Gradient boosting decision tree becomes more reliable than logistic regression in predicting probability for diabetes with big data

We sought to verify the reliability of machine learning (ML) in developing diabetes prediction models by utilizing big data. To this end, we compared the reliability of gradient boosting decision tree (GBDT) and logistic regression (LR) models using data obtained from the Kokuho-database of the Osaka prefecture, Japan. To develop the models, we focused on 16 predictors from health checkup data from April 2013 to December 2014. A total of 277,651 eligible participants were studied. The prediction models were developed using a light gradient boosting machine (LightGBM), which is an effective GBDT implementation algorithm, and LR. Their reliabilities were measured based on expected calibration error (ECE), negative log-likelihood (Logloss), and reliability diagrams. Similarly, their classification accuracies were measured in the area under the curve (AUC). We further analyzed their reliabilities while changing the sample size for training. Among the 277,651 participants, 15,900 (7978 males and 7922 females) were newly diagnosed with diabetes within 3 years. LightGBM (LR) achieved an ECE of 0.0018 ± 0.00033 (0.0048 ± 0.00058), a Logloss of 0.167 ± 0.00062 (0.172 ± 0.00090), and an AUC of 0.844 ± 0.0025 (0.826 ± 0.0035). From sample size analysis, the reliability of LightGBM became higher than LR when the sample size increased more than 104. Thus, we confirmed that GBDT provides a more reliable model than that of LR in the development of diabetes prediction models using big data. ML could potentially produce a highly reliable diabetes prediction model, a helpful tool for improving lifestyle and preventing diabetes

Age-Dependent Association Between Modifiable Risk Factors and Incident Cardiovascular Disease

BACKGROUND: There have been limited data examining the age-dependent relationship of wide-range risk factors with the incidence of each subtype of cardiovascular disease (CVD) event. We assessed age-related associations between modifiable risk factors and the incidence of CVD. METHODS AND RESULTS: We analyzed 3 027 839 participants without a CVD history enrolled in the JMDC Claims Database (mean age, 44.8±11.0 years; 57.6% men). Each participant was categorized as aged 20 to 49 years (n=2 008 559), 50 to 59 years (n=712 273), and 60 to 75 years (n=307 007). Using Cox proportional hazards models and the relative risk reduction, we identified associations between risk factors and incident CVD, consisting of myocardial infarction, angina pectoris, stroke, and heart failure (HF). We assessed whether the association of risk factors for developing CVD would be modified by age cat-egory. Over a mean follow-up of 1133 days, 6315 myocardial infarction, 56 447 angina pectoris, 28 079 stroke, and 56 369 HF events were recorded. The incidence of myocardial infarction, angina pectoris, stroke, and HF increased with age category. Hazard ratios of obesity, hypertension, and diabetes in the multivariable Cox regression analyses for myocardial infarction, angina pectoris, stroke, and HF decreased with age category. The relative risk reduction of obesity, hypertension, and diabetes for CVD events decreased with age category. For example, the relative risk reduction of hypertension for HF decreased from 59.2% in participants aged 20 to 49 years to 38.1% in those aged 60 to 75 years. CONCLUSIONS: The contribution of modifiable risk factor to the development of CVD is greater in younger compared with older individuals. Preventive efforts for risk factor modification may be more effective in younger people.</p

Randomized Controlled Trial of the Effectiveness of Genetic Counseling and a Distance, Computer-Based, Lifestyle Intervention Program for Adult Offspring of Patients with Type 2 Diabetes: Background, Study Protocol, and Baseline Patient Characteristics

Relatives of type 2 diabetic patients are at a high risk of developing type 2 diabetes and should be regarded as target of intervention for diabetes prevention. However, it is usually hard to motivate them to implement preventive lifestyle changes, because of lack of opportunity to take advises from medical professionals, inadequate risk perception, and low priority for preventive behavior. Prevention strategy for them therefore should be highly acceptable and suited for them. The parallel, three-group trial is now being conducted to investigate the effects of genetic counseling and/or a computerized behavioral program on the prevention of type 2 diabetes in that population. The preventive strategies used in this study could provide a novel solution to the numbers of genetically high-risk individuals, if found to be effective. The objective of this paper is to describe the background, protocol, and baseline patient characteristics of the trial

Racial Disparities in the Association Between Stress and Preterm Birth

Background: High levels of maternal stress have been linked to preterm births. However, findings from previous studies are inconsistent due to the varied use of stress measures. This study examined the effect of maternal stress on preterm birth, using both psychosocial and physiological measures. Methods: This study was conducted among 231 pregnant women enrolled during their first prenatal care visit. Presence of stress was assessed at enrollment using the Perceived Stress Scale (PSS) and Stressful Life Events Inventory (SLEI). Samples of maternal salivary cortisol were obtained during the first trimester and birth outcomes were ascertained at delivery. Multiple logistic regression was conducted to assess the association between stress and preterm birth. Results: The majority of the study participants were Black, not married, less educated and low income. There was an association between cortisol level and preterm birth. Per 1µg/dL increase in cortisol level, the odds of preterm birth increased by 26%. The increase was accentuated in Blacks where a unit increase in cortisol level was associated with higher odds of preterm birth (29%). Conclusions: Stress measures using PSS and SLEI did not reveal a statistically significant association with preterm birth. Health care and public health professionals should be aware of the association between increased cortisol level and preterm birth. Salivary cortisol may be a better predictor of preterm birth than PSS and SLEI

