Relación entre el Finnish Diabetes Risk Score, glucemia en ayunas y hemoglobina A1c / Relationship between the Finnish Diabetes Risk Score, fasting blood glucose and glycohemoglobin A1c

Introducción: el Finnish Diabetes Risk Score (FINDRISC) mostró alta sensibilidad y especificidad para la detección de personas que evolucionarían a diabetes mellitus (DM) en las poblaciones estudiadas, por lo cual se decidió utilizarlo entre quienes concurrieron por diferentes motivos a realizarse análisis de laboratorio en centros de la Asociación de Laboratorios de Alta Complejidad (ALAC), con el objeto de identificar personas con diferentes niveles de riesgo de presentar alteraciones de la glucemia en ayunas (GA) y de la HbA1c. Objetivos: explorar la asociación entre la puntuación del FINDRISC con GA y HbA1c, estableciendo el punto de corte de mayor sensibilidad y especificidad para encontrar una GA ≥100 mg/dL y una HbA1c ≥5,7% (38,8 mmol/mol), en una población que concurrió a centros de la ALAC. Materiales y métodos: se incluyeron 1.175 individuos de 45 laboratorios de la ALAC, procesamiento local de glucemia y centralizado de HbA1c (high performance liquid chromatography, HPLC). Análisis estadístico: chi-cuadrado, Odds Ratio, ANOVA, test de Tukey, regresión logística binomial y curvas ROC. Resultados: los puntajes totales del FINDRISC se asociaron de manera positiva y estadísticamente significativa, tanto con los valores de GA como con los niveles de HbA1c. Entre sus variables, una edad mayor o igual a 45 años, un perímetro abdominal de alto riesgo, un índice de masa corporal mayor o igual a 25 Kg/m., la presencia de antecedentes familiares de DM (padres, hermanos o hijos) y la existencia de antecedentes de medicación antihipertensiva se asociaron de manera significativa con valores de GA iguales o superiores a 100 mg/dL y/o niveles de HbA1c iguales o mayores a 5,7% (38,8 mmol/mol). No se halló asociación significativa con la realización de actividad física (al menos 30 minutos diarios) ni con el registro de ingesta diario de frutas y verduras. Los valores medios de GA y HbA1c en individuos con puntajes totales del FINDRISC menores o iguales a 11 fueron de 89,9 mg/dL y 5,2% (33,0 mmol/mol), respectivamente, elevándose hasta valores medios de 116,1 mg/dL y 6,1% (43,0 mmol/mol) en los individuos con puntajes iguales o superiores a 21, siguiendo una asociación del tipo "dosis/respuesta". Por curvas ROC, un FINDRISC de 13 presenta una sensibilidad del 81,89%, especificidad del 67,60% y 70,55% de diagnósticos correctos de HbA1c ≥5,7% (38,8 mmol/mol), y una sensibilidad del 72,50%, especificidad del 70,62% y 71,20% de diagnósticos correctos para encontrar personas con una GA ≥100 mg/dL. Conclusiones: el puntaje del FINDRISC se relacionó con niveles crecientes de GA y HbA1c, resultando útil para encontrar personas con GA ≥100 mg/dL y HbA1c ≥5,7% (38,8 mmol/mol) en la población estudiada.

