scholarly journals Detection of Gestational Diabetes Mellitus and Influence on Perinatal Outcomes from B-Mode Ultrasound Images Using Deep Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yuhui Liu ◽  
Yu Wang ◽  
Yang Zhang ◽  
Rulei Cheng
Keyword(s):  
Neural Network ◽  
Diabetes Mellitus ◽  
Risk Factors ◽  
Risk Factor ◽  
Deep Neural Network ◽  
Perinatal Outcomes ◽  
Ultrasound Images ◽  
Ctrl Group ◽  
History Of ◽  
Experimental Group

The study was intended to explore the risk factors of gestational diabetes mellitus (GDM) and their influence on perinatal outcomes through deep neural network (DNN)-based Doppler color ultrasound (B-mode ultrasound) images. Specifically, 75 women with GDM were selected as the experimental group, and 75 healthy pregnant women were selected as the control (Ctrl) group. DNN uses the unsupervised method to pretrain layer by layer and then uses the supervised method to accumulate parameters of each layer, which can obtain good performance. In this study, the risk factors of GDM and their influence on the perinatal outcomes were analyzed by DNN-based B-mode ultrasound images. It was found that pregnancy age was a risk factor for GDM (OR = 2.566), preference for sweets was a risk factor for GDM (OR = 1.678, P < 0.001 ), and family history of DM was also a risk factor for GDM (OR = 12.789, P < 0.001 ). The incidence of complications in the experimental group was higher than that in the Ctrl group ( P < 0.05 ). Therefore, the true positive recognition (TPR) rate of DNN was significantly higher than that of the traditional method, and the pregnancy age, the preference for sweets before pregnancy, and the family history of DM may be risk factors for GDM; also, GDM was an influencing factor for pregnancy outcome, neonatal outcome, and complications.

scholarly journals Screening of Hemoglobin A1c in Gestational Diabetes among women attending metabolic clinic at a tertiary care hospital in Uttar Pradesh

2019 ◽  
Vol 10 (2) ◽  
pp. 26-30
Author(s):  
Vivek Sinha ◽  
Poonam Kachhawa
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Risk Factor ◽  
Family History ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Pregnant Women ◽  
P Value ◽  
Close Monitoring ◽  
History Of

Background: Gestational diabetes mellitus (GDM) is a common medical condition that complicates pregnancies..Gestational diabetes mellitus (GDM) is a diabetic metabolic disorder that occurs in 4% of all pregnant women and 14% of ethnic groups with more prevalence of type II diabetes. It can be defined as increased or abnormal insulin resistance, decreased insulin sensitivity or glucose intolerance with first diagnosis during pregnancy. Aims and Objectives: The purpose of this study was to evaluate the diagnostic screening value of the HbA1c, prevalence of GDM and associated risk factors. Materials and Methods: The study was conducted at the metabolic clinic; in the department of Biochemistry located at SIMS, Hapur. A semi-structured pretested questionnaire was used for data collection. Following the DIPSI guidelines, patients with plasma glucose values >140 mg/dl were labeled as GDM. Statistical methods used were OR (CI95%), percentage, Chi square. Results: Out of 500, 6.72% had GDM. Among all GDM patients, 64.71% had age more than 30 years, 70.59% had BMI more than 25, 41.18% had gravida more than 3 and p- value was significant with regard to age and BMI. P value was found to be significant for risk factors namely positive family history of Diabetes Mellitus, history of big baby and presence of more than one risk factor. Conclusion: GDM is associated with high BMI, early pregnancy loss, family history of DM and previous history of big baby and there could be more than one risk factor. Thus universal screening followed by close monitoring of the pregnant women for early detection of GDM may help improving maternal and fetal outcomes.

scholarly journals Utilizing diabetes mellitus risk assessment tool in screening of hemodialysis patients at risk of diabetes mellitus

2021 ◽  
Vol 2021 (2) ◽  
Author(s):  
Osama Azoubi ◽  
Tarek Abdullatif ◽  
Abdullah Hamad ◽  
Tarek Fouda ◽  
Sahar M Ismail ◽  
...  
Keyword(s):  
Physical Activity ◽  
Diabetes Mellitus ◽  
Risk Factors ◽  
Risk Assessment ◽  
Risk Factor ◽  
Assessment Tool ◽  
Risk Group ◽  
Dialysis Patients ◽  
Group Score ◽  
History Of

