Screening for type 2 diabetes mellitus: a systematic review for the U.S. Preventive Services Task Force

Exploring in-vivo infrared spectroscopy for nail-based diabetes screening

Diabetes screening is traditionally complex, inefficient, and reliant on invasive sampling. This study evaluates near-infrared spectroscopy for non-invasive detection of glycated keratin in nails in vivo. Glycation of keratin, prevalent in tissues like nails and skin, is a key indicator of T2DM risk. In this study involving 200 participants (100 with diabetes, 100 without), NIR's efficacy was compared against a point-of-care HbA1c analyzer. Results showed a specificity of 92.9% in diabetes risk assessment. This study highlights the proposed NIR system potential as a simple, reliable tool for early diabetes screening and risk management in various healthcare settings.

Deep learning-based long-term risk evaluation of incident type 2 diabetes using electrocardiogram in a non-diabetic population: a retrospective, multicentre study

Background

Diabetes is a major public health concern. We aimed to evaluate the long-term risk of incident type 2 diabetes in a non-diabetic population using a deep learning model (DLM) detecting prevalent type 2 diabetes using electrocardiogram (ECG).

Methods

In this retrospective study, participants who underwent health checkups at two tertiary hospitals in Seoul, South Korea, between Jan 1, 2001 and Dec 31, 2022 were included. Type 2 diabetes was defined as glucose ≥126 mg/dL or glycated haemoglobin (HbA1c) ≥ 6.5%. For survival analysis on incident type 2 diabetes, we introduced an additional variable, diabetic ECG, which is determined by the DLM trained on ECG and corresponding prevalent diabetes. It was assumed that non-diabetic individuals with diabetic ECG had a higher risk of incident type 2 diabetes than those with non-diabetic ECG. The one-dimensional ResNet-based model was adopted for the DLM, and the Guided Grad-CAM was used to localise important regions of ECG. We divided the non-diabetic group into the diabetic ECG group (false positive) and the non-diabetic ECG (true negative) group according to the DLM decision, and performed a Cox proportional hazard model, considering the occurrence of type 2 diabetes more than six months after the visit.

Findings

190,581 individuals were included in the study with a median follow-up period of 11.84 years. The areas under the receiver operating characteristic curve for prevalent type 2 diabetes detection were 0.816 (0.807-0.825) and 0.762 (0.754-0.770) for the internal and external validations, respectively. The model primarily focused on the QRS duration and, occasionally, P or T waves. The diabetic ECG group exhibited an increased risk of incident type 2 diabetes compared with the non-diabetic ECG group, with hazard ratios of 2.15 (1.82-2.53) and 1.92 (1.74-2.11) for internal and external validation, respectively.

Interpretation

In the non-diabetic group, those whose ECG was classified as diabetes by the DLM were at a higher risk of incident type 2 diabetes than those whose ECG was not. Additional clinical research on the relationship between the phenotype of ECG and diabetes to support the results and further investigation with tracked data and various ECG recording systems are suggested for future works.

Funding

National Research Foundation of Korea.

Association of Protein Tyrosine Phosphatase Receptor Type D and Serine Racemase Genetic Variants with Type 2 Diabetes in Malaysian Indians

Introduction

Type 2 diabetes (T2D) candidate genes, protein tyrosine phosphatase receptor type D (PTPRD), and serine racemase (SRR) were suggested by a genome-wide association study (GWAS) in the Chinese population. Association studies have been replicated among East Asian populations. The association of PTPRD and SRR genetic variants with T2D in Southeast Asian populations still needs to be studied. This study aimed to investigate the association of PTPRD and SSR genetic variants with T2D in Malaysian Indian subjects.

Methods

The single nucleotide polymorphisms (SNPs) of PTPRD (rs649891 and rs17584499) and SRR (rs4523957, rs391300, and rs8081273) were genotyped in 397 T2D and 285 normal Malaysian Indian subjects.

Results

The homozygous dominant genotype of rs17584499 is frequent in diabetic patients (56.5%) compared to normal subjects (47.3%). In contrast, the homozygous recessive genotype of rs8081273 is more frequent among normal subjects (12.5%) than diabetic patients (5.6%). The dominant genetic model showed that PTPRD rs17584499 (CC) is a risk factor for T2D (OR = 1.42, P = 0.029), whereas the recessive genetic model showed that SRS SNP rs8081273 was protective for T2D (OR = 0.42, P = 0.003).

Conclusion

This study confirmed the association of PTPRD rs17584499 genetic variations with T2D in Malaysian Indians. While the SRR rs8081273 (TT) genotype showed protection against T2D, more investigation in different populations is required to confirm this protection.

A nomogram model for predicting 5-year risk of prediabetes in Chinese adults

Early identification is crucial to effectively intervene in individuals at high risk of developing pre-diabetes. This study aimed to create a personalized nomogram to determine the 5-year risk of pre-diabetes among Chinese adults. This retrospective cohort study included 184,188 participants without prediabetes at baseline. Training cohorts (92,177) and validation cohorts (92,011) were randomly assigned (92,011). We compared five prediction models on the training cohorts: full cox proportional hazards model, stepwise cox proportional hazards model, multivariable fractional polynomials (MFP), machine learning, and least absolute shrinkage and selection operator (LASSO) models. At the same time, we validated the above five models on the validation set. And we chose the LASSO model as the final risk prediction model for prediabetes. We presented the model with a nomogram. The model's performance was evaluated in terms of its discriminative ability, clinical utility, and calibration using the area under the receiver operating characteristic (ROC) curve, decision curve analysis, and calibration analysis on the training cohorts. Simultaneously, we also evaluated the above nomogram on the validation set. The 5-year incidence of prediabetes was 10.70% and 10.69% in the training and validation cohort, respectively. We developed a simple nomogram that predicted the risk of prediabetes by using the parameters of age, body mass index (BMI), fasting plasma glucose (FBG), triglycerides (TG), systolic blood pressure (SBP), and serum creatinine (Scr). The nomogram's area under the receiver operating characteristic curve (AUC) was 0.7341 (95% CI 0.7290-0.7392) for the training cohort and 0.7336 (95% CI 0.7285-0.7387) for the validation cohort, indicating good discriminative ability. The calibration curve showed a perfect fit between the predicted prediabetes risk and the observed prediabetes risk. An analysis of the decision curve presented the clinical application of the nomogram, with alternative threshold probability spectrums being presented as well. A personalized prediabetes prediction nomogram was developed and validated among Chinese adults, identifying high-risk individuals. Doctors and others can easily and efficiently use our prediabetes prediction model when assessing prediabetes risk.

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

BACKGROUND

Numerous laboratory tests are used in the diagnosis and management of diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially.

APPROACH

An expert committee compiled evidence-based recommendations for laboratory analysis in screening, diagnosis, or monitoring of diabetes. The overall quality of the evidence and the strength of the recommendations were evaluated. The draft consensus recommendations were evaluated by invited reviewers and presented for public comment. Suggestions were incorporated as deemed appropriate by the authors (see Acknowledgments). The guidelines were reviewed by the Evidence Based Laboratory Medicine Committee and the Board of Directors of the American Association for Clinical Chemistry and by the Professional Practice Committee of the American Diabetes Association.

CONTENT

Diabetes can be diagnosed by demonstrating increased concentrations of glucose in venous plasma or increased hemoglobin A1c (HbA1c) in the blood. Glycemic control is monitored by the people with diabetes measuring their own blood glucose with meters and/or with continuous interstitial glucose monitoring (CGM) devices and also by laboratory analysis of HbA1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of ketones, autoantibodies, urine albumin, insulin, proinsulin, and C-peptide are addressed.

SUMMARY

The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.

A follow-up cohort study on the risk of prediabetes, comparing women with previous preeclamptic or normotensive pregnancies

Studies have shown that preeclampsia is associated insulin resistance and cardiovascular events later in life. However, knowledge is lacking regarding a possible association between PE and abnormal glucose tolerance/prediabetes. Thus, the current study aimed to compare the prevalence of prediabetes in women with previous severe preeclampsia to women with previous normotensive pregnancies. Women with severe preeclampsia (index women, n = 45) admitted to Danderyds University Hospital in 1999-2004 were compared to women with normotensive pregnancies, matched for age, parity, and year of delivery (control women, n = 53). In 2013-2016 BMI, blood pressure, waist circumference, insulin, C-peptide, hsCRP, Cystatin C, HDL, triglycerides, and HbA1c were measured and an OGTT was performed. Index women had a higher BMI (p < 0.001) and blood pressure (p < 0.001) in early pregnancy. At follow-up, prediabetes was more common among index women (p = 0.001), as were hypertension (p = 0.003), heredity for diabetes/cardiovascular disease (p = 0.020), and a larger waist circumference (p = 0.024). Preeclampsia increased the risk of having a fasting plasma glucose ≥ 5.6 mmol/l (aOR 7.28, 95% CI 2.44-21.76) and of prediabetes 11-16 years after index pregnancy (aOR 4.83, 95% CI 1.80-12.97). In conclusion, preeclampsia increases the risk of prediabetes independent of heredity, hypertension, and waist circumference. These findings may have implications for screening and prevention.

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

BACKGROUND

Numerous laboratory tests are used in the diagnosis and management of diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially.

APPROACH

An expert committee compiled evidence-based recommendations for laboratory analysis in screening, diagnosis, or monitoring of diabetes. The overall quality of the evidence and the strength of the recommendations were evaluated. The draft consensus recommendations were evaluated by invited reviewers and presented for public comment. Suggestions were incorporated as deemed appropriate by the authors (see Acknowledgments). The guidelines were reviewed by the Evidence Based Laboratory Medicine Committee and the Board of Directors of the American Association of Clinical Chemistry and by the Professional Practice Committee of the American Diabetes Association.

