América Latina: tablas de mortalidad, 1950-2025 = Latin America: life tables, 1950-2025

Publicación bilingüe (Español e inglés)

América Latina: tablas de mortalidad, 1950-2025 = Latin America: life tables, 1950-2025

Publicación bilingüe (Español e inglés)

Preparation of percentile tables through anthropometric, performance, biochemical, hematological, hormonal and psychological parameters in professional soccer players

Introduction: The lack of reference values of anthropometric, performance, biochemical, hematological, hormonal and psychological parameters is an important limitation in the investigations with soccer players. Objective: To elaborate percentile tables to be used as comparison reference for further studies. Methods: 82 professional soccer players were evaluated approximately 30 days after the beginning of the main competition played by their teams. On the first day of evaluation, fast blood samples were collected for measurement of hematological parameters (i.e. erythrocytes, hemoglobin, hematocrit, mean corpuscular volume - MCV, mean corpuscular hemoglobin - MCH, mean corpuscular hemoglobin concentration - MCHC, leukocytes, eosinophils, lymphocytes, monocytes and platelets) and of concentrations of adrenaline, cortisol, creatine kinase, creatinine, norepinephrine, testosterone and urea. Subsequently, the soccer players had their anthropometric characteristics and psychological parameters assessed. In addition, the evaluation of the lactic anaerobic system efficiency was performed on a 400-m track. On the second day, both the alactic anaerobic and aerobic system efficiency was measured. Results: The percentile distribution (P-0, P-15, P-30, P-50, P-70, P-85 e P-100) was used to present the results. Conclusion: The elaboration of the percentile tables can be used as comparison reference for further studies.

La Restless Legs Syndrome aumenta il rischio cardiovascolare e la mortalità a breve termine nei pazienti emodializzati

Abstract Restless legs syndrome (RLS) is a sensori-motor neurological disorder characterzed by paraesthesia, dysaesthesia and irresistibile urge to move the legs especially at night. Its prevalence is much higher among dialysis patients at 12 to 62% compared to 3 to 9% in the general population. In our study we investigated the association between RLS and cardiovascular events risk and laboratory parameters in End-stage kidney disease (ESKD) patients on dialysis. We studied 100 ESKD patients undergoing hemodialysis that were enrolled in an 18-months prospective observational study. The main outcomes were the association of RLS with new cardiovascular events and cardiovascular mortality. RLS affected 31% of the study population. It was associated with female gender, gradual reduction in residual dieresis, lower albumin (P=0.039) and inflammation, but not the dialysis parameters spKt/V and URR. During observation, 47% of patients experienced new cardiovascular events (64.5% with and 39.1% without RLS; P=0.019). Mortality was 20.0% in all patients, 32.3% in those with and 14.5% in patients without RLS (P=0.04). This study confirmed the high prevalence of RLS among dialysis patients and the associations between the severity of RLS and the risk of new cardiovascular events and higher short-term mortality. Abstract Restless legs syndrome (RLS) is a sensori-motor neurological disorder characterzed by paraesthesia, dysaesthesia and irresistibile urge to move the legs especially at night. Its prevalence is much higher among dialysis patients at 12 to 62% compared to 3 to 9% in the general population. In our study we investigated the association between RLS and cardiovascular events risk and laboratory parameters in End-stage kidney disease (ESKD) patients on dialysis. We studied 100 ESKD patients undergoing hemodialysis that were enrolled in an 18-months prospective observational study. The main outcomes were the association of RLS with new cardiovascular events and cardiovascular mortality. RLS affected 31% of the study population. It was associated with female gender, gradual reduction in residual dieresis, lower albumin (P=0.039) and inflammation, but not the dialysis parameters spKt/V and URR. During observation, 47% of patients experienced new cardiovascular events (64.5% with and 39.1% without RLS; P=0.019). Mortality was 20.0% in all patients, 32.3% in those with and 14.5% in patients without RLS (P=0.04). This study confirmed the high prevalence of RLS among dialysis patients and the associations between the severity of RLS and the risk of new cardiovascular events and higher short-term mortality.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 1: data requirements, processing, and analysis

