Uromodulin, kidney function, cardiovascular disease, and mortality

Uromodulin (Tamm-Horsfall protein) is exclusively produced by the kidney and is the most abundant protein excreted in normal urine. The level of uromodulin in urine could represent a useful biomarker for renal tubular function. The study of Garimella et al. adds elements into the debate, by suggesting that, in elderly adults, low urinary uromodulin concentrations in spot urine identify people at risk of progressive kidney disease and mortality above and beyond established markers of kidney disease.

Weather and cardiovascular mortality.

Already in ancient Greece, Hippocrates postulated that disease showed a seasonal pattern characterised by excess winter mortality. Since then, several studies have confirmed this finding, and it was generally accepted that the increase in winter mortality was mostly due to respiratory infections and seasonal influenza. More recently, it was shown that cardiovascular disease (CVD) mortality also displayed such seasonality, and that the magnitude of the seasonal effect increased from the poles to the equator. The recent study by Yang et al assessed CVD mortality attributable to ambient temperature using daily data from 15 cities in China for years 2007-2013, including nearly two million CVD deaths. A high temperature variability between and within cities can be observed (figure 1). They used sophisticated statistical methodology to account for the complex temperature-mortality relationship; first, distributed lag non-linear models combined with quasi-Poisson regression to obtain city-specific estimates, taking into account temperature, relative humidity and atmospheric pressure; then, a meta-analysis to obtain the pooled estimates. The results confirm the winter excess mortality as reported by the Eurowinter3 and other4 groups, but they show that the magnitude of ambient temperature.

The ADO Index as a Predictor of Two-Year Mortality in General Practice-Based Chronic Obstructive Pulmonary Disease Cohorts.

BACKGROUND: Existing prediction models for mortality in chronic obstructive pulmonary disease (COPD) patients have not yet been validated in primary care, which is where the majority of patients receive care. OBJECTIVES: Our aim was to validate the ADO (age, dyspnoea, airflow obstruction) index as a predictor of 2-year mortality in 2 general practice-based COPD cohorts. METHODS: Six hundred and forty-six patients with COPD with GOLD (Global Initiative for Chronic Obstructive Lung Disease) stages I-IV were enrolled by their general practitioners and followed for 2 years. The ADO regression equation was used to predict a 2-year risk of all-cause mortality in each patient and this risk was compared with the observed 2-year mortality. Discrimination and calibration were assessed as well as the strength of association between the 15-point ADO score and the observed 2-year all-cause mortality. RESULTS: Fifty-two (8.1%) patients died during the 2-year follow-up period. Discrimination with the ADO index was excellent with an area under the curve of 0.78 [95% confidence interval (CI) 0.71-0.84]. Overall, the predicted and observed risks matched well and visual inspection revealed no important differences between them across 10 risk classes (p = 0.68). The odds ratio for death per point increase according to the ADO index was 1.50 (95% CI 1.31-1.71). CONCLUSIONS: The ADO index showed excellent prediction properties in an out-of-population validation carried out in COPD patients from primary care settings. © 2014 S. Karger AG, Basel.

Prognostication of Mortality in Critically Ill Patients With Severe Infections.

BACKGROUND: The purpose of this study was to confirm the prognostic value of pancreatic stone protein (PSP) in patients with severe infections requiring ICU management and to develop and validate a model to enhance mortality prediction by combining severity scores with biomarkers. METHODS: We enrolled prospectively patients with severe sepsis or septic shock in mixed tertiary ICUs in Switzerland (derivation cohort) and Brazil (validation cohort). Severity scores (APACHE [Acute Physiology and Chronic Health Evaluation] II or Simplified Acute Physiology Score [SAPS] II) were combined with biomarkers obtained at the time of diagnosis of sepsis, including C-reactive-protein, procalcitonin (PCT), and PSP. Logistic regression models with the lowest prediction errors were selected to predict in-hospital mortality. RESULTS: Mortality rates of patients with septic shock enrolled in the derivation cohort (103 out of 158) and the validation cohort (53 out of 91) were 37% and 57%, respectively. APACHE II and PSP were significantly higher in dying patients. In the derivation cohort, the models combining either APACHE II, PCT, and PSP (area under the receiver operating characteristic curve [AUC], 0.721; 95% CI, 0.632-0.812) or SAPS II, PCT, and PSP (AUC, 0.710; 95% CI, 0.617-0.802) performed better than each individual biomarker (AUC PCT, 0.534; 95% CI, 0.433-0.636; AUC PSP, 0.665; 95% CI, 0.572-0.758) or severity score (AUC APACHE II, 0.638; 95% CI, 0.543-0.733; AUC SAPS II, 0.598; 95% CI, 0.499-0.698). These models were externally confirmed in the independent validation cohort. CONCLUSIONS: We confirmed the prognostic value of PSP in patients with severe sepsis and septic shock requiring ICU management. A model combining severity scores with PCT and PSP improves mortality prediction in these patients.

