ABSTRACT
Background: Describe the experience and results of the use of a digital platform navigated by the MAIA artificial intelligence engine for epidemiological surveillance in the department of Magdalena, Colombia, during the public health emergency generated by the Covid-19 disease pandemic in the period July 30 to December 8, 2020. Method(s): The MAIA digital platform was adapted to extract data from Covid-19 cases from the different health institutions distributed in the municipalities of the department of Magdalena. This information is then transformed through the platform into dynamic digital dashboards with 24/7 functionality, which allowed the visualization of descriptive information, trend curves and geolocation to facilitate decision-making in public health during the operating time. Satisfaction and utility surveys of the use of the platform called "MAIA DATA CRUE CENTRO REGULACION DE URGENCIAS Y EMERGENCIAS" (MAIA DATA CRUE) designed by MEDZAIO were carried out to know the perception of users. Result(s): Currently 58 health institutions from 27 municipalities of Magdalena are using the MAIA digital platform, in more than 4 months of operation a daily use of 100% has been achieved, with information extraction every 12 hours and continuous display of information throughout the period of use. More than 1200 records have been received, which have served to consolidate live information, with which daily health decisions have been made by the Magdalena COVID-19 pandemic regulatory center, optimizing the installed hospital and ICU capacity. 100% of those surveyed agree that this type of tool should continue to be used as epidemiological surveillance in COVID-19. Conclusion(s): The adaptation and use of digital platforms such as MAIA DATA CRUE CENTRO DE REGULACIONES DE URGENCIAS Y EMERGENCIAS, is an application of digital epidemiology for the intelligent management of diseases. This article demonstrates the importance of using digital tools supported by artificial intelligence to optimize the capacities of health systems regarding the different dimensions, in this case epidemiological surveillance and public health.Copyright © 2022 Asociacion Colombiana de Infectologia. All rights reserved.
ABSTRACT
Background: In our experience during the first year of development of ACHOC-C19 study, we observed 26% mortality in patients with cancer and COVID 19 infection. The impact of vaccination was not evaluated prior to the implementation of this strategy worldwide in this kind of population. It was proposed to evaluate the effectiveness of immunization during the second phase of our investigation. Methods: Cohort study derived from the National Registry of Patients with Cancer and COVID-19 (ACHOCC-19). Data were collected from June 2021 since vaccine was available. Patients were: older than 18 years, diagnosed with cancer (solid tumors), treated and/or under follow-up, and with COVID-19 infection. The comparative analysis of the vaccinated and non-vaccinated cohort is presented. Outcomes included: all-cause mortality within 30 days of infection diagnosis, hospitalization, and mechanical ventilation. Effect estimation was performed through relative risk (RR) and multivariate analysis for each event, using generalized linear models of the binomial family. Results: 896 patients were included, 470 were older than 60 years (52.4%) and 59% women (n = 530). 172 patients were recruited in the vaccinated cohort and 724 in the non-vaccinated cohort (ratio: 1 to 4.2). The cumulative incidence of hospitalization among the unvaccinated was 42.4% (n = 307), and among the vaccinated, 29% (n = 50);invasive mechanical ventilation requirement was 8.4% (n = 61) in unvaccinated, and 4.6% (n = 8) in vaccinated. The cumulative incidence of mortality from all causes in the unvaccinated was 17% (n = 123) and in the vaccinated 4.65% (n = 8). Table summarizes the multivariate analysis. The adjusted RR for mortality for the unvaccinated is 3.4 (95% CI: 1.7-6.8), for hospitalization 1.36 (95% CI: 1.08-1.72), and for mechanical ventilation 2.1 (95% CI: 1.02-4.2). Conclusions: The incidence of complications and death in patients with cancer and COVID-19 infection is significantly higher in those who have not received a vaccination schedule compared to those who have been vaccinated. Immunization should be promoted and intensified in this population group.
