Imaging features and ultraearly hematoma growth in intracerebral hemorrhage associated with COVID-19

Purpose: Intracerebral hemorrhage (ICH) is an uncommon but deadly event in patients with COVID-19 and its imaging features remain poorly characterized. We aimed to describe the clinical and imaging features of COVID-19-associated ICH. Methods: Multicenter, retrospective, case-control analysis comparing ICH in COVID-19 patients (COV19\u2009+) versus controls without COVID-19 (COV19\u2009-). Clinical presentation, laboratory markers, and severity of COVID-19 disease were recorded. Non-contrast computed tomography (NCCT) markers (intrahematoma hypodensity, heterogeneous density, blend sign, irregular shape fluid level), ICH location, and hematoma volume (ABC/2 method) were analyzed. The outcome of interest was ultraearly hematoma growth (uHG) (defined as NCCT baseline ICH volume/onset-to-imaging time), whose predictors were explored with multivariable linear regression. Results: A total of 33 COV19\u2009+\u2009patients and 321 COV19\u2009-\u2009controls with ICH were included. Demographic characteristics and vascular risk factors were similar in the two groups. Multifocal ICH and NCCT markers were significantly more common in the COV19\u2009+\u2009population. uHG was significantly higher among COV19\u2009+\u2009patients (median 6.2 mL/h vs 3.1 mL/h, p\u2009=\u20090.027), and this finding remained significant after adjustment for confounding factors (systolic blood pressure, antiplatelet and anticoagulant therapy), in linear regression (B(SE)\u2009=\u20090.31 (0.11), p\u2009=\u20090.005). This association remained consistent also after the exclusion of patients under anticoagulant treatment (B(SE)\u2009=\u20090.29 (0.13), p\u2009=\u20090.026). Conclusions: ICH in COV19\u2009+\u2009patients has distinct NCCT imaging features and a higher speed of bleeding. This association is not mediated by antithrombotic therapy and deserves further research to characterize the underlying biological mechanisms

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

The impact of COVID-19 pandemic on AMI and stroke mortality in Lombardy: Evidence from the epicenter of the pandemic

Background The first Covid-19 epidemic outbreak has enormously impacted the delivery of clinical healthcare and hospital management practices in most of the hospitals around the world. In this context, it is important to assess whether the clinical management of non-Covid patients has not been compromised. Among non-Covid cases, patients with Acute Myocardial Infarction (AMI) and stroke need non-deferrable emergency care and are the natural candidates to be studied. Preliminary evidence suggests that the time from onset of symptoms to emergency department (ED) presentation has significantly increased in Covid-19 times as well as the 30-day mortality and in-hospital mortality.Methods We check, in a causal inference framework, the causal effect of the hospital's stress generated by Covid-19 pandemic on in-hospital mortality rates (primary end-point of the study) of AMI and stroke over several time-windows of 15-days around the implementation date of the State of Emergency restrictions for COVID-19 (March, 9(th) 2020) using two quasi-experimental approaches, regression-discontinuity design (RDD) and difference-in-regression-discontinuity (DRD) designs. Data are drawn from Spedali Civili of Brescia, one of the most hit provinces in Italy by Covid-19 during March and May 2020.Findings Despite the potential adverse effects on expected mortality due to a longer time to hospitalization and staff extra-burden generated by the first wave of Covid-19, the AMI and stroke mortality rates are overall not statistically different during the first wave of Covid-19 than before the first peak. The obtained results provided by RDD models are robust also when we account for seasonality and unobserved factors with DRD models.Interpretation The non-statistically significant impact on mortality rates for AMI and stroke patients provides evidence of the hospital ability to manage -with the implementation of a dual track organization- the simultaneous delivery of high-quality cares to both Covid and non-Covid patients

Magnitude and time-course of excess mortality during COVID-19 outbreak: population-based empirical evidence from highly impacted provinces in northern Italy

Background: The real impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on overall mortality remains uncertain as surveillance reports have attributed a limited number of deaths to novel coronavirus disease 2019 (COVID-19) during the outbreak. The aim of this study was to assess the excess mortality during the COVID-19 outbreak in highly impacted areas of northern Italy. Methods: We analysed data on deaths that occurred in the first 4 months of 2020 provided by the health protection agencies (HPAs) of Bergamo and Brescia (Lombardy), building a time-series of daily number of deaths and predicting the daily standardised mortality ratio (SMR) and cumulative number of excess deaths through a Poisson generalised additive model of the observed counts in 2020, using 2019 data as a reference. Results: We estimated that there were 5740 (95% credible set (CS) 5552–5936) excess deaths in the HPA of Bergamo and 3703 (95% CS 3535–3877) in Brescia, corresponding to a 2.55-fold (95% CS 2.50–2.61) and 1.93 (95% CS 1.89–1.98) increase in the number of deaths. The excess death wave started a few days later in Brescia, but the daily estimated SMR peaked at the end of March in both HPAs, roughly 2 weeks after the introduction of lockdown measures, with significantly higher estimates in Bergamo (9.4, 95% CI 9.1–9.7). Conclusion: Excess mortality was significantly higher than that officially attributed to COVID-19, disclosing its hidden burden likely due to indirect effects on the health system. Time-series analyses highlighted the impact of lockdown restrictions, with a lower excess mortality in the HPA where there was a smaller delay between the epidemic outbreak and their enforcement

