Viscosity and self-diffusion coefficients of dialkyl adipates: a correlation scheme with predictive capabilities

A correlation and predictive scheme for the viscosity and self-diffusivity of liquid dialkyl adipates is presented. The scheme is based on the kinetic theory for dense hard-sphere fluids, applied to the van der Waals model of a liquid to predict the transport properties. A "universal" curve for a dimensionless viscosity of dialkyl adipates was obtained using recently published experimental viscosity and density data of compressed liquid dimethyl (DMA), dipropyl (DPA), and dibutyl (DBA) adipates. The experimental data are described by the correlation scheme with a root-mean-square deviation of +/- 0.34 %. The parameters describing the temperature dependence of the characteristic volume, V-0, and the roughness parameter, R-eta, for each adipate are well correlated with one single molecular parameter. Recently published experimental self-diffusion coefficients of the same set of liquid dialkyl adipates at atmospheric pressure were correlated using the characteristic volumes obtained from the viscosity data. The roughness factors, R-D, are well correlated with the same single molecular parameter found for viscosity. The root-mean-square deviation of the data from the correlation is less than 1.07 %. Tests are presented in order to assess the capability of the correlation scheme to estimate the viscosity of compressed liquid diethyl adipate (DEA) in a range of temperatures and pressures by comparison with literature data and of its self-diffusivity at atmospheric pressure in a range of temperatures. It is noteworthy that no data for DEA were used to build the correlation scheme. The deviations encountered between predicted and experimental data for the viscosity and self-diffusivity do not exceed 2.0 % and 2.2 %, respectively, which are commensurate with the estimated experimental measurement uncertainty, in both cases.

Predictive Biomarkers of Bacillus Calmette-Gu´erin Immunotherapy Response in Bladder Cancer: Where AreWe Now?

The most effective therapeutic option for managing nonmuscle invasive bladder cancer (NMIBC), over the last 30 years, consists of intravesical instillations with the attenuated strain Bacillus Calmette-Gu´erin (the BCG vaccine). This has been performed as an adjuvant therapeutic to transurethral resection of bladder tumour (TURBT) and mostly directed towards patients with highgrade tumours, T1 tumours, and in situ carcinomas. However, from 20% to 40% of the patients do not respond and frequently present tumour progression. Since BCG effectiveness is unpredictable, it is important to find consistent biomarkers that can aid either in the prediction of the outcome and/or side effects development. Accordingly, we conducted a systematic critical review to identify themost preeminent predictive molecular markers associated with BCG response. To the best of our knowledge, this is the first review exclusively focusing on predictive biomarkers for BCG treatment outcome. Using a specific query, 1324 abstracts were gathered, then inclusion/exclusion criteria were applied, and finally 87 manuscripts were included. Several molecules, including CD68 and genetic polymorphisms, have been identified as promising surrogate biomarkers. Combinatory analysis of the candidate predictive markers is a crucial step to create a predictive profile of treatment response.

Predictive factors for response to Lamivudine in chronic hepatitis B

BACKGROUND: Lamivudine has been shown to be an efficient drug for chronic hepatitis B (CHB) treatment. AIM: To investigate predictive factors of response, using a quantitative method with high sensitivity. METHODS: We carried out a prospective trial of lamivudine in 35 patients with CHB and evidence for viral replication, regardless to their HBeAg status. Lamivudine was given for 12 months at 300 mg daily and 150 mg thereafter. Response was considered when DNA was undetectable by PCR after 6 months of treatment. Viral replication was monitored by end-point dilution PCR. Mutation associated with resistance to lamivudine was detected by DNA sequencing in non-responder patients. RESULTS: Response was observed in 23/35 patients (65.7%) but only in 5/15 (33.3%) HBeAg positive patients. Only three pre-treatment variables were associated to low response: HBeAg (p = 0.006), high viral load (DNA-VHB > 3 x 10(6) copies/ml) (p = 0.004) and liver HBcAg (p = 0.0028). YMDD mutations were detected in 7/11 non-responder patients. CONCLUSIONS: HBeAg positive patients with high viral load show a high risk for developing drug resistance. On the other hand, HBeAg negative patients show a good response to lamivudine even with high viremia.

Predictive Variables Affecting Transfusion Requirements in Orthotopic Liver Transplantation

INTRODUCTION AND AIMS: Adult orthotopic liver transplantation (OLT) is associated with considerable blood product requirements. The aim of this study was to assess the ability of preoperative information to predict intraoperative red blood cell (RBC) transfusion requirements among adult liver recipients. METHODS: Preoperative variables with previously demonstrated relationships to intraoperative RBC transfusion were identified from the literature: sex, age, pathology, prothrombin time (PT), factor V, hemoglobin (Hb), and platelet count (plt). These variables were then retrospectively collected from 758 consecutive adult patients undergoing OLT from 1997 to 2007. Relationships between these variables and intraoperative blood transfusion requirements were examined by both univariate analysis and multiple linear regression analysis. RESULTS: Univariate analysis confirmed significant associations between RBC transfusion and PT, factor V, Hb, Plt, pathology, and age (P values all < .001). However, stepwise backward multivariate analysis excluded variables Plt and factor V from the multiple regression linear model. The variables included in the final predictive model were PT, Hb, age, and pathology. Patients suffering from liver carcinoma required more blood products than those suffering from other pathologies. Yet, the overall predictive power of the final model was limited (R(2) = .308; adjusted R(2) = .30). CONCLUSION: Preoperative variables have limited predictive power for intraoperative RBC transfusion requirements even when significant statistical associations exist, identifying only a small portion of the observed total transfusion variability. Preoperative PT, Hb, age, and liver pathology seem to be the most significant predictive factors but other factors like severity of liver disease, surgical technique, medical experience in liver transplantation, and other noncontrollable human variables may play important roles to determine the final transfusion requirements.

