Diabetes Risk Scores in 2011

2010 ◽  
Vol 7 (1) ◽  
pp. 19
Author(s):  
Beverley Balkau ◽  
Lei Chen ◽  
◽  
Keyword(s):  
At Risk ◽  
Prediction Interval ◽  
Routine Care ◽  
Diabetes Risk ◽  
Intensive Treatment ◽  
Screening Tools ◽  
Risk Scores ◽  
Family History Of Diabetes ◽  
Dutch Study ◽  
History Of

Diabetes risk scores can be used as pre-screening tools to detect those likely to have diabetes. Scores usually include clinical characteristics such as age, sex, family history of diabetes and hypertension. However, it is disputed whether screening for diabetes is cost-effective. The recently reported Anglo-Danish-Dutch Study of Intensive Treatment in People with Screen Detected Diabetes in Primary Care (ADDITION) study, in which diabetes was diagnosed following screening by a risk score, did not show that intensive treatment in such individuals was different from routine care in terms of cardiovascular outcomes. Risk scores are also used to identify those at risk of diabetes in the future, and at-risk individuals may then be encouraged to participate in diabetes prevention programmes. Risk scores from routine biology, in particular fasting glucose, have also been developed to improve prediction over clinical risk factors. Now more sophisticated approaches are being used to predict diabetes – multiple biomarkers, genetics, proteomics, lipidomics and metabolomics – with the idea that if individuals are identified a long time in advance of the onset of the disease, prevention can start much earlier when it may be more successful. Diabetes risk scores follow on from a long history of cardiovascular risk scores. Scores should be given with an uncertainly or prediction interval within which the score lies with 95% confidence.

Evaluation of the Use of a Diabetes Risk Test to Identify Prediabetes in an Employee Wellness Screening

2021 ◽  
pp. 089719002199701
Author(s):  
Eileen D. Ward ◽  
Whitney A. Hopkins ◽  
Kayce Shealy
Keyword(s):  
At Risk ◽  
American Diabetes Association ◽  
Hemoglobin A1c ◽  
Screening Tool ◽  
Screening Program ◽  
Diabetes Risk ◽  
Risk Scores ◽  
Cutoff Score ◽  
Employee Wellness ◽  
History Of

Background: The American Diabetes Association (ADA) Diabetes Risk Test (DRT) is a screening tool to identify people at risk for developing diabetes. Individuals with a DRT score of 5 or higher may have prediabetes or diabetes and should see a healthcare provider. Objective: To determine how many additional employees are identified as being at risk for developing diabetes during an employee wellness screening by using a more stringent DRT cutoff score of 4 instead of 5. Methods: During an annual employee wellness screening event, a hemoglobin A1C (A1c) was drawn for participants with a DRT score of > 4 or by request regardless of risk score. A1C values were classified as normal (<5.7%), prediabetes (>5.7 and <6.5%) or diabetes (>6.5%). Risk scores and A1C values were analyzed using descriptive statistics. Cost of additional laboratory testing was also reviewed. Results: An A1C was collected for 158 participants. Fourteen of 50 (28%) participants with a DRT of 4 had A1c values in the prediabetes range and no history of diabetes or prediabetes. Using the lower DRT score of 4 resulted in an additional expenditure of $305 with $85.40 resulting in the identification of an otherwise unaware person at risk for developing diabetes. Conclusion: Using a DRT cutoff score of 4 as part of an employee wellness screening program resulted in additional laboratory costs to identify persons at risk for developing diabetes but also allowed for earlier education to slow or stop the progression to diabetes which may reduce healthcare costs over time.

scholarly journals Interaction Analysis of Lipid Accumulation Product and Family History of Diabetes on Impaired Fasting Glucose and Diabetes Risk in Population with Normotension in Eastern China: A Community-based Cross-sectional Survey

2021 ◽  
Author(s):  
Li Shu ◽  
Yingying Zhao ◽  
Yanqi Shen ◽  
Xiaolu Li ◽  
Mengting Qiu ◽  
...  
Keyword(s):  
Family History ◽  
Impaired Fasting Glucose ◽  
Lipid Accumulation ◽  
Significant Interaction ◽  
Fasting Glucose ◽  
Diabetes Risk ◽  
Lipid Accumulation Product ◽  
Family History Of Diabetes ◽  
Significant Difference ◽  
History Of

