FINDRISC in Latin America: a systematic review of diagnosis and prognosis models

A machine learning approach for type 2 diabetes diagnosis and prognosis using tailored heterogeneous feature subsets

Type 2 diabetes (T2D) is becoming one of the leading health problems in Western societies, diminishing quality of life and consuming a significant share of healthcare resources. This study presents machine learning models for T2D diagnosis and prognosis, developed using heterogeneous data from a Spanish population dataset (Di@bet.es study). The models were trained exclusively on individuals classified as controls and undiagnosed diabetics, ensuring that the results are not influenced by treatment effects or behavioral changes due to disease awareness. Two data domains are considered: environmental (patient lifestyle questionnaires and measurements) and clinical (biochemical and anthropometric measurements). The preprocessing pipeline consists of four key steps: geospatial data extraction, feature engineering, missing data imputation, and quasi-constancy filtering. Two working scenarios (Environmental and Healthcare) are defined based on the features used, and applied to two targets (diagnosis and prognosis), resulting in four distinct models. The feature subsets that best predict the target have been identified based on permutation importance and sequential backward selection, reducing the number of features and, consequently, the cost of predictions. In the Environmental scenario, models achieved an AUROC of 0.86 for diagnosis and 0.82 for prognosis. The Healthcare scenario performed better, with an AUROC of 0.96 for diagnosis and 0.88 for prognosis. A partial dependence analysis of the most relevant features is also presented. An online demo page showcasing the Environmental and Healthcare T2D prognosis models is available upon request.

FINDRISC modified for Cuba as a tool for the detection of prediabetes and undiagnosed diabetes in cuban population

BACKGROUND

Motivation for the study. There is an increase in obesity and diabetes mellitus cases in Cuba, so it is necessary to provide easy to use, fast and inexpensive tools for the identification of people with dysglycemia. Main findings. For the first time in CUBA, the optimal cut-off point for FINDRISC, LA-FINDRISC and modified FINDRISC for Cuba (CUBDRISC) questionnaires was established with its own anthropometric parameters to identify people with dysglycemia. Implications. The use of the CUBDRISC scale as a simple, fast and low-cost tool for the active screening of people with dysglycemia in Cuban population will be useful to establish timely intervention strategies for people with risk score to develop dysglycemia.

OBJECTIVES.

To evaluate the Finnish Diabetes Risk Score (FINDRISC) modified for Cuba as a tool for the detection of prediabetes and undiagnosed diabetes in Cuban population.

MATERIALS AND METHODS.

An analytical cross-sectional and secondary source epidemiological study was conducted in 3737 adults aged 19 years and older with at least one risk factor for diabetes, they did not have previous diagnosis of prediabetes and diabetes mellitus and underwent oral glucose tolerance test for the diagnosis of dysglycemia. We applied the FINDRISC and the FINDRISC modified for Latin America (LA-FINDRISC) and Cuba (CUBDRISC), each with their own anthropometric parameters. The ROC curve was used to establish the cut-off point of each scale for the diagnosis of dysglycemia. Sensitivity, specificity, predictive values and likelihood ratios were calculated. The concordance between scales was calculated with Cohen's Kappa coefficient.

RESULTS.

We found that 34.5% (n=1289) of the subjects were diagnosed with dysglycemia (28.1% had prediabetes and 6.4% had type 2 diabetes without previous diagnosis). The LA-FINDRISC and CUBDRISC scales showed an almost perfect concordance with the FINDRISC scale for the different cut-off values from 11 to 16 (0.882-0.890 and 0.910-0.922, respectively). The optimal cutoff point for detecting persons with dysglycemia was ≥ 13 for the FINDRISC and CUBDRISC scales (sensitivity was 63.6% and 61.6%; specificity was 84.3% and 86.0%, respectively) and ≥11 for LA-FINDRISC (sensitivity 58.0% and specificity 88.0%).

CONCLUSIONS.

We found almost perfect concordance between the diabetes risk scales. The FINDRISC score modified for Cuba proved to be a useful tool to identify persons with prediabetes and diabetes with a cut-off point of 13 in a Cuban population.

External validation of Finnish diabetes risk score (FINDRISC) and Latin American FINDRISC for screening of undiagnosed dysglycemia: Analysis in a Peruvian hospital health care workers sample

AIMS

To evaluate the external validity of Finnish diabetes risk score (FINDRISC) and Latin American FINDRISC (LAFINDRISC) for undiagnosed dysglycemia in hospital health care workers.

METHODS

We carried out a cross-sectional study on health workers without a prior history of diabetes mellitus (DM). Undiagnosed dysglycemia (prediabetes or diabetes mellitus) was defined using fasting glucose and two-hour oral glucose tolerance test. LAFINDRISC is an adapted version of FINDRISC with different waist circumference cut-off points. We calculated the area under the receptor operational characteristic curve (AUROC) and explored the best cut-off point.

RESULTS

We included 549 participants in the analysis. The frequency of undiagnosed dysglycemia was 17.8%. The AUROC of LAFINDRISC and FINDRISC were 71.5% and 69.2%; p = 0.007, respectively. The optimal cut-off for undiagnosed dysglycemiaaccording to Index Youden was ≥ 11 in LAFINDRISC (Sensitivity: 78.6%; Specificity: 51.7%) and ≥12 in FINDRISC (Sensitivity: 70.4%; Specificity: 53.9%).

CONCLUSION

The discriminative capacity of both questionnaires is good for the diagnosis of dysglycemia in the healthcare personnel of the María Auxiliadora hospital. The LAFINDRISC presented a small statistical difference, nontheless clinically similar, since there was no difference by age or sex. Further studies in the general population are required to validate these results.

