External validation of the ADA score for predicting thrombosis among acutely ill hospitalized medical patients from the APEX Trial.

The ADA (Age-D-dimer-Albumin) score was developed to identify hospitalized patients at an increased risk for thrombosis in the coronavirus infectious disease-19 (COVID-19) setting. The study aimed to validate the ADA score for predicting thrombosis in a non-COVID-19 medically ill population from the APEX trial. The APEX trial was a multinational, randomized trial that evaluated the efficacy and safety of betrixaban vs. enoxaparin among acutely ill hospitalized patients at risk for venous thromboembolism. The study endpoints included the composite of arterial or venous thrombosis and its components. Metrics of model calibration and discrimination were computed for assessing the performance of the ADA score as compared to the IMPROVE score, a well-validated VTE risk assessment model. Among 7,119 medical inpatients, 209 (2.9%) had a thrombosis event up to 77 days of follow-up. The ADA score demonstrated good calibration for both arterial and venous thrombosis, whereas the IMPROVE score had adequate calibration for venous thrombosis (p > 0.05 from the Hosmer-Lemeshow test). For discriminating arterial and venous thrombosis, there was no significant difference between the ADA vs. IMPROVE score (c statistic = 0.620 [95% CI: 0.582 to 0.657] vs. 0.590 [95% CI: 0.556 to 0.624]; ∆ c statistic = 0.030 [95% CI: -0.022 to 0.081]; p = 0.255). Similarly, for discriminating arterial thrombosis, there was no significant difference between the ADA vs. IMPROVE score (c statistic = 0.582 [95% CI: 0.534 to 0.629] vs. 0.609 [95% CI: 0.564 to 0.653]; ∆ c statistic = -0.027 [95% CI: -0.091 to 0.036]; p = 0.397). For discriminating venous thrombosis, the ADA score was modestly superior to the IMPROVE score (c statistic = 0.664 [95% CI: 0.607 to 0.722] vs. 0.573 [95% CI: 0.521 to 0.624]; ∆ c statistic = 0.091 [95% CI: 0.011 to 0.172]; p = 0.026). The ADA score had a higher sensitivity (0.579 [95% CI: 0.512 to 0.646]; vs. 0.440 [95% CI: 0.373 to 0.507]) but lower specificity (0.625 [95% CI: 0.614 to 0.637] vs. 0.747 [95% CI: 0.737 to 0.758]) than the IMPROVE score for predicting thrombosis. Among acutely ill hospitalized medical patients enrolled in the APEX trial, the ADA score demonstrated good calibration but suboptimal discrimination for predicting thrombosis. The findings support the use of either the ADA or IMPROVE score for thrombosis risk assessment. The applicability of the ADA score to non-COVID-19 populations warrants further research.Clinical Trial Registration: http://www.clinicaltrials.gov . Unique identifier: NCT01583218.

A Survey on Methodological Issues of Clinical Research Studies Reviewed by Independent Ethic Committees during the COVID-19 Pandemic in Italy.

The struggle for information and the hasty search for answers caused by the COVID-19 pandemic threatened the possibility of lowering study quality, as well as ethical committees' review standards during the outbreak. Our investigation aimed to assess the impact of COVID-19 on the quality of clinical research studies submitted to Italian Ethics Committees in the period between April and July 2020. All 91 Italian ethics committees were contacted via email in order to collect anonymized information on the type and quality of COVID-19-related studies submitted to each committee during the study period. The present study summarizes the characteristics of the 184 study applications collected, pointing out, especially, how the quality of the study population and statistical analysis are crucial variables in determining the study approval. Nevertheless, despite the need for high-quality and open scientific information, especially exacerbated by this particular historical period, only a minority of the ethics committees (20.9%) agreed to share their data; such scarce participation, beyond biasing the representativeness of the results obtained by the present study, more importantly, hinders the broader goal of creating trust between researchers and the general public.

Association of serum Krebs von den Lungen-6 and chest CT as potential prognostic factors in severe acute respiratory syndrome SARS-CoV-2: a preliminary experience.

PURPOSE: To correlate in COVID-19 pneumonia CT-based semi-quantitative score of pulmonary involvement with high serum levels of KL-6, a biomarker of disease severity. METHODS: Between March 28 to May 21, 2020, 196 patients with strong suspicion of SARS-CoV-2 were evaluated with RT-PCR for SARS-CoV-2, chest CT scan and blood test, including KL-6 serum protein, in our Emergency Unit. The final population included only patients who underwent blood sampling for KL-6 within 5 days from CT scan (n = 63), including n = 37 COVID-19-positive patients and n = 26 with negative RT-PCR testing for SARS-CoV-2 (control group). A semi-quantitative CT score was calculated based on the extent of lobar involvement (0:0%; 1, < 5%; 2:5-25%; 3:26-50%; 4:51-75%; 5, > 75%; range 0-5; global score 0-25). RESULTS: CT score was significantly correlated with serum value of KL-6 (r = 27, p = 0.035). This correlation was also present in COVID-19 positive patients (r = 0.423, p = 0.009) and CT score median value was significantly higher in patients with high KL-6 value (> 400 U/mL; 12.00, IQR 5.00-18.00, p-value 0.027). In control group, no statistically significant correlation was found between CT score and KL-6 value and CT score was higher in patients with high KL-6, although this difference was not statistically significant (5.00, IQR:1.75-8.00 versus 3.50, IQR:2.00-6.50). "Crazy paving" at the right upper (n = 8; 61.5%) and middle lobe (n = 4; 30.8%) and "consolidation" at the middle lobe (n=5; 38.5%) were observed in COVID-19 group with a significant difference between patients with high KL-6 value. CONCLUSION: CT score is highly correlated with KL-6 value in COVID-19 patients and might be beneficial to speed-up diagnostic workflow in symptomatic cases.