Risk of All-Cause Mortality in Alcohol-Dependent Individuals: A Systematic Literature Review and Meta-Analysis.

BACKGROUND: Alcohol dependence (AD) carries a high mortality burden, which may be mitigated by reduced alcohol consumption. We conducted a systematic literature review and meta-analysis investigating the risk of all-cause mortality in alcohol-dependent subjects. METHODS: MEDLINE, MEDLINE In-Process, Embase and PsycINFO were searched from database conception through 26th June 2014. Eligible studies reported all-cause mortality in both alcohol-dependent subjects and a comparator population of interest. Two individuals independently reviewed studies. Of 4540 records identified, 39 observational studies were included in meta-analyses. FINDINGS: We identified a significant increase in mortality for alcohol-dependent subjects compared with the general population (27 studies; relative risk [RR] = 3.45; 95% CI [2.96, 4.02]; p < 0.0001). The mortality increase was also significant compared to subjects qualifying for a diagnosis of alcohol abuse or subjects without alcohol use disorders (AUDs). Alcohol-dependent subjects continuing to drink heavily had significantly greater mortality than alcohol-dependent subjects who reduced alcohol intake, even if abstainers were excluded (p < 0.05). INTERPRETATION: AD was found to significantly increase an individual's risk of all-cause mortality. While abstinence in alcohol-dependent subjects led to greater mortality reduction than non-abstinence, this study suggests that alcohol-dependent subjects can significantly reduce their mortality risk by reducing alcohol consumption.

European cancer mortality predictions for the year 2016 with focus on leukemias.

BACKGROUND: Current cancer mortality statistics are important for public health decision making and resource allocation. Age standardized rates and numbers of deaths are predicted for 2016 in the European Union. PATIENTS AND METHODS: Population and death certification data for stomach, colorectum, pancreas, lung, breast, uterus, prostate, leukemia and total cancers were obtained from the World Health Organisation database and Eurostat. Figures were derived for the EU, France, Germany, Italy, Poland, Spain and the UK. Projected numbers of deaths by age group were obtained for 2016 by linear regression on estimated numbers of deaths over the most recent time period identified by a joinpoint regression model. RESULTS: Projected total cancer mortality trends for 2016 in the EU are favourable in both sexes with rates of 133.5/100,000 men and 85.2/100,000 women (8% and 3% falls since 2011, due to population ageing) corresponding to 753,600 and 605,900 deaths in men and women for a total number of 1,359,500 projected cancer deaths (+3% compared to 2011). In men lung, colorectal and prostate cancer fell 11%, 5% and 8% since 2011. Breast and colorectal cancer trends in women are favourable (8% and 7% falls, respectively), but lung and Pancreatic cancer rates rose 5% and 4% since 2011 reaching rates of 14.4 and 5.6/100,000 women. Leukemia shows favourable projected mortality for both sexes and all age groups with stronger falls in the younger age groups, rates are 4.0/100,000 men and 2.5/100,000 women, with respectively falls of 14% and 12%. CONCLUSION: The 2016 predictions for EU cancer mortality confirm the favourable trends in rates particularly for men. Lung cancer is likely to remain the leading site for female cancer rates. Continuing falls in mortality, larger in children and young adults, are predicted in leukemia, essentially due to advancements in management and therapy, and their subsequent adoption across Europe.

