ArticlePloS one2021
Adapting for the COVID-19 pandemic in Ecuador, a characterization of hospital strategies and patients.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Clinical Impact of Molecular Testing for Respiratory Viruses in Children Admitted with Acute Respiratory Diseases: Real-World Evidence.Risk management and healthcare policy · 2026Article
- From theoretical models to practical deployment: A perspective and case study of opportunities and challenges in AI-driven cardiac auscultation research for low-income settings.PLOS digital health · 2024Article
- Artificial intelligence in healthcare: a scoping review of perceived threats to patient rights and safety.Archives of public health = Archives belges de sante publique · 2024Article
- Review
- ChatGPT: promise and challenges for deployment in low- and middle-income countries.The Lancet regional health. Western Pacific · 2023Review
- A Multicenter Study about the Population Treated in the Respiratory Triage Stations Deployed by the Red Cross during the COVID-19 Pandemic.International journal of environmental research and public health · 2022Article
- Artificial intelligence for strengthening healthcare systems in low- and middle-income countries: a systematic scoping review.NPJ digital medicine · 2022Article
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Authors and funding
16 authors.
Funding
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Abstract
The World Health Organization (WHO) declared coronavirus disease-2019 (COVID-19) a global pandemic on 11 March 2020. In Ecuador, the first case of COVID-19 was recorded on 29 February 2020. Despite efforts to control its spread, SARS-CoV-2 overran the Ecuadorian public health system, which became one of the most affected in Latin America on 24 April 2020. The Hospital General del Sur de Quito (HGSQ) had to transition from a general to a specific COVID-19 health center in a short period of time to fulfill the health demand from patients with respiratory afflictions. Here, we summarized the implementations applied in the HGSQ to become a COVID-19 exclusive hospital, including the rearrangement of hospital rooms and a triage strategy based on a severity score calculated through an artificial intelligence (AI)-assisted chest computed tomography (CT). Moreover, we present clinical, epidemiological, and laboratory data from 75 laboratory tested COVID-19 patients, which represent the first outbreak of Quito city. The majority of patients were male with a median age of 50 years. We found differences in laboratory parameters between intensive care unit (ICU) and non-ICU cases considering C-reactive protein, lactate dehydrogenase, and lymphocytes. Sensitivity and specificity of the AI-assisted chest CT were 21.4% and 66.7%, respectively, when considering a score >70%; regardless, this system became a cornerstone of hospital triage due to the lack of RT-PCR testing and timely results. If health workers act as vectors of SARS-CoV-2 at their domiciles, they can seed outbreaks that might put 1,879,047 people at risk of infection within 15 km around the hospital. Despite our limited sample size, the information presented can be used as a local example that might aid future responses in low and middle-income countries facing respiratory transmitted epidemics.
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