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1.
Emergency radiology ; : 1-11, 2022.
Article in English | EuropePMC | ID: covidwho-1728021

ABSTRACT

Background Admission chest CT is often included in COVID-19 patient management. Purpose To evaluate the inter- and intraobserver variability of the Covid Visual Assessment Scale (“Co.V.A.Sc.”) used for stratifying chest CT disease extent and to estimate its prospect to predict clinical outcomes. Materials and methods This single-center, retrospective observational cohort study included all RT-PCR-confirmed COVID-19 adult patients undergoing admission chest CT, between 01/03/2021 and 17/03/2021. CTs were independently evaluated by two radiologists according to the “Co.V.A.Sc.” (0: 0%, 1: 1–10%, 2: 11–25%, 3: 26–50%, 4: 51–75%, 5: > 75%). Patient demographics, laboratory, clinical, and hospitalization data were retrieved and analyzed in relation to the “Co.V.A.Sc.” evaluations. Results Overall, 273 patients (mean age 60.7 ± 14.8 years;50.9% male) were evaluated. Excellent inter- and intraobserver variability was noted between the two independent radiologists’ “Co.V.A.Sc.” evaluations. “Co.V.A.Sc.” classification (Exp(B) 0.391, 95%CI 0.212–0.719;p = 0.025) and patient age (Exp(B) 0.947, 95%CI 0.902–0.993;p = 0.25) were the only variables correlated with ICU admission, while age (Exp(B) 1.111, p = 0.0001), “Co.V.A.Sc.” (Exp(B) 2.408;p = 0.002), and male gender (Exp(B) 3.213;p = 0.028) were correlated with in-hospital mortality. Specifically, for each “Co.V.A.Sc.” unit increase, the probability of ICU admission increased by 1.47 times, and the probability of death increased by 11.1 times. According to ROC analysis, “Co.V.A.Sc.” could predict ICU admission and in-hospital death with an optimal cutoff value of unit 3 (sensitivity 56.0%, specificity 84.3%) and unit 4 (sensitivity 41.9%, specificity 93.6%), respectively. Conclusion “Co.V.A.Sc.” upon hospital admittance seems to predict ICU admission and in-hospital death and could aid in optimizing risk-stratification and patient management.

2.
Emerg Radiol ; 2022 Mar 07.
Article in English | MEDLINE | ID: covidwho-1729321

ABSTRACT

BACKGROUND: Admission chest CT is often included in COVID-19 patient management. PURPOSE: To evaluate the inter- and intraobserver variability of the Covid Visual Assessment Scale ("Co.V.A.Sc.") used for stratifying chest CT disease extent and to estimate its prospect to predict clinical outcomes. MATERIALS AND METHODS: This single-center, retrospective observational cohort study included all RT-PCR-confirmed COVID-19 adult patients undergoing admission chest CT, between 01/03/2021 and 17/03/2021. CTs were independently evaluated by two radiologists according to the "Co.V.A.Sc." (0: 0%, 1: 1-10%, 2: 11-25%, 3: 26-50%, 4: 51-75%, 5: > 75%). Patient demographics, laboratory, clinical, and hospitalization data were retrieved and analyzed in relation to the "Co.V.A.Sc." RESULTS: Overall, 273 patients (mean age 60.7 ± 14.8 years; 50.9% male) were evaluated. Excellent inter- and intraobserver variability was noted between the two independent radiologists' "Co.V.A.Sc." EVALUATIONS: "Co.V.A.Sc." classification (Exp(B) 0.391, 95%CI 0.212-0.719; p = 0.025) and patient age (Exp(B) 0.947, 95%CI 0.902-0.993; p = 0.25) were the only variables correlated with ICU admission, while age (Exp(B) 1.111, p = 0.0001), "Co.V.A.Sc." (Exp(B) 2.408; p = 0.002), and male gender (Exp(B) 3.213; p = 0.028) were correlated with in-hospital mortality. Specifically, for each "Co.V.A.Sc." unit increase, the probability of ICU admission increased by 1.47 times, and the probability of death increased by 11.1 times. According to ROC analysis, "Co.V.A.Sc." could predict ICU admission and in-hospital death with an optimal cutoff value of unit 3 (sensitivity 56.0%, specificity 84.3%) and unit 4 (sensitivity 41.9%, specificity 93.6%), respectively. CONCLUSION: "Co.V.A.Sc." upon hospital admittance seems to predict ICU admission and in-hospital death and could aid in optimizing risk-stratification and patient management.