Introduction: the Finnish Diabetes Risk Score (FINDRISC) has high sensitivity and specificity for the identification of people at risk of diabetes mellitus (DM) in various populations. Therefore, we aimed to use this index to identify individuals at risk of having alterations in fasting glycemia (FG) and HbA1c among those who underwent laboratory analysis at ALAC, Argentina. Objectives: to explore the relationships of the FINDRISC score with the fasting blood glucose (FG) concentration and glycated hemoglobin (HbA1c) level, and to establish appropriate cut-off scores to predict FG ≥100 mg/dL and HbA1c ≥5.7% (38.8 mmol/mol) in this population. Materials and methods: we recruited 1,175 individuals from 45 ALAC laboratories for whom FG and HbA1c had been measured. We analyzed the data using the chi square test, odds ratios, ANOVA plus Tukey's post-hoc test, binomial logistic regression, and receiver operating characteristic (ROC) curves. Results: total FINDRISC score significantly positively correlated with both FG and HbA1c. Of the constituent variables, age ≥45 years, a large waist circumference, a body mass index ≥25 kg/m., a close family history of DM, and the use of antihypertensive medication were significantly associated with FG ≥100 mg/dL and/or HbA1c ≥5.7% (38.8 mmol/mol). However, no significant association was found with physical activity or the daily consumption of fruit and vegetables. The mean FG and HbA1c for individuals with total FINDRISC scores ≤11 were 89.9 mg/dL and 5.2% (33.0 mmol/mol), respectively, which increased to 116.1 mg/dL and 6.1% (43.0 mmol/mol) for individuals with scores ≥21, with a dose/response-type relationship. ROC analysis showed that a FINDRISC of 13 was associated with a sensitivity of 81.89%, a specificity of 67.60%, and a correct diagnosis rate of 70.55% for HbA1c ≥5.7% (38.8 mmol/mol); and a sensitivity of 72.50%, a specificity of 70.62%, and a correct diagnosis rate of 71.20% for FG ≥100 mg/dL. Conclusions: FINDRISC score increases with increasing FG and HbA1c, and is a useful means of identifying people with FG ≥100 mg/dL and HbA1c ≥5.7% (38.8 mmol/mol).

Diabetes Risk Score in Indian Population: Experience from Central India

Introduction: Diabetes is a major health problem in the world causing significant morbidity and mortality. Currently, 77 million people in India and 463 million people are living with diabetes across the world, and this number is expected to rise to 101 million in India and 578 million globally by 2030. The key to reduce the morbidity and mortality is early diagnosis and management. The Madras Diabetes Research Foundation (MDRF) has developed an Indian Diabetes Risk Score (IDRS) to identify people who are at risk of developing diabetes or are undiagnosed. Thus, we conducted a study to calculate the IDRS of people from Central India and identify those who are at risk of getting diabetes. Methods: A total of 1,500 patients or attendants, aged 18 to 60 years (mean age 41.2 years), visiting the Endocrinology clinic, and not diagnosed with diabetes earlier were included in the study after taking proper consent and IDRS was calculated. Results: The male-to-female ratio was 914:586. The mean IDRS was 51.29 in our population with 35.93%, 18.2% and 45.87% of screened subjects having a score of <30, 30-60 and ?60, respectively. Conclusion: Forty-five percent people of the population was at high risk of diabetes as estimated by IDRS, which proved to be an effective and economical tool to identify persons at increased risk of diabetes and diagnose the undiagnosed cases and start early management to reduce the morbidity and mortality.

Evaluation of Madras Diabetes Research Foundation-Indian Diabetes Risk Score in detecting undiagnosed diabetes in the Indian population: Results from the Indian Council of Medical Research-INdia DIABetes population-based study (INDIAB-15)

Background & objectives: Screening of individuals for early detection and identification of undiagnosed diabetes can help in reducing the burden of diabetic complications. This study aimed to evaluate the performance of Madras Diabetes Research Foundation (MDRF)-Indian Diabetes Risk Score (IDRS) to screen for undiagnosed type 2 diabetes in a large representative population in India. Methods: Data were acquired from the Indian Council of Medical Research–INdia DIABetes (ICMR–INDIAB) study, a large national survey that included both urban and rural populations from 30 states/union territories in India. Stratified multistage design was followed to obtain a sample of 113,043 individuals (94.2% response rate). MDRF-IDRS used four simple parameters, viz. age, waist circumference, family history of diabetes and physical activity to detect undiagnosed diabetes. Receiver operating characteristic (ROC) with area under the curve (AUC) was used to assess the performance of MDRF-IDRS. Results: We identified that 32.4, 52.7 and 14.9 per cent of the general population were under high-, moderate- and low-risk category of diabetes. Among the newly diagnosed individuals with diabetes [diagnosed by oral glucose tolerance test (OGTT)], 60.2, 35.9 and 3.9 per cent were identified under