Predictive factors of mortality in burn patients

Burn mortality statistics may be misleading unless they account properly for the many factors that can influence outcome. Such estimates are useful for patients and others making medical and financial decisions concerning their care. This study aimed to define the clinical, microbiological and laboratorial predictors of mortality with a view to focus on better burn care. Data were collected using independent variables, which were analyzed sequentially and cumulatively, employing univariate statistics and a pooled, cross-sectional, multivariate logistic regression to establish which variables better predict the probability of mortality. Survivors and non-survivors among burn patients were compared to define the predictive factors of mortality. Mortality rate was 5.0%. Higher age, larger burn area, presence of fungi in the wound, shorter length of stay and the presence of multi-resistant bacteria in the wound significantly predicted increased mortality. The authors conclude that those patients who are most apt to die are those with age > 50 years, with limited skin donor sites and those with multi-resistant bacteria and fungi in the wound.

PREDICTIVE FACTORS FOR THE PROGRESSION OF CHRONIC CHAGAS CARDIOMYOPATHY IN PATIENTS WITHOUT LEFT VENTRICULAR DYSFUNCTION

The identification of predictors for the progression of chronic Chagas cardiomyopathy (CCC) is essential to ensure adequate patient management. This study looked into a non-concurrent cohort of 165 CCC patients between 1985 and 2010 for independent predictors for CCC progression. The outcomes were worsening of the CCC scores and the onset of left ventricular dysfunction assessed by means of echo-Doppler cardiography. Patients were analyzed for social, demographic, epidemiologic, clinical and workup-related variables. A descriptive analysis was conducted, followed by survival curves based on univariate (Kaplan-Meier and Cox’s univariate model) and multivariate (Cox regression model) analysis. Patients were followed from two to 20 years (mean: 8.2). Their mean age was 44.8 years (20-77). Comparing both iterations of the study, in the second there was a statistically significant increase in the PR interval and in the QRS duration, despite a reduction in heart rates (Wilcoxon < 0.01). The predictors for CCC progression in the final regression model were male gender (HR = 2.81), Holter monitoring showing pauses equal to or greater than two seconds (HR = 3.02) increased cardiothoracic ratio (HR = 7.87) and time of use of digitalis (HR = 1.41). Patients with multiple predictive factors require stricter follow-up and treatment.

Acute Kidney Injury after Pediatric Cardiac Surgery: Risk Factors and Outcomes. Proposal for a Predictive Model

Objectives: To characterize the epidemiology and risk factors for acute kidney injury (AKI) after pediatric cardiac surgery in our center, to determine its association with poor short-term outcomes, and to develop a logistic regression model that will predict the risk of AKI for the study population. Methods: This single-center, retrospective study included consecutive pediatric patients with congenital heart disease who underwent cardiac surgery between January 2010 and December 2012. Exclusion criteria were a history of renal disease, dialysis or renal transplantation. Results: Of the 325 patients included, median age three years (1 day---18 years), AKI occurred in 40 (12.3%) on the first postoperative day. Overall mortality was 13 (4%), nine of whom were in the AKI group. AKI was significantly associated with length of intensive care unit stay, length of mechanical ventilation and in-hospital death (p<0.01). Patients’ age and postoperative serum creatinine, blood urea nitrogen and lactate levels were included in the logistic regression model as predictor variables. The model accurately predicted AKI in this population, with a maximum combined sensitivity of 82.1% and specificity of 75.4%. Conclusions: AKI is common and is associated with poor short-term outcomes in this setting. Younger age and higher postoperative serum creatinine, blood urea nitrogen and lactate levels were powerful predictors of renal injury in this population. The proposed model could be a useful tool for risk stratification of these patients.

Exploring the predictive power of Google searches over the US stock market

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Predictive analytical and numerical modeling for orthogonal cutting

In this thesis, a predictive analytical and numerical modeling approach for the orthogonal cutting process is proposed to calculate temperature distributions and subsequently, forces and stress distributions. The models proposed include a constitutive model for the material being cut based on the work of Weber, a model for the shear plane based on Merchants model, a model describing the contribution of friction based on Zorev’s approach, a model for the effect of wear on the tool based on the work of Waldorf, and a thermal model based on the works of Komanduri and Hou, with a fraction heat partition for a non-uniform distribution of the heat in the interfaces, but extended to encompass a set of contributions to the global temperature rise of chip, tool and work piece. The models proposed in this work, try to avoid from experimental based values or expressions, and simplifying assumptions or suppositions, as much as possible. On a thermo-physical point of view, the results were affected not only by the mechanical or cutting parameters chosen, but also by their coupling effects, instead of the simplifying way of modeling which is to contemplate only the direct effect of the variation of a parameter. The implementation of these models was performed using the MATLAB environment. Since it was possible to find in the literature all the parameters for AISI 1045 and AISI O2, these materials were used to run the simulations in order to avoid arbitrary assumption.