CONTENT

Diabetes can be diagnosed by demonstrating increased concentrations of glucose in venous plasma or increased hemoglobin A1c (Hb A1c) in the blood. Glycemic control is monitored by the people with diabetes measuring their own blood glucose with meters and/or with continuous interstitial glucose monitoring (CGM) devices and also by laboratory analysis of Hb A1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of ketones, autoantibodies, urine albumin, insulin, proinsulin, and C-peptide are addressed.

SUMMARY

The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.

Assessment of the Risk of Type 2 Diabetes Mellitus Among a Rural Population in South India Using the Indian Diabetic Risk Score

Objective The objective of our study was to assess the risk for diabetes using the Indian Diabetic Risk Score (IDRS) questionnaire and compare the components of IDRS between the risk groups. Methods It was a cross-sectional study involving 270 male and female attendees who visited Melmaruvathur Adhiparasakthi Institute of Medical Sciences (MAPIMS) from December 2019 to May 2020. The diabetes risk was assessed using the IDRS questionnaire. Statistical Package for Social Sciences (SPSS) version 20 (IBM Corp., Armonk, NY) was used for statistical analysis. P < 0.05 was considered statistically significant. Results IDRS categorization showed 12.6%, 73.7%, and 13.7% in the low-risk, moderate-risk, and high-risk groups, respectively. Age, waist circumference, and body mass index (BMI) were significantly (P < 0.05) higher in the high-risk group when compared with the low-risk group. Subjects with a positive family history of diabetes and no/mild physical activity were higher in the moderate and high-risk group but there is no significant association present between them. Conclusion The current study estimates the effectiveness of IDRS in identifying people at high risk for diabetes in the community. This study also emphasizes the need for early identification of high-risk individuals and planning for the appropriate intervention to prevent, or delay, the onset of diabetes and thus reduces the burden of diabetes in India.

The prevalence of hyperglycemia and its association with perioperative outcomes in gynecologic surgery: a retrospective cohort study

BACKGROUND

Preoperative hyperglycemia has been associated with perioperative morbidity in general surgery patients. Additionally, preoperative hyperglycemia may indicate underlying impaired glucose metabolism. Thus, identification of preoperative hyperglycemia may provide an opportunity to mitigate both short-term surgical and long-term health risk. We aimed to study this phenomenon specifically in the gynecologic surgery population. Specifically, we aimed to evaluate the association between preoperative hyperglycemia and perioperative complications in gynecologic surgery patients and to characterize adherence to diabetes screening guidelines.

METHODS

This retrospective cohort study included 913 women undergoing major gynecologic surgery on an enhanced recovery pathway from January 2018 to July 2019. The main exposure was day of surgery glucose ≥ 140 g/dL. Multivariate regression identified risk factors for hyperglycemia and composite and wound-specific complications.

RESULTS

Sixty-seven (7.3%) patients were hyperglycemic. Diabetes (aOR 24.0, 95% CI 12.3-46.9, P < .001) and malignancy (aOR 2.3, 95% CI 1.2-4.5, P = .01) were associated with hyperglycemia. Hyperglycemia was not associated with increased odds of composite perioperative (aOR 1.3, 95% CI 0.7-2.4, P = 0.49) or wound-specific complications (aOR 1.1, 95% CI 0.7-1.5, P = 0.76). Of nondiabetic patients, 391/779 (50%) met the USPSTF criteria for diabetes screening; 117 (30%) had documented screening in the preceding 3 years. Of the 274 unscreened patients, 94 (34%) had day of surgery glucose levels suggestive of impaired glucose metabolism (glucose ≥ 100 g/dL).

CONCLUSION

In our study cohort, the prevalence of hyperglycemia was low and was not associated with higher risk of composite or wound-specific complications. However, adherence to diabetes screening guidelines was poor. Future studies should aim to develop a preoperative blood glucose testing strategy that balances the low utility of universal glucose screening with the benefit of diagnosing impaired glucose metabolism in at-risk individuals.

The Protection Gap - Diagnosis, Treatment Status, and Disease Control for People with Diabetes and Hypertension in the US-Affiliated Pacific Islands

Hypertension and diabetes are major causes of disability and mortality in the US-Affiliated Pacific Islands (USAPI). Control of these conditions has the potential to avert much of the burden of non-communicable diseases in the region. To realize this potential, people living with hypertension and diabetes must be identified and receive treatment of sufficient intensity to control their blood pressure and blood glucose. Data from recent cross-sectional surveys conducted in 5 jurisdictions-Pohnpei, Palau, Kosrae, Marshall Islands and American Samoa-were used to estimate the adult prevalence of hypertension and diabetes as well as diagnosis awareness, treatment, and control status of the adults with these conditions. In addition to traditional prevalence indicators, the authors provide a novel presentation of non-communicable disease (NCD) data, using the concept of "protection gaps", defined as the number of people living in a community who have an NCD for which effective control is not attained. The protection gap is determined by applying survey-derived population prevalence estimates to the community's population size using census data. The protection gap is further divided into 3 groups: (1) case-finding gap-those who are unaware of their conditions; (2) tracking and outreach gap-those who are aware of their condition but not receiving treatment; and (3) treatment efficacy gap-those who are receiving treatment but whose disease is not under control. The findings show a large protection gap, with a majority of adults living with hypertension (80.8%) and diabetes (91.6%) not having their condition under control. The case-finding gap accounts for more than half of these, followed by treatment efficacy, and tracking and outreach gaps. These findings can guide public health strategies and monitoring for control of hypertension and diabetes in the USAPI region.

ModAsian FINDRISC as a Screening Tool for People with Undiagnosed Type 2 Diabetes Mellitus in Vietnam: A Community-Based Cross-Sectional Study

Purpose

Our study aims to evaluate the risk of developing type 2 diabetes mellitus in the next 10 years using ModAsian FINDRISC and additionally explore associated factors among the Vietnam population.

Participants and Methods

A cross-sectional study was conducted on 2258 participants aged 25 years old or above in Thua Thien Hue Province, Vietnam. The sample size is calculated based on the estimated sensitivity, and participants were randomly selected from different geographical and socio-economic areas. All participants were thoroughly medically examined, taking blood lipid profile and fasting blood glucose, taking blood pressure, anthropometric indexes, 12-lead electrocardiogram, and behavioral factors were investigated using the Vietnamese version of the WHO STEPS toolkit. The risk of developing T2DM was made based on the ModAsian FINDRISC.

Results

The incidence of developing type 2 diabetes mellitus among the study population was 4.21%. The group with a high or very high risk of developing type 2 diabetes mellitus in the next 10 years accounted for 2.52%. Body mass index (AUC = 0.840, 95% CI: 0.792-0.888), waist circumference (AUC = 0.824, 95% CI: 0.777-0.871), family history of diabetes mellitus (AUC = 0.751, 95% CI = 0.668-0.833), and history of antihypertensive medication use regularly (AUC = 0.708, 95% CI: 0.632-0.784) are the most associated factors of the ModAsian FINDRISC. Residential location (OR = 5.62, 95% CI: 1.91-16.54) and occupational status (OR = 0.35, 95% CI: 0.20-0.62) were significant factors associated with a high and very high risk of developing type 2 diabetes mellitus in the next 10 year.

Conclusion

Screening for the risk of type 2 diabetes mellitus and implementing intervention programs focusing on controlling weight, waist circumference, and blood pressure are essential for reducing type 2 diabetes mellitus incidence and burden in Vietnam.

Fatty acid overproduction by gut commensal microbiota exacerbates obesity

Although recent studies have highlighted the impact of gut microbes on the progression of obesity and its comorbidities, it is not fully understood how these microbes promote these disorders, especially in terms of the role of microbial metabolites. Here, we report that Fusimonas intestini, a commensal species of the family Lachnospiraceae, is highly colonized in both humans and mice with obesity and hyperglycemia, produces long-chain fatty acids such as elaidate, and consequently facilitates diet-induced obesity. High fat intake altered the expression of microbial genes involved in lipid production, such as the fatty acid metabolism regulator fadR. Monocolonization with a FadR-overexpressing Escherichia coli exacerbated the metabolic phenotypes, suggesting that the change in bacterial lipid metabolism is causally involved in disease progression. Mechanistically, the microbe-derived fatty acids impaired intestinal epithelial integrity to promote metabolic endotoxemia. Our study thus provides a mechanistic linkage between gut commensals and obesity through the overproduction of microbe-derived lipids.

[Cardiovascular preventive recommendations. PAPPS 2022 thematic updates. Working groups of the PAPPS]

The recommendations of the semFYC's Program for Preventive Activities and Health Promotion (PAPPS) for the prevention of cardiovascular diseases (CVD) are presented. The following sections are included: epidemiological review, where the current morbidity and mortality of CVD in Spain and its evolution as well as the main risk factors are described; cardiovascular (CV) risk and recommendations for the calculation of CV risk; main risk factors such as arterial hypertension, dyslipidemia and diabetes mellitus, describing the method for their diagnosis, therapeutic objectives and recommendations for lifestyle measures and pharmacological treatment; indications for antiplatelet therapy, and recommendations for screening of atrial fibrillation, and recommendations for management of chronic conditions. The quality of testing and the strength of the recommendation are included in the main recommendations.