Prediabetes and Cardiometabolic Risk: The Need for Improved Diagnostic Strategies and Treatment to Prevent Diabetes and Cardiovascular Disease

The progression from prediabetes to type-2 diabetes depends on multiple pathophysiological, clinical, and epidemiological factors that generally overlap. Both insulin resistance and decreased insulin secretion are considered to be the main causes. The diagnosis and approach to the prediabetic patient are heterogeneous. There is no agreement on the diagnostic criteria to identify prediabetic subjects or the approach to those with insufficient responses to treatment, with respect to regression to normal glycemic values or the prevention of complications. The stratification of prediabetic patients, considering the indicators of impaired fasting glucose, impaired glucose tolerance, or HbA1c, can help to identify the sub-phenotypes of subjects at risk for T2DM. However, considering other associated risk factors, such as impaired lipid profiles, or risk scores, such as the Finnish Diabetes Risk Score, may improve classification. Nevertheless, we still do not have enough information regarding cardiovascular risk reduction. The sub-phenotyping of subjects with prediabetes may provide an opportunity to improve the screening and management of cardiometabolic risk in subjects with prediabetes.

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.

External validation of the risk prediction model for early diabetic kidney disease in Taiwan population: a retrospective cohort study

OBJECTIVES

This study aims to independently and externally validate the Risk Prediction Model for Diabetic Kidney Disease (RPM-DKD) in patients with type 2 diabetes mellitus (T2DM).

DESIGN

This is a retrospective cohort study.

SETTING

Outpatient clinics at Lee's United Clinics, Taiwan, China.

PARTICIPANTS

A total of 2504 patients (average age 55.44 years, SD, 7.49 years) and 4455 patients (average age 57.88 years, SD, 8.80 years) were included for analysis in the DKD prediction and progression prediction cohorts, respectively.

EXPOSURE

The predicted risk for DKD and DKD progression for each patient were all calculated using the RPM-DKD.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome measure was overall incidence of DKD. Secondary outcomes included DKD progression. The discrimination, calibration and precision of the RPM-DKD score were assessed.

RESULTS

The DKD prediction cohort and progression prediction cohort consisted of patients with 2504 and 4455 T2DM, respectively. The RPM-DKD examined in this study showed moderately discriminative ability with area under the curve ranged from 0.636 to 0.681 for the occurrence of DKD and 0.620 to 0.654 for the progression of DKD. The Hosmer-Lemeshow χ² test indicted the RPM-DKD was not well calibrated for predicting the occurrence of DKD and overestimated the progression of DKD. The precision for predicting the occurrence and progression of DKD were 43.2% and 42.2%, respectively.

CONCLUSIONS

On external validation, the RPM-DKD cannot accurately predict the risk of DKD occurrence and progression in patients with T2DM.

A new Brazilian regional scenario of Type 2 diabetes risk in the next ten years

AIMS

According to a recent national diabetes screening performed by our group in 2018, 18.4% of the Brazilians were found to have high blood glucose. The objective of the present study was to estimate the risk of developing type 2 DM (T2DM) in the next ten years in Brazilian population.

METHODS

A cross-sectional study was carried out in community pharmacies across Brazil, in 2018, where pharmacists applied the FINDRISC questionnaire to estimate the population's risk of developing T2DM within a ten-year period.

RESULTS

The study included 977 pharmacists from 345 municipalities distributed across the five geographical regions of Brazil. Of the 17,580 people evaluated, the South region was found to have the highest frequency (59.6%) among people at very low and/or low risk of developing T2DM, while the North region, the most underserved, presented the highest and/or very highest T2DM risk (24.1%). The factors that mostly and importantly impacted these regional differences were body mass index; the highest daily consumption of vegetables and fruits; history of high blood glucose and family history of T1DM/T2DM.

CONCLUSION

These results showed an impressive change of direction concerning diabetes numbers between the most underserved region in public health care and one of the most developed and best organized regions concerning health assistance, the North and the South, respectively.

Current State of Diabetes Mellitus Prevalence, Awareness, Treatment, and Control in Latin America: Challenges and Innovative Solutions to Improve Health Outcomes Across the Continent

PURPOSE OF REVIEW

Latin America is the scenario of great inequalities where about 32 million human beings live with diabetes. Through this review, we aimed at describing the current state of the prevalence, awareness, treatment, and control of diabetes mellitus and completion of selected guidelines of care across Latin America and identify opportunities to advance research that promotes better health outcomes.

RECENT FINDINGS

The prevalence of diabetes mellitus has been consistently increasing across the region, with some variation: higher prevalence in Mexico, Haiti, and Puerto Rico and lower in Colombia, Ecuador, Dominican Republic, Peru, and Uruguay. Prevalence assessment methods vary, and potentially underestimating the real number of persons with diabetes. Diabetes unawareness varies widely, with up to 50% of persons with diabetes who do not know they may have the disease. Glycemic, blood pressure, and LDL-C control and completion of guidelines to prevent microvascular complications are not consistently assessed across studies, and the achievement of control goals is suboptimal. On the other hand, multiple interventions, point-of-care/rapid assessment tools, and alternative models of health care delivery have been proposed and tested throughout Latin America. The prevalence of diabetes mellitus continues to rise across Latin America, and the number of those with the disease may be underestimated. However, some local governments are embedding more comprehensive diabetes assessments in their local national surveys. Clinicians and public health advocates in the region have proposed and initiated various multi-level interventions to address this enormous challenge in the region.