (mean age 41.1 ± 5.6 years, 65.8% females).

RESULTS

Among parents who attended the second-stage screening, the prevalence of prediabetes (as defined by impaired fasting glucose; FPG 100-125 mg/dl) and T2D (FPG > 126 mg/dl) was 23.2 and 3.0% respectively, and it was found to be higher in the higher FINDRISC categories. The percentage of undiagnosed T2D among the participants identified with T2D was 53.5%. The prevalence of high normal BP (systolic BP 130-139 mmHg and/ or diastolic BP 85-89 mmHg) and hypertension (systolic BP ≥ 140 mmHg and/ or diastolic BP ≥ 90 mmHg) was 14 and 18.6% respectively, which was also higher in the higher FINDRISC categories. The percentage of cases not receiving antihypertensive treatment among the participants identified with hypertension was 80.3%.

CONCLUSION

The findings of the current study indicate that the two-stage school and community-based screening procedure followed, effectively identified high-risk individuals and families in vulnerable populations across Europe. This approach could be potentially scalable and sustainable and support initiatives for the early prevention of T2D and hypertension.

TRIAL REGISTRATION

The Feel4Diabetes-intervention is registered at https://clinicaltrials.gov/ (NCT02393872; date of trial registration: March 20, 2015).

Diabetes diagnosis from administrative claims and estimation of the true prevalence of diabetes among 4.2 million individuals of the Veneto region (North East Italy)

BACKGROUND AND AIMS

Diabetes can often remain undiagnosed or unregistered in administrative databases long after its onset, even when laboratory test results meet diagnostic criteria. In the present work, we analyse healthcare data of the Veneto Region, North East Italy, with the aims of: (i) developing an algorithm for the identification of diabetes from administrative claims (4,236,007 citizens), (ii) assessing its reliability by comparing its performance with the gold standard clinical diagnosis from a clinical database (7525 patients), (iii) combining the algorithm and the laboratory data of the regional Health Information Exchange (rHIE) system (543,520 subjects) to identify undiagnosed diabetes, and (iv) providing a credible estimate of the true prevalence of diabetes in Veneto.

METHODS AND RESULTS

The proposed algorithm for the identification of diabetes was fed by administrative data related to drug dispensations, outpatient visits, and hospitalisations. Evaluated against a clinical database, the algorithm achieved 95.7% sensitivity, 87.9% specificity, and 97.6% precision. To identify possible cases of undiagnosed diabetes, we applied standard diagnostic criteria to the laboratory test results of the subjects who, according to the algorithm, had no diabetes-related claims. Using a simplified probabilistic model, we corrected our claims-based estimate of known diabetes (6.17% prevalence; 261,303 cases) to account for undiagnosed cases, yielding an estimated total prevalence of 7.50%.

CONCLUSION

We herein validated an algorithm for the diagnosis of diabetes using administrative claims against the clinical diagnosis. Together with rHIE laboratory data, this allowed to identify possibly undiagnosed diabetes and estimate the true prevalence of diabetes in Veneto.

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

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.

The FINDRISC questionnaire capacity to predict diabetes mellitus II, arterial hypertension and comorbidity in women from low-and-middle-income countries

The Finnish Diabetes Risk Score (FINDRISC) has been implemented to assess diabetes risk. The authors aimed in this study to determine the prediction capacity of FINDRISC for the early detection of cardiovascular diseases in women. A prevalence study was carried out on 441 women of Pueblo Libre (Peru). Anthropometric variables, blood pressure, blood glucose and comorbidity were measured and entered in FINDRISC. 4.8% of the studied women suffered from DM2, 14.3% from AHT, 33% obesity and 8.6% comorbidity. We found that FINDRISC was the best method to discriminate DM, AHT and comorbidity. FINDRISC is an effective non-invasive tool for women from low-and-middle-income countries.

Early Lifestyle Interventions in People with Impaired Glucose Tolerance in Northern Colombia: The DEMOJUAN Project

BACKGROUND

The objective of the demonstration project for type 2 diabetes prevention in the Barranquilla and Juan Mina (DEMOJUAN) study was to investigate the extent to which it is possible to reach normal glucose metabolism with early lifestyle interventions in people at high risk of type 2 diabetes (prediabetes), compared with those who receive standard usual care.

METHODS

DEMOJUAN was a randomized controlled trial conducted in Juan Mina and Barranquilla, Northern Colombia. Eligible participants were randomized into one of three groups (control group, initial nutritional intervention, and initial physical activity intervention). The duration of the intervention was 24 months. The main study outcome in the present analysis was reversion to normoglycemia. Relative risks and their corresponding 95% confidence intervals were calculated for reversal to normoglycemia and T2D incidence.

RESULTS

There was no statistically significant association between the intervention groups and reversion to normoglycemia. The relative risk of reversion to normoglycemia was 0.88 (95% CI 0.70-1.12) for the initial nutritional intervention group participants and 0.95 (95% CI 0.75-1.20) for the initial physical activity intervention group participants.