Integrated analysis of probability of type 2 diabetes mellitus with polymorphisms and methylation of SLC30A8 gene: a nested case-control study

To estimate the associations between single-nucleotide polymorphisms (SNPs) and methylation of SLC30A8 gene and T2DM risk, and the interactions among SNPs, methylation, and environmental factors on T2DM risk. We genotyped 9 SNPs and tested methylation at 46 CpG loci of SLC30A8 in the baseline DNA of 290 T2DM cases and 290 matched controls nested in the Rural Chinese Cohort Study. A conditional logistic regression model was used to estimate the associations between SNPs and SLC30A8 methylation and T2DM risk. Multifactor Dimensionality Reduction analysis was used to estimate the effect of interactions among SNPs, methylation, and environment on T2DM risk. Probability of T2DM was decreased with rs11558471 (GG vs. AA, OR = 0.55, 95% CI 0.32, 0.96), with rs13266634 (TT vs. CC, OR = 0.55, 95% CI 0.32, 0.94), with rs3802177 (AA vs. GG, OR = 0.54, 95%CI 0.31, 0.94), and its probability was increased with rs2466293 of SLC30A8 (GA vs. AA, OR = 1.63, 95% CI 1.08-2.47). Its probability was also significantly associated with methylation of CG9 and CG45 (OR = 0.56 [95% CI 0.33-0.97] and 1.61 [95%CI 1.03--2.51]). T2DM probability was significantly associated with the interaction effect between rs2466293 and hypertension (p = 0.045). T2DM probability was also significantly associated with the combination effects of rs2466293 with BMI, hypertension, and hypertriglyceridemia, with the combination effects of hypertriglyceridemia with rs11558471, rs13266634, and methylation of CG45.

Translation and performance of the Finnish Diabetes Risk Score for detecting undiagnosed diabetes and dysglycaemia in the Indonesian population

A diabetes risk score cannot directly be translated and applied in different populations, and its performance should be evaluated in the target population. This study aimed to translate the Finnish Diabetes Risk Score (FINDRISC) instrument and compare its performance with the modified version for detecting undiagnosed type 2 diabetes mellitus (T2DM) and dysglycaemia among the Indonesian adult population. Forward and backward translations were performed and followed by cultural adaptation. In total, 1,403 participants were recruited. The FINDRISC-Bahasa Indonesia (FINDRISC-BI) was scored according to the original FINDRISC instrument, while a Modified FINDRISC-BI was analyzed using a specific body mass index and waist circumference classification for Indonesians. The area under the receiver operating characteristic curve, sensitivity, specificity, and the optimal cut-offs of both instruments were estimated. The area under the receiver operating characteristic curve for detecting undiagnosed T2DM was 0.73 (0.67–0.78) for the FINDRISC-BI with an optimal cut-off score of ≥9 (sensitivity = 63.0%; specificity = 67.3%) and 0.72 (0.67–0.78) for the Modified FINDRISC-BI with an optimal cut-off score of ≥11 (sensitivity = 59.8%; specificity = 74.9%). The area under the receiver operating characteristic curve for detecting dysglycaemia was 0.72 (0.69–0.75) for the FINDRISC-BI instrument with an optimal cut-off score of ≥8 (sensitivity = 66.4%; specificity = 67.0%), and 0.72 (0.69–0.75) for the Modified FINDRISC-BI instrument with an optimal cut-off score ≥9 (sensitivity = 63.8%; specificity = 67.6%). The Indonesian version of the FINDRISC instrument has acceptable diagnostic accuracy for screening people with undiagnosed T2DM or dysglycaemia in Indonesia. Modifying the body mass index and waist circumference classifications in the Modified FINDRISC-BI results in a similar diagnostic accuracy; however, the Modified FINDRISC-BI has a higher optimal cut-off point than the FINDRISC-BI. People with an above optimal cut-off score are suggested to take a further blood glucose test.

A Machine Learning-Based Predictive Model to Identify Patients Who Failed to Attend a Follow-up Visit for Diabetes Care After Recommendations From a National Screening Program

OBJECTIVE

Reportedly, two-thirds of the patients who were positive for diabetes during screening failed to attend a follow-up visit for diabetes care in Japan. We aimed to develop a machine-learning model for predicting people's failure to attend a follow-up visit.

RESEARCH DESIGN AND METHODS

We conducted a retrospective cohort study of adults with newly screened diabetes at a national screening program using a large Japanese insurance claims database (JMDC, Tokyo, Japan). We defined failure to attend a follow-up visit for diabetes care as no physician consultation during the 6 months after the screening. The candidate predictors were patient demographics, comorbidities, and medication history. In the training set (randomly selected 80% of the sample), we developed two models (previously reported logistic regression model and Lasso regression model). In the test set (remaining 20%), prediction performance was examined.

RESULTS

We identified 10,645 patients, including 5,450 patients who failed to attend follow-up visits for diabetes care. The Lasso regression model using four predictors had a better discrimination ability than the previously reported logistic regression model using 13 predictors (C-statistic: 0.71 [95% CI 0.69-0.73] vs. 0.67 [0.65-0.69]; P < 0.001). The four selected predictors in the Lasso regression model were lower frequency of physician visits in the previous year, lower HbA1c levels, and negative history of antidyslipidemic or antihypertensive treatment.

CONCLUSIONS

The developed machine-learning model using four predictors had a good predictive ability to identify patients who failed to attend a follow-up visit for diabetes care after a screening program.

Developing a risk score for undiagnosed prediabetes or type 2 diabetes among Saharawi refugees in Algeria

Aims

To prevent type 2 diabetes mellitus (T2D) and reduce the risk of complications, early identification of people at risk of developing T2D, preferably through simple diabetes risk scores, is essential. The aim of this study was to create a risk score for identifying subjects with undiagnosed prediabetes or T2D among Saharawi refugees in Algeria and compare the performance of this score to the Finnish diabetes risk score (FINDRISC).

Methods

A cross-sectional survey was carried out in five Saharawi refugee camps in Algeria in 2014. A total of 180 women and 175 men were included. HbA1c and cut-offs proposed by the American Diabetes Association (ADA) were used to define cases. Variables to include in the risk score were determined by backwards elimination in logistic regression. Simplified scores were created based on beta coefficients from the multivariable model after internal validation with bootstrapping and shrinkage. The empirical cut-off value for the simplified score and FINDRISC was determined by Area Under the Receiver Operating Curve (AUROC) analysis.

Results

Variables included in the final risk score were age, body mass index (BMI), and waist circumference. The area under the curve (AUC) (C.I) was 0.82 (0.76, 0.88). The sensitivity, specificity, and positive and negative predictive values were 89, 65, 28, and 97%, respectively. AUC and sensitivity were slightly higher and specificity somewhat lower than for FINDRISC.

Conclusions

The risk score developed is a helpful tool to decide who should be screened for prediabetes or T2D by blood sample analysis. The performance of the risk score was adequate based on internal validation with bootstrap analyses, but should be confirmed in external validation studies.

Effect of gestational diabetes mellitus on lipid profile: A systematic review and meta-analysis

Gestational diabetes mellitus (GDM) can have adverse effects on pregnancy. GDM is associated with changes in the lipid profile of pregnant women. Finding out the early ways to diagnose GDM can prevent the adverse outcomes. This meta-analysis study aimed to determine the effect of GDM on lipid profile. PubMed, ProQuest, Web of Science, Scopus, Science Direct, Google Scholar, and ClinicalTrial were systematically searched for published articles relating to GDM until 2021 according to PRISMA guidelines. Newcastle Ottawa scale was used to assess the quality of the studies. Thirty-three studies with a sample size of 23,792 met the criteria for entering the meta-analysis. Pooled standardized mean difference (SMD) for total cholesterol (TC) and triglyceride (TG) was 0.23 mg/dL (95% CI: 0.11–0.34) and 1.14 mg/dL (95% CI: 0.91–1.38), respectively. The mean of TC and TG in people with GDM was higher than that in normal pregnant women. A similar pattern was observed for the very low-density lipoprotein (VLDL) and TG/high-density lipoprotein (HDL) ratio, with pooled SMD of 0.99 mg (95% CI: 0.71–1.27) and 0.65 mg (95% CI: 0.36–0.94), respectively. Pooled SMD for HDL was −0.35 mg/dL (95% CI: −0.54 to −0.16), women with GDM had a mean HDL lower than normal pregnant women. Although pooled SMD was higher for low-density lipoprotein (LDL) in the GDM group, this difference was not significant (0.14 [95% CI: −0.04 to 0.32]). Of all the lipid profiles, the largest difference between the GDM and control groups was observed in TG (SMD: 1.14). Elevated serum TG had the strongest effect on GDM. Higher levels of TC, LDL, VLDL, and TG/HDL ratio, and lower level of HDL were exhibited in GDM group. So, these markers can be considered as a reliable marker in the diagnosis of GDM.

Facilitators and Barriers to Uptake of Community-Based Diabetes Prevention Program Among Multi-Ethnic Asian Patients With Prediabetes

OBJECTIVE

This study aimed to identify facilitators and barriers to the uptake of a community-based diabetes prevention program (DPP) from the perspectives of decliners with prediabetes in a multi-ethnic Asian community.

METHODS

Semi-structured interviews were conducted with 29 individuals with prediabetes who declined participation in a large community-based diabetes prevention program in Singapore. Thematic analysis was undertaken to identify themes, which were subsequently mapped onto the Capacity-Opportunity-Motivation and Behavior model (COM-B).