Sleep Quality and Its Associations with Physical and Mental Health-Related Quality of Life among University Students: A Cross-Sectional Study.

The association between sleep problems and quality of life has been well documented and the COVID-19 pandemic seemingly had an impact on both sleep quality and health-related quality of life (HRQoL). However, recent evidence about this relationship among university students is limited. The aims of this study are to investigate the prevalence of poor sleep quality and insomnia and to explore the associations between these outcomes, perceived stress, and HRQoL among Italian university students. An anonymous questionnaire comprising the Pittsburgh Sleep Quality Index, the Insomnia Severity Index, the Short Form-12 health survey, and the Perceived Stress Scale was administered to a convenience sample of 1279 students (1119 females and 160 males, mean age: 23.4 ± 2.5 years) attending one of the largest Italian universities. A total of 65% of the participants showed poor sleep quality, whereas 55% reported insomnia symptoms. Students reporting poor sleep quality and insomnia obtained higher perceived stress scores and lower physical and mental HRQoL scores. Controlling for health-related variables and perceived stress, hierarchical regression analyses showed that sleep quality components added a significant contribution to the prediction of both physical (ΔR2 = 0.1) and mental (ΔR2 = 0.02) HRQoL. As a whole, these findings confirm the relevance of sleep for university students' well-being and might inform the development of health promotion interventions for this population.

Pfizer-BioNTech COVID-19 Vaccine in Gynecologic Oncology Patients: A Prospective Cohort Study.

OBJECTIVE: To evaluate the safety and immunogenicity of the Pfizer-BioNTech COVID-19 vaccine in gynecologic oncology patients under chemotherapy. METHODS: A prospective cohort study including gynecologic oncology women who were under chemotherapy or had completed it within 6 months at the time of the study. All patients received a two-dose schedule of the Pfizer-BioNTech COVID-19 vaccine. Results were compared with a control group of healthy women vaccinated in the same period. RESULTS: Overall, 44 oncologic patients with a mean age of 61.3 ± 10.7 years were enrolled: 28 (63.6%) had ovarian cancer, 9 (20.4%) endometrial, and 7 (16%) cervical. The IgG antibody titer after 1 month from vaccination was low in 9 (20.5%) patients, moderate in 21 (47.7%), and high in 14 (31.8%). The 3-month titer was null in 2 (4.5%) patients, low in 26 (59.1%), moderate in 13 (29.5%), and high in 3 (6.8%). Patients ≥ 50 years reported lower 1-month (p = 0.018) and 3-month (p = 0.004) titers compared with <50 years. Patients with BMI < 30 kg/m2 had a higher 1-month titer compared with BMI ≥ 30 kg/m2 (p = 0.016). Compared with healthy women (n = 44), oncologic patients showed a lower 3-month titer (p < 0.001). None of the patients experienced serious adverse effects. CONCLUSIONS: The COVID-19 vaccine was safe and immunogenic in gynecologic oncology patients under chemotherapy. Serological monitoring and further vaccine shots should be considered to boost protection.

New statistical RI index allow to better track the dynamics of COVID-19 outbreak in Italy.

COVID-19 pandemic in Italy displayed a spatial distribution that made the tracking of its time course quite difficult. The most relevant anomaly was the marked spatial heterogeneity of COVID-19 diffusion. Lombardia region accounted for around 60% of fatal cases (while hosting 15% of Italian population). Moreover, 86% of fatalities concentrated in four Northern Italy regions. The 'explosive' outbreak of COVID-19 in Lombardia at the very beginning of pandemic fatally biased the R-like statistics routinely used to control the disease dynamics. To (at least partially) overcome this bias, we propose a new index RI = dH/dI (daily derivative ratio of H and I, given H = Healed and I = Infected), corresponding to the ratio between healed and infected patients relative daily changes. The proposed index is less flawed than R by the uncertainty related to the estimated number of infected persons and allows to follow (and possibly forecast) epidemic dynamics in a largely model-independent way. To analyze the dynamics of the epidemic, starting from the beginning of the virus spreading-when data are insufficient to make an estimate by adopting SIR model-a "sigmoidal family with delay" logistic model was introduced. That approach allowed in estimating the epidemic peak using the few data gathered even before mid-March. Based on this analysis, the peak was correctly predicted to occur by end of April. Analytical methodology of the dynamics of the epidemic we are proposing herein aims to forecast the time and intensity of the epidemic peak (forward prediction), while allowing identifying the (more likely) beginning of the epidemic (backward prediction). In addition, we established a relationship between hospitalization in intensive care units (ICU) versus deaths daily rates by avoiding the necessity to rely on precise estimates of the infected fraction of the population The joint evolution of the above parameters over time allows for a trustworthy and unbiased estimation of the dynamics of the epidemic, allowing us to clearly detect the qualitatively different character of the 'so-called' second wave with respect to the previous epidemic peak.