CONCLUSIONS

Our study did not find any statistically significant differences in reversion to normoglycemia or the development of type 2 diabetes between the intervention groups and the control group in this population.

Evaluation of the Finnish Diabetes Risk Score as a screening tool for undiagnosed type 2 diabetes and dysglycaemia among early middle-aged adults in a large-scale European cohort. The Feel4Diabetes-study

AIM

To assess the diagnostic accuracy of the FINDRISC for undiagnosed type 2 diabetes mellitus (T2DM) and dysglycaemia (i.e. the presence of prediabetes or T2DM) among early middle-aged adults from vulnerable groups in a large-scale European cohort.

METHODS

Participants were recruited from low-socioeconomic areas in high-income countries (HICs) (Belgium-Finland) and in HICs under austerity measures (Greece-Spain) and from the overall population in low/middle-income countries (LMICs) (Bulgaria-Hungary). Study population comprised of 2116 parents of primary-school children from families identified at increased risk of T2DM, based on parental self-reported FINDRISC. Sensitivity (Se), specificity (Sp), area under the receiver operating characteristic curves (AUC-ROC) and the optimal cut-offs of FINDRISC that indicate an increased probability for undiagnosed T2DM or dysglycaemia were calculated.

RESULTS

The AUC-ROC for undiagnosed T2DM was 0.824 with optimal cut-off ≥14 (Se = 68%, Sp = 81.7%) for the total sample, 0.839 with optimal cut-off ≥15 (Se = 83.3%, Sp = 86.9%) for HICs, 0.794 with optimal cut-off ≥12 (Se = 83.3%, Sp = 61.1%) for HICs under austerity measures and 0.882 with optimal cut-off ≥14 (Se = 71.4%, Sp = 87.8%) for LMICs. The AUC-ROC for dysglycaemia was 0.663 with optimal cut-off ≥12 (Se = 58.3%, Sp = 65.7%) for the total sample, 0.656 with optimal cut-off ≥12 (Se = 54.5%, Sp = 64.8%) for HICs, 0.631 with optimal cut-off ≥12 (Se = 59.7%, Sp = 62.0%) for HICs under austerity measures and 0.735 with optimal cut-off ≥11 (Se = 72.7%, Sp = 70.2%) for LMICs.

CONCLUSION

FINDRISC can be applied for screening primarily undiagnosed T2DM but also dysglycaemia among vulnerable groups across Europe, considering the use of different cut-offs for each subpopulation.

Circulating microRNA-21 is an early predictor of ROS-mediated damage in subjects with high risk of developing diabetes and in drug-naïve T2D

BACKGROUND

Impaired glucose tolerance (IGT) is a risk factor for the development of diabetes and related complications that ensue. Early identification of at-risk individuals might be beneficial to reduce or delay the progression of diabetes and its related complications. Recently, microRNAs emerged as potential biomarkers of diseases. The aim of the present study was to evaluate microRNA-21 as a potential biomarker for the risk of developing diabetes in adults with IGT and to investigate its downstream effects as the generation of reactive oxygen species (ROS), the induction of manganese-superoxide dismutase-2 (SOD2), and the circulating levels of 4-HNE (4-hydroxynonenal).

METHODS

To evaluate the prognostic and predictive values of plasmatic microRNA-21 in identifying metabolic derangements, we tested a selected cohort (n = 115) of subjects enrolled in the DIAPASON Study, whom were selected on ADA criteria for 2hPG. Statistical analysis was performed using ANOVA or the Kruskal-Wallis test as appropriate. ROC curves were drawn for diagnostic accuracy of the tests; positive and negative predictive values were performed, and Youden's index was used to seek the cut-off optimum truncation point. ROS, SOD2 and 4-HNE were also evaluated.

RESULTS

We observed significant upregulation of microRNA-21 in IGT and in T2D subjects, and microRNA-21 was positively correlated with glycaemic parameters. Diagnostic performance of microRNA-21 was high and accurate. We detected significant overproduction of ROS by electron paramagnetic resonance (EPR), significant accumulation of the lipid peroxidation marker 4-HNE, and defective SOD2 antioxidant response in IGT and newly diagnosed, drug-naïve T2D subjects. In addition, ROC curves demonstrated the diagnostic accuracy of markers used.

CONCLUSIONS

our data demonstrate that microRNA-21 is associated with prediabetic status and exhibits predictive value for early detection of glucose imbalances. These data could provide novel clues for miR-based biomarkers to evaluate diabetes.

FINDRISC Modified for Latin America as a Screening Tool for Persons with Impaired Glucose Metabolism in Ciudad Bolívar, Venezuela

OBJECTIVE

The Finnish Diabetes Risk Score (FINDRISC) includes anthropometric, metabolic, and lifestyle factors that predict type 2 diabetes mellitus. The objective of this study was to evaluate the FINDRISC modified for Latin America (LA-FINDRISC) as a screening tool for persons with impaired glucose metabolism in Ciudad Bolívar, Venezuela.

