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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).

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Background and objective Diabetes mellitus (DM) is a chronic, metabolic disease characterized by elevated blood glucose levels that eventually lead to several acute and chronic complications. Type 2 DM (T2DM) is a major healthcare problem globally as well as in the Kingdom of Saudi Arabia (KSA). Predicting and identifying people at high risk for developing T2DM will help implement preventive measures for these individuals. In light of this, the present study was designed to estimate the 10-year risk of developing T2DM among the Saudi general population. Methodology A descriptive, cross-sectional survey involving 15,509 Saudi individuals was undertaken. The participants were selected from all 13 provinces of KSA based on stratified random sampling. The Finnish Diabetes Risk Score (FINDRISC), a validated tool for T2DM risk assessment, was employed. Descriptive and chi-square analyses were used. Results The mean age of the participants was 28.33 years. Subjects with a moderate, high, and very high risk of developing T2DM within the next 10 years comprised approximately 18% of the sample. The mean FINDRISC was 7.53 [standard deviation (SD): 4.28], which is considered a level associated with a slightly elevated risk of developing T2DM. Of note, 938 participants (6.05%) among the sample population had a high risk of developing T2DM as predicted by FINDRISC. Education, daily physical activity, high blood glucose, and family history of DM were significantly higher in females compared to males (p<0.001). On the other hand, smoking rates and use of antihypertensive medications were substantially higher among males (p<0.001). Conclusion Based on our findings, approximately 18% of the Saudi general population has a moderate to high risk of developing T2DM. T2DM risk assessment should be widely and regularly practiced by general practitioners and internists as part of national programs for diabetes prevention.

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BACKGROUND: Non-communicable diseases such as cardiovascular conditions and diabetes are rising in sub-Saharan Africa. Prevention strategies to mitigate non-communicable diseases include improving diet, physical activity, early diagnosis, and long-term management. Early identification of individuals at risk based on risk-score models - such as the Framingham Risk Score (FRS) for 10-year risk of cardiovascular disease and the Finnish type 2 Diabetes risk score (FINDRISC) for type 2 diabetes which are used in high-income settings - have not been well assessed in sub-Saharan Africa. The purpose of this study was to qualitatively assess local knowledge of components of these risk scores in a rural Ugandan setting. METHODS: Semi-structured qualitative in-depth interviews were conducted with a purposively selected sample of 15 participants who had responded to the FRS and FINDRISC questionnaires and procedures embedded in the Rakai Community Cohort Study. Data were summarized and categorized using content analysis, with support of Atlas.ti. RESULTS: Participants described local terms for hypertension ("pulessa") and type 2 diabetes ("sukaali"). Most participants understood physical activity as leisure physical activity, but when probed would also include physical activity linked to routine farm work. Vegetables were typically described as "plants", "leafy greens", and "side dish". Vegetable and fruit consumption was described as varying seasonally, with peak availability in December after the rainy season. Participants perceived themselves to have good knowledge about their family members' history of type 2 diabetes and hypertension. CONCLUSIONS: While most items of the FRS and FINDRISC were generally well understood, physical activity needs further clarification. It is important to consider the seasonality of fruits and vegetables, especially in rural resource-poor settings. Current risk scores will need to be locally adapted to estimate the 10-year risk of cardiovascular diseases and type 2 diabetes in this setting.

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OBJECTIVE: Diabetes and periodontitis are non-transmissible chronic disorders that exhibit a mutual relationship. A study was made to evaluate the risk of prediabetes and periodontal disease, and to explore the association between them. METHODS: A descriptive cross-sectional study was made of 186 individuals over 18 years of age, without prediabetes or diabetes, or cognitive impairment. Subjects undergoing dental treatment and pregnant women were excluded. Prediabetes risk was assessed based on the Finnish Diabetes Risk Score (FINDRISC), and the individual risk of development and/or progression of periodontal disease was explored with a periodontal disease risk questionnaire. RESULTS: A total of 135 gingival risk questionnaires and 142 FINDRISC questionnaires were correctly completed. The proportion of subjects with a low, moderate and high risk of periodontal disease was 60.36%, 38.74% and 0.9%, respectively. With regard to the FINDRISC, the proportion of individuals with low, slightly increased, moderately increased and high risk of prediabetes was 54.4%, 32.8%, 8%, and 4.8%, respectively. A significant linear correlation between the two scores was observed (r = 0.3659, p < 0.0005). The variables associated with a slightly increased risk of prediabetes were age, overweight and smoking, while the variables associated with a moderately increased or high risk were age 40-65 years, tooth loss, overweight and smoking. CONCLUSIONS: These questionnaires may be of benefit to patients and can contribute to develop a chronic care model characterized by collaboration among different healthcare professionals.

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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.

