Bayesian Formulation of Time-Dependent Carrier-Borne Epidemic Model with a Single Carrier

In this paper, the time dependent carrier-borne epidemic model defined by Weiss in 1965 has been adopted into a Bayesian framework for the estimation of its parameters. A complete methodological structure has been proposed for estimating the relative infection rate and probability of survival of k out of m susceptibles after time t from the start of the epidemic. The methodology has been proposed assuming a single carrier to simplify the study of the behavioral validity of the fitted Bayesian model with respect to time and relative infection rate. Further, the proposed model has been implemented on two real data sets- the typhoid epidemic data from Zermatt in Switzerland and the Covid-19 epidemic data from Kerala in India. Results show that the proposed methodology produces reliable predictions which are consistent with those of the maximum likelihood estimates and with expected epidemiological patterns

A Correlation Technique to Reduce the Number of Predictors to Estimate the Survival Time of HIV/ AIDS Patients on ART

Till now, many research papers have been published which aims to estimate the survivle time of the HIV/AIDS patients taking into consideration all the predictors viz, Age, Sex, CD4, MOT, Smoking, Weight, HB, Coinfection, Time, BMI, Location Status, Marital Status, Drug etc, although all the predictors need not to be included in the model. Since some of the predictors may be correlated/ associated and may have some influence on the outcome variable, therefore, instead of taking both the significantly correlated/ associated predictors, we may take only one of the two. In this way, we may be able to reduce the number of predictors without affecting the estimated survival time. In this paper we have tried to reduce the number of predictors by determining the highly positively correlated predictors and then evaluating the effect of correlation/ association on the survival time of HIV/AIDS patients. These predictors that we have considered in the starting are Age, Sex, State, Smoking, Alcohol, Drugs, Opportunistic Infections (OI), Living Status (LS), Occupation (OC), Marital Status (MS) and Spouse for the data collected from 2004 to 2014 of AIDS patients in an ART center of Delhi, India. We have performed one – way ANOVA to test the association between a quantitative and a categorical variable and Chi-square test to test between two categorical variables. To select one of the two highly correlated/ associated predictors, a suitable model is fitted keeping one predictor independent at a time and other dependent and the model having the smaller AIC is considered and the independent variable in the model is included in the modified model. The fitted models are logistic, linear and multinomial logistic depending on the type of the independent variable to be fitted. Then the true model (having all the predictors) and the modified model (with reduced number of predictors) are compared on the basis of their AICs and the model having minimum AIC is chosen. In this way we could reduce the number of predictors by almost 50% without affecting the estimated survival time with a reduced standard error

Factors contributing to late stillbirth among women with pregnancy hypertension in a developing country

Objective To investigate the factors associated with late stillbirth among women with hypertensive disorders of pregnancy (HDP). Material and Methods The clinical details of women with HDP having late stillbirth were compared with controls having livebirth. Results Total 208 cases and 288 controls were included in the study. Inadequate antenatal visits (p 8 contributed significantly (p = 0.0001, OR-5.6) to stillbirth. Conclusion Poor antenatal care, birth weight below 2000gms and high BW/PW ratio was associated with a higher risk of stillbirth

Cure Fraction Model for the Estimation of Long-term Survivors of HIV/AIDS Patients under Antiretroviral Therapy

The primary aim of this research is to estimate the proportion of long-term survivors among HIV/AIDS patients receiving Antiretroviral therapy (ART). A cure fraction model has been used to accomplish the same. Although, cure fraction models are extensively being used in oncology for modeling survival time data with long-term survivors, but there are minimal research that considers this model in HIV/AIDS set up. Here, we have defined survival time under the purview of CD4 cell counts. CD4 is considered to be disease marker for HIV/AIDS patients. Bayesian Analysis of the various mixture and non-mixture cure fraction models under exponential, generalized exponential. Raleigh, Weibull, Exponentiated Weibull distributions are exemplified using a real data set. Effect of prognostic factors like baseline CD4, age, sex, medication on cure fraction are studied. The MLE’s are obtained using Gibbs sampling techniques with MCMC method in Open BUGS package. Convergence diagnostic (like trace plots, density plots & MC errors) are used to detect in any unexpected anomalies in MCMC output. The DIC (Deviance information criterion) has been utilized to compare the efficiency of different models. A real-life data set from the ART center of RML hospital, Delhi, India are taken for this study

Reference centile charts of first-trimester aneuploidy screening & Doppler parameters for Indian population