METHODS

Subjects aged between 18 and 70 years of both sexes without known diabetes were invited to participate. After informed consent, they were screened with the LA-FINDRISC questionnaire and then given an oral glucose tolerance test, using the American Diabetes Association criteria for diagnosis. To obtain the cutoff point of LA-FINDRISC for predicting impaired glucose regulation, a receiver operating characteristic curve was constructed.

RESULTS

A total of 200 subjects were evaluated, 64.5% female, with a mean age of 35.20 ± 13.84 years. Of these, 158 (79%) did not present with carbohydrate metabolism disorder, while 42 (21%) did. Age (p = 0.0001), body mass index (p = 0.011), and waist circumference (p = 0.031) were significantly higher in subjects with impaired glucose regulation when compared to those without it. There were a significantly greater number of sedentary (p = 0.039) and hypertensive subjects (p = 0.0001), as well as those with a history of glucose >100 mg/dL (p = 0.0001), in the impaired glucose metabolism group. A cutoff LA-FINDRISC of 14 points predicted a high risk of impaired glucose regulation with a sensitivity of 45.2% and a specificity of 89.9%.

CONCLUSION

A LA-FINDRISC >14 points had low sensitivity but high specificity for predicting carbohydrate metabolism disorders in this group of patients from Ciudad Bolívar.

Validity of the FINDRISC as a prediction tool for diabetes in a contemporary Norwegian population: a 10-year follow-up of the HUNT study

OBJECTIVE

The Finnish Diabetes Risk Score (FINDRISC) is a recommended tool for type 2 diabetes prediction. There is a lack of studies examining the performance of the current 0-26 point FINDRISC scale. We examined the validity of FINDRISC in a contemporary Norwegian risk environment.

RESEARCH DESIGN AND METHODS

We followed 47 804 participants without known diabetes and aged ≥20 years in the HUNT3 survey (2006-2008) by linkage to information on glucose-lowering drug dispensing in the Norwegian Prescription Database (2004-2016). We estimated the C-statistic, sensitivity and specificity of FINDRISC as predictor of incident diabetes, as indicated by incident use of glucose-lowering drugs. We estimated the 10-year cumulative diabetes incidence by categories of FINDRISC.

RESULTS

The C-statistic (95% CI) of FINDRISC in predicting future diabetes was 0.77 (0.76 to 0.78). FINDRISC ≥15 (the conventional cut-off value) had a sensitivity of 38% and a specificity of 90%. The 10-year cumulative diabetes incidence (95% CI) was 4.0% (3.8% to 4.2%) in the entire study population, 13.5% (12.5% to 14.5%) for people with FINDRISC ≥15 and 2.8% (2.6% to 3.0%) for people with FINDRISC <15. Thus, FINDRISC ≥15 had a positive predictive value of 13.5% and a negative predictive value of 97.2% for diabetes within the next 10 years. To approach a similar sensitivity as in the study in which FINDRISC was developed, we would have to lower the cut-off value for elevated FINDRISC to ≥11. This would yield a sensitivity of 73%, specificity of 67%, positive predictive value of 7.7% and negative predictive value of 98.5%.

CONCLUSIONS

The validity of FINDRISC and the risk of diabetes among people with FINDRISC ≥15 is substantially lower in the contemporary Norwegian population than assumed in official guidelines. To identify ~3/4 of those developing diabetes within the next 10 years, we would have to lower the threshold for elevated FINDRISC to ≥11, which would label ~1/3 of the entire adult population as having an elevated FINDRISC necessitating a glycemia assessment.

[Development and validation of a screening score for prediabetes and undiagnosed diabetes.]

OBJECTIVE

To develop and validate an easy-to-use risk score to detect prediabetes and undiagnosed diabetes in Mexican population.

MATERIALS AND METHODS

Using information from the Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán's cohort study of 10 234 adults, risk factors were identified and included in multiple logistic regression models stratified by sex. The beta coefficients of the final model were multiplied by 10, thus obtaining the weights of each variable in the score.

RESULTS

The proposed score correctly classifies 55.4% of women with undiagnosed diabetes and 57.2% of women with prediabetes or diabetes. While for men it correctly classifies them at 68.6% and 69.9%, respectively.

CONCLUSIONS

We present the design and validation of a risk score stratified by sex, to determine if an adult could have prediabetes or diabetes, in which case laboratory studies should be performed to confirm or not the diagnosis.

Latest Considerations in Diagnosis and Treatment of Appendicitis During Pregnancy

Pregnancy can obscure signs and symptoms of acute appendicitis, making diagnosis challenging. Furthermore, avoiding radiation-based imaging due to fetal risk limits the diagnostic options clinicians have. Once appendicitis has been diagnosed, performing appendectomies has been the more commonly accepted course of action, but conservative, nonsurgical approaches are now being considered. This report describes the latest recommendations from different fields and organizations for the diagnosis and treatment of appendicitis during pregnancy.

