Clinical Impact of the COVID-19 Pandemic in Mexican Patients with Thoracic Malignancies

BACKGROUND: Accumulated evidence indicates that patients with lung cancer are a vulnerable population throughout the pandemic. Limited information is available in Latin America regarding the impact of the pandemic on medical care. The goal of this study was to describe the clinical and social effect of COVID-19 on patients with thoracic cancer and to ascertain outcomes in those with a confirmed diagnosis. MATERIALS AND METHODS: This cohort study included patients with thoracic neoplasms within a single institution between March 1, 2020, and February 28, 2021. All variables of interest were extracted from electronic medical records. During this period, the Depression Anxiety and Stress Scale 21 (DASS-2) was applied to evaluate and identify more common psychological disorders. RESULTS: The mean age for the total cohort (n = 548) was 61.5 ± 12.9 years; non-small cell lung cancer was the most frequent neoplasm (86.9%), advanced stages predominated (80%), and most patients were under active therapy (82.8%). Any change in treatment was reported in 23.9% of patients, of which 78.6% were due to the COVID-19 pandemic. Treatment delays (≥7 days) were the most frequent modifications in 41.9% of cases, followed by treatment suspension at 37.4%. Patients without treatment changes had a more prolonged progression-free survival and overall survival (hazard ratio [HR] 0.21, p < .001 and HR 0.28, p < .001, respectively). The mean DASS-21 score was 10.45 in 144 evaluated patients, with women being more affected than men (11.41 vs. 9.08, p < .001). Anxiety was reported in 30.5% of cases, followed by depression and distress in equal proportions (18%). Depressed and stressed patients had higher odds of experiencing delays in treatment than patients without depression (odds ratio [OR] 4.5, 95% confidence interval [CI] 1.53–13.23, p = .006 and OR 3.18, 95% CI 1.2–10.06, p = .006, respectively). CONCLUSION: Treatment adjustments in patients with thoracic malignancies often occurred to avoid COVID-19 contagion with detrimental effects on survival. Psychological disorders could have a role in adherence to the original treatment regimen

Aguará: An Improved Face Recognition Algorithm through Gabor Filter Adaptation

We developed an EBGM-based algorithm that successfully implements face recognition under constrained conditions. A suitable adaptation of the Gabor filters was found through a power spectral analisys (PSD) of the face images. We outperformed the best-known implementations of the EBGM algorithm in the FERET database. The results are comparable with those of the state of the art. 1