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.

Maternal neurotic symptoms and infants' risk of developing persistent diarrhoea

A previously calculated predictive model for health risk selects infants who suffer 4-5 times more morbidity than their unselected peers. Preliminary results suggested that this risk is related to maternal neurotic symptomatology. To evaluate this hypothesis, 52 consecutive mothers whose infants had a positive predictive score (Group 1) and 52 in whom this was negative (Group 2) were evaluated by means of Goldberg's General Health Questionnaire (GHQ - 30). A total of 41.9% and 20.5% of the mothers in Groups 1 and 2, respectively, scored above 11 points in GHQ-30, established as the cut off point. It is concluded that among poor urban families in Santiago mothers of infants with high risk of persistent diarrhoea have increased frequency of detectable neurotic symptoms. New programs aimed at this type of infant should include psychological support for their mothers.

Otimização dos parâmetros de produção de hidrolisados protéicos enzimáticos utilizando pescado de baixo valor comercial

The enzymatic modification of proteins has been widely studied with the aim of add value to low commercial value fish. The objective of this work was to evaluate and optimize the parameters involved in the production process of an enzymatic protein hydrolyzed with high protein content. The results showed that for Alcalase the most significant parameters were temperature, pH and substrate concentration and for Flavourzyme were pH, substrate concentration and enzyme concentration. It was obtained for Alcalase a predictive model for the recovered nitrogen and for Flavourzyme a predictive model for the hydrolysis degree.

Método QuEChERS para determinação de ocratoxina a e citrinina em arroz e farelo de arroz

The present study was carried out to establish the optimal conditions for performing ochratoxin A (OTA) and citrinin (CIT) extraction using the QuEChERS method in rice. Employing the factorial experimental design, variables that significantly influenced the extraction stages were determined. The following variables were analyzed: addition of water, acidification of acetonitrile with glacial acetic acid, as well as amounts of magnesium sulfate, sodium acetate, sodium citrate and diatomaceous earth. The best combining procedure resulted in a predictive model using more water and less diatomaceous earth. Recoveries of CIT and OTA were 78-105%.

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.

Associations, causation and model in psychiatry

This paper discusses models, associations and causation in psychiatry. The different types of association (linear, positive, negative, exponential, partial, U shaped relationship, hidden and spurious) between variables involved in mental disorders are presented as well as the use of multiple regression analysis to disentangle interrelatedness amongst multiple variables. A useful model should have internal consistency, external validity and predictive power; be dynamic in order to accommodate new sound knowledge; and should fit facts rather than they other way around. It is argued that whilst models are theoretical constructs they also convey a style of reasoning and can change clinical practice. Cause and effect are complex phenomena in that the same cause can yield different effects. Conversely, the same effect can have a different range of causes. In mental disorders and human behaviour there is always a chain of events initiated by the indirect and remote cause; followed by intermediate causes; and finally the direct and more immediate cause. Causes of mental disorders are grouped as those: (i) which are necessary and sufficient; (ii) which are necessary but not sufficient; and (iii) which are neither necessary nor sufficient, but when present increase the risk for mental disorders.

Predictive factors of in-hospital mortality and of severe perioperative complications in myocardial revascularization surgery

OBJECTIVE: To investigate preoperative predictive factors of severe perioperative intercurrent events and in-hospital mortality in coronary artery bypass graft (CABG) surgery and to develop specific models of risk prediction for these events, mainly those that can undergo changes in the preoperative period. METHODS: We prospectively studied 453 patients who had undergone CABG. Factors independently associated with the events of interest were determined with multiple logistic regression and Cox proportional hazards regression model. RESULTS: The mortality rate was 11.3% (51/453), and 21.2% of the patients had 1 or more perioperative intercurrent events. In the final model, the following variables remained associated with the risk of intercurrent events: age ³ 70 years, female sex, hospitalization via SUS (Sistema Único de Saúde - the Brazilian public health system), cardiogenic shock, ischemia, and dependence on dialysis. Using multiple logistic regression for in-hospital mortality, the following variables participated in the model of risk prediction: age ³ 70 years, female sex, hospitalization via SUS, diabetes, renal dysfunction, and cardiogenic shock. According to the Cox regression model for death within the 7 days following surgery, the following variables remained associated with mortality: age ³ 70 years, female sex, cardiogenic shock, and hospitalization via SUS. CONCLUSION: The aspects linked to the structure of the Brazilian health system, such as factors of great impact on the results obtained, indicate that the events investigated also depend on factors that do not relate to the patient's intrinsic condition.