Prev Chronic Dis

IntroductionAs one of the most prevalent chronic diseases in the United States, diabetes, especially type 2 diabetes, affects the health of millions of people and puts an enormous financial burden on the US economy. We aimed to develop predictive models to identify risk factors for type 2 diabetes, which could help facilitate early diagnosis and intervention and also reduce medical costs.MethodsWe analyzed cross-sectional data on 138,146 participants, including 20,467 with type 2 diabetes, from the 2014 Behavioral Risk Factor Surveillance System. We built several machine learning models for predicting type 2 diabetes, including support vector machine, decision tree, logistic regression, random forest, neural network, and Gaussian Naive Bayes classifiers. We used univariable and multivariable weighted logistic regression models to investigate the associations of potential risk factors with type 2 diabetes.ResultsAll predictive models for type 2 diabetes achieved a high area under the curve (AUC), ranging from 0.7182 to 0.7949. Although the neural network model had the highest accuracy (82.4%), specificity (90.2%), and AUC (0.7949), the decision tree model had the highest sensitivity (51.6%) for type 2 diabetes. We found that people who slept 9 or more hours per day (adjusted odds ratio [aOR] = 1.13, 95% confidence interval [CI], 1.03\u20131.25) or had checkup frequency of less than 1 year (aOR = 2.31, 95% CI, 1.86\u20132.85) had higher risk for type 2 diabetes.ConclusionOf the 8 predictive models, the neural network model gave the best model performance with the highest AUC value; however, the decision tree model is preferred for initial screening for type 2 diabetes because it had the highest sensitivity and, therefore, detection rate. We confirmed previously reported risk factors and also identified sleeping time and frequency of checkup as 2 new potential risk factors related to type 2 diabetes.31538566PMC6795062692

Medical Genetic Counseling Of Women With Congenital Heart Diseases Of Fetus

Aim of the work. Determine the effectiveness of prenatal diagnosis of congenital heart defects in the fetus and the informativeness of different markers used in the medical-genetic counseling of pregnant women..Materials and methods. The analysis of the results of medical genetic counseling of pregnant women with fetal heart diseases was carried out. The effectiveness of using different methods of prenatal diagnosis in 67 pregnant women is estimated. The data of somatic, genealogical and reproductive anamnesis, biochemical markers of chromosomal pathology of the 1st and 2nd trimester of pregnancy, and the spectrum of the detected fetal heart disease were studied.Results of the research. It was found that 46 (68.7 %) women had somatic diseases: pathology of the cardiovascular system (11.9 %); endocrine system - at 8 (11,9 %); respiratory disease – 3 (4.5 %) and urinary system – 2 (3.0 %). 13 (19.4 %) out of 67 women had acute respiratory viral infections in the first trimester of pregnancy. In 4 (6 %) cases - bad habits. The first time pregnant were 31 (46.3 %) women, 21 (31.3 %) – the second time, 10 (14.9 %) in the third, and 5 (7.5 %) in the fourth or more times. In history, 58 (86.6 %) women did not have reproductive function disorders, 8 (11.9 %) had unauthorized miscarriages and frozen pregnancy. The burden of gynecological anamnesis was observed in 12 (17.9 %) women, and hereditary - in 6 (9.0 %) women. In the structure of congenital defects of the heart, false anatomical anomalies were found more often: hypoplasia of the left heart organs – 14 (20.9 %), tetralogy of Fallot - 9 (13.3 %). Biochemical markers of chromosomal pathology in the first trimester in 11 (16.4 %) women recorded indicators that are characteristic of the risk of chromosomal pathology, and in the second trimester – in 9 (13.4 %). Two pregnant women used a NIPT (non-invasive prenatal test) test that did not detect chromosomal abnormalities in the fetus. In 8 cases, invasive prenatal diagnosis of the fetus was recommended, which was carried out by three women, and five refused.Conclusions. The peculiarities of somatic (in 46–68.7 % of women), reproductive (in 8-11.9 % of women) gynecological anamnesis (in 12–17.9 % of women), which can be the risk factors of congenital fetal heart disease, are revealed. In the structure of congenital defects of the heart of the fetus more often revealed hypoplasia of the left heart organs – 14 (20.9 %), tetralogy of Fallot – 9 (13.3 %). In 11 (16.4 %) women recorded indicators of biochemical markers, characteristic for the risk of chromosomal pathology, in the first trimester, and – in 9 (13.4 %) pregnant women – in the second trimester. Comparative data on prenatal diagnosis of congenital heart defects in the fetus of chromosomal, monogenic and multifactorial etiology are given. On the basis of the obtained results an algorithm of medical-genetic counseling of this contingent of patients was offered