Undetected dysglycaemia common in primary care patients treated for hypertension and/or dyslipidaemia: on the need for a screening strategy in clinical practice. A report from EUROASPIRE IV a registry from the EuroObservational Research Programme of the European Society of Cardiology

Background

Dysglycaemia defined as type 2 diabetes (T2DM) and impaired glucose tolerance (IGT), increases the risk of cardiovascular disease (CVD). The negative impact is more apparent in the presence of hypertension and/or dyslipidaemia. Thus, it seems reasonable to screen for dysglycaemia in patients treated for hypertension and/or dyslipidaemia. A simple screening algorithm would enhance the adoption of such strategy in clinical practice.

Objectives

To test the hypotheses (1) that dysglycaemia is common in patients with hypertension and/or dyslipidaemia and (2) that initial screening with the Finnish Diabetes Risk Score (FINDRISC) will decrease the need for laboratory based tests.

Methods

2395 patients (age 18–80 years) without (i) a history of CVD or TDM2, (ii) prescribed blood pressure and/or lipid lowering drugs answered the FINDRISC questionnaire and had an oral glucose tolerance test (OGTT) and HbA1c measured.

Results

According to the OGTT 934 (39%) had previously undetected dysglycaemia (T2DM 19%, IGT 20%). Of patients, who according to FINDRISC had a low, moderate or slightly elevated risk 20, 34 and 41% and of those in the high and very high-risk category 49 and 71% had IGT or T2DM respectively. The OGTT identified 92% of patients with T2DM, FPG + HbA1c 90%, FPG 80%, 2hPG 29% and HbA1c 22%.

Conclusions

(1) The prevalence of dysglycaemia was high in patients treated for hypertension and/or dyslipidaemia. (2) Due to the high proportion of dysglycaemia in patients with low to moderate FINDRISC risk scores its initial use did not decrease the need for subsequent glucose tests. (3) FPG was the best test for detecting T2DM. Its isolated use is limited by the inability to disclose IGT. A pragmatic strategy, decreasing the demand for an OGTT, would be to screen all patients with FPG followed by OGTT in patients with IFG.

A demonstration area for type 2 diabetes prevention in Barranquilla and Juan Mina (Colombia): Baseline characteristics of the study participants

Type 2 diabetes (T2D) imposes a heavy public health burden in both developed and developing countries. It is necessary to understand the effect of T2D in different settings and population groups. This report aimed to present baseline characteristics of study participants in the demonstration area for the "Type 2 Diabetes Prevention in Barranquilla and Juan Mina" (DEMOJUAN) project after randomization and to compare their fasting and 2-hour glucose levels according to lifestyle and T2D risk factor levels.The DEMOJUAN project is a randomized controlled field trial. Study participants were recruited from study sites using population-wide screening using the Finnish Diabetes Risk Score (FINDRISC) questionnaire. All volunteers with FINDRISC of ≥13 points were invited to undergo an oral glucose tolerance test (OGTT). Participant inclusion criteria for the upcoming field trial were either FINDRISC of ≥13 points and 2-hour post-challenge glucose level of 7.0 to 11.0 mmol/L or FINDRISC of ≥13 points and fasting plasma glucose level of 6.1 to 6.9 mmol/L. Lifestyle habits and risk factors for T2D were assessed by trained interviewers using a validated questionnaire.Among the 14,193 participants who completed the FINDRISC questionnaire, 35% (n = 4915) had a FINDRISC score of ≥13 points and 47% (n = 2306) agreed to undergo the OGTT. Approximately, 33% (n = 772) of participants underwent the OGTT and met the entry criteria; these participants were randomized into 3 groups. There were no statistically significant differences found in anthropometric or lifestyle risk factors, distribution of the glucose metabolism categories, or other diabetes risk factors between the 3 groups (P > .05). Women with a past history of hyperglycaemia had significantly higher fasting glucose levels than those without previous hyperglycaemia (103 vs 99 mg/dL; P < .05).Lifestyle habits and risk factors were evenly distributed among the 3 study groups. No differences were found in fasting or 2-hour glucose levels among different lifestyle or risk factor categories with the exception of body mass index, past history of hyperglycaemia, and age of ≥64 years in women.

TRIAL REGISTRATION

NCT01296100 (2/12/2011; Clinical trials.gov).

