Prediction for cardiovascular diseases based on laboratory data: An analysis of random forest model. Su Xi,Xu Yongyong,Tan Zhijun,Wang Xia,Yang Peng,Su Yani,Jiang Yangyang,Qin Sijia,Shang Lei Journal of clinical laboratory analysis BACKGROUND:To establish a prediction model for cardiovascular diseases (CVD) in the general population based on random forests. METHODS:A retrospective study involving 498 subjects was conducted in Xi'an Medical University between 2011 and 2018. The random forest algorithm was used to screen out the variables that greatly affected the CVD prediction and to establish a prediction model. The important variables were included in the multifactorial logistic regression analysis. The area under the curve (AUC) was compared between logistic regression model and random forest model. RESULTS:The random forest model revealed the variables, including the age, body mass index (BMI), fasting blood glucose (FBG), diastolic blood pressure (DBP), triglyceride (TG), systolic blood pressure (SBP), total cholesterol (TC), waist circumference, and high-density lipoprotein-cholesterol (HDL-C), were more significant for CVD prediction; the AUC was 0.802 in CVD prediction. Multifactorial logistic regression analysis indicated that the risk factors for CVD included the age [odds ratio (OR): 1.14, 95% confidence intervals (CI): 1.10-1.17, P < .001], BMI (OR: 1.13, 95% CI: 1.06-1.20, P < .001), TG (OR: 1.11, 95% CI: 1.02-1.22, P = .023), and DBP (OR: 1.04, 95% CI: 1.02-1.06, P = .001); the AUC was 0.843 in CVD prediction. The established logistic regression prediction model was Logit P = Log[P/(1 - P)] = -11.47 + 0.13 × age + 0.12 × BMI + 0.11 × TG + 0.04 × DBP; P = 1/[1 + exp(-Logit P)]. People were prone to develop CVD at the time of P > .51. CONCLUSIONS:A prediction model for CVD is developed in the general population based on random forests, which provides a simple tool for the early prediction of CVD. 10.1002/jcla.23421

Significance of assay of nucleated RBCs in umbilical cord blood in neonates with meconium-stained amniotic fluid. Elsokkary M,Mamdouh A,Nossair W,Abd El Fattah O,Hemeda H,Sallam S,Taema M,Hussain M,Shafik A,Nawara M,Samy M,Abd El Aleem M,Abdelhadi R,Sakna N,Salama A,Salama D,El-Tohamy O,Elsaid N The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians BACKGROUND:Approximately 8-15% of all infants are born with evidence of meconium-stained amniotic fluid (MSAF). MSAF is a potentially serious sign of fetal compromise and may indicate fetal hypoxia Objectives and aim of the work: The present study was designed to evaluate the relationship between meconium stained amniotic fluid and fetal nucleated red blood cell counts. As well, we aim to evaluate the relationship between the presence of meconium in amniotic fluid and Apgar scores in neonates. SUBJECTS AND METHODS:A prospectively case-controlled study was performed on 40 women with clear amniotic fluid as control and 40 women with meconium-stained amniotic fluid as the study group. At delivery, 2 ml of umbilical cord blood was collected and analyzed for nucleated red blood cell (NRBC). RESULTS:The mean NRBC counts in meconium-stained amniotic fluid was significantly higher than the control group (18.35 ± 7.7 and 9.6 ± 4.96), respectively (p < .001). There were statistically significant differences concerning 1- and 5-min Apgar scores with lower values in the MSAF group (p < .001 and .001, respectively). CONCLUSION:Our results support previous studies which indicate the presence of meconium can be associated with chronic fetal hypoxia as demonstrated by elevated fetal NRBC levels. 10.1080/14767058.2017.1384457