Background: Hamad General Hospital is the main provider of hemodialysis (HD) in Qatar, for approximately 650 patients per year. Over 60% of these patients have Diabetes Mellitus (DM) and 55% of them suffer from end stage renal disease (ESRD). 2% of ESRD patients develop DM after their first year of dialysis. The aims of this quality improvement study were early DM detection, risk factors modifications, and reduction of diabetes complications in our patients. Methods: A risk assessment tool was adapted to identify the risk level of HD patients to develop DM. They were screened to determine their risk score across 8 categories. Six categories (gender, history of gestational diabetes, family history of high blood pressure, diabetes, physical activity and smoking) were scored 0 to 1, age was scored 0 to 3, and relationship between weight and height scored 1 to 3. (Overall score range: 1-12). Patients were classified into two groups: a low-risk group (score < 5) and a high-risk group (score ≥ 5). Patients were referred to different medical specialties for further management according to the risk factor and a lifestyle modification management plan was set individually. Results: 189 non-diabetic dialysis patients were screened in the first quarter of 2020, their mean age was 51 years-old, and 69% were male. Forty-three percent of patients were found to be at high risk of developing DM. The most important risk factors were family history (55%), obesity (40%), age >60 years (32%), low physical activity (14%), and smoking (11%). Thirty-seven percent of patients were referred to the obesity clinic, 10% to the smoking cessation clinic, 5% to physiotherapy, and 100% of patients were referred to the multidisciplinary care. Conclusion: Screening for diabetes is pivotal for early detection and risk factor modification in dialysis patients. We recommend quarterly data assessment and evaluation so patients can be managed according to the findings.

scholarly journals ACUTE MYOCARDIAL INFARCTION

2016 ◽  
Vol 23 (03) ◽  
pp. 293-297
Author(s):  
Rafaqat Malik ◽  
Shazma Begum ◽  
Muhammad Nazar Afridi
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Risk Factor ◽  
Modifiable Risk Factors ◽  
Common Risk Factor ◽  
Cardiology Department ◽  
The World ◽  
History Of

The frequency of modifiable risk factors of acute myocardial infarction variesgreatly in different countries and populations of the world. Objective: To find out the frequencyof modifiable risk factors in patients with acute myocardial infarction. Design: Cross-sectionalstudy. Setting: Cardiology Department. Ayub Teaching Hospital Abbottabad, Period: 1st Jan2015 and 30th June 2015. Material and Methods: A total of 224 patients of acute myocardialinfarction Patients were enquired about the presence of hypertension, diabetes mellitus,smoking and family history of ischemic heart disease. Fasting blood sugar and lipid profilewere recorded. Results: Out of 224, 90.6% patients had at least one risk factor. Hypertensionwas found to be the most common risk factor (55.4%), followed by smoking (43.8%) andDiabetes Mellitus (27.2%). Dyslipidemia was found to be the least common (23.2%) risk factor.Conclusion: Hypertension is the most common modifiable risk factor in patients of acutemyocardial infarction, followed by smoking and diabetes.

scholarly journals Low birth weight at term and maternal contributing factors in community based hospital Korangi, Karachi.

2020 ◽  
Vol 27 (02) ◽  
pp. 324-329
Author(s):  
Saba Pario ◽  
Haniyah Qamar ◽  
Rozina Mustafa
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Risk Factor ◽  
Birth Weight ◽  
Low Birth Weight ◽  
Gestational Diabetes ◽  
Pregnancy Induced Hypertension ◽  
Fetal Gender ◽  
Induced Hypertension ◽  
History Of