A unique plasma microRNA profile defines type 2 diabetes progression

A major unmet medical need to better manage Type 2 Diabetes (T2D) is the accurate disease prediction in subjects who show glucose dysmetabolism, but are not yet diagnosed as diabetic. We investigated the possibility to predict/monitor the progression to T2D in these subjects by retrospectively quantifying blood circulating microRNAs in plasma of subjects with i) normal glucose tolerance (NGT, n = 9); ii) impaired glucose tolerance (IGT, n = 9), divided into non-progressors (NP, n = 5) and progressors (P, n = 4) based on subsequent diabetes occurrence, and iii) newly diagnosed T2D (n = 9). We found that impaired glucose tolerance associated with a global increase of plasma circulating microRNAs. While miR-148 and miR-222 were specifically modulated in diabetic subjects and correlated with parameters of glucose tolerance, the most accentuated microRNA dysregulation was found in NP IGT subjects, with increased level of miR-122, miR-99 and decreased level of let-7d, miR-18a, miR-18b, miR-23a, miR-27a, miR-28 and miR-30d in comparison with either NGT or T2D. Interestingly, several of these microRNAs significantly correlated with parameters of cholesterol metabolism. In conclusion, we observed the major perturbation of plasma circulating microRNA in NP pre-diabetic subjects and identified a unique microRNA profile that may become helpful in predicting diabetic development.

Skin autofluorescence improves the Finnish Diabetes Risk Score in the detection of diabetes in a large population-based cohort: The LifeLines Cohort Study

AIM

The aim of the present study was to investigate whether skin autofluorescence would improve the Finnish Diabetes Risk Score (FINDRISC) in detecting undiagnosed diabetes in a large population-based cohort.

METHODS

Included were participants from the Dutch LifeLines Cohort Study. Skin autofluorescence was assessed in an unselected subset of participants using the AGE Reader. After the exclusion of participants with previously diagnosed diabetes (n=1635), pregnant women (n=58) and those using corticosteroids (n=345), 79,248 subjects were eligible for analysis. Diabetes was defined as fasting plasma glucose ≥7.0mmol/L, non-fasting plasma glucose ≥11.1mmol/L or HbA1c ≥6.5% (48mmol/mol).

RESULTS

Diabetes was detected in 1042 participants (aged 55±12 years; 54% male). Skin autofluorescence improved the area under the receiver operating characteristic (AUROC) curve of the FINDRISC model from 0.802 to 0.811 (P<0.001). Furthermore, the addition of skin autofluorescence to FINDRISC reclassified 8-15% of all participants into more accurate risk categories (NRI: 0.080, 95% CI: 0.052-0.110). The proportion of reclassified participants was especially high (>30%) in the intermediate (1% to <5% and 5% to<10%) risk categories. When skin autofluorescence was added to a simplified model (age+body mass index), its discriminatory performance was similar to the full model+skin autofluorescence (AUROC: 0.806, P=0.062).

CONCLUSION

Skin autofluorescence is a non-invasive tool that can be used to further improve the FINDRISC for diabetes detection. The new resultant model is especially useful for reclassifying people in the intermediate-risk categories, where additional blood glucose testing is needed to confirm the presence of diabetes.

Predictive models for conversion of prediabetes to diabetes

AIM

To clarify the natural course of prediabetes and develop predictive models for conversion to diabetes.

METHODS

A retrospective longitudinal study of 2105 adults with prediabetes was carried out with a mean observation period of 4.7years. Models were developed using multivariate logistic regression analysis and verified by 10-fold cross-validation. The relationship between [final BMI minus baseline BMI] (δBMI) and incident diabetes was analyzed post hoc by comparing the diabetes conversion rate for low (< -0.31kg/m²) and high δBMI (≥ -0.31kg/m²) subjects after matching the two groups for the covariates.

RESULTS

Diabetes developed in 252 (2.5%/year), and positive family history, male sex, higher systolic blood pressure, plasma glucose (fasting and 1h- and 2h-values during 75g OGTT), hemoglobin A1c (HbA1c) and alanine aminotransferase were significant, independent predictors for the conversion. By using a risk score (RS) that took account of all these variables, incident diabetes was predicted with an area under the ROC curve (95% CI) of 0.80 (0.70-0.87) and a specificity of prediction of 61.8% at 80% sensitivity. On division of the participants into high- (n=248), intermediate- (n=336) and low-risk (n=1521) populations, the conversion rates were 40.1%, 18.5% and 5.9%, respectively. The conversion rate was lower in subjects with low than high δBMI (9.2% vs 14.4%, p=0.003).

CONCLUSIONS

Prediabetes conversion to diabetes could be predicted with accuracy, and weight reduction during the observation was associated with lowered conversion rate.

