Burnout of health care providers during the COVID-19 pandemic: Focus on Medical Oncologists.

The spread of the coronavirus disease 2019 (Covid-19) has challenged hard the national health system worldwide. At any level, the role of health care providers has been rapidly revisited and eventually modified to face the pandemic. The search of the balance between the provision of the most appropriate health-related services and safety of both patients and health care providers has become an indisputable necessity. The consequently increased work load, along with a widespread feeling of intellectual isolation, emotional overload, sense of inadequacy for involvement in tasks and disciplines which are not always familiar have all been proposed as factors related to the onset and/or worsening of the burnout phenomenon. This latter is sadly renown among care givers and is particularly common among medical oncologists. We herein share our perspectives on the burnout phenomenon over the course of the Covid-19 pandemic, with a specific focus on medical oncologists. Results from the most recent and inherent studies are presented and commented in light of hints provided by the experience matured by a quite restricted, still potentially representative, number of professionals figures from the medical oncologists' category. Reasons are proposed to explain the sense of inadequacy currently perceived in relation to the limits imposed by the current pandemic. In more detail, we illustrate the nature and extents of some of the most relevant difficulties in the optimal management of cancer patients and constant efforts towards the scientific upgrade which allows for the improvement of the professional performance. The need for a deeper understanding of the roots and consequences of the Covid-19 pandemic on the mental health of medical oncologists is finally stressed.

COVID-19 risk in breast cancer patients receiving CDK4/6 inhibitors: literature data and a monocentric experience.

Substantial changes in the management of cancer patients have been required worldwide in response to the COVID-19 pandemic. Beyond the due details on the primitive cancer site and setting at diagnosis, these latter adaptions are most commonly exemplified by a significant reduction in the screening of asymptomatic subjects, delays in elective surgery and radiotherapy for primary tumors, and dose reductions and/or delays in systemic therapy administration. Advanced breast cancer patients with hormonal receptor positive, HER2 negative tumors are usually treated with endocrine therapy combined with CDK 4/6 inhibitors as first- and second-line treatment. During the pandemic, experts' recommendations have suggested the omission or delay of CDK 4/6 inhibitors delivery, or a careful evaluation of their real need due to the hypothesized increased risk of SARS-Cov-2 infection and disease possibly related to neutropenia. The inherent literature is sparse and inconsistent. We herein present data on the use of CDK 4/6 inhibitors during the pandemic. The evidence reported punctually reflects the experience matured at our Institution, a comprehensive cancer centre, on the topic of interest.

Automatic Pleural Line Extraction and COVID-19 Scoring From Lung Ultrasound Data.

Recent works highlighted the significant potential of lung ultrasound (LUS) imaging in the management of subjects affected by COVID-19. In general, the development of objective, fast, and accurate automatic methods for LUS data evaluation is still at an early stage. This is particularly true for COVID-19 diagnostic. In this article, we propose an automatic and unsupervised method for the detection and localization of the pleural line in LUS data based on the hidden Markov model and Viterbi Algorithm. The pleural line localization step is followed by a supervised classification procedure based on the support vector machine (SVM). The classifier evaluates the healthiness level of a patient and, if present, the severity of the pathology, i.e., the score value for each image of a given LUS acquisition. The experiments performed on a variety of LUS data acquired in Italian hospitals with both linear and convex probes highlight the effectiveness of the proposed method. The average overall accuracy in detecting the pleura is 84% and 94% for convex and linear probes, respectively. The accuracy of the SVM classification in correctly evaluating the severity of COVID-19 related pleural line alterations is about 88% and 94% for convex and linear probes, respectively. The results as well as the visualization of the detected pleural line and the predicted score chart, provide a significant support to medical staff for further evaluating the patient condition.