Social differences in avoidable mortality between small areas of 15 European cities: an ecological study

Health and inequalities in health among inhabitants of European cities are of major importance for European public health and there is great interest in how different health care systems in Europe perform in the reduction of health inequalities. However, evidence on the spatial distribution of cause-specific mortality across neighbourhoods of European cities is scarce. This study presents maps of avoidable mortality in European cities and analyses differences in avoidable mortality between neighbourhoods with different levels of deprivation. Methods: We determined the level of mortality from 14 avoidable causes of death for each neighbourhood of 15 large cities in different European regions. To address the problems associated with Standardised Mortality Ratios for small areas we smooth them using the Bayesian model proposed by Besag, York and Mollié. Ecological regression analysis was used to assess the association between social deprivation and mortality. Results: Mortality from avoidable causes of death is higher in deprived neighbourhoods and mortality rate ratios between areas with different levels of deprivation differ between gender and cities. In most cases rate ratios are lower among women. While Eastern and Southern European cities show higher levels of avoidable mortality, the association of mortality with social deprivation tends to be higher in Northern and lower in Southern Europe. Conclusions: There are marked differences in the level of avoidable mortality between neighbourhoods of European cities and the level of avoidable mortality is associated with social deprivation. There is no systematic difference in the magnitude of this association between European cities or regions. Spatial patterns of avoidable mortality across small city areas can point to possible local problems and specific strategies to reduce health inequality which is important for the development of urban areas and the well-being of their inhabitants

Combining Advanced Forecasting Methods with System Dynamics - the Case of Finnish Seaports

Seaports play an important part in the wellbeing of a nation. Many nations are highly dependent on foreign trade and most trade is done using sea vessels. This study is part of a larger research project, where a simulation model is required in order to create further analyses on Finnish macro logistical networks. The objective of this study is to create a system dynamic simulation model, which gives an accurate forecast for the development of demand of Finnish seaports up to 2030. The emphasis on this study is to show how it is possible to create a detailed harbor demand System Dynamic model with the help of statistical methods. The used forecasting methods were ARIMA (autoregressive integrated moving average) and regression models. The created simulation model gives a forecast with confidence intervals and allows studying different scenarios. The building process was found to be a useful one and the built model can be expanded to be more detailed. Required capacity for other parts of the Finnish logistical system could easily be included in the model.

Cancer mortality inequalities in urban areas: a Bayesian small area analysis in Spanish cities [correcció]

After publication of this work in 'International Journal of Health Geographics' on 13 january 2011 was wrong. The map of Barcelona in Figure two (figure 1 here) was reversed. The final correct Figure is presented here

Association of early repolarization with risk of cardiac mortality in the general population

Early repolarization, which is characterized by an elevation of the J-point on 12-lead electrocardiography, is a common finding that has been considered as benign for decades. However, in the last years, it has been related with vulnerability to idiopathic ventricular fibrillation and with cardiac mortality in the general population. Recently, 4 potential ECG predictors that could differentiate the benign from the malignant form of early repolarization have been suggested. Any previous study about early repolarization has been done in Spain. Aim. To ascertain whether the presence of early repolarization pattern in a resting electrocardiogram is associated with a major risk of cardiac death in a Spanish general population and to determine whether the presence of potential predictors of malignancy in a resting electrocardiogram increases the risk of cardiac mortality in patients with early repolarization pattern. Methods. We will analyse the presence of early repolarization and the occurrence of cardiac mortality in a retrospective cohort study of 4,279 participants aged 25 to 74 years in the province of Girona. This cohort has been followed during a mean of 9.8 years. Early repolarization will be stratified according to the degree of J-point elevation (≥0.1 mV or ≥0.2 mV), the morphology of the J-wave (slurring, notching or any of these two), the ST-segment pattern (ascending or descending) and the localization (inferior leads, lateral leads, or both). Association of early repolarization with cardiac death will be assessed by adjusted Cox-proportional hazards models

Framework for Traffic Pattern Identification: Required Step for Short-term Forecasting

In the world of transport management, the term ‘anticipation’ is gradually replacing ‘reaction’. Indeed, the ability to forecast traffic evolution in a network should ideally form the basis for many traffic management strategies and multiple ITS applications. Real-time prediction capabilities are therefore becoming a concrete need for the management of networks, both for urban and interurban environments, and today’s road operator has increasingly complex and exacting requirements. Recognising temporal patterns in traffic or the manner in which sequential traffic events evolve over time have been important considerations in short-term traffic forecasting. However, little work has been conducted in the area of identifying or associating traffic pattern occurrence with prevailing traffic conditions. This paper presents a framework for detection pattern identification based on finite mixture models using the EM algorithm for parameter estimation. The computation results have been conducted taking into account the traffic data available in an urban network.