RESULTS

We identified 16 key themes under three COM-B domains. Health status at the time of invitation, perceived ability of self-management, understanding of prediabetes condition and/or the program intention (Capability) were important determinants. Family commitment had the strong potential to enable or hinder physical and social Opportunity related to participation. Many participants desired involvement of physician as part of program invitation and component. Fear of exacerbation coupled with an automatic aversion for suffering influenced Motivation for participation.

CONCLUSION

Identifying facilitators and barriers embedded in the COM-B will assist systematic program modifications to increase participation of individuals with prediabetes. How information about modifiable risk factors is communicated by physicians at the point of diagnosis and program introduction is key to participation. Co-locating programs with family activity, development of mHealth, readiness assessment, and tailored explanation of program purpose may increase participation. These findings will be used to guide future national interventions in the community to ensure successful implementation.

Are There Different Viewpoints About the Management of Type 2 Diabetes Mellitus and Comorbidities? A Multidisciplinary Spanish Qualitative Research

INTRODUCTION

The aim of this study was to explore the vision of a large multidisciplinary group of physicians treating type 2 diabetes mellitus (T2DM) in Spain, with a special focus on controversial management aspects. The perceptions of primary care (PC) physicians and hospital care (HC) specialists were compared.

METHODS

This was a mixed survey that included Delphi-like statements and opinion, attitude and behaviour (OAB) questions. The Delphi-like statements were assessed on the basis of the degree of agreement among respondents, and a descriptive analysis was performed on the answers to the OAB questions.

RESULTS

A total of 296 participants responded to the first wave of the survey, of whom 293 responded to the second wave (211 from PC and 80 from HC, with two respondents for whom there were no data on specialty). A high degree of consensus (CNS ≥ 0.8) was obtained in all the statements. A proactive approach to detect prediabetes or T2DM in asymptomatic people was highly supported (80.4% of agreement). Introducing early treatment intensification was considered to favour the durability of glycaemic control and to delay the progression of the disease (80.4%). There was agreement on the statement that glycaemic variability constitutes a risk factor for chronic complications, although differences in the perceptions of HC physicians and PC specialists were identified (86.3 vs. 80.1%, respectively). More HC physicans than PC specialists considered comorbidities to affect the ability to self-care (95 vs. 82.9%, respectively).

CONCLUSIONS

The survey revealed that there was a high, albeit not universal, degree of agreement amongst PC physicians and HC specialists in relation to prevention, screening and diagnosis of T2DM; early treatment intensification; dysglycaemias; and the management of patients with comorbidities. The statement on the management of patients with comorbidities elicited the highest difference between PC physicans and HC specialists. The results of this survey indicate that there is room for improvement in terms of implementing strategies in these areas.

Incidence and Risk Factors for Progression to Diabetes Mellitus: A Retrospective Cohort Study

(1) Objective: This study examined the incidence and risk factors contributing to the progression to diabetes mellitus (DM) in a seven-year follow-up study of non-diabetic National Health Examinees. (2) Methods: For this retrospective observational cohort study, we used two national representative databases: the National Health Screening (HEALS) database 2009 and the National Health Insurance Service (NHIS) database 2009-2015. The eligible subjects without DM with blood sugar levels of <126 mg/dL were selected using the HEALS database. The subsequent follow-up and clinical outcomes were evaluated using the NHIS database. Cox proportional hazard regression was applied to examine the effects of the covariates on progression to diabetes. (3) Results: Among those who took part in the national health screening in 2009, 4,205,006 subjects who met the eligibility criteria were selected. Of these, 587,015 were diagnosed with DM during the follow-up by 2015. The incidence of progression from non-diabetes to DM was 14.0%, whereas that from impaired fasting glucose (IFG) to DM was 21.9%. Compared to the normal group, the newly diagnosed DM group was more likely to comprise older, female, currently smoking, and high-risk drinking participants and participants with IFG, hypertension, dyslipidemia, and metabolic syndrome. (4) Conclusions: This epidemiological study in the Republic of Korea found risk factors similar to those of other studies, but the incidence of progression to DM was 22.8 per 1000 person-years, which is higher than that previously reported. Hence, more care is needed to prevent DM.

Screening for Diabetes and Prediabetes

Overt type 2 diabetes mellitus (T2DM) is preceded by prediabetes and latent diabetes (lasts 9-12 years). Key dysglycemia screening tests are fasting plasma glucose and hemoglobin A1C. Screen-detected T2DM benefits from multifactorial management of cardiovascular risk beyond glycemia. Prediabetes is best addressed by lifestyle modification, with the goal of preventing T2DM. Although there is no trial evidence of prediabetes/T2DM screening effectiveness, simulations suggest that clinic-based opportunistic screening of high-risk individuals is cost-effective. The most rigorous extant recommendations are those of the American Diabetes Association and US Preventive Services Task Force, which advise opportunistic 3-yearly screening.

Who is getting screened for diabetes according to body mass index and waist circumference categories in Peru? a pooled analysis of national surveys between 2015 and 2019

BACKGROUND

At the population level we would expect that people with obesity undergo diabetes screening tests more often than people with overweight and much more often than people with normal weight. We described the trends of diabetes screening according to body mass index (BMI) and waist circumference (WC) in Peru.

METHODS

Pooled analysis of health national surveys (2015-2019); men and women aged 35-70 years. We used relative frequencies to study: among those who have had a glucose test in the last year, how many there were in each BMI and WC category. We fitted a Poisson model to study whether people with high BMI or WC were more likely to have had a glucose test.

RESULTS

People with overweight (PR = 1.34; 95% CI: 1.29-1.38), obesity (PR = 1.57; 95% CI: 1.51-1.63) and central obesity (PR = 1.63; 95% CI: 1.35-1.96) were more likely to have had a glucose test. At the sub-national level, there was one (of twenty-five) region in which men with obesity were more often screened for diabetes than men with overweight and much more than men with normal weight. There were seven regions in which women with obesity were the most often screened for diabetes.

CONCLUSIONS

Consistent with a risk-based prevention approach, people with obesity would be screened for diabetes more often than those with overweight and those with normal weight. This ideal profile was only observed in few regions. Diabetes screening strategies should be strengthened and homogenised, so that they reach those at high risk of diabetes.

Diabetes and Oral Health: Summary of Current Scientific Evidence for Why Transdisciplinary Collaboration Is Needed

This Perspective provides a brief summary of the scientific evidence for the often two-way links between hyperglycemia, including manifest diabetes mellitus (DM), and oral health. It delivers in a nutshell examples of current scientific evidence for the following oral manifestations of hyperglycemia, along with any available evidence for effect in the opposite direction: periodontal diseases, caries/periapical periodontitis, tooth loss, peri-implantitis, dry mouth (xerostomia/hyposalivation), dysbiosis in the oral microbiome, candidiasis, taste disturbances, burning mouth syndrome, cancer, traumatic ulcers, infections of oral wounds, delayed wound healing, melanin pigmentation, fissured tongue, benign migratory glossitis (geographic tongue), temporomandibular disorders, and osteonecrosis of the jaw. Evidence for effects on quality of life will also be reported. This condensed overview delivers the rationale and sets the stage for the urgent need for delivery of oral and general health care in patient-centered transdisciplinary collaboration for early detection and management of both hyperglycemia and oral diseases to improve quality of life.

Examining if the relationship between BMI and incident type 2 diabetes among middle-older aged adults varies by race/ethnicity: evidence from the Multi-Ethnic Study of Atherosclerosis (MESA)

AIMS

Disparities persist on the prevalence of undiagnosed type 2 diabetes in racial/ethnic minorities in the USA. This study evaluated the association between BMI and incident type 2 diabetes risk by racial/ethnic group, to determine whether BMI and presence of type 2 diabetes risk factors may help clinicians better target type 2 diabetes screening.

METHODS

This prospective cohort analysis included 5659 adults free of type 2 diabetes at baseline from the Multi-Ethnic Study of Atherosclerosis (MESA), a population-based cohort (2000-2011). BMI was measured at baseline and time-updated at subsequent visits. Incident type 2 diabetes was defined as fasting glucose ≥ 7.0 mmol/l, or use of any diabetes medications.

RESULTS

The mean (sd) age was 62 (10) years and 42% of participants were white, 26% African American, 20% Hispanic and 12% Chinese American. During follow-up, 696 (12%) new type 2 diabetes cases were observed. In age- and sex-adjusted models, in the presence of one or more type 2 diabetes risk factors (the most common scenario), a 10% risk of incident type 2 diabetes was observed at a BMI of 21.7 kg/m² [95% confidence interval (CI) 20.1 to 22.8] in Chinese Americans, 23.8 kg/m² (22.7 to 24.9) in Hispanics, 24.7 kg/m² (23.7 to 25.6) in African Americans and 26.2 kg/m² (25.1 to 26.9) in white participants.

CONCLUSIONS

This study supports including BMI and presence of type 2 diabetes risk factors as action points for clinicians to prioritize which adults aged ≥ 45 years should be screened. The application of race/ethnicity-specific BMI thresholds may reduce the disparity of undiagnosed type 2 diabetes observed in minority groups.

Measuring Adherence to U.S. Preventive Services Task Force Diabetes Prevention Guidelines Within Two Healthcare Systems

ABSTRACT

Measuring adherence to the 2015 U.S. Preventive Services Task Force (USPSTF) diabetes prevention guidelines can inform implementation efforts to prevent or delay Type 2 diabetes. A retrospective cohort was used to study patients without a diagnosis of diabetes attributed to primary care clinics within two large healthcare systems in our state to study adherence to the following: (1) screening at-risk patients and (2) referring individuals with confirmed prediabetes to participate in an intensive behavioral counseling intervention, defined as a Center for Disease Control and Prevention (CDC)-recognized Diabetes Prevention Program (DPP). Among 461,866 adults attributed to 79 primary care clinics, 45.7% of patients were screened, yet variability at the level of the clinic ranged from 14.5% to 83.2%. Very few patients participated in a CDC-recognized DPP (0.52%; range 0%-3.53%). These findings support the importance of a systematic implementation strategy to specifically target barriers to diabetes prevention screening and referral to treatment.

