Correlates of diabetic retinopathy: A case study.

Prevalence of diabetes mellitus is increasing worldwide particularly in developing countries as according to International Diabetes Federation, globally a rise from 451 million diabetic people in 2017 to 693 million in 2045 is expected. Diabetic retinopathy is one of the major consequences of diabetes mellitus, so knowing its risk factors can be very helpful. For identifying the risk factors of the Diabetic Retinopathy (DR) in Faisalabad and to determine whether DR is more caused by type 1 or type 2 diabetes, a cross-sectional study was conducted at major hospitals in Faisalabad district during February-July 2016. Descriptive statistics were used for initial screening of the significant variables. Then binary logistic regression was applied to measure the influence of different factors on likelihood of DR. Using Odds Ratio (OR) from logistic regression as measure of influence, the problem of DR was found to be higher among males (OR=1.913; 95% C.I, 1.072~3.413), married patients (OR=5.678; 95% C.I=2.206~14.616), patients with type 1 diabetes (OR=2.195; 95% C.I=1.205~3.997), patients with obesity (OR=25.736; 95% C.I=11.033~60.031), patients using insulin treatment (OR=6.678; 95% C.I=2.330~10.138). The study demonstrated a high prevalence of DR in Faisalabad. Eye examination, social status of patients and duration of diabetes were also found as significant variables affecting DR.

Risk factors of neonatal mortality in Faisalabad, Pakistan.

The objective of study was to find out major correlates of neonatal mortality. The main focus was in determining the impact of different demographic and health related characteristics of neonates and their mothers. A planned questionnaire was prepared in order to collect the information from mothers of newborns. The data were collected from different public and private hospitals of Faisalabad district. Discharge condition of neonate (dead or alive) was taken as response. Binary logistic regression was applied in order to unveil the impact of different contributory factors on the chances of neonatal mortality. Marriage age of mother, age of mother at baby birth, number of pregnancies, time since last birth, antenatal care, delivery mode, gender of baby, baby weight, baby disease and its nature, domestic violence, baby nutrition and residence were found to be significant factors affecting neonatal mortality. Odds ratio was used as a measure of association. From the results, it can be summed up that marriages at optimal ages, lesser frequency of pregnancies, early initiation of mother feeding, increased care during pregnancy to avoid low birth weight and birth time diseases, and increased facilities of antenatal care in rural areas can effectively reduce the neonatal mortality rates.

Characterization of a salt resistant bacterial strain Proteus sp. NA6 capable of decolorizing reactive dyes in presence of multi-metal stress.

Microbial biotechnologies for the decolorization of textile wastewaters have attracted worldwide attention because of their economic suitability and easiness in handling. However, the presence of high amounts of salts and metal ions in textile wastewaters adversely affects the decolorization efficiency of the microbial bioresources. In this regard, the present study was conducted to isolate salt tolerant bacterial strains which might have the potential to decolorize azo dyes even in the presence of multi-metal ion mixtures. Out of the tested 48 bacteria that were isolated from an effluent drain, the strain NA6 was found relatively more efficient in decolorizing the reactive yellow-2 (RY2) dye in the presence of 50 g L(-1) NaCl. Based on the similarity of its 16S rRNA gene sequence and its position in a phylogenetic tree, this strain was designated as Proteus sp. NA6. The strain NA6 showed efficient decolorization (>90 %) of RY2 at pH 7.5 in the presence of 50 g L(-1) NaCl under static incubation at 30 °C. This strain also had the potential to efficiently decolorize other structurally related azo dyes in the presence of 50 g L(-1) NaCl. Moreover, Proteus sp. NA6 was found to resist the presence of different metal ions (Co(+2), Cr(+6), Zn(+2), Pb(+2), Cu(+2), Cd(+2)) and was capable of decolorizing reactive dyes in the presence of different levels of the mixtures of these metal ions along with 50 g L(-1) NaCl. Based on the findings of this study, it can be suggested that Proteus sp. NA6 might serve as a potential bioresource for the biotechnologies involving bioremediation of textile wastewaters containing the metal ions and salts.

Efficient estimation of Pareto model: Some modified percentile estimators.

The article proposes three modified percentile estimators for parameter estimation of the Pareto distribution. These modifications are based on median, geometric mean and expectation of empirical cumulative distribution function of first-order statistic. The proposed modified estimators are compared with traditional percentile estimators through a Monte Carlo simulation for different parameter combinations with varying sample sizes. Performance of different estimators is assessed in terms of total mean square error and total relative deviation. It is determined that modified percentile estimator based on expectation of empirical cumulative distribution function of first-order statistic provides efficient and precise parameter estimates compared to other estimators considered. The simulation results were further confirmed using two real life examples where maximum likelihood and moment estimators were also considered.

Survival analysis of heart failure patients: A case study.

This study was focused on survival analysis of heart failure patients who were admitted to Institute of Cardiology and Allied hospital Faisalabad-Pakistan during April-December (2015). All the patients were aged 40 years or above, having left ventricular systolic dysfunction, belonging to NYHA class III and IV. Cox regression was used to model mortality considering age, ejection fraction, serum creatinine, serum sodium, anemia, platelets, creatinine phosphokinase, blood pressure, gender, diabetes and smoking status as potentially contributing for mortality. Kaplan Meier plot was used to study the general pattern of survival which showed high intensity of mortality in the initial days and then a gradual increase up to the end of study. Martingale residuals were used to assess functional form of variables. Results were validated computing calibration slope and discrimination ability of model via bootstrapping. For graphical prediction of survival probability, a nomogram was constructed. Age, renal dysfunction, blood pressure, ejection fraction and anemia were found as significant risk factors for mortality among heart failure patients.