Coronavirus disease 2019 and allergen immunotherapy

Larenas‐Linnemann, Désiree; Rodríguez-Pérez, Noel; Ortega-Martell, José Antonio; Blandón-Vijil, Virginia; Luna-Pech, Jorge A.

doi:10.1016/j.anai.2020.06.009

Cited by 13 publications

(6 citation statements)

References 10 publications

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“…Aunque ambas modalidades (ITSC e ITSL) han demostrado ser eficaces, en GUIDAMEX preferimos la ITSL por su mejor perfil de seguridad, la posibilidad de usarla incluso en niños muy pequeños, a partir de los 3 años, y la menor sobreestimulación de la piel en los primeros dos o tres meses comparada con la ITSC. Existen reportes de que con los primeros viales de ITSC se exacerba la DA, lo que podría limitar el apego al tratamiento si no se ajusta la pauta de aplicación oportunamente 110 .…”

Section: Inmunoterapia Con Aeroalérgenos (Ita)unclassified

Guía de dermatitis atópica para México (GUIDAMEX): lineamientos usando metodología ADAPTE

Larenas‐Linnemann¹,

Rincón-Pérez²,

Luna-Pech³

et al. 2023

GMM

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Section: Inmunoterapia Con Aeroalérgenos (Ita)unclassified

Guía de dermatitis atópica para México (GUIDAMEX): lineamientos usando metodología ADAPTE

Larenas‐Linnemann¹,

Rincón-Pérez²,

Luna-Pech³

et al. 2023

GMM

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“…It appears therefore conceivable that the immune tolerance induced by AIT might have a putative protective role in severe COVID-19 patients with cytokine storm. Furthermore, starting AIT in eligible patients, the sublingual route of administration (SLIT) is preferred to minimize in-person encounters for subcutaneous injections (SCIT); indeed, SLIT can be administered at home, thus avoiding the need to travel to or stay in an allergy clinic or doctor's office, which would be associated with a risk of infection [153,154].…”

Section: Allergen Immunotherapy and Covid-19mentioning

confidence: 99%

Asthma and COVID-19: a dangerous liaison?

Lombardi

Gani²,

Berti

et al. 2021

asthma res and pract

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The coronavirus disease 2019 (COVID-19) pandemic, caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), provoked the most striking international public health crisis of our time. COVID-19 can cause a range of breathing problems, from mild to critical, with potential evolution to respiratory failure and acute respiratory distress syndrome. Elderly adults and those affected with chronic cardiovascular, metabolic, and respiratory conditions carry a higher risk of severe COVID-19. Given the global burden of asthma, there are well-founded concerns that the relationship between COVID-19 and asthma could represent a “dangerous liaison”.Here we aim to review the latest evidence on the links between asthma and COVID-19 and provide reasoned answers to current concerns, such as the risk of developing SARS-CoV-2 infection and/or severe COVID-19 stratified by asthmatic patients, the contribution of type-2 vs. non-type-2 asthma and asthma-COPD overlap to the risk of COVID-19 development. We also address the potential role of both standard anti-inflammatory asthma therapies and new biological agents for severe asthma, such as mepolizumab, reslizumab, and benralizumab, on the susceptibility to SARS-CoV-2 infection and severe COVID-19 outcomes.

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“…They represent true cases, false positive cases, false negative cases, and true negative cases, respectively, which indicate relationship between predicted value and the manual ground truth. Based on them, Accuracy (ACC), Precision (PRE), Recall (REC), and Dice Coefficient (DSC) [40] are defined as assessment indicators: (13) where ACC represents proportion of all voxels with correct predictions, including TP and TN; PRE introduces accuracy of the predicted positive cases; REC is the accuracy of correct infection prediction; DSC reveals coincidence rate of predicted value and the manual ground truth.…”

Section: Initializationmentioning

confidence: 99%

“…Thus, reconstruction of COVID-19 infection can provide a digital model and quantitative analysis basis for diagnosis and treatment of COVID-19. It helps to build a more objective evaluation system and provides theoretical guidance for staff in related fields [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

DW-UNet: Loss Balance under Local-Patch for 3D Infection Segmentation from COVID-19 CT Images

Chen

Zhou

et al. 2021

Diagnostics

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(1) Background: COVID-19 has been global epidemic. This work aims to extract 3D infection from COVID-19 CT images; (2) Methods: Firstly, COVID-19 CT images are processed with lung region extraction and data enhancement. In this strategy, gradient changes of voxels in different directions respond to geometric characteristics. Due to the complexity of tubular tissues in lung region, they are clustered to the lung parenchyma center based on their filtered possibility. Thus, infection is improved after data enhancement. Then, deep weighted UNet is established to refining 3D infection texture, and weighted loss function is introduced. It changes cost calculation of different samples, causing target samples to dominate convergence direction. Finally, the trained network effectively extracts 3D infection from CT images by adjusting driving strategy of different samples. (3) Results: Using Accuracy, Precision, Recall and Coincidence rate, 20 subjects from a private dataset and eight subjects from Kaggle Competition COVID-19 CT dataset tested this method in hold-out validation framework. This work achieved good performance both in the private dataset (99.94–00.02%, 60.42–11.25%, 70.79–09.35% and 63.15–08.35%) and public dataset (99.73–00.12%, 77.02–06.06%, 41.23–08.61% and 52.50–08.18%). We also applied some extra indicators to test data augmentation and different models. The statistical tests have verified the significant difference of different models. (4) Conclusions: This study provides a COVID-19 infection segmentation technology, which provides an important prerequisite for the quantitative analysis of COVID-19 CT images.

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Coronavirus disease 2019 and allergen immunotherapy

Cited by 13 publications

References 10 publications

Guía de dermatitis atópica para México (GUIDAMEX): lineamientos usando metodología ADAPTE

Guía de dermatitis atópica para México (GUIDAMEX): lineamientos usando metodología ADAPTE

Asthma and COVID-19: a dangerous liaison?

DW-UNet: Loss Balance under Local-Patch for 3D Infection Segmentation from COVID-19 CT Images

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