3.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-309680

ABSTRACT

Background: The accuracy of a new optical biosensor (OB) point-of-care device for the detection of severe infections is studied. Methods: The OB emits different wavelengths and outputs information associated with heart rate, pulse oximetry, levels of nitric oxide and kidney function. At the derivation phase, recordings were done every two hours for three consecutive days after hospital admission in 142 patients at high-risk for sepsis by placing the OB on the forefinger. At the validation phase, single recordings were done in 54 patients with symptoms of viral infection;38 were diagnosed with COVID-19. Results: At the derivation phase, the cutoff value of positive likelihood of 18 provided 100% specificity and 100% positive predictive value for the diagnosis of sepsis. These were 87.5% and 91.7% respectively at the validation phase. OB diagnosed severe COVID-19 with 83.3% sensitivity and 87.5% negative predictive value. Conclusions: The studied OB seems valuable for the discrimination of infection severity.

4.
Open Forum Infect Dis ; 9(1): ofab588, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1608344

ABSTRACT

Background: Therapeutic options for hospitalized patients with severe coronavirus disease 2019 (sCOVID-19) are limited. Preliminary data have shown promising results with baricitinib, but real-life experience is lacking. We assessed the safety and effectiveness of add-on baricitinib to standard-of-care (SOC) including dexamethasone in hospitalized patients with sCOVID-19. Methods: This study is a 2-center, observational, retrospective cohort study of patients with sCOVID-19, comparing outcomes and serious events between patients treated with SOC versus those treated with SOC and baricitinib combination. Results: We included 369 patients with sCOVID-19 (males 66.1%; mean age 65.2 years; median symptom duration 6 days). The SOC was administered in 47.7% and combination in 52.3%. Patients treated with the combination reached the composite outcome (intensive care unit [ICU] admission or death) less frequently compared with SOC (22.3% vs 36.9%, P = .002). Mortality rate was lower with the combination in the total cohort (14.7% vs 26.6%, P = .005), and ICU admission was lower in patients with severe acute respiratory distress syndrome (29.7% vs 44.8%, P = .03). By multivariable analysis, age (odds ratio [OR] = 1.82, 95% confidence interval [CI] = 1.36-2.44, per 10-year increase), partial pressure of oxygen/fraction of inspired oxygen ratio (OR = 0.60, 95% CI = .52-0.68, per 10 units increase), and use of high-flow nasal cannula (OR = 0.34; 95% CI, .16-0.74) were associated with the composite outcome, whereas baricitinib use was marginally not associated with the composite outcome (OR = 0.52; 95% CI, .26-1.03). However, baricitinib use was found to be significant after inverse-probability weighted regression (OR = 0.93; 95% CI, .87-0.99). No difference in serious events was noted between treatment groups. Conclusions: In real-life settings, addition of baricitinib to SOC in patients hospitalized with sCOVID-19 is associated with decreased mortality without concerning safety signals.

7.
Front Med (Lausanne) ; 8: 575580, 2021.
Article in English | MEDLINE | ID: covidwho-1147389

ABSTRACT

The advent of highly sensitive molecular diagnostic techniques has improved our ability to detect viral pathogens leading to severe and often fatal infections that require admission to the Intensive Care Unit (ICU). Viral infections in the ICU have pleomorphic clinical presentations including pneumonia, acute respiratory distress syndrome, respiratory failure, central or peripheral nervous system manifestations, and viral-induced shock. Besides de novo infections, certain viruses fall into latency and can be reactivated in both immunosuppressed and immunocompetent critically ill patients. Depending on the viral strain, transmission occurs either directly through contact with infectious materials and large droplets, or indirectly through suspended air particles (airborne transmission of droplet nuclei). Many viruses can efficiently spread within hospital environment leading to in-hospital outbreaks, sometimes with high rates of mortality and morbidity, thus infection control measures are of paramount importance. Despite the advances in detecting viral pathogens, limited progress has been made in antiviral treatments, contributing to unexpectedly high rates of unfavorable outcomes. Herein, we review the most updated data on epidemiology, common clinical features, diagnosis, pathogenesis, treatment and prevention of severe community- and hospital-acquired viral infections in the ICU settings.