Impact of components of metabolic syndrome on the risk of adverse renal outcomes in patients with atrial fibrillation: a nationwide cohort study

Background: The renal effect of metabolic syndrome components is unclear in patients with atrial fibrillation. This study aimed to investigate the association between metabolic syndrome components and incident end-stage renal disease among patients with atrial fibrillation. Methods: A total of 202,434 atrial fibrillation patients without prevalent end-stage renal disease were identified from the National Health Insurance Service database between 2009 and 2016. We defined the metabolic score range from 0 to 5 points such that a patient received every 1 point if the patient met each component listed in the diagnostic criteria of metabolic syndrome. The population was divided into 6 groups: MS 0–MS 5 for a metabolic score of 0–5, respectively. Multivariate Cox regression analysis was used to estimate the risks of end-stage renal disease. Results: There were 12,747, 31,059, 40,361, 48,068, 46,630, and 23,569 patients for MS 0–MS 5, respectively. Compared with MS 0, MS 5 had a higher CHA 2DS 2-VASc score (3.8 vs. 1.0) (P &lt;.001). During a median follow-up of 3.5 years, compared with MS 0, MS 1–MS 5 were associated with a gradually increasing incidence of end-stage renal disease, in relation to an increase in the metabolic score, (log-rank P &lt;.001). After multivariate adjustment, a higher metabolic score was associated with a greater risk of incident end-stage renal disease: adjusted hazard ratio [95% confidence interval] = 1.60 [0.78–3.48], 2.08 [1.01–4.31], 2.94 [1.43–6.06], 3.71 [1.80–7.66], and 4.82 [2.29–10.15], for MS 1–MS 5, respectively. Conclusions: Metabolic syndrome components additively impacts the risk of incident end-stage renal disease among patients with atrial fibrillation.</p

Assessment of effectiveness of fetal medicine foundation calculator in predicting risk for preterm preeclampsia using first trimester mean uterine artery pulsatility index and maternal factors in Indian population

Background: Preeclampsia (PE) is a hypertensive disorder of pregnancy associated with significant maternal morbidity and mortality. The outcome of the disease depends to a large extent on risk factors, maternal vascular responsiveness, screening performance and prevention effectiveness. Fetal medicine foundation has developed an online calculator that predicts the risk for PE in pregnant woman in first trimester using MUAPI (mean uterine artery pulsatility index) and maternal factors.Methods: Diagnostic test evaluation of FMF (fetal medicine foundation) calculator done using data collected from consenting 316 women with singleton pregnancy between the gestational age 11 weeks to 14 weeks+1 day who fulfilled inclusion and exclusion criteria. All cases were followed up and results were analyzed statistically.Results: FMF calculator predicted a high-risk population of 12 pregnant women. On follow up of 316 subjects 13 pregnant women developed preterm preeclampsia with an incidence of 4.1%. Among high-risk population 9 subjects developed preterm PE and among the 304 cases in low-risk group 4 patient developed preterm PE. In this study sensitivity of FMF calculator was 69.2% and specificity was 99% with a PPV of 75, NPV of 98.6, positive likelihood ratio of 69.9 and diagnostic odds ratio of 225. The area under ROC was 0.841 with 95% CI (0.711-0.972) was high indicating that the algorithm was able to differentiate between pregnant women at high or low risk for preterm PE.Conclusions: This study concludes that the algorithm used in FMF calculator in first trimester is highly specific and have high sensitivity for predicting preterm PE and can be used in routine clinical practice to identify women at high risk

INCIDENCE OF METABOLIC SYNDROME IN THE URBAN POPULATION OF INDORE, M. P., INDIA

ABSTRACTBackground- The present study determines the prevalence of metabolic syndrome (MS), with special reference to hyperglycaemia and hyperlipidemia within urban population of a tertiary health care hospital in Indore (Madhya Pradesh), India.Material and method- This cross-sectional study involved 726 subjects (467 men &amp; 259 women). MS was defined using revised National Cholesterol Education Program (NCEP) criteria.Results- When compared with the modified NCEP criteria, the prevalence of MS was found to be 7.51% (5.99% in men and 8.11% in women). Descriptive analysis exemplified a significantly increased mean values of FBS (P&lt;0.01), PPBS (P&lt;0.01) and lipid values (P&lt;0.05) in the population. However, as compared to man, women showed significant elevated TCHO (P&lt;0.05) and HDL (P&lt;0.01). On the other hand, man exhibited increased TGL (P&lt;0.05), cardiac risk ratio [C/H (P&lt;0.01) and L/H (P&lt;0.01)] than women. The highest prevalence of MS was seen in men of age group of 55-75 yrs and in women of age group of 20-34 yrs.Conclusion- Our test population showed an increased rate of hyperglycaemia and hyperlipidemia, with increase in age, indicating a need to implement policies to control this abnormal MS. Key words- Cardiac risk ratio, diabetes mellitus, fasting blood sugar, metabolic syndrome, serum cholesterolÂ