Management of Allergic Diseases During COVID-19 Outbreak

Coronavirus infections; Rhinitis, Allergic; Drug hypersensitivityInfecciones por coronavirus; Rinitis alérgica; Hipersensibilidad medicamentosaInfeccions per coronavirus; Rinitis al·lèrgica; Hipersensibilitat medicamentosaPurpose of review: The coronavirus disease 2019 (COVID-19) has challenged healthcare system capacities and safety for health care workers, reshaping doctor-patient interaction favoring e-Health or telemedicine. The pandemic situation may make difficult to prioritize patients with allergies diseases (AD), face-to-face evaluation, and moreover concern about the possible COVID-19 diagnosis, since COVID-19 shared many symptoms in common with AD. Being COVID-19 a novel disease, everyone is susceptible; there are some advances on vaccine and specific treatment. We evaluate existing literature on allergic diseases (AD): allergic rhinitis, asthma, food allergy, drug allergy, and skin allergy, and potential underlying mechanisms for any interrelationship between AD and COVID-19. Recent findings: There is inconclusive and controversial evidence of the association between AD and the risk of adverse clinical outcomes of COVID-19. AD patients should minimize hospital and face-to-face visits, and those who have used biologics and allergen immunotherapy should continue the treatment. It is essential to wear personal protective equipment for the protection of health care workers. Social distancing, rational use of facemasks, eye protection, and hand disinfection for health care workers and patients deserve further attention and promotion. Teleconsultation during COVID-19 times for AD patients is very encouraging and telemedicine platform can provide a reliable service in patient care

The 8-Odorant Barcelona Olfactory Test (BOT-8): Validation of a New Test in the Spanish Population During the COVID-19 Pandemic

COVID-19; Pèrdua d'olfacte; Prova de l'olfacteCOVID-19; Loss of smell; Smell testCOVID-19; Pérdida de olfato; Prueba del olfatoBackground and objective: Most smell tests are difficult to implement in daily clinical practice owing to their long duration. The aim of the present study was to develop and validate a short, easy-to-perform, and reusable smell test to be implemented during the COVID-19 pandemic. Methods: The study population comprised 120 healthy adults and 195 patients with self-reported olfactory dysfunction (OD). The 8-Odorant Barcelona Olfactory Test (BOT-8) was used for detection, memory/recognition, and forced-choice identification. In addition, a rose threshold test was performed, and a visual analog scale was applied. The Smell Diskettes Olfaction Test (SDOT) was used for correlation in healthy volunteers, and the University of Pennsylvania Smell Identification Test (UPSIT) was used for patients with OD to establish cut-offs for anosmia and hyposmia. In order to take account of the COVID-19 pandemic, disposable cotton swabs with odorants were compared with the original test. Results: In healthy persons, the mean (SD) BOT-8 score was 100% for detection, 94.5% (1.07) for memory/recognition, and 89.6% (0.86) for identification. In patients with OD, the equivalent values were 86% (32.8), 73.2% (37.9), and 77.1% (34.2), respectively. BOT-8 demonstrated good test-retest reliability, with agreement of 96.7% and a quadratic k of 0.84 (P<.001). A strong correlation was observed between BOT-8 and SDOT (r=0.67, P<.001) and UPSIT (r=0.86, P<.001). Agreement was excellent for disposable cotton swabs, with a k of 0.79 compared with the original test. The cut-off point for anosmia was ≤3 (area under the curve, 0.83; sensitivity, 0.673; specificity, 0.993). Conclusion: BOT-8 offers an efficient and fast method for assessment of smell threshold, detection, memory, and identification in daily clinical practice. Disposable cotton swabs with odorants proved to be useful and safe during the COVID-19 pandemic

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Clinical characterization of data-driven diabetes subgroups in Mexicans using a reproducible machine learning approach

Introduction Previous reports in European populations demonstrated the existence of five data-driven adult-onset diabetes subgroups. Here, we use self-normalizing neural networks (SNNN) to improve reproducibility of these data-driven diabetes subgroups in Mexican cohorts to extend its application to more diverse settings.Research design and methods We trained SNNN and compared it with k-means clustering to classify diabetes subgroups in a multiethnic and representative population-based National Health and Nutrition Examination Survey (NHANES) datasets with all available measures (training sample: NHANES-III, n=1132; validation sample: NHANES 1999–2006, n=626). SNNN models were then applied to four Mexican cohorts (SIGMA-UIEM, n=1521; Metabolic Syndrome cohort, n=6144; ENSANUT 2016, n=614 and CAIPaDi, n=1608) to characterize diabetes subgroups in Mexicans according to treatment response, risk for chronic complications and risk factors for the incidence of each subgroup.Results SNNN yielded four reproducible clinical profiles (obesity related, insulin deficient, insulin resistant, age related) in NHANES and Mexican cohorts even without C-peptide measurements. We observed in a population-based survey a high prevalence of the insulin-deficient form (41.25%, 95% CI 41.02% to 41.48%), followed by obesity-related (33.60%, 95% CI 33.40% to 33.79%), age-related (14.72%, 95% CI 14.63% to 14.82%) and severe insulin-resistant groups. A significant association was found between the SLC16A11 diabetes risk variant and the obesity-related subgroup (OR 1.42, 95% CI 1.10 to 1.83, p=0.008). Among incident cases, we observed a greater incidence of mild obesity-related diabetes (n=149, 45.0%). In a diabetes outpatient clinic cohort, we observed increased 1-year risk (HR 1.59, 95% CI 1.01 to 2.51) and 2-year risk (HR 1.94, 95% CI 1.13 to 3.31) for incident retinopathy in the insulin-deficient group and decreased 2-year diabetic retinopathy risk for the obesity-related subgroup (HR 0.49, 95% CI 0.27 to 0.89).Conclusions Diabetes subgroup phenotypes are reproducible using SNNN; our algorithm is available as web-based tool. Application of these models allowed for better characterization of diabetes subgroups and risk factors in Mexicans that could have clinical applications