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1.
Sexes ; 2(1):104, 2021.
Article in English | ProQuest Central | ID: covidwho-1834879

ABSTRACT

The attention to transgender medicine has changed over the last decade and the interest is most likely going to increase in the future due to the fact that gender-affirming treatments are now being requested by an increasing number of transgender people. Even if gender-affirming hormone therapy (GAHT) is based on a multidisciplinary approach, this review is going to focus on the procedures adopted by the endocrinologist in an out-clinic setting once an adult patient is referred by another specialist for ‘gender affirming’ therapy. Before commencing this latter treatment, several background information on unmet needs regarding medical and surgical outcomes should be investigated. We summarized our endocrinological clinical and therapeutic approaches to adult transgender individuals before and during GAHT based on a non-systematic review. Moreover, the possible relationships between GAHT, gender-related pharmacology, and COVID-19 are also reported.

2.
Sensors (Basel) ; 21(24)2021 Dec 20.
Article in English | MEDLINE | ID: covidwho-1580509

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic has affected hundreds of millions of individuals and caused millions of deaths worldwide. Predicting the clinical course of the disease is of pivotal importance to manage patients. Several studies have found hematochemical alterations in COVID-19 patients, such as inflammatory markers. We retrospectively analyzed the anamnestic data and laboratory parameters of 303 patients diagnosed with COVID-19 who were admitted to the Polyclinic Hospital of Bari during the first phase of the COVID-19 global pandemic. After the pre-processing phase, we performed a survival analysis with Kaplan-Meier curves and Cox Regression, with the aim to discover the most unfavorable predictors. The target outcomes were mortality or admission to the intensive care unit (ICU). Different machine learning models were also compared to realize a robust classifier relying on a low number of strongly significant factors to estimate the risk of death or admission to ICU. From the survival analysis, it emerged that the most significant laboratory parameters for both outcomes was C-reactive protein min; HR=17.963 (95% CI 6.548-49.277, p < 0.001) for death, HR=1.789 (95% CI 1.000-3.200, p = 0.050) for admission to ICU. The second most important parameter was Erythrocytes max; HR=1.765 (95% CI 1.141-2.729, p < 0.05) for death, HR=1.481 (95% CI 0.895-2.452, p = 0.127) for admission to ICU. The best model for predicting the risk of death was the decision tree, which resulted in ROC-AUC of 89.66%, whereas the best model for predicting the admission to ICU was support vector machine, which had ROC-AUC of 95.07%. The hematochemical predictors identified in this study can be utilized as a strong prognostic signature to characterize the severity of the disease in COVID-19 patients.


Subject(s)
COVID-19 , Hospital Mortality , Humans , Machine Learning , Prognosis , Retrospective Studies , SARS-CoV-2 , Survival Analysis
3.
Electronics ; 10(20):2475, 2021.
Article in English | MDPI | ID: covidwho-1463591

ABSTRACT

The COVID-19 pandemic is inevitably changing the world in a dramatic way, and the role of computed tomography (CT) scans can be pivotal for the prognosis of COVID-19 patients. Since the start of the pandemic, great care has been given to the relationship between interstitial pneumonia caused by the infection and the onset of thromboembolic phenomena. In this preliminary study, we collected n = 20 CT scans from the Polyclinic of Bari, all from patients positive with COVID-19, nine of which developed pulmonary thromboembolism (PTE). For eight CT scans, we obtained masks of the lesions caused by the infection, annotated by expert radiologists;whereas for the other four CT scans, we obtained masks of the lungs (including both healthy parenchyma and lesions). We developed a deep learning-based segmentation model that utilizes convolutional neural networks (CNNs) in order to accurately segment the lung and lesions. By considering the images from publicly available datasets, we also realized a training set composed of 32 CT scans and a validation set of 10 CT scans. The results obtained from the segmentation task are promising, allowing to reach a Dice coefficient higher than 97%, posing the basis for analysis concerning the assessment of PTE onset. We characterized the segmented region in order to individuate radiomic features that can be useful for the prognosis of PTE. Out of 919 extracted radiomic features, we found that 109 present different distributions according to the Mann–Whitney U test with corrected p-values less than 0.01. Lastly, nine uncorrelated features were retained that can be exploited to realize a prognostic signature.

4.
Int J Environ Res Public Health ; 17(10)2020 05 22.
Article in English | MEDLINE | ID: covidwho-361256

ABSTRACT

Patients with diabetes have been reported to have enhanced susceptibility to severe or fatal COVID-19 infections, including a high risk of being admitted to intensive care units with respiratory failure and septic complications. Given the global prevalence of diabetes, affecting over 450 million people worldwide and still on the rise, the emerging COVID-19 crisis poses a serious threat to an extremely large vulnerable population. However, the broad heterogeneity and complexity of this dysmetabolic condition, with reference to etiologic mechanisms, degree of glycemic derangement and comorbid associations, along with the extensive sexual dimorphism in immune responses, can hamper any patient generalization. Even more relevant, and irrespective of glucose-lowering activities, DPP4 inhibitors and GLP1 receptor agonists may have a favorable impact on the modulation of viral entry and overproduction of inflammatory cytokines during COVID-19 infection, although current evidence is limited and not univocal. Conversely, SGLT2 inhibitors may increase the likelihood of COVID-19-related ketoacidosis decompensation among patients with severe insulin deficiency. Mindful of their widespread popularity in the management of diabetes, addressing potential benefits and harms of novel antidiabetic drugs to clinical prognosis at the time of a COVID-19 pandemic deserves careful consideration.


Subject(s)
Betacoronavirus/isolation & purification , Coronavirus Infections/physiopathology , Hypoglycemic Agents/therapeutic use , Pandemics , Pneumonia, Viral/physiopathology , Blood Glucose , COVID-19 , Coronavirus Infections/epidemiology , Coronavirus Infections/virology , Diabetes Mellitus , Humans , Hypoglycemic Agents/adverse effects , Insulin , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , SARS-CoV-2
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