The early phase of the COVID-19 epidemic in Lombardy, Italy

Background In the night of February 20, 2020, the first epidemic of the novel coronavirus disease (COVID-19) outside Asia was uncovered by the identification of its first patient in Lombardy region, Italy. In the following weeks, Lombardy experienced a sudden increase in the number of ascertained infections and strict measures were imposed to contain the epidemic spread. Methods We analyzed official records of cases occurred in Lombardy to characterize the epidemiology of SARS-CoV-2 during the early phase of the outbreak. A line list of laboratory-confirmed cases was set up and later retrospectively consolidated, using standardized interviews to ascertained cases and their close contacts. We provide estimates of the serial interval, of the basic reproduction number, and of the temporal variation of the net reproduction number of SARS-CoV-2. Results Epidemiological investigations detected over 500 cases (median age: 69, IQR: 57–78) before the first COVID-19 diagnosed patient (February 20, 2020), and suggested that SARS-CoV-2 was already circulating in at least 222 out of 1506 (14.7%) municipalities with sustained transmission across all the Lombardy provinces. We estimated the mean serial interval to be 6.6 days (95% CrI, 0.7–19). Our estimates of the basic reproduction number range from 2.6 in Pavia (95% CI, 2.1–3.2) to 3.3 in Milan (95% CI, 2.9–3.8). A decreasing trend in the net reproduction number was observed following the detection of the first case. Conclusions At the time of first case notification, COVID-19 was already widespread in the entire Lombardy region. This may explain the large number of critical cases experienced by this region in a very short timeframe. The slight decrease of the reproduction number observed in the early days after February 20, 2020 might be due to increased population awareness and early interventions implemented before the regional lockdown imposed on March 8, 2020

The early phase of the COVID-19 epidemic in Lombardy, Italy

Background: In the night of February 20, 2020, the first epidemic of the novel coronavirus disease (COVID-19) outside Asia was uncovered by the identification of its first patient in Lombardy region, Italy. In the following weeks, Lombardy experienced a sudden increase in the number of ascertained infections and strict measures were imposed to contain the epidemic spread. Methods: We analyzed official records of cases occurred in Lombardy to characterize the epidemiology of SARSCoV- 2 during the early phase of the outbreak. A line list of laboratory-confirmed cases was set up and later retrospectively consolidated, using standardized interviews to ascertained cases and their close contacts. We provide estimates of the serial interval, of the basic reproduction number, and of the temporal variation of the net reproduction number of SARS-CoV-2

IER-START nomogram for prediction of three-month unfavorable outcome after thrombectomy for stroke

BACKGROUND: The applicability of the current models for predicting functional outcome after thrombectomy in strokes with large vessel occlusion (LVO) is affected by a moderate predictive performance. AIMS: We aimed to develop and validate a nomogram with pre- and post-treatment factors for prediction of the probability of unfavorable outcome in patients with anterior and posterior LVO who received bridging therapy or direct thrombectomy <6 h of stroke onset. METHODS: We conducted a cohort study on patients data collected prospectively in the Italian Endovascular Registry (IER). Unfavorable outcome was defined as three-month modified Rankin Scale (mRS) score 3-6. Six predictors, including NIH Stroke Scale (NIHSS) score, age, pre-stroke mRS score, bridging therapy or direct thrombectomy, grade of recanalization according to the thrombolysis in cerebral ischemia (TICI) grading system, and onset-to-end procedure time were identified a priori by three stroke experts. To generate the IER-START, the pre-established predictors were entered into a logistic regression model. The discriminative performance of the model was assessed by using the area under the receiver operating characteristic curve (AUC-ROC). RESULTS: A total of 1802 patients with complete data for generating the IER-START was randomly dichotomized into training ( n = 1219) and test ( n = 583) sets. The AUC-ROC of IER-START was 0.838 (95% confidence interval [CI]): 0.816-0.869) in the training set, and 0.820 (95% CI: 0.786-0.854) in the test set. CONCLUSIONS: The IER-START nomogram is the first prognostic model developed and validated in the largest population of stroke patients currently candidates to thrombectomy which reliably calculates the probability of three-month unfavorable outcome