Classification tree obtained by artificial intelligence for the prediction of heart failure after acute coronary syndromes. / Árboles de clasificación obtenidos mediante inteligencia artificial para la predicción de insuficiencia cardiaca tras el síndrome coronario agudo.

BACKGROUND: Coronary heart disease is the leading cause of heart failure (HF), and tools are needed to identify patients with a higher probability of developing HF after an acute coronary syndrome (ACS). Artificial intelligence (AI) has proven to be useful in identifying variables related to the development of cardiovascular complications. METHODS: We included all consecutive patients discharged after ACS in two Spanish centers between 2006 and 2017. Clinical data were collected and patients were followed up for a median of 53months. Decision tree models were created by the model-based recursive partitioning algorithm. RESULTS: The cohort consisted of 7,097 patients with a median follow-up of 53months (interquartile range: 18-77). The readmission rate for HF was 13.6% (964 patients). Eight relevant variables were identified to predict HF hospitalization time: HF at index hospitalization, diabetes, atrial fibrillation, glomerular filtration rate, age, Charlson index, hemoglobin, and left ventricular ejection fraction. The decision tree model provided 15 clinical risk patterns with significantly different HF readmission rates. CONCLUSIONS: The decision tree model, obtained by AI, identified 8 leading variables capable of predicting HF and generated 15 differentiated clinical patterns with respect to the probability of being hospitalized for HF. An electronic application was created and made available for free.

Usefulness of open data to determine the incidence of COVID-19 and its relationship with atmospheric variables in Spain during the 2020 lockdown.

The SARS-CoV-2 pandemic and the spread of the COVID-19 disease led to a lockdown being imposed in Spain to minimise contagion from 16 March 2020 to 1 May 2020. Over this period, measures were taken to reduce population mobility (a key factor in disease transmission). The scenario thus created enabled us to examine the impact of factors other than mobility (in this case, meteorological conditions) on the incidence of the disease, and thus to identify which environmental variables played the biggest role in the pandemic's evolution. Worthy of note, the data required to perform the study was entirely extracted from governmental open data sources. The present work therefore demonstrates the utility of such data to conduct scientific research of interest to society, leading to studies that are also fully reproducible. The results revealed a relationship between temperatures and the spread of COVID-19. The trend was that of a slightly lower disease incidence as the minimum temperature rises, i.e. the lower the minimum temperature, the greater the number of cases. Furthermore, a link was found between the incidence of the disease and other variables, such as altitude and proximity to the sea. There were no indications, however, in the study's data, of a relationship between incidence and precipitation or wind.

Trends in hospitalizations and deaths in HIV-infected patients in Spain over two decades.

BACKGROUND: The prognosis of HIV infection dramatically improved after the introduction of triple antiretroviral therapy 25 years ago. Herein, we report the impact of further improvements in HIV management since then, looking at all hospitalizations in persons with HIV (PWH) in Spain. METHODS: A retrospective study using the Spanish National Registry of Hospital Discharges. Information was retrieved since 1997-2018. RESULTS: From 79 647 783 nationwide hospital admissions recorded during the study period, 532 668 (0.67%) included HIV as diagnosis. The mean age of PWH hospitalized increased from 33 to 51 years (P < 0.001). The rate of HIV hospitalizations significantly declined after 2008. Comparing hospitalizations during the first (1997-2007) and last (2008-2018) decades, the rate of non-AIDS illnesses increased, mostly due to liver disease (from 35.9 to 38.3%), cardiovascular diseases (from 12.4 to 28.2%), non-AIDS cancers (from 6.4 to 15.5%), and kidney insufficiency (from 5.4 to 13%). In-hospital deaths occurred in 5.5% of PWH, declining significantly over time. Although most deaths were the result from AIDS conditions (34.8%), the most frequent non-AIDS deaths were liver disease (47.1%), cardiovascular events (29.2%), non-AIDS cancers (24.2%), and kidney insufficiency (20.7%). CONCLUSION: Hospital admissions in PWH significantly declined after 2008, following improvements in HIV management and antiretroviral therapy. Non-AIDS cancers, cardiovascular events and liver disease represent a growing proportion of hospital admissions and deaths in PWH.