Predictive markers for hepatitis C virus infection among Brazilian inmates

Hepatitis C virus (HCV) infection has quite high prevalence in the prison system, reaching rates of up to 40%. This survey aimed to estimate the prevalence of HCV infection and evaluate risk factors for this exposure among male inmates at the Ribeirão Preto Prison, State of São Paulo, Brazil, between May and August 2003. A total of 333 participants were interviewed using a standardized questionnaire and underwent immunoenzymatic assaying to investigate anti-HCV. The prevalence of HCV infection among the inmates was 8.7% (95% CI: 5.7-11.7). The participants'mean age was 30.1 years, and the prevalence was predominantly among individuals over 30 years of age. Multivariate analysis showed that the variables that were independently associated with HCV infection were age > 30 years, tattooing, history of previous hepatitis, previous injection drug use and previous needle-sharing.

Predictive factors of post-discharge surgical site infections among patients from a teaching hospital

Introduction Surgical site infections (SSIs) often manifest after patients are discharged and are missed by hospital-based surveillance. Methods We conducted a case-reference study nested in a prospective cohort of patients from six surgical specialties in a teaching hospital. The factors related to SSI were compared for cases identified during the hospital stay and after discharge. Results Among 3,427 patients, 222 (6.4%) acquired an SSI. In 138 of these patients, the onset of the SSI occurred after discharge. Neurological surgery and the use of steroids were independently associated with a greater likelihood of SSI diagnosis during the hospital stay. Conclusions Our results support the idea of a specialty-based strategy for post-discharge SSI surveillance.

Evaluation of the predictive indices for candidemia in an adult intensive care unit

INTRODUCTION: To evaluate predictive indices for candidemia in an adult intensive care unit (ICU) and to propose a new index. METHODS: A prospective cohort study was conducted between January 2011 and December 2012. This study was performed in an ICU in a tertiary care hospital at a public university and included 114 patients staying in the adult ICU for at least 48 hours. The association of patient variables with candidemia was analyzed. RESULTS: There were 18 (15.8%) proven cases of candidemia and 96 (84.2%) cases without candidemia. Univariate analysis revealed the following risk factors: parenteral nutrition, severe sepsis, surgical procedure, dialysis, pancreatitis, acute renal failure, and an APACHE II score higher than 20. For the Candida score index, the odds ratio was 8.50 (95% CI, 2.57 to 28.09); the sensitivity, specificity, positive predictive value, and negative predictive value were 0.78, 0.71, 0.33, and 0.94, respectively. With respect to the clinical predictor index, the odds ratio was 9.45 (95%CI, 2.06 to 43.39); the sensitivity, specificity, positive predictive value, and negative predictive value were 0.89, 0.54, 0.27, and 0.96, respectively. The proposed candidemia index cutoff was 8.5; the sensitivity, specificity, positive predictive value, and negative predictive value were 0.77, 0.70, 0.33, and 0.94, respectively. CONCLUSIONS: The Candida score and clinical predictor index excluded candidemia satisfactorily. The effectiveness of the candidemia index was comparable to that of the Candida score.

Predictive factors for Leishmania infantum infection in dogs examined at a veterinary teaching hospital in Teresina, State of Piauí, Brazil

Abstract: INTRODUCTION: In Brazil, culling of seropositive dogs is one of the recommended strategies to control visceral leishmaniasis. Since infectiousness is correlated with clinical signs, control measures targeting symptomatic dogs could be more effective. METHODS: A cross-sectional study was carried out among 1,410 dogs, predictive models were developed based on clinical signs and an indirect immunofluorescence antibody test. RESULTS: The validated predictive model showed sensitivity and specificity of 86.5% and 70.0%, respectively. CONCLUSIONS: Predictive models could be used as tools to aid control programs in focusing on a smaller fraction of dogs contributing more to infection dissemination.

Predictive value of the ankle-brachial index in the evaluation of intermittent claudication

The purpose of this study was to determine whether the ankle-brachial index (ABI) could be used to predict the prognosis for a patient with intermittent claudication (IC). We studied 611 patients prospectively during 28 months of follow-up. We analyzed the predictive power of using various levels of ABI - 0.30 to 0.70 at 0.05 increments - in terms of the measure's specificity (association with a favorable outcome after exercise rehabilitation therapy) and sensitivity (association with a poor outcome after exercise rehabilitation therapy). We found that using an ABI of 0.30 as a cut-off value produced the lowest margin of error overall, but the predictive power was still low with respect to identifying the patients with a poor prognosis after non-aggressive therapeutic treatment. Further study is needed to perhaps identify a second factor that could increase the sensitivity of the test.