Global validation of the WSES Sepsis Severity Score for patients with complicated intra-abdominal infections: a prospective multicentre study (WISS Study).

BACKGROUND To validate a new practical Sepsis Severity Score for patients with complicated intra-abdominal infections (cIAIs) including the clinical conditions at the admission (severe sepsis/septic shock), the origin of the cIAIs, the delay in source control, the setting of acquisition and any risk factors such as age and immunosuppression. METHODS The WISS study (WSES cIAIs Score Study) is a multicenter observational study underwent in 132 medical institutions worldwide during a four-month study period (October 2014-February 2015). Four thousand five hundred thirty-three patients with a mean age of 51.2 years (range 18-99) were enrolled in the WISS study. RESULTS Univariate analysis has shown that all factors that were previously included in the WSES Sepsis Severity Score were highly statistically significant between those who died and those who survived (p < 0.0001). The multivariate logistic regression model was highly significant (p < 0.0001, R2 = 0.54) and showed that all these factors were independent in predicting mortality of sepsis. Receiver Operator Curve has shown that the WSES Severity Sepsis Score had an excellent prediction for mortality. A score above 5.5 was the best predictor of mortality having a sensitivity of 89.2 %, a specificity of 83.5 % and a positive likelihood ratio of 5.4. CONCLUSIONS WSES Sepsis Severity Score for patients with complicated Intra-abdominal infections can be used on global level. It has shown high sensitivity, specificity, and likelihood ratio that may help us in making clinical decisions.

Endoscopic retrograde cholangiopancreatography for suspected choledocholithiasis : from guidelines to clinical practice

Endoscopic retrograde cholangiopancreatography for suspected choledocholithiasis: From guidelines to clinical practice.

Development of computational and experimental methods for biomass composition and evaluation of its impact in genome-scale models prediction

The use of genome-scale metabolic models has been rapidly increasing in fields such as metabolic engineering. An important part of a metabolic model is the biomass equation since this reaction will ultimately determine the predictive capacity of the model in terms of essentiality and flux distributions. Thus, in order to obtain a reliable metabolic model the biomass precursors and their coefficients must be as precise as possible. Ideally, determination of the biomass composition would be performed experimentally, but when no experimental data are available this is established by approximation to closely related organisms. Computational methods however, can extract some information from the genome such as amino acid and nucleotide compositions. The main objectives of this study were to compare the biomass composition of several organisms and to evaluate how biomass precursor coefficients affected the predictability of several genome-scale metabolic models by comparing predictions with experimental data in literature. For that, the biomass macromolecular composition was experimentally determined and the amino acid composition was both experimentally and computationally estimated for several organisms. Sensitivity analysis studies were also performed with the Escherichia coli iAF1260 metabolic model concerning specific growth rates and flux distributions. The results obtained suggest that the macromolecular composition is conserved among related organisms. Contrasting, experimental data for amino acid composition seem to have no similarities for related organisms. It was also observed that the impact of macromolecular composition on specific growth rates and flux distributions is larger than the impact of amino acid composition, even when data from closely related organisms are used.

Methods to solve the equations of motion

"Series title: Springerbriefs in applied sciences and technology, ISSN 2191-530X"

Detection of the viable myocardium. A perfusion scintigraphic study, before and after coronary bypass surgery in myocardial infarction patients

OBJECTIVE: To compare single-photon-emission computed tomography (SPECT) imaging scans using 201Tl and 99mTc-MIBI in detection of viable myocardium, in regions compromised by infarction. METHODS: Thirty-two (59.3±9.8 years old and 87% male) myocardial infarction patients were studied. All had Q waves on the ECG and left ventricle ejection fraction of <50%. They underwent coronary and left ventricle angiographies and SPECT before (including 201Tl reinjection) and after coronary artery bypass surgery (CABG). Improvement in perfusion observed after surgery was considered the gold standard for myocardial viability. RESULTS: Among 102 studied regions of the heart, there were 40 (39.2%) areas of transient perfusion defects in the conventional protocol with 201Tl and 52 (51.0%) after reinjection. Therefore, 12/62 (19.4%) more viable regions were identified by reinjection. Using 99mTc-MIBI, only 14 (13.7%) regions with transient defects were identified, all of which were seen also in 201Tl protocols. After surgery, 49 of a total of 93 regions analyzed (52.7%) were viable. Sensitivity, specificity, accuracy, positive and negative prediction values were, respectively, 201Tl SPECT scans - 65.3%, 90.9%, 77.4%, 88.9% and 70.2%, reinjection protocol with 201Tl scans - 81.6%, 81.8%, 81.7%, 83.3% and 80.0%; 99mTc-MIBI SPECT scans - 20.4%, 90.9%, 53.8%, 71.4% and 50.6%. Logistic regression demonstrated that the reinjection protocol with 201Tl was the best predictor of viability (P<0.001). CONCLUSION: Our data suggest the election of 201Tl for viability studies, especially when using the reinjection protocol.