This is the first part of a study investigating a model-based transient calibration process for diesel engines. The motivation is to populate hundreds of parameters (which can be calibrated) in a methodical and optimum manner by using model-based optimization in conjunction with the manual process so that, relative to the manual process used by itself, a significant improvement in transient emissions and fuel consumption and a sizable reduction in calibration time and test cell requirements is achieved. Empirical transient modelling and optimization has been addressed in the second part of this work, while the required data for model training and generalization are the focus of the current work. Transient and steady-state data from a turbocharged multicylinder diesel engine have been examined from a model training perspective. A single-cylinder engine with external air-handling has been used to expand the steady-state data to encompass transient parameter space. Based on comparative model performance and differences in the non-parametric space, primarily driven by a high engine difference between exhaust and intake manifold pressures (ΔP) during transients, it has been recommended that transient emission models should be trained with transient training data. It has been shown that electronic control module (ECM) estimates of transient charge flow and the exhaust gas recirculation (EGR) fraction cannot be accurate at the high engine ΔP frequently encountered during transient operation, and that such estimates do not account for cylinder-to-cylinder variation. The effects of high engine ΔP must therefore be incorporated empirically by using transient data generated from a spectrum of transient calibrations. Specific recommendations on how to choose such calibrations, how many data to acquire, and how to specify transient segments for data acquisition have been made. Methods to process transient data to account for transport delays and sensor lags have been developed. The processed data have then been visualized using statistical means to understand transient emission formation. Two modes of transient opacity formation have been observed and described. The first mode is driven by high engine ΔP and low fresh air flowrates, while the second mode is driven by high engine ΔP and high EGR flowrates. The EGR fraction is inaccurately estimated at both modes, while EGR distribution has been shown to be present but unaccounted for by the ECM. The two modes and associated phenomena are essential to understanding why transient emission models are calibration dependent and furthermore how to choose training data that will result in good model generalization.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 2: modelling and optimization

This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.

Practice Literate Research: Turning the Tables

Researchers complain how difficult it is to get practitioners and policymakers to use research. In contrast, this paper looks at the issues from the perspective of practice, and argues that it is the researcher’s job to become more practice-literate, so that research begins with practice concerns and develops practice-based solutions. The paper explores the relationship between research and practice and suggests that research has insufficiently engaged with the nature of practice and practice knowledge. Using the Salisbury Statement on practice research (Salisbury Statement 2010) the paper offers a definition of practice research and analyses what would be required for an agenda for practice research. Finally the paper proposes five functions for practice research.

The Car Resequencing Problem with Pull-Off Tables

The car sequencing problem determines sequences of different car models launched down a mixed-model assembly line. To avoid work overloads of workforce, car sequencing restricts the maximum occurrence of labor-intensive options, e.g., a sunroof, by applying sequencing rules. We consider this problem in a resequencing context, where a given number of buffers (denoted as pull-off tables) is available for rearranging a stirred sequence. The problem is formalized and suited solution procedures are developed. A lower bound and a dominance rule are introduced which both reduce the running time of our graph approach. Finally, a real-world resequencing setting is investigated.

Pretreatment Tables Predicting Pathologic Stage of Locally Advanced Prostate Cancer

BACKGROUND Pretreatment tables for the prediction of pathologic stage have been published and validated for localized prostate cancer (PCa). No such tables are available for locally advanced (cT3a) PCa. OBJECTIVE To construct tables predicting pathologic outcome after radical prostatectomy (RP) for patients with cT3a PCa with the aim to help guide treatment decisions in clinical practice. DESIGN, SETTING, AND PARTICIPANTS This was a multicenter retrospective cohort study including 759 consecutive patients with cT3a PCa treated with RP between 1987 and 2010. INTERVENTION Retropubic RP and pelvic lymphadenectomy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Patients were divided into pretreatment prostate-specific antigen (PSA) and biopsy Gleason score (GS) subgroups. These parameters were used to construct tables predicting pathologic outcome and the presence of positive lymph nodes (LNs) after RP for cT3a PCa using ordinal logistic regression. RESULTS AND LIMITATIONS In the model predicting pathologic outcome, the main effects of biopsy GS and pretreatment PSA were significant. A higher GS and/or higher PSA level was associated with a more unfavorable pathologic outcome. The validation procedure, using a repeated split-sample method, showed good predictive ability. Regression analysis also showed an increasing probability of positive LNs with increasing PSA levels and/or higher GS. Limitations of the study are the retrospective design and the long study period. CONCLUSIONS These novel tables predict pathologic stage after RP for patients with cT3a PCa based on pretreatment PSA level and biopsy GS. They can be used to guide decision making in men with locally advanced PCa. PATIENT SUMMARY Our study might provide physicians with a useful tool to predict pathologic stage in locally advanced prostate cancer that might help select patients who may need multimodal treatment.