SARS-CoV-2 Vaccine Effectiveness in Hospitalized Patients: A Multicenter Test-Negative Case-Control Study.

BACKGROUND: Phase III clinical trials have documented the efficacy of the SARS-CoV-2 vaccines in preventing symptomatic COVID-19. Nonetheless, it is imperative to continue analyzing the clinical response to different vaccines in real-life studies. Our objective was to evaluate the effectiveness of five different vaccines in hospitalized patients with COVID-19 during the third COVID-19 outbreak in Mexico dominated by the Delta variant. METHODS: A test-negative case-control study was performed in nine tertiary-care hospitals for COVID-19. We estimated odds ratios (OR) adjusted by variables related a priori with the likelihood of SARS-CoV-2 infection and its severity. RESULTS: We studied 761 subjects, 371 cases, and 390 controls with a mean age of 53 years (SD, 17 years). Overall, 51% had a complete vaccination scheme, and an incomplete scheme (one dose from a scheme of two), 14%. After adjustment for age, gender, obesity, and diabetes mellitus, we found that the effectiveness of avoiding a SARS-CoV-2 infection when hospitalized with at least one vaccination dose was 71% (OR 0.29, 95% CI 0.19-0.45), that of an incomplete vaccination scheme, 67% (OR 0.33, 95% CI 0.18-0.62), and that of any complete vaccination scheme, 73% (OR 0.27, 95% CI 0.17-0.43). CONCLUSIONS: The SARS-CoV-2 vaccination program showed effectiveness in preventing SARS-CoV-2 infection in hospitalized patients during a Delta variant outbreak.

Supervised Machine Learning Methods for Seasonal Influenza Diagnosis.

Influenza has been a stationary disease in Mexico since 2009, and this causes a high cost for the national public health system, including its detection using RT-qPCR tests, treatments, and absenteeism in the workplace. Despite influenza's relevance, the main clinical features to detect the disease defined by international institutions like the World Health Organization (WHO) and the United States Centers for Disease Control and Prevention (CDC) do not follow the same pattern in all populations. The aim of this work is to find a machine learning method to facilitate decision making in the clinical differentiation between positive and negative influenza patients, based on their symptoms and demographic features. The research sample consisted of 15480 records, including clinical and demographic data of patients with a positive/negative RT-qPCR influenza tests, from 2010 to 2020 in the public healthcare institutions of Mexico City. The performance of the methods for classifying influenza cases were evaluated with indices like accuracy, specificity, sensitivity, precision, the f1-measure and the area under the curve (AUC). Results indicate that random forest and bagging classifiers were the best supervised methods; they showed promise in supporting clinical diagnosis, especially in places where performing molecular tests might be challenging or not feasible.

Clinical validation of 3D-printed swabs in adults and children for SARS-CoV-2 detection.

Throughout the entire coronavirus disease 19 (COVID-19) pandemic, there were disruptions in the supply chain of test materials around the world, primarily in poor- and middle-income countries. The use of 3D prints is an alternative to address swab supply shortages. In this study, the feasibility of the clinical use of 3D-printed swabs for oropharyngeal and nasopharyngeal sampling for the detection of SARS-CoV-2 infection was evaluated. For that purpose, paired samples with the 3D printed and the control swabs were taken from 42 adult patients and 10 pediatric patients, and the results obtained in the detection of SARS-CoV-2 by reverse transcription and quantitative polymerase chain reaction (RT-qPCR) were compared. Additionally, in those cases where the result was positive for SARS-CoV-2, the viral load was calculated by means of a mathematical algorithm proposed by us. For both adults and children, satisfactory results were obtained in the detection of SARS-CoV-2 by RT-qPCR; no significant differences were found in the quantification cycle values between the 3D-printed swab samples and the control samples. Furthermore, we corroborated that the 3D-printed swabs caused less discomfort and pain at the time of sampling. In conclusion, this study shows the feasibility of routinely using 3D-printed swabs for both adults and children. In this way, it is possible to maintain local and cheaper consumption along with fewer distribution difficulties.

COVID-19: critical case of a patient with an atypical manifestation of the disease.

BACKGROUND: COVID-19 was initially described as a severe acute respiratory disease that could drive to pneumonia, compromising the life of the patients in the worst scenario. However, even though in most of the cases the respiratory symptoms are still the most common manifestations of the disease, nowadays it is considered as a complex multisystem illness, affecting a variety of organs and tissues. Asymptomatic and atypic cases have also been described, where symptoms are not related to those first described, as is the case of this report. CASE PRESENTATION: On November 23, 2020, a 53-year-old woman goes to the emergency room due to gastrointestinal symptoms. The admission diagnosis was inflammatory bowel disease and a mild event of idiopathic chronic ulcerative colitis, and the initial treatment was focused on the metabolic acidosis, and the reestablishment the hydroelectrolytic and hemodynamic balance. Then, she was transferred to the Gastroenterology Unit where she was treated for one week. During her hospitalization, she showed a refractory shock caused by progressive organ deterioration (renal and neurological), requiring a double-vasopressor support, oxygenation, and ventilation. Considering the laboratory tests results and computed tomography scans, a COVID-19 test was carried out, obtaining a positive result with a high viral load. The S gene of the virus was amplified and sequenced, finding an uncommon mutation rarely reported worldwide. After considerable systemic deterioration, the patient presented cardiorespiratory arrest, with no response and died on December 1, after 8 days of hospitalization. CONCLUSIONS: In this report we describe the pathogenesis, clinical manifestations, and outcome of a patient with atypical COVID-19 symptoms (mainly gastrointestinal), rapidly evolving and with lethal consequences. Therefore, it is important to emphasize the need to strengthen patient surveillance in health centers, including those who do not present typical symptoms of COVID-19. In addition, it will be important to track the identified mutation (H1058Y) in the S viral gene and assess whether it could be associated with a different clinical manifestation of the disease or if it was just an isolated event.