CT Scan-Guided Fine Needle Aspiration Cytology for Lung Cancer Diagnosis through the COVID-19 Pandemic: What We Have Learned.

BACKGROUND AND RATIONALE: Novel coronavirus-related disease (COVID-19) has profoundly influenced hospital organization and structures worldwide. In Italy, the Lombardy Region, with almost 17% of the Italian population, rapidly became the most severely affected area since the pandemic beginning. The first and the following COVID-19 surges significantly affected lung cancer diagnosis and subsequent management. Much data have been already published regarding the therapeutic repercussions whereas very few reports have focused on the consequences of the pandemic on diagnostic procedures. METHODS: We, here, would like to analyze data of novel lung cancer diagnosis performed in our Institution in Norther Italy where we faced the earliest and largest outbreaks of COVID-19 in Italy. RESULTS: We discuss, in detail, the strategies developed to perform biopsies and the safe pathways created in emergency settings to protect lung cancer patients in subsequent therapeutic phases. Quite unexpectedly, no significant differences emerged between cases enrolled during the pandemic and those before, and the two populations were homogeneous considering the composition and diagnostic and complication rates. CONCLUSIONS: By pointing out the role of multidisciplinarity in emergency contexts, these data will be of help in the future for designing tailored strategies to manage lung cancer in a real-life setting.

Machine Learning-based Voice Assessment for the Detection of Positive and Recovered COVID-19 Patients.

Many virological tests have been implemented during the Coronavirus Disease 2019 (COVID-19) pandemic for diagnostic purposes, but they appear unsuitable for screening purposes. Furthermore, current screening strategies are not accurate enough to effectively curb the spread of the disease. Therefore, the present study was conducted within a controlled clinical environment to determine eventual detectable variations in the voice of COVID-19 patients, recovered and healthy subjects, and also to determine whether machine learning-based voice assessment (MLVA) can accurately discriminate between them, thus potentially serving as a more effective mass-screening tool. Three different subpopulations were consecutively recruited: positive COVID-19 patients, recovered COVID-19 patients and healthy individuals as controls. Positive patients were recruited within 10 days from nasal swab positivity. Recovery from COVID-19 was established clinically, virologically and radiologically. Healthy individuals reported no COVID-19 symptoms and yielded negative results at serological testing. All study participants provided three trials for multiple vocal tasks (sustained vowel phonation, speech, cough). All recordings were initially divided into three different binary classifications with a feature selection, ranking and cross-validated RBF-SVM pipeline. This brough a mean accuracy of 90.24%, a mean sensitivity of 91.15%, a mean specificity of 89.13% and a mean AUC of 0.94 across all tasks and all comparisons, and outlined the sustained vowel as the most effective vocal task for COVID discrimination. Moreover, a three-way classification was carried out on an external test set comprised of 30 subjects, 10 per class, with a mean accuracy of 80% and an accuracy of 100% for the detection of positive subjects. Within this assessment, recovered individuals proved to be the most difficult class to identify, and all the misclassified subjects were declared positive; this might be related to mid and short-term vocal traces of COVID-19, even after the clinical resolution of the infection. In conclusion, MLVA may accurately discriminate between positive COVID-19 patients, recovered COVID-19 patients and healthy individuals. Further studies should test MLVA among larger populations and asymptomatic positive COVID-19 patients to validate this novel screening technology and test its potential application as a potentially more effective surveillance strategy for COVID-19.

Venous thromboembolism and COVID-19: a single center experience from an academic tertiary referral hospital of Northern Italy.

Preliminary evidence supports the notion that COVID-19 patients may have an increased susceptibility to develop venous thromboembolism (VTE). However, the magnitude of this association still needs to be defined. Furthermore, clinical predictors of thrombogenesis, and the relationship with the inflammatory status are currently unknown. On this basis, we conducted a retrospective, observational study on 259 consecutive COVID-19 patients admitted to an academic tertiary referral hospital in Northern Italy between March 19th and April 6th, 2020. Records of COVID-19 patients with a definite VTE event were reviewed for demographic information, co-morbidities, risk factors for VTE, laboratory tests, and anticoagulation treatment. Twenty-five cases among 259 COVID-19 patients developed VTE (9.6%), all of them having a Padua score > 4, although being under standard anticoagulation prophylaxis since hospital admission. In the VTE subcohort, we found a significant positive correlation between platelet count (PLT) and either C reactive protein (CRP) (p < 0.0001) or lactate dehydrogenase (LDH) (p = 0.0013), while a significant inverse correlation was observed between PLT and mean platelet volume (p < 0.0001). Platelet-to-lymphocyte ratio significantly correlated with CRP (p < 0.0001). The majority of VTE patients was male and younger compared to non-VTE patients (p = 0.002 and p = 0.005, respectively). No significant difference was found in D-dimer levels between VTE and non VTE patients, while significantly higher levels of LDH (p = 0.04) and IL-6 (p = 0.04) were observed in VTE patients in comparison to non-VTE patients. In conclusion, our findings showed a quite high prevalence of VTE in COVID-19 patients. Raised inflammatory indexes and increased serum levels of pro-inflammatory cytokines should raise the clinical suspicion of VTE.

Cardiac involvement at presentation in patients hospitalized with COVID-19 and their outcome in a tertiary referral hospital in Northern Italy.

The correlation between myocardial injury and clinical outcome in COVID-19 patients is gaining attention in the literature. The aim of the present study was to evaluate the role of cardiac involvement and of respiratory failure in a cohort of COVID-19 patients hospitalized in an academic hospital in Lombardy, one of the most affected Italian (and worldwide) regions by the epidemic. The study included 405 consecutive patients with confirmed COVID-19 admitted to a medical ward from February 25th to March 31st, 2020. Follow-up of surviving patients ended either at hospital discharge or by July 30th, 2020. Myocardial injury was defined on the basis of the presence of blood levels of hs-TnI above the 99th percentile upper reference limit. Respiratory function was assessed as PaO2/FiO2 (P/F) ratio. The primary end-point was death for any cause. During hospitalization, 124 patients died. Death rate increased from 7.9% in patients with normal hs-TnI plasma levels and no cardiac comorbidity to 61.5% in patients with elevated hs-TnI and cardiac involvement (p < 0.001). At multivariable analysis, older age, P/F ratio < 200 (both p < 0.001) and hs-TnI plasma levels were independent predictors of death. However, it must be emphasized that the median values of hs-TnI were within normal range in non-survivors. Cardiac involvement at presentation was associated with poor prognosis in COVID-19 patients, but, even in a population of COVID-19 patients who did not require invasive ventilation at hospital admission, mortality was mainly driven by older age and respiratory failure.