Abstract Background: Lipid accumulation product (LAP) is considered to be a new convenient useful indicator to assess the visceral fat. However, the association between LAP and family history of diabetes remains an undetermined concept. Therefore, we aimed to evaluate the risk factors of impaired fasting glucose (IFG) and diabetes, and explore the possible interacting influences of LAP with other factors on the risk of IFG and diabetes among Chinese normotension adults.Methods: A multistage stratified cluster sampling method was conducted to select urban residents aged 45-86 years in Bengbu, China. For each eligible participant, data on questionnaire survey, anthropometric measurements and laboratory tests were obtained. LAP was calculated and divided into four categories according to quartile. The effects of body mass index (BMI), waist circumference (WC), waist to height ratio (WHtR) and LAP for predicting IFG and diabetes were performed by multiple logistic regressions and receiver operating characteristic (ROC) analyses. The interaction effects were evaluated by relative excess risk of interaction (RERI), attributable proportion due to interaction (AP) and synergy index (SI). If the 95% CI of RERI and AP do not include 0, the 95% CI of SI do not include 1, the interactions are statistically significant. Results: 6467 normotension subjects (2695 men and 3772 women) were enrolled in our study, the prevalence of IFG and diabetes were 9.37% and 14.33%, respectively. It was revealed that the prevalence rates of IFG and diabetes were gradually increased according to increasing LAP quartiles (P for trend <0.001). When assessed using ROC curve analysis, LAP exhibited higher diagnostic accuracy for identifying IFG and diabetes than BMI, the area under the AUC curve was 0.650 (95% CI: 0.637 to 0.662). After adjustment for age, sex, educational level and other confounding factors, multivariate logistic regression analyses indicated that subjects with the fourth quartile of LAP were more likely to develop IFG (adjusted OR: 2.735, 95% CI: 1.794-4.170) and diabetes (adjusted OR: 1.815, 95% CI: 1.297-2.541) than those with the first quartile. A significant interaction between LAP and family history of diabetes was observed in participants (RERI=1.538, 95%CI: 0.167 to 3.612; AP=0.375, 95%CI: 0.118 to 0.631; SI=1.980, 95%CI: 1.206 to 3.251), but there is no statistically significant difference between LAP and general obesity. However, a significant interaction between LAP and abdominal obesity was indicated by the value of RERI (1.492, 95%CI: 0.087 to 3.723) and AP (0.413, 95%CI: 0.014 to 0.756), but not the value of SI (1.824, 95%CI: 0.873 to 3.526). Conclusion: LAP significantly associates with IFG and diabetes risk in the study population, it has better performance than BMI, WC and WHtR. Apart from that, our results also demonstrated that there might be synergistic effect between LAP and family history of diabetes on the risk of IFG and diabetes.

scholarly journals Development and Validation of a Novel Dementia Risk Score in the UK Biobank Cohort

2021 ◽  
Author(s):  
Melis Anatürk ◽  
Raihaan Patel ◽  
Georgios Georgiopoulos ◽  
Danielle Newby ◽  
Anya Topiwala ◽  
...  
Keyword(s):  
At Risk ◽  
Cardiovascular Risk ◽  
Risk Score ◽  
Disease Risk ◽  
Risk Index ◽  
Risk Scores ◽  
Uk Biobank ◽  
Dementia Risk ◽  
History Of ◽  
The Uk

INTRODUCTION: Current prognostic models of dementia have had limited success in consistently identifying at-risk individuals. We aimed to develop and validate a novel dementia risk score (DRS) using the UK Biobank cohort.METHODS: After randomly dividing the sample into a training (n=166,487, 80%) and test set (n=41,621, 20%), logistic LASSO regression and standard logistic regression were used to develop the UKB-DRS.RESULTS: The score consisted of age, sex, education, apolipoprotein E4 genotype, a history of diabetes, stroke, and depression, and a family history of dementia. The UKB-DRS had good-to-strong discrimination accuracy in the UKB hold-out sample (AUC [95%CI]=0.79 [0.77, 0.82]) and in an external dataset (Whitehall II cohort, AUC [95%CI]=0.83 [0.79,0.87]). The UKB-DRS also significantly outperformed four published risk scores (i.e., Australian National University Alzheimer’s Disease Risk Index (ANU-ADRI), Cardiovascular Risk Factors, Aging, and Dementia score (CAIDE), Dementia Risk Score (DRS), and the Framingham Cardiovascular Risk Score (FRS) across both test sets.CONCLUSION: The UKB-DRS represents a novel easy-to-use tool that could be used for routine care or targeted selection of at-risk individuals into clinical trials.

