ABSTRACT
BackgroundCoronavirus disease 2019 (COVID-19) leads to peripheral and central disorders, frequently with neurological implications. Blood-brain barrier disruption (BBBd) has been hypothesized as a mechanisms in the acute phase. We tested whether markers of BBBd, brain injury and inflammation could help identify a blood signature for disease severity and neurological complications. MethodsBiomarkers of BBBd (MMP-9, GFAP), neuronal damage (NFL) and inflammation (PPIA, IL-10, TNF) were measured by SIMOA, AlphaLISA and ELISA, in two COVID-19 patient cohorts with high disease severity (ICU Covid; n=79) and neurological complications (NeuroCovid; n=78), and in two control groups with no COVID-19 history: healthy subjects (n=20) and patients with amyotrophic lateral sclerosis (ALS; n=51). ResultsBiomarkers of BBBd and neuronal damage were high in COVID-19 patients, with levels similar to or higher than in ALS. NeuroCovid patients had lower levels of PPIA but higher levels of MMP-9 than ICU Covid patients. There was evidence of different temporal dynamics in ICU Covid compared to NeuroCovid patients with PPIA and IL-10 levels highest in ICU Covid patients in the acute phase. In contrast, MMP-9 was higher in the acute phase in NeuroCovid patients, with severity-dependency in the long term. We also found clear severity-dependency of NFL and GFAP. ConclusionsThe overall picture points to an increased risk of neurological complications in patients with high levels of biomarkers of BBBd. Our observations may provide hints for therapeutic approaches mitigating BBBd to reduce the neurological damage in the acute phase and potential dysfunction in the long term.
ABSTRACT
BackgroundThe coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Prediction models that accurately estimate mortality risk in hospitalized patients could assist medical staff in treatment and allocating limited resources. AimsTo externally validate two promising previously published risk scores that predict in-hospital mortality among hospitalized COVID-19 patients. MethodsTwo cohorts were available; a cohort of 1028 patients admitted to one of nine hospitals in Lombardy, Italy (the Lombardy cohort) and a cohort of 432 patients admitted to a hospital in Leiden, the Netherlands (the Leiden cohort). The primary endpoint was in-hospital mortality. All patients were adult and tested COVID-19 PCR-positive. Model discrimination and calibration were assessed. ResultsThe C-statistic of the 4C mortality score was good in the Lombardy cohort (0.85, 95CI: 0.82-0.89) and in the Leiden cohort (0.87, 95CI: 0.80-0.94). Model calibration was acceptable in the Lombardy cohort but poor in the Leiden cohort due to the model systematically overpredicting the mortality risk for all patients. The C-statistic of the CURB-65 score was good in the Lombardy cohort (0.80, 95CI: 0.75-0.85) and in the Leiden cohort (0.82, 95CI: 0.76-0.88). The mortality rate in the CURB-65 development cohort was much lower than the mortality rate in the Lombardy cohort. A similar but less pronounced trend was found for patients in the Leiden cohort. ConclusionAlthough performances did not differ greatly, the 4C mortality score showed the best performance. However, because of quickly changing circumstances, model recalibration may be necessary before using the 4C mortality score.
ABSTRACT
BackgroundThe coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Identification of predictors of poor outcomes will assist medical staff in treatment and allocating limited healthcare resources. AimsThe primary aim was to study the value of D-dimer as a predictive marker for in-hospital mortality. MethodsThis was a cohort study. The study population consisted of hospitalized patients (age >18 years), who were diagnosed with COVID-19 based on real-time PCR at 9 hospitals during the first COVID-19 wave in Lombardy, Italy (Feb-May 2020). The primary endpoint was in-hospital mortality. Information was obtained from patient records. Statistical analyses were performed using a Fine-Gray competing risk survival model. Model discrimination was assessed using Harrells C-index and model calibration was assessed using a calibration plot. ResultsOut of 1049 patients, 501 patients had evaluable data. Of these 501 patients, 96 died. The cumulative incidence of in-hospital mortality within 30 days was 20% (95CI: 16%-23%), and the majority of deaths occurred within the first 10 days. A prediction model containing D-dimer as the only predictor had a C-index of 0.66 (95%CI: 0.61-0.71). Overall calibration of the model was very poor. The addition of D-dimer to a model containing age, sex and co-morbidities as predictors did not lead to any meaningful improvement in either the C-index or the calibration plot. ConclusionThe predictive value of D-dimer alone was moderate, and the addition of D-dimer to a simple model containing basic clinical characteristics did not lead to any improvement in model performance.
ABSTRACT
There are gender differences in susceptibility and vulnerability to the Coronavirus disease 2019 (COVID-19). The S protein of coronaviruses facilitates viral entry into target cells and employs the host cellular serine protease TMPRSS2 for S protein priming. The TMPRSS2 gene expression is responsive to androgen stimulation and it could partially explain gender differences. We tested the hypothesis that men who received 5-Alpha reductase inhibitors (5ARIs) or androgen deprivation therapy (ADT) for prostate cancer could have a different susceptibility to COVID-19. We carried out an observational study on patients who were referred to our COVID-19 regional centre in Lombardy from 1 to 31st March 2020. Data from 421 patients, 137 women (32.54%) and 284 men (67.44%) with laboratory-confirmed COVID-19, were included in this report. Overall 84 patients died: 28 women (33.33%) and 56 men (66.67%). Among men, 12 patients (4.22%) reported assuming 5ARI treatment, and 6 were under ADT. Over 12 patients under 5ARIs, 3 (25%) died; 2 deaths (33%) were reported in patients under ADT. Our findings showed that only 4.22% of the overall population received 5ARI anti-androgen therapy, a percentage, which revealed to be significantly lower (P<0.0001) than what observed in Italian men aged more than 40 years (14.97%).