Diabetes Risk Score in Indian Population: Experience from Central India

Introduction: Diabetes is a major health problem in the world causing significant morbidity and mortality. Currently, 77 million people in India and 463 million people are living with diabetes across the world, and this number is expected to rise to 101 million in India and 578 million globally by 2030. The key to reduce the morbidity and mortality is early diagnosis and management. The Madras Diabetes Research Foundation (MDRF) has developed an Indian Diabetes Risk Score (IDRS) to identify people who are at risk of developing diabetes or are undiagnosed. Thus, we conducted a study to calculate the IDRS of people from Central India and identify those who are at risk of getting diabetes. Methods: A total of 1,500 patients or attendants, aged 18 to 60 years (mean age 41.2 years), visiting the Endocrinology clinic, and not diagnosed with diabetes earlier were included in the study after taking proper consent and IDRS was calculated. Results: The male-to-female ratio was 914:586. The mean IDRS was 51.29 in our population with 35.93%, 18.2% and 45.87% of screened subjects having a score of <30, 30-60 and ?60, respectively. Conclusion: Forty-five percent people of the population was at high risk of diabetes as estimated by IDRS, which proved to be an effective and economical tool to identify persons at increased risk of diabetes and diagnose the undiagnosed cases and start early management to reduce the morbidity and mortality.

Effectiveness and validation of Modified Indian Diabetic Risk Score tool. : A cross sectional study

Introduction: India is diabetic capital of world, with maximum number of diabetic patients. There is large burden of undetected diabetic cases in community. There is increasing risk of diabetes in urban as well as rural areas, because of illiteracy, lack of awareness, low socioeconomic status and unhealthy life style. We have developed Modified Indian Diabetes Risk Score (MIDRS) to detect high risk individuals likely to be benefited by lifestyle interventions in preventing or delaying Type 2 diabetes. Screening for diabetes was carried out from urban and rural community ofMethods: Unjha Taluka district Mehsana Gujarat state. The sample size was 989. MIDRS (Modified Indian Diabetes Risk Score) tool comprising of five modifiable (BMI, waist circumference, physical activity, calorie intake and personal habits) and three non-modifiable risk factors (age, family history and h/o hypertension) for diabetes was used to assess the risk of diabetes. Anthropometry data was obtained. Conformation of diabetes was done using blood sugar levels on fasting and post prandial 2 hours venous sample. Mean and SD for age of study subjects were 42.6 + 15.4years, BMI 25.9 +Results: 3.9 kg/m2, waist hip ratio (females) 0.87 + 0.07 cm, waist hip ratio (males) 0.87 + 0.07 cm, waist circumference (females) 87.6 + 9.8 cm, waist circumference (males) 88.9 + 10.1cm, SBP 134.6 + 20.5 mm Hg and DBP 83.6 + 12.1 mm Hg. MIDRS predicted the risk of diabetes mellitus with sensitivity of 90% and specificity of 71.6% in individuals with score >60. Mean MIDRS score is 52.9. MIDRS can be used as an effective tool for detect high risk individuals likely toConclusion: be benefited by lifestyle interventions in preventing or delaying Type 2 diabetes.

