Mortality after emergency department discharge: an analysis of 453599 cases.

Objectives: To quantify and analyze mortality in patients who die within 30 days of discharge home from a hospital emergency department (ED).

Material And Methods: All patients older than 14 years of age who were discharged home from the ED of a tertiary care hospital over a 5-year period were included. We collected age, sex, and other demographic variables, as well as the Charlson Comorbidity Index (CCI).

Spatio-temporal small area surveillance of the COVID-19 pandemic.

The emergence of COVID-19 requires new effective tools for epidemiological surveillance. Spatio-temporal disease mapping models, which allow dealing with small units of analysis, are a priority in this context. These models provide geographically detailed and temporally updated overviews of the current state of the pandemic, making public health interventions more effective.

Geographical Variability in Mortality in Urban Areas: A Joint Analysis of 16 Causes of Death.

The geographical distribution of mortality has frequently been studied. Nevertheless, those studies often consider isolated causes of death. In this work, we aim to study the geographical distribution of mortality in urban areas, in particular, in 26 Spanish cities.

[Magnitude and factors associated with the solitary death phenomenon of the elderly in the Valencian Community.].

Objective: In the Valencian Community 23% of the elderly people live alone, representing the solitary death among aged persons an unwanted effect of aging. Our aim was to determine the magnitude of this phenomenon and its risk factors in the population over 64 years of the CV during the period 2015-2017.

Methods: Cross-sectional study was carried out.

Beyond standardized mortality ratios; some uses of smoothed age-specific mortality rates on small areas studies.

Background: Most epidemiological risk indicators strongly depend on the age composition of populations, which makes the direct comparison of raw (unstandardized) indicators misleading because of the different age structures of the spatial units of study. Age-standardized rates (ASR) are a common solution for overcoming this confusing effect. The main drawback of ASRs is that they depend on age-specific rates which, when working with small areas, are often based on very few, or no, observed cases for most age groups.

Towards a Multidimensional Approach to Bayesian Disease Mapping.

Multivariate disease mapping enriches traditional disease mapping studies by analysing several diseases jointly. This yields improved estimates of the geographical distribution of risk from the diseases by enabling borrowing of information across diseases. Beyond multivariate smoothing for several diseases, several other variables, such as sex, age group, race, time period, and so on, could also be jointly considered to derive multivariate estimates.

Supervised filters for EEG signal in naturally occurring epilepsy forecasting.

Nearly 1% of the global population has Epilepsy. Forecasting epileptic seizures with an acceptable confidence level, could improve the disease treatment and thus the lifestyle of the people who suffer it. To do that the electroencephalogram (EEG) signal is usually studied through spectral power band filtering, but this paper proposes an alternative novel method of preprocessing the EEG signal based on supervised filters.

Lessons from healthcare utilization in children with obstructive sleep apnoea syndrome.

Introduction And Objectives: Paediatric Obstructive Sleep Apnoea-Hypopnoea Syndrome (OSAS) is a multisystemic condition affecting child's health status that may be investigated analyzing demand for healthcare.

Objective: to quantify the frequency of medical consultations in children with OSAS over a 5-year period, compared to a healthy population.

Methods: A longitudinal, case-control, ambispective study was conducted at a hospital pertaining to the national public health system.

Crowdsourcing reproducible seizure forecasting in human and canine epilepsy.

SEE MORMANN AND ANDRZEJAK DOI101093/BRAIN/AWW091 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE  : Accurate forecasting of epileptic seizures has the potential to transform clinical epilepsy care. However, progress toward reliable seizure forecasting has been hampered by lack of open access to long duration recordings with an adequate number of seizures for investigators to rigorously compare algorithms and results. A seizure forecasting competition was conducted on kaggle.

Online learning algorithm for time series forecasting suitable for low cost wireless sensor networks nodes.

Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning) systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN) algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network.

Do socioeconomic inequalities in mortality vary between different Spanish cities? a pooled cross-sectional analysis.

Background: The relationship between deprivation and mortality in urban settings is well established. This relationship has been found for several causes of death in Spanish cities in independent analyses (the MEDEA project). However, no joint analysis which pools the strength of this relationship across several cities has ever been undertaken.

A kernel-based spatio-temporal surveillance system for monitoring influenza-like illness incidence.

The threat of pandemics has made influenza surveillance systems a priority in epidemiology services around the world. The emergence of A-H1N1 influenza has required accurate surveillance systems in order to undertake specific actions only when and where they are necessary. In that sense, the main goal of this article is to describe a novel methodology for monitoring the geographical distribution of the incidence of influenza-like illness, as a proxy for influenza, based on information from sentinel networks.

Spatio-temporal evolution of female lung cancer mortality in a region of Spain, is it worth taking migration into account?

Background: The Comunitat Valenciana (CV) is a tourist region on the Mediterranean coast of Spain with a high rate of retirement migration. Lung cancer in women is the cancer mortality cause that has increased most in the CV during the period 1991 to 2000. Moreover, the geographical distribution of risk from this cause in the CV has been previously described and a non-homogenous pattern was determined.