Predictive factors of complications after coronary stent implantation

OBJECTIVE: To analyze the predictive factors of complications after implantation of coronary stents in a consecutive cohort study. METHODS: Clinical and angiographic characteristics related to the procedure were analyzed, and the incidence of major cardiovascular complications (myocardial infarction, urgent surgery, new angioplasty, death) in the in-hospital phase were recorded. Data were stored in an Access database and analyzed by using the SPSS 6.0 statistical program and a stepwise backwards multiple logistic regression model. RESULTS: One thousand eighteen (mean age of 61±11 years, 29% females) patients underwent 1,070 stent implantations. The rate of angiographic success was 96.8%, the rate of clinical success was 91%, and the incidence of major cardiovascular complications was 7.9%. The variables independently associated with major cardiovascular complications, with their respective odds ratio (OR) were: rescue stent, OR = 5.1 (2.7-9.6); filamentary stent, OR = 4.5 (2.2-9.1); first-generation tubular stent, OR = 2.4 (1.2-4.6); multiple stents, OR = 3 (1.6-5.6); complexity of the lesion, OR = 2.4 (1.1-5.1); thrombus, OR = 2 (1.1-3.5). CONCLUSION: The results stress the importance of angiographic variables and techniques in the risk of complications and draw attention to the influence of the stent's design on the result of the procedure.

Survival and Predictive Factors of Lethality in Hemodyalisis: D/I Polymorphism of The Angiotensin I-Converting Enzyme and of the Angiotensinogen M235T Genes

Background: End-stage kidney disease patients continue to have markedly increased cardiovascular disease morbidity and mortality. Analysis of genetic factors connected with the renin-angiotensin system that influences the survival of the patients with end-stage kidney disease supports the ongoing search for improved outcomes. Objective: To assess survival and its association with the polymorphism of renin-angiotensin system genes: angiotensin I-converting enzyme insertion/deletion and angiotensinogen M235T in patients undergoing hemodialysis. Methods: Our study was designed to examine the role of renin-angiotensin system genes. It was an observational study. We analyzed 473 chronic hemodialysis patients in four dialysis units in the state of Rio de Janeiro. Survival rates were calculated by the Kaplan-Meier method and the differences between the curves were evaluated by Tarone-Ware, Peto-Prentice, and log rank tests. We also used logistic regression analysis and the multinomial model. A p value ≤ 0.05 was considered to be statistically significant. The local medical ethics committee gave their approval to this study. Results: The mean age of patients was 45.8 years old. The overall survival rate was 48% at 11 years. The major causes of death were cardiovascular diseases (34%) and infections (15%). Logistic regression analysis found statistical significance for the following variables: age (p = 0.000038), TT angiotensinogen (p = 0.08261), and family income greater than five times the minimum wage (p = 0.03089), the latter being a protective factor. Conclusions: The survival of hemodialysis patients is likely to be influenced by the TT of the angiotensinogen M235T gene.

Development and Validation of Predictive Models of Cardiac Mortality and Transplantation in Resynchronization Therapy