Outcomes in prediabetes vs. diabetes in patients with non-ST-segment elevation myocardial infarction undergoing percutaneous intervention

OBJECTIVE

The comparative long-term clinical outcomes between patients with prediabetes and diabetes in patients with non-ST-elevation myocardial infarction (NSTEMI) and multivessel disease (MVD) who were undergoing percutaneous coronary intervention (PCI) are not well known. We therefore compared the 2-year clinical outcomes in such patients.

METHODS

A total of 2963 patients with NSTEMI and MVD [normoglycemia (group A, n = 629), prediabetes (group B, n = 802), and diabetes (group C, n = 1532)] were evaluated. The primary outcomes were the occurrence of major adverse cardiac events (MACE) defined as all-cause death, recurrent myocardial infarction (Re-MI), and any repeat revascularization. The secondary outcome was stent thrombosis.

RESULTS

The cumulative incidence of MACE as well as for death or MI in group B and C were similar when compared to each other. However, they (P = 0.048 and P = 0.017, respectively and P = 0.022 and P = 0.001, respectively) were significantly higher than in group A. The cumulative incidence of all-cause death in group B (P = 0.042) and all-cause death and cardiac death in group C (P = 0.001 and P = 0.028, respectively) were significantly higher than in group A. However, those of all-cause death, cardiac death, Re-MI, any repeat revascularization, and ST were not significantly different between groups B and C.

CONCLUSION

In this study, patients with NSTEMI and MVD who underwent successful implantation of newer-generation DES and were prediabetic had worse outcomes compared to normoglycemics and comparable to those with diabetes.

The Role of H2S in the Metabolism of Glucose and Lipids

Glucose and lipids are essential elements for maintaining the body's homeostasis, and their dysfunction may participate in the pathologies of various diseases, particularly diabetes, obesity, metabolic syndrome, cardiovascular ailments, and cancers. Among numerous endogenous mediators, the gasotransmitter hydrogen sulfide (H₂S) plays a central role in the maintenance of glucose and lipid homeostasis. Current evidence from both pharmacological studies and transgenic animal models suggest a complex relationship between H₂S and metabolic dysregulation, especially in diabetes and obesity. This notion is achieved through tissue-specific expressions and actions of H₂S on target metabolic and hormone organs including the pancreas, skeletal muscle, livers, and adipose. In this chapter, we will summarize the roles and mechanisms of H₂S in several metabolic organs/tissues that are necessary for glucose and lipid metabolic homeostasis. In addition, future research directions and valuable therapeutic avenues around the pharmacological regulation of H₂S in glycolipid metabolism disorder will be also discussed.

Machine Learning for Predicting the 3-Year Risk of Incident Diabetes in Chinese Adults

Purpose: We aimed to establish and validate a risk assessment system that combines demographic and clinical variables to predict the 3-year risk of incident diabetes in Chinese adults. Methods: A 3-year cohort study was performed on 15,928 Chinese adults without diabetes at baseline. All participants were randomly divided into a training set (n = 7,940) and a validation set (n = 7,988). XGBoost method is an effective machine learning technique used to select the most important variables from candidate variables. And we further established a stepwise model based on the predictors chosen by the XGBoost model. The area under the receiver operating characteristic curve (AUC), decision curve and calibration analysis were used to assess discrimination, clinical use and calibration of the model, respectively. The external validation was performed on a cohort of 11,113 Japanese participants. Result: In the training and validation sets, 148 and 145 incident diabetes cases occurred. XGBoost methods selected the 10 most important variables from 15 candidate variables. Fasting plasma glucose (FPG), body mass index (BMI) and age were the top 3 important variables. And we further established a stepwise model and a prediction nomogram. The AUCs of the stepwise model were 0.933 and 0.910 in the training and validation sets, respectively. The Hosmer-Lemeshow test showed a perfect fit between the predicted diabetes risk and the observed diabetes risk (p = 0.068 for the training set, p = 0.165 for the validation set). Decision curve analysis presented the clinical use of the stepwise model and there was a wide range of alternative threshold probability spectrum. And there were almost no the interactions between these predictors (most P-values for interaction >0.05). Furthermore, the AUC for the external validation set was 0.830, and the Hosmer-Lemeshow test for the external validation set showed no statistically significant difference between the predicted diabetes risk and observed diabetes risk (P = 0.824). Conclusion: We established and validated a risk assessment system for characterizing the 3-year risk of incident diabetes.

Best Practices in the Management of Overweight and Obesity

Obesity is a chronic disease caused by dysregulated energy homeostasis pathways that encourage the accumulation of adiposity, which in turn results in the development or exacerbation of weight-related comorbidities. Treatment of obesity relies on a foundation of lifestyle modification; weight loss pharmacotherapy, bariatric surgery and devices are additional tools to help patients achieve their health goals. Appropriate management of patients with obesity provides multiple metabolic benefits beyond weight loss.

A prediction nomogram for the 3-year risk of incident diabetes among Chinese adults

Identifying individuals at high risk for incident diabetes could help achieve targeted delivery of interventional programs. We aimed to develop a personalized diabetes prediction nomogram for the 3-year risk of diabetes among Chinese adults. This retrospective cohort study was among 32,312 participants without diabetes at baseline. All participants were randomly stratified into training cohort (n = 16,219) and validation cohort (n = 16,093). The least absolute shrinkage and selection operator model was used to construct a nomogram and draw a formula for diabetes probability. 500 bootstraps performed the receiver operating characteristic (ROC) curve and decision curve analysis resamples to assess the nomogram's determination and clinical use, respectively. 155 and 141 participants developed diabetes in the training and validation cohort, respectively. The area under curve (AUC) of the nomogram was 0.9125 (95% CI, 0.8887-0.9364) and 0.9030 (95% CI, 0.8747-0.9313) for the training and validation cohort, respectively. We used 12,545 Japanese participants for external validation, its AUC was 0.8488 (95% CI, 0.8126-0.8850). The internal and external validation showed our nomogram had excellent prediction performance. In conclusion, we developed and validated a personalized prediction nomogram for 3-year risk of incident diabetes among Chinese adults, identifying individuals at high risk of developing diabetes.

Glutathione S-transferases gene polymorphism influence on the age of diabetes type 2 onset

INTRODUCTION

Type 2 diabetes (T2D) is a multifactorial disease affecting mostly adults older than 40 years. The aim of the study was to examine GST gene polymorphism influence on the risk of T2D, especially in young adults.

RESEARCH DESIGN AND METHODS

200 diabetic patients and 221 healthy controls participated in this study. Three GST gene polymorphism have been analyzed: GSTP1 (single-nucleotide polymorphism Ile₁₀₅Val), homozygous deletion of GSTT1 (null/null) and GSTM1 (null/null), using TaqMan real-time quantitative PCR.

RESULTS

The distribution of examined polymorphisms was similar in patient group and control group. Statistically significant differences were demonstrated for the combination of GSTP1 Val/Val and GSTT1 null/null genotypes between patients diagnosed before 40 years of age and healthy people (12.5% vs 0.9%, p=0.016). Moreover, all three examined gene polymorphism together (GSTP1 Val/Val, GSTM1nul/null and GSTT1 null/null genotype) was observed in 12.5% of patients diagnosed before 40 years of age and in 0.5% of healthy individuals (p=0.013).

CONCLUSION

In conclusion, the results suggest that GST polymorphism may be one of the risk factors for developing T2D at a younger age than the T2D population average.

[Cardiovascular preventive recommendations. PAPPS 2020 update]

The recommendations of the semFYC's Program for Preventive Activities and Health Promotion (PAPPS) for the prevention of cardiovascular diseases (CVD) are presented. The following sections are included: Epidemiological review, where the current morbidity and mortality of CVD in Spain and its evolution as well as the main risk factors are described; Cardiovascular (CV) risk tables and recommendations for the calculation of CV risk; Main risk factors such as arterial hypertension, dyslipidemia and diabetes mellitus, describing the method for their diagnosis, therapeutic objectives and recommendations for lifestyle measures and pharmacological treatment; Indications for antiplatelet therapy, and recommendations for screening of atrial fibrillation. The quality of testing and the strength of the recommendation are included in the main recommendations.

Evaluation of the Finnish Diabetes Risk Score (FINDRISC) for diabetes screening in Kayseri, Turkey

AIM

Diabetes is a major health problem worldwide, as its prevalence is increasing dramatically. Lifestyle modification can delay or prevent the onset of type 2 diabetes. Therefore, screening for prediabetes and type 2 diabetes risk through an assessment of risk factors is important. The objective of the study was to investigate the risk for type 2 diabetes using the Finnish Diabetes Risk Score (FINDRISC) in Kayseri.

METHODS

In total, 1500 adults aged 18 years or older were interviewed using the FINDRISC as Diabetes Risk Questionnaire and fasting serum glucose levels. The findings of FINDRISC were grouped according to gender and a score of 15 and above was accepted as a high risk in terms of Type 2 diabetes.

