Impact of the COVID-19 Pandemic on the Epidemiological Situation of Pulmonary Tuberculosis–Using Natural Language Processing

Abstract

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.

Joint Expedition: Exploring the Intersection of Digital Health and AI in Precision Medicine with Team Integration

“…This Special Issue has successfully achieved a significant milestone, featuring 20 contributions (Co)s (excluding this editorial) [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28].…”

“…The published papers (see Figure 1), according to the selected categories, encompass 1 introductory editorial [9], 7 full scientific articles [10][11][12][13][14][15][16], 5 reviews [17][18][19][20][21], 2 systematic reviews [22,23], 4 perspectives [24][25][26][27], and 1 opinion article [28].…”

“…The retrospective study proposed by Morena et al [11] utilizing artificial intelligence aimed to assess the impact of the COVID-19 pandemic on pulmonary tuberculosis (TB). Analyzing electronic health records from Spain's Castilla-La Mancha region, this study compared data from 2015 to 2020.…”

“…Twenty distinct contributions [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28] weave through the intricate fields of the health domain focused on the integration of digital health and AI with precision medicine. These studies, spanning diverse medical domains, collectively leverage several AI and digital health approaches to precision medicine.…”

“…The scientific articles [10][11][12][13][14][15][16] offer a glimpse into the current priorities of scholars, with a distinct focus on the integration of digital health and AI within the realm of precision medicine. These articles illuminate the ongoing efforts of researchers, underscoring the increasing importance of incorporating advanced technologies into healthcare practices.…”