Patients with Chronic Obstructive Pulmonary Disease (COPD) have a higher prevalence of coronary ischemia and other factors that put them at risk for COVID-19-related complications. We aimed to explore the impact of COVID-19 in a large population-based sample of patients with COPD in Castilla-La Mancha, Spain. We analyzed clinical data in electronic health records from 1 January to 10 May 2020 by using Natural Language Processing through the SAVANA Manager^® clinical platform. Out of 31,633 COPD patients, 793 had a diagnosis of COVID-19. The proportion of patients with COVID-19 in the COPD population (2.51%; 95% CI 2.33–2.68) was significantly higher than in the general population aged >40 years (1.16%; 95% CI 1.14–1.18); p < 0.001. Compared with COPD-free individuals, COPD patients with COVID-19 showed significantly poorer disease prognosis, as evaluated by hospitalizations (31.1% vs. 39.8%: OR 1.57; 95% CI 1.14–1.18) and mortality (3.4% vs. 9.3%: OR 2.93; 95% CI 2.27–3.79). Patients with COPD and COVID-19 were significantly older (75 vs. 66 years), predominantly male (83% vs. 17%), smoked more frequently, and had more comorbidities than their non-COPD counterparts. Pneumonia was the most common diagnosis among COPD patients hospitalized due to COVID-19 (59%); 19% of patients showed pulmonary infiltrates suggestive of pneumonia and heart failure. Mortality in COPD patients with COVID-19 was associated with older age and prevalence of heart failure (p < 0.05). COPD patients with COVID-19 showed higher rates of hospitalization and mortality, mainly associated with pneumonia. This clinical profile is different from exacerbations caused by other respiratory viruses in the winter season.

In recent years, many studies have analyzed the importance of integrating time, or aging, into the equation that relates genetics and the environment to the development and origin of COPD. Under conditions of daily clinical practice, our study attempts to identify the differences in the clinical profile of patients with COPD according to age and the impact on the global burden of the disease. This study is non-interventional and observational, using artificial intelligence and data captured from electronic medical records. The study population included patients who were diagnosed with COPD between 2011 and 2021. A total of 73,901 patients had a diagnosis of COPD. The mean age was 73 years (95% CI: 72.9–73.1), and 56,763 were men (76.8%). We observed a specific prevalence of obesity, heart failure, depression, and hiatal hernia in women (p < 0.001), and ischemic heart disease and obstructive sleep apnea (OSA) in men (p < 0.001). In the analysis by age ranges, a progressive increase in cardiovascular risk factors was observed with age. In conclusion, in a real-life setting, COPD is a disease that primarily affects older subjects and frequently presents with comorbidities that are decisive in the evolutionary course of the disease.

Objective: The objective of this study is to define the real-life clinical profile and therapeutic management of patients with idiopathic pulmonary fibrosis using artificial intelligence. Methods: We have conducted an observational, retrospective, non-interventional study using data from the Castilla-La Mancha Regional Healthcare Service (SESCAM) in Spain between January 2012 and December 2020. The Savana Manager 3.0 artificial intelligence platform was used to collect information from electronic medical records by applying natural language processing. Results: Our study includes 897 subjects whose diagnosis was compatible with idiopathic pulmonary fibrosis; 64.8% were men, with a mean age of 72.9 years (95% CI 71.9–73.8), and 35.2% were women, with a mean age of 76.8 years (95% CI 75.5–78). Patients who had a family history of IPF (98 patients; 12%) were younger and predominantly female (53.1%). Regarding treatment, 45% of patients received antifibrotic therapy. Patients who had undergone lung biopsy, chest CT, or bronchoscopy were younger than the patient population in whom these studies were not completed. Conclusions: This study has used artificial intelligence techniques to analyze a large population over a 9-year period and determine the situation of IPF in standard clinical practice by identifying the patient clinical profile, use of diagnostic tests and therapeutic management.

Background: We aimed to analyze the impact of the COVID-19 pandemic on pulmonary tuberculosis (TB) using artificial intelligence. To do so, we compared the real-life situation during the pandemic with the pre-2020 situation. Methods: This non-interventional, retrospective, observational study applied natural language processing to the electronic health records of the Castilla-La Mancha region of Spain. The analysis was conducted from January 2015 to December 2020. Results: A total of 2592 patients were diagnosed with pulmonary tuberculosis; 64.6% were males, and the mean age was 53.5 years (95%CI 53.0–54.0). In 2020, pulmonary tuberculosis diagnoses dropped by 28% compared to 2019. In total, 62 (14.2%) patients were diagnosed with COVID-19 and pulmonary tuberculosis coinfection in 2020, with a mean age of 52.3 years (95%CI 48.3–56.2). The main symptoms in these patients were dyspnea (27.4%) and cough (35.5%), although their comorbidities were no greater than patients with isolated TB. The female sex was more frequently affected, representing 53.4% of this patient subgroup. Conclusions: During the first year of the COVID-19 pandemic, a decrease was observed in the incidence of pulmonary tuberculosis. Women presented a significantly higher risk for pulmonary tuberculosis and COVID-19 coinfection, although the symptoms were not more severe than patients diagnosed with pulmonary tuberculosis alone.