scholarly journals Prevalence of Diabetes and Its Determinants in the Young Adults Indian Population-Call for Yoga Intervention

2020 ◽  
Vol 11 ◽  
Author(s):  
Raghuram Nagarathna ◽  
Parul Bali ◽  
Akshay Anand ◽  
Vinod Srivastava ◽  
Suchitra Patil ◽  
...  
Keyword(s):  
Young Adults ◽  
High Risk ◽  
Indian Population ◽  
Action Plan ◽  
Central Zone ◽  
Diabetes Risk ◽  
Parental History ◽  
Family History Of Diabetes ◽  
Validated Questionnaire ◽  
History Of

BackgroundThe young Indian population, which constitutes 65% of the country, is fast adapting to a new lifestyle, which was not known earlier. They are at a high risk of the increasing burden of diabetes and associated complications. The new evolving lifestyle is not only affecting people’s health but also mounting the monetary burden on a developing country such as India.AimWe aimed to collect information regarding the prevalence of risk of diabetes in young adults (&lt;35 years) in the 29 most populous states and union territories (7 zones) of India, using a validated questionnaire.MethodsA user-friendly questionnaire-based survey using a mobile application was conducted on all adults in the 29 most populous states/union territories of India, after obtaining ethical clearance for the study. Here, we report the estimation of the prevalence of the risk of diabetes and self-reported diabetes on 58,821 young individuals below the age of 35 years. Risk for diabetes was assessed using a standardized instrument, the Indian diabetes risk score (IDRS), that has 4 factors (age, family history of diabetes, waist circumference, and physical activity). Spearman’s correlation coefficient was used to check the correlations.ResultsThe prevalence of high (IDRS score &gt; 60), moderate (IDRS score 30–50), and low (IDRS &lt; 30) diabetes risk in young adults (&lt;35 years) was 10.2%, 33.1%, and 56.7%, respectively. Those with high-risk scores were highest (14.4%) in the Jammu zone and lowest (4.1%) in the central zone. The prevalence of self-reported diabetes was 1.8% with a small difference between men (1.7%) and women (1.9%), and the highest (8.4%) in those with a parental history of diabetes. The south zone had the highest (2.5%), and the north west zone had the lowest (4.4%) prevalence.ConclusionsIndian youth are at high risk for diabetes, which calls for an urgent action plan through intensive efforts to promote lifestyle behavior modifications during the pandemics of both communicable and noncommunicable diseases.

scholarly journals Identification of Potential Type II Diabetes in a Chinese Population with a Sensitive Decision Tree Approach

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Dongmei Pei ◽  
Chengpu Zhang ◽  
Yu Quan ◽  
Qiyong Guo
Keyword(s):  
Family History ◽  
Decision Tree ◽  
Positive Family History ◽  
Screening Tools ◽  
Significant Feature ◽  
Work Related Stress ◽  
Family History Of Diabetes ◽  
Work Related ◽  
History Of ◽  
Related Stress

Background. Diabetes mellitus is a chronic disease with a steadfast increase in prevalence. Due to the chronic course of the disease combining with devastating complications, this disorder could easily carry a financial burden. The early diagnosis of diabetes remains as one of the major challenges medical providers are facing, and the satisfactory screening tools or methods are still required, especially a population- or community-based tool. Methods. This is a retrospective cross-sectional study involving 15,323 subjects who underwent the annual check-up in the Department of Family Medicine of Shengjing Hospital of China Medical University from January 2017 to June 2017. With a strict data filtration, 10,436 records from the eligible participants were utilized to develop a prediction model using the J48 decision tree algorithm. Nine variables, including age, gender, body mass index (BMI), hypertension, history of cardiovascular disease or stroke, family history of diabetes, physical activity, work-related stress, and salty food preference, were considered. Results. The accuracy, precision, recall, and area under the receiver operating characteristic curve (AUC) value for identifying potential diabetes were 94.2%, 94.0%, 94.2%, and 94.8%, respectively. The structure of the decision tree shows that age is the most significant feature. The decision tree demonstrated that among those participants with age≤49, 5497 participants (97%) of the individuals were identified as nondiabetic, while age>49, 771 participants (50%) of the individuals were identified as nondiabetic. In the subgroup where people were 34<age≤49 and BMI≥25, when with positive family history of diabetes, 89 (92%) out of 97 individuals were identified as diabetic and, when without family history of diabetes, 576 (58%) of the individuals were identified as nondiabetic. Work-related stress was identified as being associated with diabetes. In individuals with 34<age≤49 and BMI≥25 and without family history of diabetes, 22 (51%) of the individuals with high work-related stress were identified as nondiabetic while 349 (88%) of the individuals with low or moderate work-related stress were identified as not having diabetes. Conclusions. We proposed a classifier based on a decision tree which used nine features of patients which are easily obtained and noninvasive as predictor variables to identify potential incidents of diabetes. The classifier indicates that a decision tree analysis can be successfully applied to screen diabetes, which will support clinical practitioners for rapid diabetes identification. The model provides a means to target the prevention of diabetes which could reduce the burden on the health system through effective case management.

