Trends in prevalence and the effects on hospital outcomes of dementia in patients hospitalized with acute COPD exacerbation.

AIMS: To assess changes in prevalence and the effects on hospital outcomes of dementia among patients hospitalized with an acute exacerbation of chronic obstructive pulmonary disease (AE-COPD); and to evaluate sex-differences, as well as the impact of COVID-19 pandemic in this relationship. METHODS: We used a nationwide discharge database to select patients admitted with AE-COPD in Spain from 2011 to 2020. We identified those with any type of dementia, vascular dementia (VaD) or Alzheimer's disease (AD). RESULTS: We identified 658,429 hospitalizations with AE-COPD (4.45% had any type of dementia, 0.79% VaD and 1.57% AD). The presence of any type of dementia remained stable from 2011 to 2015, and increased significantly between 2016 and 2020. For VaD, the time trend showed no change until 2020, when a significant increment was found. The probability of AD decreased significantly overtime. The in-hospital mortality (IHM) among patients with any type of dementia remained stable overtime until 2020, when it increased significantly. Older age, higher comorbidity, COVID-19, and use of mechanical ventilation were variables associated to IHM. Women had lower risk of dying in the hospital than men in all subgroups. CONCLUSIONS: After a previous period of stability, the prevalence of any type of dementia increased over the last 5 years of the study, although we identified different trends depending on the specific cause of dementia. The IHM remained stable overtime until 2020, when it increased, probably related to the COVID-19 pandemic. It is remarkable the protective effect of female sex for IHM.

Time Trends in Clinical Characteristics and Hospital Outcomes of Hospitalizations for Lung Transplantation in COPD Patients in Spain from 2016 to 2020-Impact of the COVID-19 Pandemic.

(1) Background: To examine the clinical characteristics and hospital outcomes of hospitalization for lung transplantation in COPD patients in Spain from 2016 to 2020; and to assess if the COVID-19 pandemic has affected the number or the outcomes of lung transplantations in these patients. (2) Methods: We used the Spanish National Hospital Discharge Database to select subjects who had a code for COPD (ICD-10: J44) and had undergone a lung transplantation (ICD-10 codes OBYxxxx). (3) Results: During the study period, 704 lung transplants were performed among COPD patients (single 31.68%, bilateral 68.32%). The absolute number of transplants increased with raising rates of 8%, 14% and 19% annually from 2016 to 2019. However, a marked decrease of -18% was observed from 2019 to year 2020. Overall, 47.44% of the patients suffered at least one complication, being the most frequent lung transplant rejection (24.15%), followed by lung transplant infection (13.35%). The median length of hospital stay (LOHS) was 33 days and the in-hospital-mortality (IHM) was 9.94%. Variables associated with increased risk of mortality were a Comorbidity Charlson Index ≥ 1 (OR 1.82; 95%CI 1.08-3.05) and suffering any complication of the lung transplantation (OR 2.14; 95%CI 1.27-3.6). COPD patients in 2020 had a CCI ≥ 1 in a lower proportion than 2019 patients (29.37 vs. 38.51%; p = 0.015) and less frequently suffered any complications after the lung transplantation (41.26 vs. 54.6%; p = 0.013), no changes in the LOHS or the IHM were detected from 2019 to 2020. (4) Conclusions: Our study showed a constant increase in the number of lung transplantations from 2016 to 2019 in COPD patients, with a drop from 2019 to 2020, probably related to the COVID-19 pandemic. However, no changes in LOHS or IHM were detected over time.

The polyhedric reality of the interaction between COVID-19, asthma and inhaled corticosteroids.

The impact of ICS on the prognosis for #COVID19 in #asthma patients requires a thorough evaluation of a range of factors that interact in this process, in order to draw solid conclusions, since at the present time the debate continues https://bit.ly/3xLNBrc.

Risk Factors of Mortality in Hospitalized Patients With COVID-19 Applying a Machine Learning Algorithm Factores de riesgo de mortalidad en pacientes hospitalizados con COVID-19 aplicando un algoritmo de aprendizaje automático

Introduction Risk stratification of patients with COVID-19 can be fundamental to support clinical decision-making and optimize resources. The objective of our study is to identify among the routinely tested clinical and analytical parameters those that would allow us to determine patients with the highest risk of dying from COVID-19. Material and methods We carried out a retrospective cohort multicentric study by consecutively, including hospitalized patients with COVID-19 admitted in any of the 11 hospitals in the healthcare network of HM Hospitals-Spain. We collected the clinical, demographic, analytical, and radiological data from the patient's medical records. To assess each of the biomarkers’ predictive impact and measure the statistical significance of the variables involved in the analysis, we applied a random forest with a permutation method. We used the similarity measure induced by a previously classification model and adjusted the k-groups clustering algorithm based on the energy distance to stratify patients into a high and low-risk group. Finally, we adjusted two optimal classification trees to have a schematic representation of the cut-off points. Results We included 1246 patients (average age of 65.36 years, 62% males). During the study one hundred sixty-eight patients (13%) died. High values of age, D-Dimer, White Blood Cell, Na, CRP, and creatinine represent the factors that identify high-risk patients who would die. Conclusions Age seems to be the primary predictor of mortality in patients with SARS-CoV-2 infection, while the impact of acute phase reactants and blood cellularity is also highly relevant.