Nonlaboratory-based risk assessment model for type 2 diabetes mellitus screening in Chinese rural population: a joint bagging-boosting model

2021 ◽  
pp. 1-1
Author(s):  
Liying Zhang ◽  
Yikang Wang ◽  
Miaomiao Niu ◽  
Chongjian Wang ◽  
Zhenfei Wang
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Risk Assessment ◽  
Type 2 Diabetes Mellitus ◽  
Rural Population ◽  
Assessment Model ◽  
Risk Assessment Model

Risk assessment of adult residents in ile-ife, South-Western Nigeria for type 2 diabetes mellitus

2013 ◽  
pp. 1-1
Author(s):  
Gbadebo Ajani ◽  
Rosemary Ikem ◽  
Adenike Enikuomehin ◽  
David Soyoye ◽  
Babatope Kolawole
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Risk Assessment ◽  
Type 2 Diabetes Mellitus

A Descriptive Study to Assess the Risk of Stroke among Patients with Hypertension and Type 2 Diabetes Mellitus at a Selected Hospital, Bangalore

2021 ◽  
Vol 6 (3) ◽  
pp. 407-412
Author(s):  
Leena Dorothy W ◽  
Pavithra C ◽  
Umadevi A K
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Risk Assessment ◽  
Type 2 Diabetes Mellitus ◽  
Stroke Risk ◽  
Family Type ◽  
Survey Method ◽  
Risk Category

Objective: Stroke is a major public health problem, both in developed and developing countries. Stroke is becoming an important cause of early death and disability in India due to increasing prevalence of the major key modifiable risk factors like type 2 diabetes mellitus and hypertension. Hence there is an urgent need for recognition of stroke risk factors and its warning signs. With this intention the present study aimed to assess the risk of stroke among patients with hypertension and type 2 diabetes mellitus. Methods: A non-experimental, descriptive survey method was adopted. Samples were selected by using quota sampling technique and 60 hypertensive and type 2 diabetes mellitus patients who met the inclusion criteria were selected for the study. Data were collected by an interview technique using a modified stroke risk assessment tool by the National Stroke Association, USA. Results: Out of 60 samples 48.3% of them were in high-risk category, 28.3% were in caution and 23.3% in low-risk category. There was a significant association found in relation to socio demographic variables such as education qualification, type of family, type of diet, weight and complications of hypertension (P<0.05). Discussion: The findings of the study suggested that there is an increased risk of stroke in hypertension and type 2 diabetes patients which can be aggravated by other risk factors and co-morbid conditions. Hence modifying these risk factors by changing lifestyle can help in prevention of stroke. Keywords: Stroke, risk assessment, hypertension and type 2 diabetes mellitus, comorbid conditions.

scholarly journals TYPE 2 DIABETES MELLITUS PREDICTION IN MALAYSIA USING MODIFIED DIABETES RISK ASSESSMENT TOOL

2020 ◽  
Vol 20 (1) ◽  
pp. 15-21
Author(s):  
Aung Myo Oo ◽  
Al-abed Ali Ahmed Al-abed ◽  
Ohn Mar Lwin ◽  
Sowmya Sham Kanneppady ◽  
Tee Yee Sim ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Risk Assessment ◽  
Type 2 Diabetes Mellitus ◽  
High Risk ◽  
Assessment Tool ◽  
Cost Effective ◽  
Risk Assessment Tool ◽  
Type 2 Dm

Type 2 diabetes mellitus (DM) is becoming major health threat worldwide and it is extremely common in clinical setting. Malaysia is one of the highest diabetic populations among Asian countries and the new cases are increasing day to day. Early detection of people with high risk of Type 2 DM by using simple, easy and cost-effective assessment tool is the better way to identify and prevent the community from this non-communicable disease. The objectives of the study were to identify those are high risk to become type 2DM among Malaysians by using risk scoring form and to educate them how to prevent it. Total 591 subjects were recruited from the health screening programs carried out by the collaboration of Petaling Jaya Development Council (MBPJ) and Lincoln University College, Malaysia. Modified form of Finnish Type 2 Diabetes Risk Assessment Tool was used to identify people at risk of becoming type 2 DM. Descriptive analysis was performed for all included variables in this study by using SPSS version 21. The study found out that almost half of the participants were found to have family history of DM, 60% of them were overweight and obese and 47% were having above normal waist circumference. We observed that nearly 60 % of participants in the study were having moderate to high risk of becoming type 2 DM in next 10 years. To conclude, the result of our study would be helpful in implementation of cost-effective, convenient Type 2 DM risk assessment tool which has yet to be implemented in Malaysia.

scholarly journals Stratification of patients with type 2 diabetes mellitus for painless ischemic heart disease

2012 ◽  
Vol 15 (1) ◽  
pp. 19-24
Author(s):  
Natalya Ivanovna Volkova ◽  
Andrey Vladimirovich Kharakhashyan ◽  
Yulia Alekseevna Sorokina ◽  
Il'ya Yur'evich Davidenko
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Heart Disease ◽  
Ischemic Heart Disease ◽  
Assessment Model ◽  
Ischemic Heart ◽  
Dm Type 2

Aims. Development of assessment model for type 2 diabetes mellitus (DM) patient stratification for painless ischemic heart disease(IHD). Materials and methods. 258 patients with DM type 2 participated in this study (109 male and 149 female) of mean age 58.4?8.5 withDM experience of 7.9?6.1 years. All participants were subdivided into three groups: first - DM type 2 without history of painless IHD(138 individuals); second - DM type 2 with diagnosed painless IHD (50 individuals); third - DM type 2 with painful myocardialischemia. We assessed "classic" risk factors for IHD, immediately connected with DM comorbidity, as well as "additional" risk factors,potentially capable of provoking both painless and painful IHD. In addition, we screened our patients for structural abnormalitiesof heart by means of echocardiography. Painless IHD was diagnosed by treadmill-tests or Holter monitoring with submaximal exercise.Accumulated data was statistically processed with the use of Spearman's rank correlation, as well as binary logistic regression method.Results were deemed statistically significant at р

Sign in / Sign up

Export Citation Format

Share Document