AbstractBackground:30-40% of cardiac resynchronization therapy cases do not achieve favorable outcomes.Objective:This study aimed to develop predictive models for the combined endpoint of cardiac death and transplantation (Tx) at different stages of cardiac resynchronization therapy (CRT).Methods:Prospective observational study of 116 patients aged 64.8 ± 11.1 years, 68.1% of whom had functional class (FC) III and 31.9% had ambulatory class IV. Clinical, electrocardiographic and echocardiographic variables were assessed by using Cox regression and Kaplan-Meier curves.Results:The cardiac mortality/Tx rate was 16.3% during the follow-up period of 34.0 ± 17.9 months. Prior to implantation, right ventricular dysfunction (RVD), ejection fraction < 25% and use of high doses of diuretics (HDD) increased the risk of cardiac death and Tx by 3.9-, 4.8-, and 5.9-fold, respectively. In the first year after CRT, RVD, HDD and hospitalization due to congestive heart failure increased the risk of death at hazard ratios of 3.5, 5.3, and 12.5, respectively. In the second year after CRT, RVD and FC III/IV were significant risk factors of mortality in the multivariate Cox model. The accuracy rates of the models were 84.6% at preimplantation, 93% in the first year after CRT, and 90.5% in the second year after CRT. The models were validated by bootstrapping.Conclusion:We developed predictive models of cardiac death and Tx at different stages of CRT based on the analysis of simple and easily obtainable clinical and echocardiographic variables. The models showed good accuracy and adjustment, were validated internally, and are useful in the selection, monitoring and counseling of patients indicated for CRT.

A temperature predicting model for manufacturing processes requiring coiling

A model for predicting temperature evolution for automatic controling systems in manufacturing processes requiring the coiling of bars in the transfer table is presented. Although the method is of a general nature, the presentation in this work refers to the manufacturing of steel plates in hot rolling mills. The predicting strategy is based on a mathematical model of the evolution of temperature in a coiling and uncoiling bar and is presented in the form of a parabolic partial differential equation for a shape changing domain. The mathematical model is solved numerically by a space discretization via geometrically adaptive finite elements which accomodate the change in shape of the domain, using a computationally novel treatment of the resulting thermal contact problem due to coiling. Time is discretized according to a Crank-Nicolson scheme. Since the actual physical process takes less time than the time required by the process controlling computer to solve the full mathematical model, a special predictive device was developed, in the form of a set of least squares polynomials, based on the off-line numerical solution of the mathematical model.

Hypomagnesemia in critically ill cancer patients: a prospective study of predictive factors

Hypomagnesemia is the most common electrolyte disturbance seen upon admission to the intensive care unit (ICU). Reliable predictors of its occurrence are not described. The objective of this prospective study was to determine factors predictive of hypomagnesemia upon admission to the ICU. In a single tertiary cancer center, 226 patients with different diagnoses upon entering were studied. Hypomagnesemia was defined by serum levels <1.5 mg/dl. Demographic data, type of cancer, cause of admission, previous history of arrhythmia, cardiovascular disease, renal failure, drug administration (particularly diuretics, antiarrhythmics, chemotherapy and platinum compounds), previous nutrition intake and presence of hypovolemia were recorded for each patient. Blood was collected for determination of serum magnesium, potassium, sodium, calcium, phosphorus, blood urea nitrogen and creatinine levels. Upon admission, 103 (45.6%) patients had hypomagnesemia and 123 (54.4%) had normomagnesemia. A normal dietary habit prior to ICU admission was associated with normal Mg levels (P = 0.007) and higher average levels of serum Mg (P = 0.002). Postoperative patients (N = 182) had lower levels of serum Mg (0.60 ± 0.14 mmol/l compared with 0.66 ± 0.17 mmol/l, P = 0.006). A stepwise multiple linear regression disclosed that only normal dietary habits (OR = 0.45; CI = 0.26-0.79) and the fact of being a postoperative patient (OR = 2.42; CI = 1.17-4.98) were significantly correlated with serum Mg levels (overall model probability = 0.001). These findings should be used to identify patients at risk for such disturbance, even in other critically ill populations.

Evaluation of a new mathematical model to describe Clostridium perfringens growth during the cooling of cooked ground beef

A mathematical model previously developed to study microbial growth in food products under an isothermal environment was adapted to a time-varying temperature regime. The resulting model was applied to study the growth of Clostridium perfringens in meat products. This micro-organism is of particular relevance to public health and economy due to the loss of productivity caused by it. Results showed a similar performance of the model used compared to the Baranyi model under an isothermal situation and a slightly better performance under a non-isothermal temperature profile.