Diabetes self-assessment score and the development of diabetes: A 10-year prospective study

To verify that the Korean Diabetes Score (KDS), a self-assessment, predicts the risk of diabetes in various comprehensive risk models, and to investigate factors that enhance its predictive ability in a large cohort. We analyzed 8735 adults without diabetes in the Korean Genome and Epidemiology Study, an ongoing large community-based 10-year cohort study. Incident diabetes was defined as fasting blood glucose ≥126 mg/dL or postload 2-hour glucose ≥200 mg/dL by 75 g oral glucose tolerance test conducted biennually, or currently taking medication for diabetes. Hazard ratios (HRs) using Cox regression were calculated for relative risk of developing diabetes as associated with the KDS, and performance of risk models was assessed by area under the receiver-operating characteristic curve (AUC). Of 8735 participants, 1497 (17.1%) developed diabetes over 10 years. The prevalence of incident diabetes was 10.3% in people with a KDS <5 and was 21.8% in those with KDS ≥5 (P < .001). Increasing KDS was significantly associated with developing diabetes (adjusted HR: 1.13; 95% confidence interval:1.09,1.18). The comprehensive prediction model with KDS added to fasting glucose, glycated hemoglobin, postload 2-hour glucose, and triglyceride showed a markedly higher AUC (0.782) compared to KDS alone (0.641). A low insulinogenic index (IGI) level, but not insulin resistance, was a significant determinant of developing diabetes in subjects who had baseline KDS < 5. We confirmed that KDS as a 10-year risk model to predict diabetes becomes more potent when added to relevant laboratory parameters. Beta-cell function as assessed by IGI should be taken into account when predicting diabetes using the KDS.

Systematic literature review of the health economic implications of early detection by screening populations at risk for type 2 diabetes

BACKGROUND

Undetected/uncontrolled diabetes is associated with substantial morbidity and mortality and consequent costs. Early detection through screening identifies patients at risk, allowing for earlier treatment initiation.

OBJECTIVES

To determine the economic impact of screening for type 2 diabetes (T2DM).

DATA SOURCES

We systematically reviewed health economic analyses of screening programs for T2DM/pre-diabetes.

STUDY ELIGIBILITY CRITERIA

Published between 2000 and 2015 in any language. Articles must have reported costs of screening, test/patient outcomes and cost-effectiveness.

PARTICIPANTS AND INTERVENTIONS

Any type of screening (universal, targeted, opportunistic) was accepted.

METHODS

Data were extracted from Scopus/Medline/Embase, then tabulated.

RESULTS

There were 137 studies identified, 108 rejected; 29 were analyzed. Screening types included 18 universal, 8 targeted and 8 opportunistic. One study screened for pre-diabetes, 16 for T2DM and 12 examined both. Fourteen (48%) reported costs of screening only, 9 (31%) costs of screening combined with interventions and 6 (21%) presented all costs separately. Screening was compared to no screening in 13 studies (45%); screening was cost-effective in 8 (62%), not cost-effective in 4 (31%) and neither in 1 (8%). When comparing different screening methods, 6 found targeted screening was cost-effective compared with universal screening (none found the opposite), 2 found opportunistic superior to universal. Sensitivity analyses generally confirmed primary findings. Cost drivers included prevalence of T2DM/pre-diabetes, type of blood test used and uptake of testing. For optimal cost-effectiveness, screening for both T2DM and pre-diabetes should be initiated around age 45-50, with repeated testing every 5 years.

CONCLUSIONS/IMPLICATIONS

Targeted screening appears to be cost-effective compared to universal screening.

A community-based primary prevention programme for type 2 diabetes mellitus integrating identification and lifestyle intervention for prevention: a cluster randomised controlled trial

Background

Prevention of type 2 diabetes mellitus (T2DM) is a global priority; however, there is a lack of evidence investigating how to effectively translate prevention research into a primary care setting.

Objectives

(1) To develop and validate a risk score to identify individuals at high risk of T2DM in the UK; and (2) to establish whether or not a structured education programme targeting lifestyle and behaviour change was clinically effective and cost-effective at preventing progression to T2DM in people with prediabetes mellitus (PDM), identified through a risk score screening programme in primary care.

Design

A targeted screening study followed by a cluster randomised controlled trial (RCT), with randomisation at practice level. Participants were followed up for 3 years.

Setting

A total of 44 general practices across Leicestershire, UK. The intervention took place in the community.

Participants

A total of 17,972 individuals from 44 practices identified through the risk score as being at high risk of T2DM were invited for screening; of these, 3449 (19.2%) individuals attended. All received an oral glucose tolerance test. PDM was detected in 880 (25.5%) of those screened. Those with PDM were included in the trial; of these, 36% were female, the average age was 64 years and 16% were from an ethnic minority group.

Intervention

Practices were randomised to receive either standard care or the intervention. The intervention consisted of a 6-hour group structured education programme, with an annual refresher and regular telephone contact.

Main outcome measures

The primary outcome was progression to T2DM. The main secondary outcomes were changes in glycated haemoglobin concentrations, blood glucose levels, cardiovascular risk, the presence of metabolic syndrome, step count and the cost-effectiveness of the intervention.