Background & objectives: The risk estimation for foetal aneuploidies in the first trimester of pregnancy uses reference curves based on western data. The objective of this study was to construct the reference curves of first-trimester foetal aneuploidy screening parameters for the Indian women. Methods: Cross-sectional data were obtained from 1204 singleton pregnancies between the crown-rump length (CRL) of 40-84 mm. Linear regression models were constructed; the mean, median and standard deviation were derived as a function of CRL. Results: The mean value of CRL was 61.3 mm. The regression analysis showed a significant correlation between all variables and CRL (P< 0.001). There was a positive correlation of CRL with nuchal translucency (NT) (y=0.010x+0.629, R2=0.116) and pregnancy-associated plasma protein-A (PAPP-A) (y=0.107x−1.079, R2=0.173), whereas inverse correlation was seen with free β-human chorionic gonadotropin (β-hCG) (y=−0.409x+75.025, R2=0.018) and Doppler parameters pulsatility index (PI) (y=−0.008x+1.924 R2=0.053). The centile charts of NT, PAPP-A, free β-hCG and uterine artery (Ut A) Doppler PI were constructed. Interpretation & conclusions: The reference centile charts of first trimester aneuploidy screening along with Doppler parameters were derived in Indian pregnant women. These centile charts may be used as a reference for clinical use in Indian population

Role of Platelet Function Test in Predicting Postoperative Bleeding Risk after Coronary Artery Bypass Grafting: A Prospective Observational Study

Patients undergoing cardiac surgery are at risk of excessive bleeding and its associated complications. Excessive bleeding during and after cardiac surgery has an incidence of ~20%. Massive bleeding and subsequent requirement for blood product administration and mediastinal reexploration are associated with significant morbidity and mortality. Postoperative, nonsurgical bleeding in cardiac surgical patients is often multifactorial. Platelet dysfunction, excessive fibrinolysis, hypothermia, preoperative anemia, and deficiency of coagulation factors or their dilution are all suggested etiologies of postoperative bleeding. In the Arachidonic Acid Thromboelastometry (ARATEM) test, platelets are activated with arachidonic acid; in Adenosine diphosphate Thromboelastometry (ADPTEM) test, platelets are activated with adenosine diphosphate; and in TRAPTEM test, platelets are activated with thrombin receptor-activating peptide 6. Measurement time is 6 minutes, and results are expressed in three different parameters: A6 (amplitude at 6 minutes, in Ohm); MS (maximum slope of the aggregation curve in Ohm/min), and AUC (area under the curve in Ohm.min). Algorithm-based point-of-care platelet function testing helped us to preemptively give the right blood component therapy, avoiding fibrinolytic bleeding in the postoperative period

Platelet Function Test in Coronary Artery Bypass Grafting: Does It Predict Postoperative Bleeding?

Background Patients undergoing on-pump coronary artery bypass grafting (CABG) are at increased risk of perioperative bleeding and morbidity associated with transfusion as a result of acquired and pharmacologically induced impaired platelet function. Settings and Design In this a prospective observational study where 52 patients underwent on-pump CABG were analyzed with ROTEM platelet aggregometry. Materials and Methods Patients were assigned to the “nonexcessive” and “excessive” postoperative bleeding groups according to the postoperative chest tube drainage over 24 hours. Platelet function was assessed by ROTEM platelet using three different activators (arachidonic acid, adenosine diphosphate, and thrombin receptor-activating peptide), at two perioperative time points (T1, before heparinization and T2, 5–10 minutes after protamine administration). Results There were no differences regarding demographic, pre–cardiopulmonary bypass (CPB) platelet count and antiplatelet therapy. Platelet function was impaired over the time course in all parameters with three different activators. At T2 point, area under the curve (AUC) of all the three platelet indices, that is, TRAPTEM, ARATEM, and ADPTEM, showed significant difference between excessive and nonexcessive groups. At both T1 and T2 points, the amplitude after 6 minutes (A6) and maximum slope (MS) parameters of TRAPTEM, ARATEM, and ADPTEM tests were not significantly different in excessive and nonexcessive groups. At T1 point, AUC was also not significantly different in all three ROTEM platelet tests. Results after protamine administration showed correlation with postoperative chest tube drainage. Cut-off values, as determined by receiver operating characteristics (ROC) analyses, had a consistently weak positive predictive value for all tests at T2 time point, whereas negative predictive values were higher. Conclusion Platelet function analysis using ROTEM platelet can help to exclude platelet dysfunction as the reason for bleeding after cardiac surgery. Point-of-care platelet function analysis, particularly in combination with viscoelastic testing can reduce perioperative bleeding and transfusion requirements, as well as improve patient outcomes in cardiac surgery