Toxoplasma gondii infection in hospitalized people living with HIV in Spain, 1997 to 2015.

Toxoplasma gondii infection was one of the most frequent AIDS-defining conditions in HIV-infected individuals until the advent of combination antiretroviral therapy. We aimed to assess the clinical load, coinfection, and mortality, as well as time trends for people living with HIV and hospitalized with Toxoplasma gondii infection, in Spain from 1997 to 2015. Retrospective observational analysis using the Spanish National Registry of Hospital Discharges. Information was retrieved for the study period using the International Classification of Diseases, 9th revision. There were 66,451,094 hospital admissions in Spain from 1997 to 2015, including 472,269 (0.71%) in people living with HIV. Toxoplasma gondii infection was registered in 9006 of these (overall prevalence 1.91%), making it the fifth most common opportunistic infection in hospitalized HIV-positive patients. Prevalence of Toxoplasma gondii infection declined in this group from 4.2% in 1997 to 0.8% in 2015 (p < 0.001), while mean age increased, from 35 years in 1997 to 44 years in 2015. The overall in-hospital mortality rate declined from 13.5% in 1997 to 8.9% in 2015, and it was higher in the concomitant presence of bacterial pneumonia (28.9% vs. 10.2%, p < 0.001), cryptosporidiosis (26.9% vs. 11.5%; p = 0.03), cytomegalovirus disease (18.2% vs. 11.2%, p < 0.001), Pneumocystis jiroveci pneumonia (31.5% vs. 10.5%, p < 0.001), leukoencephalopathy (19.8% vs. 11.78% p < 0.001), and wasting syndrome (29.3% vs 10.9%; p < 0.001). Toxoplasma gondii infection prevalence has significantly declined among hospitalized HIV-infected patients in Spain during the last two decades, coinciding with the widespread use of combination antiretroviral therapy.

Chemical and technological properties of bologna-type sausages with added black quinoa wet-milling coproducts as binder replacer.

The objective of this study was to evaluate different strategies for adding 3% black quinoa (either as whole seeds or as a fiber-rich fraction of quinoa from its wet-milling process) to bologna-type sausage. This addition was evaluated in terms of its influence on nutritional composition and technological properties (emulsion stability, pH, water activity, color changes, textural properties, residual nitrite level and lipid oxidation). Both strategies resulted in commercially feasible sausages with increased nutritive properties (dietary fiber) and with some modifications in their technological properties. Compared with control sausages, they showed better emulsion stability, lower water activity and lipid oxidation values (interesting properties for sausages shelf-life). Color changes were more evident when the fiber-rich fraction was added. The residual nitrite level increased with the addition of quinoa so that it would be necessary to incorporate less nitrites, or it might even be unnecessary, contributing to the production of more natural products.

Estimation of parameters in sewage sludge by near-infrared reflectance spectroscopy (NIRS) using several regression tools.

Sewage sludge application to agricultural soils is a common practice in several countries in the European Union. Nevertheless, the application dose constitutes an essential aspect that must be taken into account in order to minimize environmental impacts. In this study, near infrared reflectance spectroscopy (NIRS) was used to estimate in sewage sludge samples several parameters related to agronomic and environmental issues, such as the contents in organic matter, nitrogen and other nutrients, metals and carbon fractions, among others. In our study (using 380 biosolid samples), two regression models were fitted: the common partial least square regression (PLSR) and the penalized signal regression (PSR). Using PLSR, NIRS became a feasible tool to estimate several parameters with good goodness of fit, such as total organic matter, total organic carbon, total nitrogen, water-soluble carbon, extractable organic carbon, fulvic acid-like carbon, electrical conductivity, Mg, Fe and Cr, among other parameters, in sewage sludge samples. For parameters such as C/N ratio, humic acid-like carbon, humification index, the percentage of humic acid-like carbon, the polymerization ratio, P, K, Cu, Pb, Zn, Ni and Hg, the performance of NIRS calibrations developed with PLSR was not sufficiently good. Nevertheless, the use of PSR provided successful calibrations for all parameters.