Search

During the COVID-19 pandemic, bioethical concerns were raised and there was even a ″resurgence of bioethics. ″ In this work, we review the scientific articles published by Spanish authors in relation to bioethical issues in the three years following the declaration of the pandemic. Seventy publications have been selected. Of all of them, the topic that lent itself to the most debate was that of prioritization in the use of health resources. A consensus was reached that ruled out that age could be considered as a sole exclusion criterion in healthcare or in a possible admission to the ICU. And the importance of taking special care of the most vulnerable and adapting care to the conditions of each patient without excluding anyone was recalled. Other relevant topics were the contrast between autonomy and the common good, the immune passport, vaccination, rigor in research and the publication of results, the professionalism of health personnel, misinformation, care for nursing homes, telemedicine, and the importance of the exercise of virtues. After the experience of both vulnerability and the need to exercise solidarity, many works raise the desire and the possibility of being able to overcome the pandemic being better.

COVID-19 is responsible for high mortality, but robust machine learning-based predictors of mortality are lacking. To generate a model for predicting mortality in patients hospitalized with COVID-19 using Gradient Boosting Decision Trees (GBDT). The Spanish SEMI-COVID-19 registry includes 24,514 pseudo-anonymized cases of patients hospitalized with COVID-19 from 1 February 2020 to 5 December 2021. This registry was used as a GBDT machine learning model, employing the CatBoost and BorutaShap classifier to select the most relevant indicators and generate a mortality prediction model by risk level, ranging from 0 to 1. The model was validated by separating patients according to admission date, using the period 1 February to 31 December 2020 (first and second waves, pre-vaccination period) for training, and 1 January to 30 November 2021 (vaccination period) for the test group. An ensemble of ten models with different random seeds was constructed, separating 80% of the patients for training and 20% from the end of the training period for cross-validation. The area under the receiver operating characteristics curve (AUC) was used as a performance metric. Clinical and laboratory data from 23,983 patients were analyzed. CatBoost mortality prediction models achieved an AUC performance of 84.76 (standard deviation 0.45) for patients in the test group (potentially vaccinated patients not included in model training) using 16 features. The performance of the 16-parameter GBDT model for predicting COVID-19 hospital mortality, although requiring a relatively large number of predictors, shows a high predictive capacity., (© 2023. The Author(s), under exclusive licence to Società Italiana di Medicina Interna (SIMI).)

Background: There is currently much uncertainty regarding the most optimal treatment for COVID-19. This study analyze the change in the clinical condition of patients hospitalized for severe COVID-19 pneumonia and treated with remdesivir in a real-life setting, based on the WHO Ordinal Scale. Clinical complications, treatment safety, and impact of other associated drugs were also analyzed. Methods: We conducted an observational, retrospective study including patients treated with remdesivir. The need for admission to the ICU, the length of ICU and hospital stay, and the need for ventilatory support were analyzed. The laboratory parameters, drugs administered concomitantly, and difference in the length of hospital stay according to the concomitant treatment received were also evaluated. A univariate and multivariate Cox regression analysis was performed to analyze associated factors. Results: A total of 92 patients were included. The mean length of hospital stay was 15 days, and 90% of the patients had been discharged from the hospital 28 days after starting treatment with remdesivir. The likelihood of hospital discharge among patients not presenting with hypertension as a comorbidity was significantly higher than that of those with this condition (HR = 3.19, P = 0.008). Nineteen patients had to be admitted to the ICU (mean of 18 days). Approximately 11% required invasive mechanical ventilation (mean of 22 days). Almost 37% of the patients received high-flow oxygen therapy and 14% non-invasive mechanical ventilation. Four deaths were recorded within the first week. Main adverse events were increases in transaminase and creatinine levels. Nosocomial infections were more frequent when remdesivir was combined with immunosuppressive drugs. Conclusions: Patients with severe COVID-19 pneumonia and treated with remdesivir require relatively prolonged hospital stays, many with a need for ventilatory support and, in a considerable proportion of cases, admission to the ICU. However, the observed survival rate is high, and the drug is well tolerated. [ABSTRACT FROM AUTHOR]

Moved by the current epidemiological event, the covid-19, and the economic breakdowns we are witnessing, in this study we ask ourselves about the impact of the bloodiest pandemic of the 20th century on the economy and working conditions in Argentina: the Spanish flu. This approach, carried out using a qualitative methodology anchored in hermeneutics, is based on the study of journalistic sources and medical testimonies of the time. From them we intend to show how the advent of the disease - crystallized in two great waves - shook the economic and productive structures of different regions of the country, generating particular labor logics. [ABSTRACT FROM AUTHOR]