Indian Diabetes Risk Score (IDRS): An effective tool to screen undiagnosed diabetes

Background: Diabetes is an insidious public health problem. India has the second largest number of adults living with diabetes worldwide (77 million). Indian Diabetes Risk Score (IDRS) is a simple, cost-effective and feasible tool for mass screening programme at community level. Aim & Objective: To assess diabetes risk in adults aged 30 years and above and to identify high risk subjects for screening undiagnosed diabetes in an urban population of Meerut. Settings and Design: Community based cross-sectional study. Methods and Material: All adults who were ?30 years of age and non-diabetic were interviewed using pre-designed, pre-tested questionnaire for their socio-demographic profile and lifestyle. Fasting Blood glucose of all study subjects were done to screen undiagnosed diabetics. Statistical analysis used: Centers for Disease Control (CDC), Epi Info TM 7.2.3.1 was used. Pearson’s Chi Square were applied. Results: 33.4% were found to have high diabetes risk. Risk of diabetes increases with age. 7.6% of the study subjects were found to be diabetic and were unaware of their diabetic status. Physical inactivity and increasing waist circumference were found to be significantly associated with risk of diabetes. Diabetes risk was also significantly associated with positive family history. Conclusions: Screening and early identification of high risk individuals would help in early diagnosis and treatment to prevent or to delay the onset of diabetes mellitus and its complications.

Assessment of heart rate variability among individuals with different risk levels for type 2 diabetes mellitus

Background: Cardiac autonomic function is altered in type 2 diabetes mellitus (T2DM) individuals. It is evidenced by decreased heart rate variability (HRV). Decreased HRV results in cardiac autonomic neuropathy and increased risk for sudden cardiac death. Identifying individuals with high risk for T2DM can be an important approach to prevent or delay T2DM complications. In India, the Indian Diabetes Risk Score (IDRS) questionnaire was developed for screening Indian population. To the best of our knowledge, there are no data available evaluating HRV among adults with different risk levels for T2DM (categorized using IDRS). Aim and Objective: In our study, we evaluated HRV among adults with different risk levels for T2DM. Materials and Methods: This study was done in the Department of Physiology, MAPIMS. It is a cross-sectional study done on 130 male and female staffs, attenders, and laboratory technicians working in MAPIMS. All the participants will be asked to complete the IRDS questionnaire. Then, based on the IRDS score, they are divided into Groups I, II, and III. In all the three groups, 5 min short-term HRV will be recorded using RMS Polyrite. Data were analyzed by SPSS 20.0 version software. One-way ANOVA was used to find any statistical difference between the groups. Correlations between the variables were done using Pearson correlation test. Results: Statistically significant (P < 0.05) difference in HRV between different risk levels for diabetes was determined by one-way ANOVA and the post hoc (Dunn’s) test revealed that HRV levels were significantly reduced in high risk, moderate risk when compared to mild risk group. Conclusion: HRV levels reduced as the risk for diabetes increased, that is, HRV negatively correlated with the risk score.

Neck circumference as a risk indicator for type 2 diabetes mellitus: a community based cross-sectional study

Background: Diabetes mellitus is a metabolic syndrome due to insulin deficiency, characterized by hyperglycaemia. Indian diabetes risk score (IDRS) is the most commonly used one to determine the risk status. However there is lot of inconvenience and possible errors in measuring the waist circumference to determine the IDRS, hence the study was planned to evaluate if neck circumference could replace waist circumference in determining the diabetes risk.Methods: This cross sectional study was conducted among 300 study participants fulfilling the eligible criteria. Socio-demographic variables, parameters required for determining the IDRS was assessed, in addition, neck circumference (NC) was measured using standard protocol. Another risk score was calculated by replacing waist circumference (WC) with neck circumference and scoring was named as IDRS-NC. Pearson correlation and Wilcoxan sign rank test was done to find out the relationship between WC and NC and also to determine if IDRS-NC could replace IDRS.Results: Out of 300 study population, majority of the participants are in the age group of <35 years 129 (43%) and around 2/3rd of the participants were females. Among the study participants proportion of participants belonging to low risk, medium risk and high risk assessed using IDRS and IDRS-NC was 18.7%, 41%, 40.3% and 31.7%, 38%, 30.3% respectively. There was a strong positive correlation (r=0.837) between the neck circumference and waist circumference. Wilcoxan sign rank test was significant between the 2 scores having a p value of <0.05.Conclusions: In our study there was a positive correlation between neck circumference and waist circumference.