Low birth weight is a key determinant of infant survival, health and development. Low birth weight infants are at a greater risk of morbidity and mortality than an infant of normal birth weight and create a substantial strain on the healthcare system. Objectives: To determine the frequency of low birth weight at term and maternal contributing risk factors in women attending antenatal clinic at Creek General Hospital Korangi, Karachi. Study Design: Descriptive cross sectional study. Setting: Department of Obstetrics and Gynecology of Creek General Hospital, United Medical and Dental College Karachi. Period: From May 2017 to April 2018. Material & Methods: Those women who gave birth to babies with less than 2500gm at term, were included in the study to ascertain the frequency and risk factors of low birth weight including age, parity, booking status for antenatal care, pre-pregnancy BMI, history of tobacco intake, medical disorders arising in pregnancy like anemia, pregnancy induced hypertension and gestational diabetes mellitus, birth weight and fetal gender. The data was analyzed on SPSS software. Results: The prevalence of term low birth weight was 22%. Percentage of low birth weight babies among teenage mothers was 72.8%, among the studied mothers 67.4% were primipara, 91.5% had standard antenatal care, Pre-pregnancy BMI was found to be normal in 93% of mothers, 9 mothers (7%) had history of tobacco/ betel nut chewing habit. In this study, iron deficiency anemia was found to be most significant factor leading to LBW babies (62 %). 12% and 8% of mothers were diagnosed with Pregnancy induced Hypertension and Gestational Diabetes mellitus respectively. Regarding fetal gender, 68 were females (52.7%) and 61 (47.3%) were males. Conclusion: Low Birth Weight is an important contributing risk factor for perinatal mortality and morbidity in Pakistan. Anemia was found to be most significant risk factor leading to Low birth weight in our study.

Risk Factors for Coronary Artery Disease in Patients Undergoing Coronary Angiogram at a Tertiary Level Hospital in Nepal

2022 ◽  
Vol 6 (1) ◽  
Author(s):  
Jeetendra Mishra ◽  
Achutanand Lal Karn ◽  
Alok Kumar Singh ◽  
Asraf Hussain ◽  
Ramji Ram ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Coronary Artery Disease ◽  
Risk Factor ◽  
Coronary Artery ◽  
Family History ◽  
Coronary Arteries ◽  
History Of ◽  
Premature Cad ◽  
Artery Disease

Background: Ischemic heart disease is the leading cause of CVD health loss globally, as well as in each world region, followed by stroke.  In Nepal, CVD was found to be the second most common non-communicable disease among indoor patients of the non-specialist hospital. Age, gender, smoking, obesity, dyslipidemia, physical inactivity, hypertension, and diabetes mellitus (DM) are established risk factors for CVD.  In Nepal, hypertension is found to be the most prevalent risk factor for CVD. Aims and Objectives: This study aimed to assess risk factors for coronary artery disease in patients undergoing coronary angiograms in Nepal. This study also investigated the socio-demographic characteristics of the participants and the nature of the involvement of coronary arteries. Materials and Methods: We examined in this cross-sectional study a total of 74 patients who underwent coronary angiography (CAG) at National Medical College between May 2020 and June 2021. Patients were grouped according to the number of major epicardial coronary arteries involved in SVD, DVD, and TVD. Patients were checked for risk factors like smoking, diabetes mellitus, hypertension, dyslipidemia, family history of coronary artery disease, and obesity. Microsoft Office Excel and SPSS version 21.0 were used for data analysis. The study was approved by the ethical committee. Results: Among 74 participants 53 were male. The mean age was 59.65±10.74 years. Premature coronary artery disease was present in six patients. SVD was the commonest CAD type. Hypertension was the commonest risk factor followed by Diabetes mellitus. Hypertension, Diabetes mellitus, Family history of premature CAD, and obesity were found to be statistically significant. Keywords: CAD, Risk factors for CAD, Premature CAD, Hypertension, Diabetes, obesity, family history of CAD, dyslipidemia, Smoking, SVD, DVD, TVD, Nepal

scholarly journals Risk factors for type 2 diabetes mellitus in adolescents secondary school students in Port Harcourt, Nigeria

1970 ◽  
Vol 42 (2) ◽  
pp. 137-141
Author(s):  
T Jaja ◽  
IE Yarhere
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Risk Factor ◽  
Family History ◽  
Fasting Glucose ◽  
Family History Of Diabetes ◽  
History Of

Background: The prevalence of Type 2 diabetes mellitus (T2 DM) in children and adolescents is on the increase, therefore, prevention and early detection are important.Objective: To assess for easily identifiable risk factors (overweight/obesity, hypertension, Impaired Fasting Glucose (IFG) and family history of diabetes) for T2DM in adolescents in public secondary schoolsResult: Eight hundred and eighty adolescents aged 10 to 19 years were screened and 124(14.1%) were overweight/obese. 457 (51.9%) of students had none of the risk factors while 272(30.9%) had at least one risk factor. Using the American Diabetes Association criteria for identification of those at risk for T2DM, 21(2.4%) were identified. The frequency of presence of risk factors was more in females (3.3%), mid adolescent age group (3.1%) and those with positive family history of diabetes. These findings were however not statistically significant. There was a statistically significant association between presence of hypertension and impaired fasting glucose and risk factor for type 2 DM.Conclusion: The significant risk factors identified in this study were prehypertension/hypertension and impaired fasting blood glucose.Key words: Adolescence, Risk factors, Type 2 diabetes mellitus

scholarly journals Clinical Symptoms of Patient with Heart Failure in Dr. Soetomo General Hospital: A Descriptive Study