scholarly journals Diabetes Risk among Medical Students in Tabuk City, Saudi Arabia

2020 ◽  
Vol 26 (1) ◽  
pp. 27-30
Author(s):  
Hyder Osman Mirghani ◽  
Abdelmoneum Saleh
Keyword(s):  
Diabetes Mellitus ◽  
Saudi Arabia ◽  
Medical Students ◽  
Fruits And Vegetables ◽  
Vegetable Consumption ◽  
Diabetes Risk ◽  
Fruit And Vegetable Consumption ◽  
Central Adiposity ◽  
Family History Of Diabetes ◽  
History Of

<b><i>Introduction:</i></b> Diabetes risk estimation is essential for the implementation of preventive measures. <b><i>Objectives:</i></b> We aimed to assess the diabetes risk among medical students in Tabuk, Saudi Arabia. <b><i>Methods:</i></b> This cross-sectional study was conducted among 169 medical students in the Medical College, University of Tabuk, Saudi Arabia, from October 2017 to April 2018. Participants signed a written informed consent and then responded to a questionnaire modified from the Finnish and the ARABRISK diabetes score. The questionnaire consisted of eight components inquiring about age, BMI, central adiposity, fruit and vegetable consumption, physical activity if found to have high blood pressure or blood sugar, and family history of diabetes mellitus. The Statistical Package for Social Sciences (SPSS) was used for data analysis. <b><i>Results:</i></b> Out of 169 students (68% with a family history of diabetes), obesity and overweight were found in 21.3 and 26.6%, respectively, 45.6% had central adiposity, more than half were not practicing exercise daily, and 60.4% were not consuming fruits and vegetables daily. A significant percentage was found to have high blood sugar (9.5%) and high blood pressure (4.7%). The diabetes risk score was high or moderate in 16% of the students. <b><i>Conclusion:</i></b> Medical students in Tabuk City were at high risk for diabetes mellitus. Obesity, overweight, central adiposity, physical inactivity, and less consumption of fruits and vegetables substantially contributed to the risk. Measures to prevent obesity, improving fruit and vegetable consumption, and exercise are needed.

scholarly journals Community-Based Diabetes Screening and Risk Assessment in Rural West Virginia

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Ranjita Misra ◽  
Cindy Fitch ◽  
David Roberts ◽  
Dana Wright
Keyword(s):  
Risk Assessment ◽  
Family History ◽  
High Risk ◽  
West Virginia ◽  
Diabetes Risk ◽  
Older Age ◽  
Community Based ◽  
Family History Of Diabetes ◽  
History Of ◽  
Rural West Virginia

This project utilized a cross-sectional study design to assess diabetes risk among 540 individuals from 12 counties using trained extension agents and community organizations in West Virginia. Individuals were screened for diabetes using (1) the validated 7-item diabetes risk assessment survey and (2) hemoglobin A1c tests. Demographic and lifestyle behaviors were also collected. The average age, body mass index, and A1c were51.2±16.4,31.1±7.5, and5.8±0.74, respectively. The majority were females, Non-Hispanic Whites with no prior diagnosis of diabetes. Screenings showed that 61.8% of participants were at high risk for diabetes. Family history of diabetes (siblings or parents), overweight or obese status, sedentary lifestyle, and older age were commonly prevalent risk factors. Higher risk scores computed from the 7-item questions correlated positively with higher A1c (r=0.221,P<0.001). In multivariate logistic regression analyses, higher diabetes risk was predicted by obesity, older age, family history of hypertension, and gestational diabetes. Females were 4 times at higher risk than males. The findings indicated that community-based screenings were an effective way to assess diabetes risk in rural West Virginia. Linking diabetes screenings with referrals to lifestyle programs for high risk individuals can help reduce the burden of diabetes in the state.