RESULTS

13.5% of the participants were in the high- risk group. There was a statistically significant relationship between total FINDRISC score and gender (p < 0.001). While 15.2% of the women were in the high -risk group, 12.4% of the men were in the high- risk group. The percentage of women in the low-risk group (35.9%) is less than the men with low- risk of diabetes (38.5%). As the BMI increased, the individuals were found to have a high risk evaluated with the use of FINDRISC. 14.3% of women with waist circumference >88 and 6.7% of men with waist circumference >102 were in the high- risk group. (p < 0.001) CONCLUSIONS: Risk of diabetes was found to be higher with the FINDRISC score as the BMI and waist circumference increased. FINDRISC can be used in the primary care for this purpose; fast and easy to be applied.

Preventive Role of Diet Interventions and Dietary Factors in Type 2 Diabetes Mellitus: An Umbrella Review

BACKGROUND

Although the body of evidence indicates clear benefits of dietary modifications for prevention of type-2 diabetes mellitus (T2DM), it may be difficult for healthcare providers to recommend which diet interventions or dietary factors are appropriate for patients as there are too many modalities available. Accordingly, we performed an umbrella review to synthesize evidence on diet interventions and dietary factors in prevention of T2DM.

METHODS

Medline and Scopus databases were searched for relevant studies. Systematic reviews with meta-analyses of randomized-controlled trial or observational studies were eligible if they measured effects of diet interventions and/or dietary factors including dietary patterns, food groups, and nutrients on risk of T2DM. The effect of each diet intervention/factor was summarized qualitatively.

RESULTS

Sixty systematic reviews and meta-analyses were eligible. Results of the review suggest that healthy dietary patterns such as Mediterranean and Dietary Approaches to Stop Hypertension (DASH) diets, and high consumption of whole grains, low-fat dairy products, yogurt, olive oil, chocolate, fiber, magnesium, and flavonoid significantly reduced the risk of T2DM. In contrast, high glycemic index and glycemic load diets, high consumption of red and processed meat, and sugar or artificial sugar-sweetened beverages significantly increased risk of T2DM. Prescribing diet interventions with or without physical activity interventions significantly decreased risk of T2DM in both high-risk and general population.

CONCLUSION

High consumption of Mediterranean and DASH diet, and interventions that modified the quality of diet intake significantly reduced risk of T2DM especially in the high-risk population. These lifestyle modifications should be promoted in both individual and population levels to prevent and decrease burden from T2DM in the future.

Screening strategies for adults with type 2 diabetes mellitus: a systematic review protocol

BACKGROUND

There is limited evidence on whether screening for type 2 diabetes mellitus affects health outcomes. A recent systematic review of randomised clinical trials found only one trial that met their inclusion criteria; therefore, current guidelines for screening interventions for type 2 diabetes mellitus are based on expert opinions and best practice rather than synthesised evidence. This systematic review seeks to collate evidence from non-randomised studies to investigate the effect of screening for adults with type 2 diabetes on outcomes including diabetes-related morbidity, mortality (all-cause and diabetes-related) and harms.

METHODS

This systematic review will follow Effective Practice and Organisation of Care (EPOC) guidelines for the synthesis of non-randomised studies. We will search PubMed/MEDLINE, Scopus, Web of Science, CINAHL, Academic Search Premier and Health Source Nursing Academic (from inception onwards). We will include non-randomised trials, controlled before-after studies, interrupted time-series studies, repeated measures studies and concurrently controlled prospective cohort studies. The primary outcome will be diabetes-related morbidity (microvascular complications of diabetic retinopathy, nephropathy or neuropathy or macrovascular complications of non-fatal myocardial infarction, peripheral arterial disease or non-fatal stroke). The secondary outcomes will be mortality (all-cause and diabetes-related) and harms of screening strategies to patients (including psychological harms or adverse events following treatments) or to health care system (including resource allocation for false-positives or overdiagnosis). Two reviewers will independently screen all citations and full-text articles. Data will be abstracted by one reviewer and checked by a second. The risk of bias of individual studies will be appraised using the ROBINS-I tool. GRADE will be used to determine the quality of the scientific evidence. If feasible, we will conduct random effects meta-analysis where appropriate. If necessary, analyses will be conducted to explore the potential sources of heterogeneity (e.g. age, sex, socio-economic status, rural versus urban or low-middle income versus high-income country). We will disseminate the findings via publications and through relevant networks.

DISCUSSION

The protocol outlines the methods for systematically reviewing and synthesising evidence of screening strategies for type 2 diabetes mellitus and their effect on health outcomes associated with the disease. The potential impact of this systematic review is improved evidence-informed decision-making for policies and practice for screening of type-2 diabetes.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020147439.

Screening for type 2 diabetes mellitus

BACKGROUND

Diabetes mellitus, a metabolic disorder characterised by hyperglycaemia and associated with a heavy burden of microvascular and macrovascular complications, frequently remains undiagnosed. Screening of apparently healthy individuals may lead to early detection and treatment of type 2 diabetes mellitus and may prevent or delay the development of related complications.

OBJECTIVES

To assess the effects of screening for type 2 diabetes mellitus.

SEARCH METHODS

We searched CENTRAL, MEDLINE, LILACS, the WHO ICTRP, and ClinicalTrials.gov from inception. The date of the last search was May 2019 for all databases. We applied no language restrictions.

SELECTION CRITERIA

We included randomised controlled trials involving adults and children without known diabetes mellitus, conducted over at least three months, that assessed the effect of diabetes screening (mass, targeted, or opportunistic) compared to no diabetes screening.

DATA COLLECTION AND ANALYSIS

Two review authors independently screened titles and abstracts for potential relevance and reviewed the full-texts of potentially relevant studies, extracted data, and carried out 'Risk of bias' assessment using the Cochrane 'Risk of bias' tool. We assessed the overall certainty of the evidence using the GRADE approach.

MAIN RESULTS

We screened 4651 titles and abstracts identified by the search and assessed 92 full-texts/records for inclusion. We included one cluster-randomised trial, the ADDITION-Cambridge study, which involved 20,184 participants from 33 general practices in Eastern England and assessed the effects of inviting versus not inviting high-risk individuals to screening for diabetes. The diabetes risk score was used to identify high-risk individuals; it comprised variables relating to age, sex, body mass index, and the use of prescribed steroid and anti-hypertensive medication. Twenty-seven practices were randomised to the screening group (11,737 participants actually attending screening) and 5 practices to the no-screening group (4137 participants). In both groups, 36% of participants were women; the average age of participants was 58.2 years in the screening group and 57.9 years in the no-screening group. Almost half of participants in both groups were on antihypertensive medication. The findings from the first phase of this study indicate that screening compared to no screening for type 2 diabetes did not show a clear difference in all-cause mortality (hazard ratio (HR) 1.06, 95% confidence interval (CI) 0.90 to 1.25, low-certainty evidence). Screening compared to no screening for type 2 diabetes mellitus showed an HR of 1.26, 95% CI 0.75 to 2.12 (low-certainty evidence) for diabetes-related mortality (based on whether diabetes was reported as a cause of death on the death certificate). Diabetes-related morbidity and health-related quality of life were only reported in a subsample and did not show a substantial difference between the screening intervention and control. The included study did not report on adverse events, incidence of type 2 diabetes, glycosylated haemoglobin A1c (HbA1c), and socioeconomic effects.

AUTHORS' CONCLUSIONS

We are uncertain about the effects of screening for type 2 diabetes on all-cause mortality and diabetes-related mortality. Evidence was available from one study only. We are therefore unable to draw any firm conclusions relating to the health outcomes of early type 2 diabetes mellitus screening. Furthermore, the included study did not assess all of the outcomes prespecified in the review (diabetes-related morbidity, incidence of type 2 diabetes, health-related quality of life, adverse events, socioeconomic effects).

Agreement between Type 2 Diabetes Risk Scales in a Caucasian Population: A Systematic Review and Report

Early detection of people with undiagnosed type 2 diabetes (T2D) is an important public health concern. Several predictive equations for T2D have been proposed but most of them have not been externally validated and their performance could be compromised when clinical data is used. Clinical practice guidelines increasingly incorporate T2D risk prediction models as they support clinical decision making. The aims of this study were to systematically review prediction scores for T2D and to analyze the agreement between these risk scores in a large cross-sectional study of white western European workers. A systematic review of the PubMed, CINAHL, and EMBASE databases and a cross-sectional study in 59,042 Spanish workers was performed. Agreement between scores classifying participants as high risk was evaluated using the kappa statistic. The systematic review of 26 predictive models highlights a great heterogeneity in the risk predictors; there is a poor level of reporting, and most of them have not been externally validated. Regarding the agreement between risk scores, the DETECT-2 risk score scale classified 14.1% of subjects as high-risk, FINDRISC score 20.8%, Cambridge score 19.8%, the AUSDRISK score 26.4%, the EGAD study 30.3%, the Hisayama study 30.9%, the ARIC score 6.3%, and the ITD score 3.1%. The lowest agreement was observed between the ITD and the NUDS study derived score (κ = 0.067). Differences in diabetes incidence, prevalence, and weight of risk factors seem to account for the agreement differences between scores. A better agreement between the multi-ethnic derivate score (DETECT-2) and European derivate scores was observed. Risk models should be designed using more easily identifiable and reproducible health data in clinical practice.