2021 ◽  
Vol 12 (2) ◽  
pp. 61
Author(s):  
Niki Kusuma Bangsa ◽  
Rochmad Romdoni ◽  
Subagyo Subagyo
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Heart Failure ◽  
Cardiovascular Disease ◽  
Risk Factor ◽  
General Hospital ◽  
Clinical Symptoms ◽  
Smoking Status ◽  
Common Symptom ◽  
History Of

Introduction: Heart failure (HF) has emerged as a cardiovascular disease with high prevalence in developing countries. The highest number was expected to increase over the next few decades. Moreover, most people with HF do not show specific symptoms earlier, thus death often occurs. This study was undertaken to give an insight into the clinical symptoms and risk factors of HF.Methods: This cross-sectional study utilized medical records from Dr. Soetomo General Hospital between 6 months (July-December 2016). Eligibility criteria included female patients diagnosed with HF at the hospital with a classification of NYHA I-IV. Risk factors data from the participants such as hypertension, diabetes mellitus, dyslipidemia, body mass index (BMI), smoking status, and history of cardiovascular disease were collected. Clinical symptoms were reported descriptively.Results: From 84 patients admitted with HF in the hospital from July until December 2016, 53 were males (63.1%). In all groups, hypertension (35.6%) was the highest prevalence risk factor, followed by diabetes mellitus (25.3%), and a history of cardiovascular disease (17.2%). In this study, the most common symptom was shortness of breathing, contributing to 72.6%, followed by chest pain (10.7%), and body weakness (6%).Conclusion: This study concluded that most of the respondents were male, aged 46-65 years old. The highest risk factor that contribute to an HF was hypertension. The most common symptom in patients with HF in the hospital was shortness of breathing. Studies further emphasize the need for primordial prevention related to symptoms and risk factors of HF. 

Knowledge, awareness and perceptions of diabetes mellitus among the Saudi population

2020 ◽  
Vol 9 (6) ◽  
pp. 413-422
Author(s):  
Muhammad H Mujammami ◽  
Abdulaziz A Alodhayani ◽  
Mohammad Ibrahim AlJabri ◽  
Ahmad Alhumaidi Alanazi ◽  
Sultan Sayyaf Alanazi ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Social Media ◽  
Risk Factor ◽  
Healthcare Workers ◽  
Health Workers ◽  
Saudi Population ◽  
Limited Data ◽  
High Prevalence ◽  
Associated Risk Factors

Background: High prevalence of undiagnosed cases of diabetes mellitus (DM) has increased over the last two decades, most patients with DM only become aware of their condition once they develop a complication. Limited data are available regarding the knowledge and awareness about DM and the associated risk factors, complications and management in Saudi society. Aim: This study aimed to assess knowledge of DM in general Saudi society and among Saudi healthcare workers. Results: Only 37.3% of the participants were aware of the current DM prevalence. Obesity was the most frequently identified risk factor for DM. Most comparisons indicated better awareness among health workers. Conclusion: A significant lack of knowledge about DM in Saudi society was identified. Social media and educational curriculum can improve knowledge and awareness of DM.

scholarly journals Incidence of diabetes mellitus and associated risk factors in the adult population of the Basque country, Spain

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Inés Urrutia ◽  
◽  
Alicia Martín-Nieto ◽  
Rosa Martínez ◽  
J Oriol Casanovas-Marsal ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Family History ◽  
Basque Country ◽  
Adult Population ◽  
Tolerance Test ◽  
Oral Glucose ◽  
Family History Of Diabetes ◽  
History Of ◽  
Incident Cases