Screening for diabetes using Indian diabetic risk score in the field practice area of tertiary care hospital, Maharashtra

Background: Globally, people living with diabetes were estimated to be 422 million in year 2014. In India, an estimated 7.8% have diabetes. Early detection and prompt treatment for diabetes is key to achieve sustained control and prevent complications. The Indian diabetic risk score (IDRS) is one of simple screening tool to find the risk for diabetes in the community of filed practice area of teaching hospital.Methods: A community based cross sectional study was conducted in urban and rural field practice area during the period of 1st January to 30th September 2018. As per global health report on diabetes, World Health Organization 2016, prevalence of diabetes in India was found to be 7.8%. Considering allowable error as 20% sample size was 1183 which was rounded up to 1200 with 600 each in urban and rural field practice area. The data was collected with bio- data and IDRS questionnaire which includes age, physical exercise, waist circumference and family history of diabetes.Results: Total 1200 Study participants were included in the study. It was observed that 821 (68.41%) were female participants and 379 (31.59%) were male participants. High risk for diabetes was observed in 329 (27.42%) participants. Among the high-risk participants, 194 (58.96%) were from the urban area and 135 (41.04%) were from the rural area. The association between increasing BMI with high IDRS was observed and found statistically significant. High blood pressure was observed among the participants having high IDRS and findings were statistically significant.Conclusions: This simplified IDRS is cost-effective tool to screen the community on large scale.

An evaluation on the clinical application of risk score method in predicting type 2 diabetes mellitus / 预防医学

Objective To evaluate the application value of the new chinese diabetes risk score in the clinical diagnosis of type 2 diabetes mellitus.Methods A total of 232 subjects who received physical examination at the outpatient department of endocrinology were selected.Medical history and demographic information were collected.Physical examination and 75 g oral glucose tolerance test (OGTT)were conducted.Fasting or 2 -h blood glucose,HbA1 c,serum triglyceride (TG), total cholesterol (TC)and low density lipoprotein cholesterol (LDL-C)were measured.Results The area under the receiver operating curve was 0. 788 (95%CI=0. 725 -0. 852),with 0. 832 (95%CI=0. 748 -0. 916)in males and 0. 754 (95%CI=0. 664-0. 844)in females.At the optimal cutoff value (25 scores)for detecting type 2 diabetes,the sensitivity was 88. 06%and the specificity was 37. 58%.The Diabetes Risk Score was positively related to the probability of type 2 diabetes.Conclusion The new chinese diabetes risk score could be a reliable screening tool to evaluate undiagnosed type 2 diabetes in the Chinese population.

Investigation and application of a diabetes risk score in predicting incident diabetes in male senile people in Beijing / 中华内分泌代谢杂志

Objective To develop a diabetes risk score (DRS)to predict the risk of development of incident diabetes in male senile people in Beijing. Methods DRS was developed basing on a test group including a cohort of 1 370 individuals aged 48-87 years without diabetes at baseline, followed for 10 years by Logistic regression and validated on a value group including a cohort of 340 individuals aged 43-88 years without diabetes at baseline. Results The model with the highest area under the ROC curve ( AUC ) included age, hypertension,history of hyperglycemia, body mass index, fasting plasma glucose, triglycerides, and high-density lipoproteincholesterol (HDL-C). DRS was developed basing on this model with a range from 0 to 12 and an optimal cut-off of 4. AUC were respectively 0. 726 ( 95% CI0. 692-0. 759 ) and 0. 765 ( 95% CI0. 691-0. 839 ) in test group and validation group. The sum score value ≥4 had sensitivity of 65.3% and 68. 1%, specificity of 70. 0% and 64.8%, positive predictive value of 37.0% and 23.2%, negative predictive value of 88.2% and 94. 1%.Conclusion The DRS, derived from clinical information combined with plasma glucose and lipids, is an effective tool to predict incident diabetes.