scholarly journals Importance of family history of diabetes in computing a diabetes risk score in Korean prediabetic population

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Morena Ustulin ◽  
Sang Youl Rhee ◽  
Suk Chon ◽  
Kyu Keung Ahn ◽  
Ji Eun Lim ◽  
...  
Keyword(s):  
Family History ◽  
Risk Score ◽  
Diabetes Risk ◽  
Family History Of Diabetes ◽  
History Of ◽  
Diabetes Risk Score

scholarly journals USING MODELING TO COMPARE THE ABILITY OF FALLS SCREENING TOOLS TO PREDICT FUTURE FALLS

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S566-S567
Author(s):  
Elizabeth R Burns ◽  
Vicki J Pineau ◽  
Rosalind Koff ◽  
Sarah Hodge ◽  
Bess Welch
Keyword(s):  
Older Adults ◽  
At Risk ◽  
Fall Risk ◽  
Screening Tools ◽  
Risk Of Falling ◽  
History Of ◽  
Nationally Representative ◽  
Key Questions

Abstract The STEADI initiative recommends screening older adults for falls annually using either the 12-item “Stay Independent” or the “three-key questions” screening tools. Both tools ask about falling in the preceding year. However, the comparative predictability of each tool has not been assessed. In response, CDC and NORC, assessed both tools’ ability to predict falls at six and twelve months. Adults 65+ (n=1900), were recruited from a nationally representative panel and were screened for fall risk at baseline using both tools and then followed for a year to determine if they fell. At baseline, 38% of older adults were categorized at-risk of falling based on the 12-item “Stay Independent” and 56% were considered at-risk based on the three-key questions. The history of falling question was excluded for the six month analyses. The “Stay Independent” identified 60% of fallers and the remaining two questions of the three-key questions identified 57% of fallers.

scholarly journals Community Based Screening for Diabetes and Prediabetes using the Indian Diabetes Risk Score among Adults in a Semi-Urban Area in Kathmandu, Nepal

2019 ◽  
Vol 21 (1) ◽  
pp. 12-20
Author(s):  
Vinutha Silvanus ◽  
N Dhakal ◽  
A Pokhrel ◽  
BK Baral ◽  
PP Panta
Keyword(s):  
High Risk ◽  
Urban Area ◽  
Risk Score ◽  
Plasma Glucose ◽  
Diabetes Risk ◽  
Low Risk ◽  
Screening Tools ◽  
Community Based ◽  
Family History Of Diabetes ◽  
Diabetes Risk Score

 Diabetes has been recognized as a “global health emergency” with an estimated 9% of adults being affected. However, about half of these adults remain undiagnosed. Conventional screening tools like fasting plasma glucose (FPG), oral glucose tolerance testing (OGTT) and glycosylated haemoglobin (HbA1c) can be inconvenient and expensive in a community-based setting. The Indian Diabetes Risk Score (IDRS) is a simple, non-invasive tool which has been validated for use in the Indian population. Age, abdominal obesity, family history of diabetes and physical activity levels have been weighted for a maximum score of 100. Persons with IDRS of <30 are categorized as low risk, 30-50 as medium risk and those with > 60 as high risk for diabetes. A community based, cross-sectional, analytical study was planned to assess the performance of IDRS among adults in a semi-urban area in Kathmandu, Nepal. A total of 256 (170 female, 86 male) persons without diabetes from 260 households were screened during the study period. A majority (46.09%) were classified as high risk, 44.53% as moderate risk and 9.38% as low risk for developing diabetes. Among them, 162 (63.28%) volunteered for definitive testing. The prevalence of undiagnosed diabetes and prediabetes was 4.32% (95% CI: 1.75% to 8.70%) and 7.14% (95% CI: 3.89% to 12.58%) respectively. IDRS predicted the combined risk of diabetes and prediabetes with sensitivity of 84.21% and specificity of 55.24% in adults with score of 60 and above. The area under the ROC curve (AUC) of IDRS for identifying diabetes and prediabetes was 0.69 as compared to the gold standard (2hour Plasma Glucose) AUC of 0.98. IDRS may be a suitable screening tool for diabetes and prediabetes in the adult Nepalese study population.

Sign in / Sign up

Export Citation Format

Share Document