Results

A total of 22.6% of the intervention group did not attend the education and 29.1% attended all sessions. A total of 131 participants developed T2DM (standard care,n = 67; intervention,n = 64). There was a 26% reduced risk of T2DM in the intervention arm compared with standard care, but this did not reach statistical significance (hazard ratio 0.74, 95% confidence interval 0.48 to 1.14;p = 0.18). There were statistically significant improvements in glycated haemoglobin concentrations, low-density lipoprotein cholesterol levels, psychosocial well-being, sedentary time and step count in the intervention group. The intervention was found to result in a net gain of 0.046 quality-adjusted life-years over 3 years at a cost of £168 per patient, with an incremental cost-effectiveness ratio of £3643 and a probability of 0.86 of being cost-effective at a willingness-to-pay threshold of £20,000.

Conclusions

We developed and validated a risk score for detecting those at high risk of undiagnosed PDM/T2DM. We screened > 3400 people using a two-stage screening programme. The RCT showed that a relatively low-resource pragmatic programme may lead to a reduction in T2DM and improved biomedical and psychosocial outcomes, and is cost-effective.

Limitations

Only 19% of those invited to screening attended, which may limit generalisability. The variation in cluster size in the RCT may have limited the power of the study.

Future work

Future work should focus on increasing attendance to both screening and prevention programmes and offering the programme in different modalities, such as web-based modalities. A longer-term follow-up of the RCT participants would be valuable.

Trial registration

Current Controlled Trials ISRCTN80605705.

Funding

The National Institute for Health Research Programme Grants for Applied Research programme.

Finnish Diabetes Risk Score Is Associated with Impaired Insulin Secretion and Insulin Sensitivity, Drug-Treated Hypertension and Cardiovascular Disease: A Follow-Up Study of the METSIM Cohort

We investigated the association of the Finnish Diabetes Risk Score (FINDRISC) with insulin secretion, insulin sensitivity, and risk of type 2 diabetes, drug-treated hypertension, cardiovascular (CVD) events and total mortality in a follow-up study of the Metabolic Syndrome in Men (METSIM) cohort. The METSIM study includes 10,197 Finnish men, aged 45-73 years, and examined in 2005-2010. Of 8,749 non-diabetic participants of the METSIM study 693 developed incident type 2 diabetes, 225 started antihypertensive medication, 351 had a CVD event, and 392 died during a 8.2-year follow-up. The FINDRISC was significantly associated with decreases in insulin secretion and insulin sensitivity (P<0.0001), and with a 4.14-fold increased risk of incident type 2 diabetes, 2.43-fold increased risk of drug-treated hypertension, 1.61-fold increased risk of CVD, and 1.55-increased risk of total mortality (the FINDRISC ≥12 vs. < 12 points). In conclusion, the FINDRISC predicts impairment in insulin secretion and insulin sensitivity, the conversion to type 2 diabetes, drug-treated hypertension, CVD events and total mortality.

Development of new diabetes risk scores on the basis of the current definition of diabetes in Japanese subjects [Rapid Communication]

To develop diabetes risk score (RS) based on the current definition of diabetes, we retrospectively analyzed consecutive 4,159 health examinees who were non-diabetic at baseline. Diabetes, diagnosed by fasting plasma glucose (FPG) ≥7.0 mmol/L, 2hPG ≥11.1 mmol/L and/or HbA1c ≥6.5% (48 mmol/mol), developed in 279 of them during the mean period of 4.9 years. A full RS (RS_Full), a RS without 2hPG (RS_-2hPG) and a non-invasive RS (RS_NI) were created on the basis of multivariate Cox proportional model by weighted grading based on hazard ratio in half the persons assigned. The RSs were verified in the remaining half of the participants. Positive family history (FH), male sex, smoking and higher age, systolic blood pressure (SBP), FPG, 2hPG and HbA1c were independent predictors for RS_Full. For RS_-2hPG, 7 independent predictors, exclusive of 2hPG and smoking but inclusive of elevated triglycerides (TG) comparing to RS_Full, were selected. FH, male sex, and higher age, SBP and HbA1c were independent predictors in RS_NI. In the validation cohort, C-statistic (95%CI) of RS_Full, RS_-2hPG and RS_NI were 0.80 (0.76-0.84), 0.75 (0.70-0.78) and 0.68 (0.63-0.72), respectively, which were significantly different from each other (P <0.01). Absolute percentage difference between predicted probability and observed diabetes were 1.9%, 0.7% and 0.9%, by the three scores, respectively, and not significantly different from each other. In conclusion, diabetes defined by the current criteria was predicted by the new diabetes risk scores with reasonable accuracy. Nonetheless, RS_Full with a postchallenge glucose value performed superior to RS_-2hPG and RS_NI.

Screening for type 2 diabetes mellitus in overweight and obese subjects made easy by the FINDRISC score

AIM

To evaluate the use of the FINDRISC score in an overweight and obese population to predict glucose status.

METHODS

In 651 overweight/obese subjects (M/F: 193/458, age 43±13 y, BMI 38.2±6.1kg/m(2)) glucose status was tested using OGTT and HbA1c. Furthermore, the FINDRISC questionnaire and CT visceral fat (VAT) and subcutaneous fat (SAT) were examined.