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CONTEXT: India is currently becoming capital for diabetes mellitus. This significantly increasing incidence of diabetes putting an additional burden on health care in India. Unfortunately, half of diabetic individuals are unknown about their diabetic status. Hence, there is an emergent need of effective screening instrument to identify "diabetes risk" individuals. AIMS: The aim is to evaluate and compare the diagnostic accuracy and clinical utility of Indian Diabetes Risk Score (IDRS) and Finnish Diabetes Risk Score (FINDRISC). SETTINGS AND DESIGN: This is retrospective, record-based study of diabetes detection camp organized by a teaching hospital. Out of 780 people attended this camp voluntarily only 763 fulfilled inclusion criteria of the study. SUBJECTS AND METHODS: In this camp, pro forma included the World Health Organization STEP guidelines for surveillance of noncommunicable diseases. Included primary sociodemographic characters, physical measurements, and clinical examination. After that followed the random blood glucose estimation of each individual. STATISTICAL ANALYSIS USED: Diagnostic accuracy of IDRS and FINDRISC compared by using receiver operative characteristic curve (ROC). Sensitivity, specificity, likelihood ratio, positive predictive and negative predictive values were compared. Clinical utility index (CUI) of each score also compared. SPSS version 22, Stata 13, R3.2.9 used. RESULTS: Out of 763 individuals, 38 were new diabetics. By IDRS 347 and by FINDRISC 96 people were included in high-risk category for diabetes. Odds ratio for high-risk people in FINDRISC for getting affected by diabetes was 10.70. Similarly, it was 4.79 for IDRS. Area under curves of ROCs of both scores were indifferent (P = 0.98). Sensitivity and specificity of IDRS was 78.95% and 56.14%; whereas for FINDRISC it was 55.26% and 89.66%, respectively. CUI was excellent (0.86) for FINDRISC while IDRS it was "satisfactory" (0.54). Bland-Altman plot and Cohen's Kappa suggested fair agreement between these score in measuring diabetes risk. CONCLUSIONS: Diagnostic accuracy and clinical utility of FINDRISC is fairly good than IDRS.

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AIM: To assess the performance of the Finnish Diabetes Risk Score (FINDRISC) questionnaire for detecting and predicting type 2 diabetes mellitus (DM2) in a Colombian population. METHODS: This is a longitudinal observational study conducted in Floridablanca, Colombia. Adult subjects (age ≥ 35 years) without known diabetes, were included. A modified version of FINDRISC was completed, and the glycemia values from all the subjects were collected from the hospital's database. Firstly, a cross-sectional analysis was performed and then, the subsample of prediabetic participants was followed for diabetes incidence. RESULTS: A total of 772 subjects were suitable for the study. The overall prevalence of undiagnosed DM2 was 2.59%, and the incidence of DM2 among the prediabetic participants was 7.5 per 100 person-years after a total of 265257 person-years follow-up. The FINDRISC at baseline was significantly associated with undiagnosed and incident DM2. The area under receiver operating characteristics curve of the FINDRISC score for detecting undiagnosed DM2 in both men and women was 0.7477 and 0.7175, respectively; and for predicting the incidence of DM2 among prediabetics was 71.99% in men and 67.74% in women. CONCLUSION: The FINDRISC questionnaire is a useful screening tool to identify cross-sectionally unknown DM2 and to predict the incidence of DM2 among prediabetics in the Colombian population.

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AIM: The strong association between the Finnish Diabetes Risk Score (FINDRISC) and risk of diabetes reported in European populations cannot necessarily be generalized to other populations. The aim of this study was to evaluate the ability of FINDRISC to predict progression to diabetes in an Iranian population without diabetes. METHODS: A total of 1537 first-degree relatives (FDR) without diabetes of consecutive people with type 2 diabetes 30-70 years old (376 men and 1161 women) were examined and followed for a mean (SD) of 7.8 (1.7) years for diabetes incidence. We examined the incidence of diabetes across quartiles of FINDRISC and plotted a receiver operating characteristic (ROC) curve to assess discrimination. At baseline and through follow-up, participants underwent a standard 75-g 2-h oral glucose tolerance test. Data for the FINDRISC were available from each participant. RESULTS: During 12,046 person-years of follow-up, 41 men and 154 women developed diabetes. The incidence of type 2 diabetes was 14.0 per 1000 person-years in men and 16.9 in women. Those in the top quartile of FINDRISC were 21.7 times more likely to develop diabetes than those in the bottom quartile (relative risk 21.7; 95% CI 9.90, 47.39). The area under the ROC was 75.1% (95% CI 71.3, 78.8). CONCLUSIONS: The results of this study show that FINDRISC is a robust predictor of type 2 diabetes in high-risk individuals in Iran.

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AIM: The performance of the Finnish Diabetes Risk Score (FINDRISC) and 2 modifications in community screening for undiagnosed type 2 diabetes (UDD) in the Philippines was evaluated. METHODS: Active community-based screening for diabetes was conducted where FINDRISC assessment was done. Modified (modFINDRISC) and simplified (simpFINDRISC) versions were rendered based on Asian standards, study results, and local context. Diabetes was diagnosed through 2 separate blood glucose tests. Areas under the receiver operating characteristic curve (ROC-AUC) and statistics for diagnostic tests for FINDRISC and the modifications were analyzed. RESULTS: Complete data was collected from 1752 people aged 20-92; 8.6% tested positive for diabetes. ROC-AUC for UDD were 0.738 (FINDRISC), 0.743 (modFINDRISC) and 0.752 (simpFINDRISC). The differences between the FINDRISC and the modifications were not statistically significant (p=0.172). CONCLUSIONS: The performance of all 3 risk score calculators in the screening for UDD in the Philippines was good and may be useful in populations having similar characteristics. Considering the setting and resource constraints, the simpFINDRISC is preferred.

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