Analytical Performances of the COVISTIXTM Antigen Rapid Test for SARS-CoV-2 Detection in an Unselected Population (All-Comers).

The performance and validity of the COVISTIXTM rapid antigen test for the detection of SARS-CoV-2 were evaluated in an unselected population. Additionally, we assessed the influence of the Omicron SARS-CoV-2 variant in the performance of this antigen rapid test. Swab samples were collected at two point-of-care facilities in Mexico City from individuals that were probable COVID-19 cases, as they were either symptomatic or asymptomatic persons at risk of infection due to close contact with SARS-CoV-2 positive cases. Detection of the Omicron SARS-CoV-2 variant was performed in 91 positive cases by Illumina sequencing. Specificity and sensitivity of the COVISTIXTM rapid antigen test was 96% (CI 95% 94-98) and 81% (CI 95% 76-85), respectively. The accuracy parameters were not affected in samples collected after 7 days of symptom onset, and it was possible to detect almost 65% of samples with a Ct-value between 30 and 34. The COVISTIXTM antigen rapid test is highly sensitive (93%; CI 95% 88-98) and specific (98%; CI 95% 97-99) for detecting Omicron SARS-CoV-2 variant carriers. The COVISTIXTM rapid antigen test is adequate for examining asymptomatic and symptomatic individuals, including those who have passed the peak of viral shedding, as well as carriers of the highly prevalent Omicron SARS-CoV-2 variant.

The Evolutionary Landscape of SARS-CoV-2 Variant B.1.1.519 and Its Clinical Impact in Mexico City.

The SARS-CoV-2 pandemic is one of the most concerning health problems around the globe. We reported the emergence of SARS-CoV-2 variant B.1.1.519 in Mexico City. We reported the effective reproduction number (Rt) of B.1.1.519 and presented evidence of its geographical origin based on phylogenetic analysis. We also studied its evolution via haplotype analysis and identified the most recurrent haplotypes. Finally, we studied the clinical impact of B.1.1.519. The B.1.1.519 variant was predominant between November 2020 and May 2021, reaching 90% of all cases sequenced in February 2021. It is characterized by three amino acid changes in the spike protein: T478K, P681H, and T732A. Its Rt varies between 0.5 and 2.9. Its geographical origin remain to be investigated. Patients infected with variant B.1.1.519 showed a highly significant adjusted odds ratio (aOR) increase of 1.85 over non-B.1.1.519 patients for developing a severe/critical outcome (p = 0.000296, 1.33-2.6 95% CI) and a 2.35-fold increase for hospitalization (p = 0.005, 1.32-4.34 95% CI). The continuous monitoring of this and other variants will be required to control the ongoing pandemic as it evolves.

Inadequate prediction of postoperative complications in breast cancer surgery: An evaluation of the ACS Surgical Risk Calculator.

BACKGROUND: The American College of Surgeon (ACS) Surgical Risk Calculator is an online tool that helps surgeons estimate the risk of postoperative complications for numerous surgical procedures across several surgical specialties. METHODS: We evaluated the predictive performance of the calculator in 385 cancer patients undergoing breast surgery. Calculator-predicted complication rates were compared with observed complication rates; calculator performance was evaluated using calibration and discrimination analyses. RESULTS: The mean calculator-predicted rates for any complication (4.1%) and serious complication (3.2%) were significantly lower than the observed rates (11.2% and 5.2%, respectively). The area under the curve was 0.617 for any complication and 0.682 for serious complications. p Values for the Hosmer-Lemeshow test were significant (<.05) for both outcomes. Brier scores were 0.102 for any complication and 0.048 for serious complication. CONCLUSIONS: The ACS risk calculator is not an ideal tool for predicting individual risk of complications following breast surgery in a Mexican cohort. The most valuable use of the calculator may reside in its role as an aid for patient-led surgery planning. The possibility of introducing breast surgery-specific data could improve the performance of the calculator. Furthermore, a disease-specific calculator could provide more accurate predictions and include complications more frequently found in breast cancer surgery.