ABSTRACT
Background: There are not specific information about otucomes of COVID-19 infection in patients with breast cancer. We aimed to describe the outcomes in this population in our national cohort of patients with cancer and infection for COVID-19. Methods: ACHOCC-19B registry is a multicenter observational study composed of a cross-sectional and a prospective cohort component. Eligibility criteria were the diagnosis of breast cancer and COVID-19 infection confirmed with RT-PCR. Follow-up of 30 days was completed. Clinical data were extracted of the multicentric register of cancer and covid-19 in Colombia (ACHOCC-19), collected from Apr 1 until Oct 31, 2020. The primary outcome was 30-day mortality from all causes and secondary outcome was asymptomatic disease. Associations between demographic or clinical characteristics and outcomes were measured with odds ratios (ORs) with 95% CIs using multivariable logistic regression. Results: 132 patients were included(18,5% of global ACHOCC-19 cohort). 18,2% died and 25,8% was asymptomatic. In relation to the patients who died vs did not died, 68 vs 66% were > 50 years, 20 vs 10,2% with obesity, 32 vs 51,4% without comorbidities: 24 vs 12% with Diabetes, 56 vs 29% arterial Hypertension, 17,75 vs 3.88% ECOG >2, 50 vs 12,5% progressive cancer, 20 vs 5,6% bacterial coinfection, 65 vs 25,2% received antibiotic and 68 vs 19% steroids for Covid-19 infection. 11.3% had severe infection and received ventilatory support and 66% died. About the asymptomatic patients 74% were > 50 years, 2,9% had obesity, 56% without comorbidities, 56% with ECOG 0 and 17,6% had metastatic disease. In the logistic regression analysis, age > 50 years (OR 2,7 95% 0,54-13,81), >2 comorbidities (OR 3,48 95% 0,26-45,71), progressive disease (OR 3,52 95% 0,47-26,57), steroids (OR 6,62 95% 1,5-26,6) and antibiotic treatment for Covid19 (OR 6,88 95% 1,60-29,76) behaved as a risk factors for mortality, but only steroids and antibiotic was statistically significant. Conclusions: In our study, breast cancer patients have high mortality by Covid-19 infection. Age, comorbidities, ECOG >2, progressive disease, and use of antibiotic and steroids are factors for worse prognosis. Legal entity responsible for the study: The authors. Funding: Has not received any funding. Disclosure: All authors have declared no conflicts of interest.
ABSTRACT
Background: Cancer has been described as a risk factor for worse prognosis in people with Covid-19. However, there are few studies informing on the characteristics of cancer patients that have asymptomatic SARS-cov2 infection. The ACHOCC-19 study included asymptomatic patients. Methods: Analytical cohort study of patients with cancer and SARScov2 infection in Colombia. From April 1 to October 31, 2020, we collected data on demographic and clinical variables related to cancer and COVID-19 infection. We describe the characteristics and outcomes of patients who had no symptoms of COVID19. Association between outcomes and prognostic variables was analyzed using logistic regression models. Results: We included 742 patients, of which 205 (27.6%) were asymptomatic. Of these 62.2% were older than 61 years, 66% were women, 1.42% were smokers. The most frequent malignancy was breast cancer (25%), followed by colon-rectum (14.6%), sarcoma/soft tissues (5.66%) and lung cancer (5.19%). Patients were more likely to be asymptomatic if they had fewer comorbidities (0-1 comorbidities: 84% asymptomatic, 2 comorbidities: 10.85%, more than 2 comorbidities: 5.15%). 90.5% lived in urban areas and 53.37% had low income. 35.4% of patients had metastatic disease, 8.7% had progressive cancer, 40% had stable disease or partial response. No patient had an ECOG PS of 4 or more, and only 1.91% had ECOG 3. In logistic regression analysis statistically significant associations for having symptomatic disease included: man, presence of 1, 2 or > 2 comorbidities, ECOG 1,2 or 3 and cancer in progression. On the other hand, the statistically significant ORs for having asymptomatic disease were age between 18 and 30 years old, cancer in remission and receiving non-cytotoxic treatment. Table sumarizes ORs and their respective 95% CIs of the variables adjusted in the logistic regression model. Conclusions: In our stumdy, cancer patients had a higher probability of asymptomatic COVID-19 infection if they were women, between the ages of 18 and 30 years, had cancer in remission , ECOG 0 and no comorbidities. This is the first cohort of patients with cancer and asymptomatic covid 19 with a significant sample size in Latin America.
ABSTRACT
The COVID-19 pandemic caused a change in our society and put health systems in crisis worldwide. Different risk factors and comorbidities have been found that increase the risk of mortality when acquiring this infection. The use of alternative devices to the cigarette like the electronic cigarettes, the vapers have been studied widely and generators of great controversy since it has been discovered that they also produce different pulmonary affections. When developing the SARS-CoV2 infection, different theories have been generated about the greater predisposition to a worse prognosis of people who use electronic cigarettes; however, the information on this continues in discovery. A group of experts made up of oncologists, infectologists, pulmonologists, and epidemiologists met to review the literature and then generate theories about the impact of electronic cigarettes on SARS-CoV2 infection.