Background: Some oral lesions have been described in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); the possibility has been raised that the buccal lesions observed in patients with the coronavirus disease 2019 (COVID-19) are due to this virus and the patient’s systemic condition. The aim of this review was to integrate the knowledge related to the oral lesions associated with COVID-19 and the participation of the buccal cavity in the establishment of immunity against SARS-CoV-2. Methods: A literature search on the manifestations of buccal lesions from the beginning of the pandemic until October 2021 was carried out by using the PubMed database. A total of 157 scientific articles were selected from the library, which included case reports and reports of lesions appearing in patients with COVID-19. Results: Oral lesions included erosions, ulcers, vesicles, pustules, plaques, depapillated tongue, and pigmentations, among others. The oral cavity is a conducive environment for the interaction of SARS-CoV-2 with the mucosal immune system and target cells; direct effects of the virus in this cavity worsen the antiviral inflammatory response of underlying oral disorders, immunodeficiencies, and autoimmunity primarily. Conclusions: The oral cavity is an accessible and privileged environment for the interaction of SARS-CoV-2 with the mucosal immune system and target cells; the direct effects of the virus in this cavity worsen the antiviral inflammatory response of underlying oral disorders, in particular those related to immunodeficiencies and autoimmunity.

Background: Acute appendicitis is a common emergency requiring abdominal surgery. Despite its prevalence, there are no specific biomarkers for its diagnosis and prognosis. The aim of this study was to assess the basic laboratory tests of patients with acute appendicitis and to evaluate and integrate biochemical variables into the diagnosis of appendicitis. Methods: This was a retrospective, cross-sectional cohort study that included data from patients who underwent an appendectomy. Two groups of patients were considered based on their surgical (non-complicated/complicated appendicitis) or pathological diagnosis (non-perforated/perforated appendicitis). Factor analysis was carried out to identify communalities to put forward classificatory indices. Receiver operating characteristic (ROC) analysis was used to assess the accuracy of the predictions. Results: The cohort included 246 patients (51.6% male, mean age: 24.79 ± 19.32 years). By using their biochemical data, we generated 6 new indices whose areas under the ROC curve (AUC) ranged between 0.632 and 0.762 for complicated appendicitis and from 0.597 to 0.742 for perforated appendicitis. Inflammatory Metabolic Index (IMI) at the fixed cutoffs was a promising biomarker for both histopathological and surgical diagnoses with odds ratios (OR) of 10.45 and 5.21, respectively. The Metabolic-Inflammatory Stress Index (MISI) showed high specificity (over 72%) and significant AUC values for both diagnoses (0.742 and 0.676). These findings were reinforced by significant p-values and Youden indices. Conclusions: IMI and MISI were demonstrated to be effective biomarkers for complicated and perforated appendicitis. IMI provides predictive capability, while MISI offers specificity and significant AUC values for both histopathological and surgical diagnoses. Incorporating these biomarkers could enhance the accuracy of appendicitis diagnosis and potentially guide clinical decision-making.

Objectives: To analyze the gene variants of the renin-angiotensin-aldosterone system and determine their association with the severity and outcome of COVID-19. Methods: A total of 104 patients were included in the study: 34 asymptomatic patients with COVID-19 as controls and 70 symptomatic patients as cases. The genetic variants ACE rs4343, ACE2 rs2074192, AGTR1 rs5182, and AGT rs4762 were identified using TaqMan genotyping tests. Results: Patients with the T/T genotype of AGTR1 rs5182 have a higher probability of developing symptomatic COVID-19 (odds ratio [OR] 12.25, 95% confidence interval [CI] 1.34-111.9, P <= 0.001) and a higher risk of hospitalization because of disease (OR 14.00, 95% CI 1.53-128.49, P = 0.012). The haplotype CTG ( AGTR1 rs5182, ACE2 rs2074192, ACE rs4343) decreased the odds of death related to COVID-19 in the study population (OR 0.03, 95% CI 0.0-0.06, P = 0.026). Conclusions: The T/T genotype of the AGTR1 rs5182 variant increased the probability of symptomatic COVID-19 and hospitalization, whereas the haplotype CTG (consisting of AGTR1 rs5182, ACE2 rs2074192, and ACE rs4343) decreased the odds of death related to COVID-19 by 97% in the hospitalized patients with COVID-19. These results support the participation of renin-angiotensin-aldosterone system gene variants as modifiers of the severity of symptoms associated with SARS-CoV-2 infection and the outcome of COVID-19. (c) 2024 The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )

Stevens–Johnson Syndrome (SJS)/toxic epidermal necrolysis (TEN) is a severe mucocutaneous reaction often induced by medications. The co-occurrence of SJS/TEN and COVID-19 presents a unique challenge due to overlapping inflammatory pathways. This case study examined the cytokine profile of a patient with both TEN (triggered by lamotrigine) and COVID-19. The clinical history of the patient, including lamotrigine exposure and COVID-19 diagnosis, was documented. A 13-cytokine profile assessment was performed in peripheral blood mononuclear cells from the patient and their parents by using quantitative Real Time-Polymerase Chain Reaction (qRT-PCR). A 6-year-old male patient developed lamotrigine-induced TEN with concomitant COVID-19 affecting 90% of the body surface area. Compared with their parents, who were positive for COVID-19, IL-6, IL-4, and IL-12 were modulated (downregulated) by TEN. The cytokine profile showed elevated levels of IL-1α, IL-1β, IL-5, IL-8, NF-κβ, and interferons (IFN; α, β, and γ), indicating a robust antiviral response. The immune profile suggested a hyperactivated immune state that contributed to the severity of the patient’s clinical manifestations, leading to death 18 days after hospitalization. Understanding the immune response is important for developing future targeted therapeutic strategies and improving patient outcomes. Further research is needed to explore the interaction between drug-induced SJS/TEN and infections.

Background: Acute appendicitis is the most common abdominal surgical emergency, with diagnostic uncertainty greatest in resource-limited settings. Objectives: To develop and internally validate an interpretable, laboratory-driven machine learning approach to assist clinical decision-making in suspected appendicitis, including diagnosis, perforation detection, and surgical severity stratification. Methods: A retrospective cohort of 246 patients with histopathologically confirmed appendicitis and 45 controls with similar abdominal pain was analyzed at a secondary-level hospital in Mexico. After cleaning and imputation, 41 laboratory variables were used to train three models: Random Forest for appendicitis detection and perforation identification, and Support Vector Machine for surgical severity stratification. Class imbalance was addressed with synthetic oversampling, and feature selection prioritized clinical interpretability. Results: Appendicitis detection achieved excellent discrimination (AUC = 0.94), correctly identifying 90% of cases, with 100% specificity. The perforation model reached 100% sensitivity (AUC = 0.875), prioritizing safe detection of high-risk cases, while severity stratification showed moderate performance (AUC = 0.721), correctly identifying 81% of complicated cases without imaging. Conclusions: Laboratory-based ML models accurately detected acute appendicitis and identified all perforated cases using routine data alone, while surgical severity stratification showed moderate discrimination in the absence of imaging. These findings demonstrate the feasibility of laboratory-driven decision support for early risk assessment in resource-limited emergency settings and support further external validation.