Development of a prediction model to target screening for high blood pressure in children

Targeted screening for childhood high blood pressure may be more feasible than routine blood pressure measurement in all children to avoid unnecessary harms, overdiagnosis or costs. Targeting maybe based e.g. on being overweight, but information on other predictors may also be useful. Therefore, we aimed to develop a multivariable diagnostic prediction model to select children aged 9-10 years for blood pressure measurement. Data from 5359 children in a population-based prospective cohort study were used. High blood pressure was defined as systolic or diastolic blood pressure ≥ 95th percentile for gender, age, and height. Logistic regression with backward selection was used to identify the strongest predictors related to pregnancy, child, and parent characteristics. Internal validation was performed using bootstrapping. 227 children (4.2%) had high blood pressure. The diagnostic model included maternal hypertensive disease during pregnancy, maternal BMI, maternal educational level, parental hypertension, parental smoking, child birth weight standard deviation score (SDS), child BMI SDS, and child ethnicity. The area under the ROC curve was 0.73, compared to 0.65 when using only child overweight. Using the model and a cut-off of 5% for predicted risk, sensitivity and specificity were 59% and 76%; using child overweight only, sensitivity and specificity were 47% and 84%. In conclusion, our diagnostic prediction model uses easily obtainable information to identify children at increased risk of high blood pressure, offering an opportunity for targeted screening. This model enables to detect a higher proportion of children with high blood pressure than a strategy based on child overweight only.

[Tanatogenetic role of type 2 diabetes in neurosurgical patients]

The idea of diabetes in the aspects of its impact on the course of different diseases and tanatogenesis remains little investigated.

OBJECTIVE

To define the tanatogenetic significance of 2 type diabetes in neurosurgical patients.

SUBJECT AND METHODS

Forty-three patients aged 22-75 years, who had died after neurosurgery, were examined. Case histories and the time course of changes in blood glucose levels were analyzed. The manifestations of macroangiopathy were taken into account at autopsy; those of microangiopathy were considered at microscopy of the internal organs and tissues; Van Gieson and periodic acid-Schiff staining was additionally applied. The expression of insulin, glucagon, synaptophysin, S100 proteins, and neurofilament protein was found in the pancreas. The number and volume of islets and an insulin-to-glucagon ratio were morphometrically estimated.

RESULTS

Type 2 diabetes mellitus was identified in 28 (65.1%) patients: 11 (25.6%), 8 (18.6%), and 9 (20.9%) with clinically obvious, subtle, and latent types, respectively; while it was as a background underlying disease in 3 (7.0%) patients. Among the immediate causes of death, there was a preponderance of local angiogenic complications (hemorrhages, infarctions, swelling, and displacement of the brain) (64%). Indurative pancreatitis was not inferior to cardiovascular diseases among complications and concomitant diseases and was detected in most diabetic patients (n=24, or 85.7%) and in 6 (a quarter) patients with acute pancreatic necrosis, which was the immediate cause of death in 2 cases. In the places of paravasal sclerosis, there was a reduction in the terminals of nerve fibers as a manifestation of diabetic neuropathy.

CONCLUSION

Type 2 diabetes mellitus was much more frequently encountered in the most critically ill and dead neurosurgical patients than in the general population and was embodied in the pattern of immediate causes of death. Diabetic neuropathy with a reduction in the terminals of nerve fibers can serve as a substantial basis not only for vascular, but also for ductal dystonia and dyskinesia, which can become an important factor in the pathogenesis of chronic pancreatitis in patients with diabetes mellitus.

Simple and non-invasive screening method for diabetes based on myoinositol levels in urine samples collected at home

OBJECTIVE

To establish a simple screening method for diabetes based on myoinositol (MI) in urine samples collected at home.

RESEARCH DESIGN AND METHODS

Initially, we evaluated the stability of urinary MI (UMI) at room temperature (RT; 25°C) and 37°C in 10 outpatients with type 2 diabetes. We then enrolled 115 volunteers without a current or history of diabetes. In all subjects, glucose intolerance was diagnosed by 75 g oral glucose tolerance test (75gOGTT). To assess the association between UMI or urine glucose (UG) and plasma glucose (PG), urine samples were also collected at 0 and 2 hours during 75gOGTT. All the subjects collected urine samples at home before and 2 hours after consuming the commercially available test meal. UMI levels at wake-up time (UMI_wake-up), before (UMI_premeal) and 2 hours after the test meal (UMI_{2h-postprandial}) were measured using an enzymatic method. ΔUMI was defined as UMI_{2h-postprandial} minus UMI_premeal.

RESULTS

Differing from UG, UMI was stable at RT and 37°C. UMI was increased linearly along with an increase in PG, and no threshold for UMI was observed. UMI was closely associated with blood glucose parameters obtained from a 75gOGTT and hemoglobin A1c (HbA1c) at hospital after adjustment for age, sex, body mass index and serum creatinine. UMI_wake-up, UMI_premeal, UMI_{2h-postprandial} and ΔUMI at home were higher in diabetic subjects than non-diabetic subjects even after the above adjustment. Receiver operating characteristics curve (ROC) analyses revealed that for the screening of diabetes, the area under the curve for ROC for UMI_{2h-postprandial} and ΔUMI (0.83 and 0.82, respectively) were not inferior to that for HbA1c ≥48 mmol/mol, which is the American Diabetes Association (ADA) criteria for diabetes.

CONCLUSIONS

MI measurement in urine samples collected at home before and after the meal would be a simple, non-invasive and valuable screening method for diabetes.

Evaluation of the Diabetes Screening Component of a National Cardiovascular Risk Assessment Programme in England: a Retrospective Cohort Study

Type 2 Diabetes (T2D) is increasing but the effectiveness of large-scale diabetes screening programmes is debated. We assessed associations between coverage of a national cardiovascular and diabetes risk assessment programme in England (NHS Health Check) and detection and management of incident cases of non-diabetic hyperglycaemia (NDH) and T2D. Retrospective analysis employing propensity score covariate adjustment method of prospectively collected data of 348,987 individuals aged 40-74 years and registered with 455 general practices in England (January 2009-May 2016). We examined differences in diagnosis of NDH and T2D, and changes in blood glucose levels and cardiovascular risk score between individuals registered with general practices with different levels (tertiles) of programme coverage. Over the study period 7,126 cases of NDH and 12,171 cases of T2D were detected. Compared with low coverage practices, incidence rate of detection in medium and high coverage practices were 15% and 19% higher for NDH and 10% and 9% higher for T2D, respectively. Individuals with NDH in high coverage practices had 0.2 mmol/L lower mean fasting plasma glucose and 0.9% lower cardiovascular risk score at follow-up. General practices actively participating in the programme had higher detection of NDH and T2D and improved management of blood glucose and cardiovascular risk factors.

A Novel Indicator of Children's Lipid Accumulation Product Associated with Impaired Fasting Glucose in Chinese Children and Adolescents

BACKGROUND

Diabetes is one of the most prevalent noncommunicable diseases worldwide. Children's lipid accumulation product (CLAP) is a novel indicator to show children's lipid accumulation and is effectively associated with metabolic syndrome among children and adolescents. The aim of the present study was to explore an association between CLAP and impaired fasting glucose (IFG) in Chinese children and adolescents.

METHODS

A total of 683 children and adolescents aged 8-15 years were recruited using the stratified cluster sampling method in this cross-sectional study and were measured for body height, weight, waist circumference (WC), abdominal skinfold thickness (AST), triglycerides (TG), fasting plasma glucose, dietary behaviors and physical activities. A logistic regression model and receiver operating characteristic (ROC) curve were used to compare the effects of CLAP for predicting IFG.

RESULTS

The prevalence of IFG in children and adolescents was 13.8%: 16.9% in boys and 10.1% in girls (P<0.05). The CLAP, height, weight, WC, AST, waist-to-height ratio (WHtR), and TG among boys with IFG were significantly higher than those among boys without IFG (P<0.05). The area under the ROC curve of CLAP for predicting IFG (0.637 (0.562-0.712)) was higher than those of WC, WHtR, AST, and TG. The cutoff point of P ₇₅ CLAP was the optimal value to predict IFG among boys, and the OR (95% CI) was 2.48 (1.40-4.42) and area under the ROC curve was 0.595 (0.513-0.676).

CONCLUSION

The CLAP was a novel indicator associated with IFG in Chinese boys, and it performed better than WC, WHtR, AST and TG.

Phenotyping individuals with newly-diagnosed type 2 diabetes at risk for all-cause mortality: a single centre observational, prospective study

BACKGROUND

Type 2 diabetes (T2D) shows a high mortality rate, dependent on disease duration, comorbidities and glucose control over time. Data on patients with short disease duration are scanty.

METHODS

We prospectively followed a cohort of newly-diagnosed T2D patients referring to a single diabetes centre, treated according to the international guidelines and checked every 6-12 months. All-cause mortality and major cardiovascular (CV) events were registered.

RESULTS

289 patients out of 3019 consecutive first attendances matched inclusion criteria and were included in the observation. Mean follow-up was 51.2 months. At 31 December 2018, 253 patients were alive and 36 deceased. At baseline, deceased individuals were older, with lower eGFR and lower uric acid, higher prevalence of atrial fibrillation. During the follow-up, 18 non-fatal CV events were adjudicated; patients with incident CV disease (CVD) differed at baseline for sex, previous history of CVD and retinopathy, higher use of secretagogues and lower use of metformin. At multivariate analysis, age and previous CVD were the only independent determinants of all-cause mortality and incident CVD, respectively. In deceased individuals, eGFR slope was markedly unstable and ΔeGFR at the end of the follow-up was higher (p < 0.001), and predicted mortality.

CONCLUSION

Newly-diagnosed T2D patients followed according to the best clinical practice show a mortality rate similar to that reported in more complicated patients with longer disease duration; none of the clinical and biochemical variables commonly measured at baseline can predict mortality or incident CVD; early metformin use seems to be associated with no risk of prevalent or incident retinopathy.