A critical evaluation of methods for the reconstruction of tissue-specific models

Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Safety and efficacy of angioplasty with intracoronary stenting in patients with unstable coronary syndromes. Comparison with stable coronary syndromes

OBJECTIVE: To assess safety and efficacy of coronary angioplasty with stent implantation in unstable coronary syndromes. METHODS: Retrospective analysis of in-hospital and late evolution of 74 patients with unstable coronary syndromes (unstable angina or infarction without elevation of the ST segment) undergoing coronary angioplasty with stent placement. These 74 patients were compared with 31 patients with stable coronary syndromes (stable angina or stable silent ischemia) undergoing the same procedure. RESULTS: No death and no need for revascularization of the culprit artery occurred in the in-hospital phase. The incidences of acute non-Q-wave myocardial infarction were 1.4% and 3.2% (p=0.6) in the unstable and stable coronary syndrome groups, respectively. In the late follow-up (11.2±7.5 months), the incidences of these events combined were 5.7% in the unstable coronary syndrome group and 6.9% (p=0.8) in the stable coronary syndrome group. In the multivariate analysis, the only variable with a tendency to significance as an event predictor was diabetes mellitus (p=0.07; OR=5.2; 95% CI=0.9-29.9). CONCLUSION: The in-hospital and late evolutions of patients with unstable coronary syndrome undergoing angioplasty with intracoronary stent implantation are similar to those of the stable coronary syndrome group, suggesting that this procedure is safe and efficacious when performed in unstable coronary syndrome patients.

Predictive value of clinical and electrophysiological variables in patients with chronic chagasic cardiomyopathy and nonsustained ventricular tachycardia

OBJECTIVE: Risk stratification of patients with nonsustained ventricular tachycardia (NSVT) and chronic chagasic cardiomyopathy (CCC). METHODS: Seventy eight patients with CCC and NSVT were consecutively and prospectively studied. All patients underwent to 24-hour Holter monitoring, radioisotopic ventriculography, left ventricular angiography, and electrophysiologic study. With programmed ventricular stimulation. RESULTS: Sustained monomorphic ventricular tachycardia (SMVT) was induced in 25 patients (32%), NSVT in 20 (25.6%) and ventricular fibrillation in 4 (5.1%). In 29 patients (37.2%) no arrhythmia was inducible. During a 55.7-month-follow-up, 22 (28.2%) patients died, 16 due to sudden death, 2 due to nonsudden cardiac death and 4 due to noncardiac death. Logistic regression analysis showed that induction was the independent and main variable that predicted the occurrence of subsequent events and cardiac death (probability of 2.56 and 2.17, respectively). The Mantel-Haenszel chi-square test showed that survival probability was significantly lower in the inducible group than in the noninductible group. The percentage of patients free of events was significantly higher in the noninducible group. CONCLUSION: Induction of SMVT during programmed ventricular stimulation was a predictor of arrhythmia occurrence cardiac death and general mortality in patients with CCC and NSVT.