RESULTS

Exactly 50.4% were found to have prediabetes and 11.1% were newly diagnosed with type 2 diabetes (T2DM) (M/F=22.2/8.8%). Subjects without T2DM had a FINDRISC score of 11±3, those with pre-DM 13±4, and subjects with de novo T2DM 15±5. The aROC of the FINDRISC for detecting T2DM was 0.76 (95% CI 0.72-0.82), with 13 as cutoff point. The FINDRISC score correlated with VAT (r=0.34, p<0.001) and VAT/SAT ratio (r=0.39, p<0.001). The aROC of the FINDRISC to detect excess VAT was 0.79 (95%CI 0.72-0.84).

CONCLUSIONS

In a large group of overweight and obese subjects, 50.4% were found to have pre-DM and 11.1% were newly diagnosed with T2DM. The FINDRISC score increased with worsening of glucose tolerance status and proved to be an independent predictor of T2DM status, as did HOMA-B, HOMA-S and VAT. The FINDRISC can also function as a good tool to predict visceral obesity.

Performance of the Finnish Diabetes Risk Score and a Simplified Finnish Diabetes Risk Score in a Community-Based, Cross-Sectional Programme for Screening of Undiagnosed Type 2 Diabetes Mellitus and Dysglycaemia in Madrid, Spain: The SPREDIA-2 Study

Aim

To evaluate the performance of the Finnish Diabetes Risk Score (FINDRISC) and a simplified FINDRISC score (MADRISC) in screening for undiagnosed type 2 diabetes mellitus (UT2DM) and dysglycaemia.

Methods

A population-based, cross-sectional, descriptive study was carried out with participants with UT2DM, ranged between 45–74 years and lived in two districts in the north of metropolitan Madrid (Spain). The FINDRISC and MADRISC scores were evaluated using the area under the receiver operating characteristic curve method (ROC-AUC). Four different gold standards were used for UT2DM and any dysglycaemia, as follows: fasting plasma glucose (FPG), oral glucose tolerance test (OGTT), HbA1c, and OGTT or HbA1c. Dysglycaemia and UT2DM were defined according to American Diabetes Association criteria.

Results

The study population comprised 1,426 participants (832 females and 594 males) with a mean age of 62 years (SD = 6.1). When HbA1c or OGTT criteria were used, the prevalence of UT2DM was 7.4% (10.4% in men and 5.2% in women; p<0.01) and the FINDRISC ROC-AUC for UT2DM was 0.72 (95% CI, 0.69–0.74). The optimal cut-off point was ≥13 (sensitivity = 63.8%, specificity = 65.1%). The ROC-AUC of MADRISC was 0.76 (95% CI, 0.72–0.81) with ≥13 as the optimal cut-off point (sensitivity = 84.8%, specificity = 54.6%). FINDRISC score ≥12 for detecting any dysglycaemia offered the best cut-off point when HbA1c alone or OGTT and HbA1c were the criteria used.

Conclusions

FINDRISC proved to be a useful instrument in screening for dysglycaemia and UT2DM. In the screening of UT2DM, the simplified MADRISC performed as well as FINDRISC.

Impact of sex and age on the performance of FINDRISC: the HUNT Study in Norway

OBJECTIVE

The Finnish Diabetes Risk Score (FINDRISC) is recommended as a screening tool for diabetes risk. However, there is a lack of well-powered studies examining the performance of FINDRISC by sex and age. We aim to estimate, by sex and age, the prevalence of elevated FINDRISC and positive predictive value (PPV) of FINDRISC for identifying impaired glucose metabolism (IGM) in a general Norwegian population.

RESEARCH DESIGN AND METHODS

We estimated the prevalence of elevated FINDRISC (≥15) among 47 694 adults in the third survey of the Nord-Trøndelag Health Study (HUNT3, 2006-08). Among 2559 participants who participated in oral glucose tolerance testing, we estimated the PPV of elevated FINDRISC for identifying unknown prevalent diabetes and other forms of IGM.

RESULTS

The prevalence of elevated FINDRISC was 12.1% in women, 9.6% in men, and increased from 1.5% at age 20-39 to 25.1% at age 70-79 years. The PPVs of elevated FINDRISC were 9.8% for diabetes, 16.9% for impaired glucose tolerance, 8.2% for impaired fasting glucose, and 34.9% for any form of IGM. The PPV for IGM was lower in women (31.2%) than in men (40.4%), and increased from 19.1% at age 20-39 to 55.5% at age ≥80 years.

CONCLUSIONS

FINDRISC identified more women than men as high-risk individuals for diabetes. FINDRISC had a high PPV for detecting prevalent IGM, and the PPV was higher in men than in women and in the older individuals. Our data indicate that the impact of sex and age on diabetes risk is not fully captured by FINDRISC, and that refinements to it might improve diabetes prediction.