Patient-related Risk Factors for Postoperative Stiffness Requiring Surgical Intervention After Arthroscopic Rotator Cuff Repair

INTRODUCTION

Risk factors for stiffness after arthroscopic rotator cuff repair (RCR) have been limited to studies with small patient numbers. The objective is to determine patient-related risk factors for stiffness after RCR.

METHODS

The PearlDiver database was queried from 2007 to 2015 for patients undergoing isolated arthroscopic RCR. A multivariate binomial logistic regression analysis assessed for risk factors requiring a postoperative manipulation under anesthesia (MUA) or lysis of adhesions (LOA) within 9 months after RCR.

RESULTS

Two hundred thirty-two of 19,229 patients (1.2%) underwent a LOA and/or MUA within 9 months after arthroscopic RCR. Significant risk factors identified were age less than 50 years (odds ratio [OR], 1.9; P < 0.0001), female gender (OR, 2.0; P < 0.0001), diabetes mellitus (DM) type I (OR, 2.7; P < 0.0001), hypothyroidism (OR, 1.3; P = 0.020), and systemic lupus erythematosus (OR, 2.1; P = 0.004). However, tobacco use was associated with a 0.5 risk of developing stiffness (P < 0.0001).

DISCUSSION

Systemic lupus erythematosus, hypothyroidism, and DMI (but not DMII) in addition to young age and female gender were risk factors for LOA/MUA after arthroscopic RCR.

Health system performance for people with diabetes in 28 low- and middle-income countries: A cross-sectional study of nationally representative surveys

BACKGROUND

The prevalence of diabetes is increasing rapidly in low- and middle-income countries (LMICs), urgently requiring detailed evidence to guide the response of health systems to this epidemic. In an effort to understand at what step in the diabetes care continuum individuals are lost to care, and how this varies between countries and population groups, this study examined health system performance for diabetes among adults in 28 LMICs using a cascade of care approach.

METHODS AND FINDINGS

We pooled individual participant data from nationally representative surveys done between 2008 and 2016 in 28 LMICs. Diabetes was defined as fasting plasma glucose ≥ 7.0 mmol/l (126 mg/dl), random plasma glucose ≥ 11.1 mmol/l (200 mg/dl), HbA1c ≥ 6.5%, or reporting to be taking medication for diabetes. Stages of the care cascade were as follows: tested, diagnosed, lifestyle advice and/or medication given ("treated"), and controlled (HbA1c < 8.0% or equivalent). We stratified cascades of care by country, geographic region, World Bank income group, and individual-level characteristics (age, sex, educational attainment, household wealth quintile, and body mass index [BMI]). We then used logistic regression models with country-level fixed effects to evaluate predictors of (1) testing, (2) treatment, and (3) control. The final sample included 847,413 adults in 28 LMICs (8 low income, 9 lower-middle income, 11 upper-middle income). Survey sample size ranged from 824 in Guyana to 750,451 in India. The prevalence of diabetes was 8.8% (95% CI: 8.2%-9.5%), and the prevalence of undiagnosed diabetes was 4.8% (95% CI: 4.5%-5.2%). Health system performance for management of diabetes showed large losses to care at the stage of being tested, and low rates of diabetes control. Total unmet need for diabetes care (defined as the sum of those not tested, tested but undiagnosed, diagnosed but untreated, and treated but with diabetes not controlled) was 77.0% (95% CI: 74.9%-78.9%). Performance along the care cascade was significantly better in upper-middle income countries, but across all World Bank income groups, only half of participants with diabetes who were tested achieved diabetes control. Greater age, educational attainment, and BMI were associated with higher odds of being tested, being treated, and achieving control. The limitations of this study included the use of a single glucose measurement to assess diabetes, differences in the approach to wealth measurement across surveys, and variation in the date of the surveys.

CONCLUSIONS

The study uncovered poor management of diabetes along the care cascade, indicating large unmet need for diabetes care across 28 LMICs. Performance across the care cascade varied by World Bank income group and individual-level characteristics, particularly age, educational attainment, and BMI. This policy-relevant analysis can inform country-specific interventions and offers a baseline by which future progress can be measured.

Undiagnosing to prevent overprescribing

Health care focuses on controlling symptoms and managing risk factors to improve survival by avoiding future complications. Diagnoses describe a group of signs and symptoms, often implying specific aetiologies and underlying pathophysiological disease processes. The diagnosis provides a tool for the health professional to conceptualise and classify a presentation, and thus manage the condition, and can provide the patient with an explanation or validation of their experience. Not every diagnosis holds significant clinical implications. There are diagnosed conditions that do not require treatment and, moreover, where treatment has the potential for harm without the potential for benefit. Promoting investigations and diagnoses can lead to overdiagnosis related to vested interests in increased services, use of devices or therapeutics. Multiple factors drive this issue, including broadening disease definitions and cultural factors that encourage tests and treatments, as well as medicolegal factors. While the traditional medicine review process typically involved cross-referencing medicines used with current diagnoses, a more sophisticated version of this process critically reviews the medicines and associated diagnosis, giving less emphasis to diagnoses that are no longer relevant. Known as undiagnosis, this process facilitates the withdrawal of corresponding medicines used to manage those conditions. Systematically reviewing diagnoses regularly and the associated medicine management strategies could reduce prescribing. The novel ERASE process can help clinicians Evaluate diagnoses to consider Resolved conditions, Ageing normally and Selecting appropriate targets to Eliminate unnecessary diagnoses and their corresponding medicines.

General health checks in adults for reducing morbidity and mortality from disease

BACKGROUND

General health checks are common elements of health care in some countries. They aim to detect disease and risk factors for disease with the purpose of reducing morbidity and mortality. Most of the commonly used individual screening tests offered in general health checks have been incompletely studied. Also, screening leads to increased use of diagnostic and therapeutic interventions, which can be harmful as well as beneficial. It is therefore important to assess whether general health checks do more good than harm. This is the first update of the review published in 2012.

OBJECTIVES

To quantify the benefits and harms of general health checks.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, two other databases and two trials registers on 31 January 2018. Two review authors independently screened titles and abstracts, assessed papers for eligibility and read reference lists. One review author used citation tracking (Web of Knowledge) and asked trial authors about additional studies.

SELECTION CRITERIA

We included randomised trials comparing health checks with no health checks in adults unselected for disease or risk factors. We did not include geriatric trials. We defined health checks as screening for more than one disease or risk factor in more than one organ system.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted data and assessed the risk of bias in the trials. We contacted trial authors for additional outcomes or trial details when necessary. When possible, we analysed the results with a random-effects model meta-analysis; otherwise, we did a narrative synthesis.

MAIN RESULTS

We included 17 trials, 15 of which reported outcome data (251,891 participants). Risk of bias was generally low for our primary outcomes. Health checks have little or no effect on total mortality (risk ratio (RR) 1.00, 95% confidence interval (CI) 0.97 to 1.03; 11 trials; 233,298 participants and 21,535 deaths; high-certainty evidence, I² = 0%), or cancer mortality (RR 1.01, 95% CI 0.92 to 1.12; 8 trials; 139,290 participants and 3663 deaths; high-certainty evidence, I² = 33%), and probably have little or no effect on cardiovascular mortality (RR 1.05, 95% CI 0.94 to 1.16; 9 trials; 170,227 participants and 6237 deaths; moderate-certainty evidence; I² = 65%). Health checks have little or no effect on fatal and non-fatal ischaemic heart disease (RR 0.98, 95% CI 0.94 to 1.03; 4 trials; 164,881 persons, 10,325 events; high-certainty evidence; I² = 11%), and probably have little or no effect on fatal and non-fatal stroke (RR 1.05 95% CI 0.95 to 1.17; 3 trials; 107,421 persons, 4543 events; moderate-certainty evidence, I² = 53%).

AUTHORS' CONCLUSIONS

General health checks are unlikely to be beneficial.

Diagnostic accuracy of the Finnish Diabetes Risk Score (FINDRISC) for undiagnosed T2DM in Peruvian population

AIMS

To assess the diagnostic accuracy of the Finnish Diabetes Risk Score (FINDRISC) for undiagnosed T2DM and to compare its performance with the Latin-American FINDRISC (LA-FINDRISC) and the Peruvian Risk Score.

MATERIALS AND METHODS

A population-based study was conducted. T2DM and undiagnosed T2DM were defined using oral glucose tolerance test (OGTT). Risk scores assessed were FINDRISC, LA-FINDRISC and Peruvian Risk Score. Diagnostic accuracy of risk scores was estimated using the c-statistic and the area under the ROC curve (aROC). A simplified version of FINDRISC was also derived.

RESULTS

Data from 1609 individuals, mean age 48.2 (SD: 10.6), 810 (50.3%) women, were collected. A total of 176 (11.0%; 95%CI: 9.4%-12.5%) were classified as having T2DM, and 71 (4.7%; 95%CI: 3.7%-5.8%) were classified as having undiagnosed T2DM. Diagnostic accuracy of the FINDRISC (aROC=0.69), LA-FINDRISC (aROC=0.68), and Peruvian Risk Score (aROC=0.64) was similar (p=0.15). The simplified FINDRISC, with 4 variables, had a slightly better performance (aROC=0.71) than the other scores.

CONCLUSION

The performance of FINDRISC, LA-FINDRISC and Peruvian Risk Score for undiagnosed T2DM was similar. A simplified FINDRISC can perform as well or better for undiagnosed T2DM. The FINDRISC may be useful to detect cases of undiagnosed T2DM in resource-constrained settings.