Prognostic factors of rheumatic mitral stenosis during pregnancy and puerperium

OBJECTIVE: To identifity characteristics associated with complications during pregnancy and puerperium in patients with rheumatic mitral stenosis. METHODS: Forty-one pregnant women (forty-five pregnancies) with mitral stenosis, followed-up from 1991 to 1999 were retrospectively evaluated. Predictor variables: the mitral valve area (MVA), measured by echocardiogram, and functional class (FC) before pregnancy (NYHA criteria).Maternal events: progression of heart failure, need for cardiac surgery or balloon mitral valvulotomy, death, and thromboembolism. Fetal/neonatal events: abortion, fetal or neonatal death, prematurity or low birth weight (<2,500g), and extended stay in the nursery or hospitalization in newborn ICU. RESULTS: The mean ± SD of age of the patients was 28.8±4.6 years. The eventful and uneventful patients were similar in age and percentage of first pregnancies. As compared with the level 1 MVA, the relative risk (RR) of maternal events was 5.5 (95% confidence interval (CI) =0.8-39.7) for level 2 MVA and 11.4 (95% CI=1.7-74.5) for level 3 MVA. The prepregnancy FC (FC > or = II and III versus I) was also associated with a risk for maternal events (RR=2.7; 95% CI=1.4-5.3).MVA and FC were not importantly associated with these events, although a smaller frequency of fetal/neonatal events was observed in patients who had undergone balloon valvulotomy. CONCLUSION: In pregnant women with mitral stenosis, the MVA and the FC are strongly associated with maternal complications but are not associated with fetal/neonatal events. Balloon mitral valvulotomy could have contributed to reducing the risks of fetal/neonatal events in the more symptomatic patients who had to undergo this procedure during pregnancy.

Numerical methods in multibody system dynamics

"Series: Solid mechanics and its applications, vol. 226"

Some predictors of cardiovascular mortality among the elderly population of Botucatu (SP)

OBJECTIVE: To detect factors associated with cardiovascular mortality in the elderly of Botucatu. METHODS: We evaluated 29 variables of interest in a cohort of patients aged ³60 using data from a survey conducted between 1983/84. The elderly cohort was analyzed in 1992 to detect the occurrence of cardiovascular deaths. Survival analysis was performed using the Kaplan-Meier method, the log-rank test, and Cox regression analysis. Three models were adapted for each group of variables, and a final model was chosen from those variables selected from each group. RESULTS: We identified predictor for cardiovascular death according to age for elderly males not supporting the family, not possessing a vehicle, and previous cardiovascular disease. In elderly females, the predictor variables were previous cardiovascular disease and diabetes mellitus. CONCLUSION: Socioeconomic indicators (family heading and vehicle ownerrship) may be added to well stabilished medical factors (diabete mellitus and hypertension to select target groups for programs intended to reduce deaths due to cardiovascular diseases in elderly people.

Validation study of an automated wrist monitor, omron model HEM-608, compared with the standard methods for blood pressure measurement

OBJECTIVE - The aim of our study was to assess the profile of a wrist monitor, the Omron Model HEM-608, compared with the indirect method for blood pressure measurement. METHODS - Our study population consisted of 100 subjects, 29 being normotensive and 71 being hypertensive. Participants had their blood pressure checked 8 times with alternate techniques, 4 by the indirect method and 4 with the Omron wrist monitor. The validation criteria used to test this device were based on the internationally recognized protocols. RESULTS - Our data showed that the Omron HEM-608 reached a classification B for systolic and A for diastolic blood pressure, according to the one protocol. The mean differences between blood pressure values obtained with each of the methods were -2.3 +7.9mmHg for systolic and 0.97+5.5mmHg for diastolic blood pressure. Therefore, we considered this type of device approved according to the criteria selected. CONCLUSION - Our study leads us to conclude that this wrist monitor is not only easy to use, but also produces results very similar to those obtained by the standard indirect method.

Hierarchical modelling of timber reference properties using probabilistic methods: Maximum Likelihood Method, Bayesian Methods and Probability Networks

In recent decades, an increased interest has been evidenced in the research on multi-scale hierarchical modelling in the field of mechanics, and also in the field of wood products and timber engineering. One of the main motivations for hierar-chical modelling is to understand how properties, composition and structure at lower scale levels may influence and be used to predict the material properties on a macroscopic and structural engineering scale. This chapter presents the applicability of statistic and probabilistic methods, such as the Maximum Likelihood method and Bayesian methods, in the representation of timber’s mechanical properties and its inference accounting to prior information obtained in different importance scales. These methods allow to analyse distinct timber’s reference properties, such as density, bending stiffness and strength, and hierarchically consider information obtained through different non, semi or destructive tests. The basis and fundaments of the methods are described and also recommendations and limitations are discussed. The methods may be used in several contexts, however require an expert’s knowledge to assess the correct statistic fitting and define the correlation arrangement between properties.