AbstractThe aim of this study was to estimate the incidence of diabetes mellitus in the Basque Country and the risk factors involved in the disease by reassessing an adult population after 7 years of follow-up. In the previous prevalence study, 847 people older than 18 years were randomly selected from all over the Basque Country and were invited to answer a medical questionnaire, followed by a physical examination and an oral glucose tolerance test. In the reassessment, the same variables were collected and the resulting cohort comprised 517 individuals of whom 43 had diabetes at baseline. The cumulative incidence of diabetes was 4.64% in 7 years and the raw incidence rate was 6.56 cases/1000 person-years (95%CI: 4.11–9.93). Among the incident cases, 59% were undiagnosed. The most strongly associated markers by univariate analyses were age > 60 years, dyslipidaemia, prediabetes and insulin resistance. We also found association with hypertension, obesity, family history of diabetes and low education level. Multivariate analysis adjusted for age and sex showed that a set of risk factors assessed together (dyslipidaemia, waist-to-hip-ratio and family history of diabetes) had great predictive value (AUC-ROC = 0.899, 95%CI: 0.846–0.953, p = 0.942), which suggests the need for early intervention before the onset of prediabetes.

Prevalence and prognostic impact of left ventricular systolic dysfunction after acute myocardial infarction

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
T.J Jernberg ◽  
E.O Omerovic ◽  
E.H Hamilton ◽  
K.L Lindmark ◽  
L.D Desta ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Myocardial Infarction ◽  
Atrial Fibrillation ◽  
Risk Factor ◽  
Reperfusion Therapy ◽  
Left Ventricular ◽  
Funding Source ◽  
Additional Risk Factor ◽  
Additional Risk

Abstract Background Left ventricular dysfunction after an acute myocardial infarction (MI) is associated with poor outcome. The PARADISE-MI trial is examining whether an angiotensin receptor-neprilysin inhibitor reduces the risk of cardiovascular death or worsening heart failure (HF) in this population. The aim of this study was to examine the prevalence and prognosis of different subsets of post-MI patients in a real-world setting. Additionally, the prognostic importance of some common risk factors used as risk enrichment criteria in the PARADISE-MI trial were specifically examined. Methods In a nationwide myocardial infarction registry (SWEDEHEART), including 87 177 patients with type 1 MI between 2011–2018, 3 subsets of patients were identified in the overall MI cohort (where patients with previous HF were excluded); population 1 (n=27 568 (32%)) with signs of acute HF or an ejection fraction (EF) &lt;50%, population 2 (n=13 038 (15%)) with signs of acute HF or an EF &lt;40%, and population 3 (PARADISE-MI like) (n=11 175 (13%)) with signs of acute HF or an EF &lt;40% and at least one risk factor (Age ≥70, eGFR &lt;60, diabetes mellitus, prior MI, atrial fibrillation, EF &lt;30%, Killip III-IV and STEMI without reperfusion therapy). Results When all MIs, population 1 (HF or EF &lt;50%), 2 (HF or EF &lt;40%) and 3 (HF or EF &lt;40% + additional risk factor (PARADISE-MI like)) were compared, the median (IQR) age increased from 70 (61–79) to 77 (70–84). Also, the proportion of diabetes (22% to 33%), STEMI (38% to 50%), atrial fibrillation (10% to 24%) and Killip-class &gt;2 (1% to 7%) increased. After 3 years of follow-up, the cumulative probability of death or readmission because of heart failure in the overall MI population and in population 1 to 3 was 17.4%, 26.9%, 37.6% and 41.8%, respectively. In population 2, all risk factors were independently associated with death or readmission because of HF (Age ≥70 (HR (95% CI): 1.80 (1.66–1.95)), eGFR &lt;60 (1.62 (1.52–1.74)), diabetes mellitus (1.35 (1.26–1.44)), prior MI (1.16 (1.07–1.25)), atrial fibrillation (1.35 (1.26–1.45)), EF &lt;30% (1.69 (1.58–1.81)), Killip III-IV (1.34 (1.19–1.51)) and STEMI without reperfusion therapy (1.34 (1.21–1.48))) in a multivariable Cox regression analysis. The risk increased with increasing number of risk factors (Figure 1). Conclusion Depending on definition, post MI HF is present in 13–32% of all MI patients and is associated with a high risk of subsequent death or readmission because of HF. The risk increases significantly with every additional risk factor. There is a need to optimize management and improve outcomes for this high risk population. Figure 1 Funding Acknowledgement Type of funding source: Private company. Main funding source(s): Novartis

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