9.
BMC Infect Dis ; 20(1): 860, 2020 Nov 19.
Article in English | MEDLINE | ID: covidwho-934260

ABSTRACT

BACKGROUND: The accuracy of a new optical biosensor (OB) point-of-care device for the detection of severe infections is studied. METHODS: The OB emits different wavelengths and outputs information associated with heart rate, pulse oximetry, levels of nitric oxide and kidney function. At the first phase, recordings were done every two hours for three consecutive days after hospital admission in 142 patients at high-risk for sepsis by placing the OB on the forefinger. At the second phase, single recordings were done in 54 patients with symptoms of viral infection; 38 were diagnosed with COVID-19. RESULTS: At the first phase, the cutoff value of positive likelihood of 18 provided 100% specificity and 100% positive predictive value for the diagnosis of sepsis. These were 87.5 and 91.7% respectively at the second phase. OB diagnosed severe COVID-19 with 83.3% sensitivity and 87.5% negative predictive value. CONCLUSIONS: The studied OB seems valuable for the discrimination of infection severity.


Subject(s)
Biosensing Techniques/methods , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Sepsis/diagnosis , Aged , Aged, 80 and over , Algorithms , Area Under Curve , Betacoronavirus/isolation & purification , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques , Coronavirus Infections/pathology , Coronavirus Infections/virology , Early Diagnosis , Female , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/pathology , Pneumonia, Viral/virology , ROC Curve , SARS-CoV-2 , Sensitivity and Specificity , Severity of Illness Index
11.
EBioMedicine ; 59: 102939, 2020 Sep.
Article in English | MEDLINE | ID: covidwho-716658

ABSTRACT

BACKGROUND: There is an increased attention to stroke following SARS-CoV-2. The goal of this study was to better depict the short-term risk of stroke and its associated factors among SARS-CoV-2 hospitalized patients. METHODS: This multicentre, multinational observational study includes hospitalized SARS-CoV-2 patients from North and South America (United States, Canada, and Brazil), Europe (Greece, Italy, Finland, and Turkey), Asia (Lebanon, Iran, and India), and Oceania (New Zealand). The outcome was the risk of subsequent stroke. Centres were included by non-probability sampling. The counts and clinical characteristics including laboratory findings and imaging of the patients with and without a subsequent stroke were recorded according to a predefined protocol. Quality, risk of bias, and heterogeneity assessments were conducted according to ROBINS-E and Cochrane Q-test. The risk of subsequent stroke was estimated through meta-analyses with random effect models. Bivariate logistic regression was used to determine the parameters with predictive outcome value. The study was reported according to the STROBE, MOOSE, and EQUATOR guidelines. FINDINGS: We received data from 26,175 hospitalized SARS-CoV-2 patients from 99 tertiary centres in 65 regions of 11 countries until May 1st, 2020. A total of 17,799 patients were included in meta-analyses. Among them, 156(0.9%) patients had a stroke-123(79%) ischaemic stroke, 27(17%) intracerebral/subarachnoid hemorrhage, and 6(4%) cerebral sinus thrombosis. Subsequent stroke risks calculated with meta-analyses, under low to moderate heterogeneity, were 0.5% among all centres in all countries, and 0.7% among countries with higher health expenditures. The need for mechanical ventilation (OR: 1.9, 95% CI:1.1-3.5, p = 0.03) and the presence of ischaemic heart disease (OR: 2.5, 95% CI:1.4-4.7, p = 0.006) were predictive of stroke. INTERPRETATION: The results of this multi-national study on hospitalized patients with SARS-CoV-2 infection indicated an overall stroke risk of 0.5%(pooled risk: 0.9%). The need for mechanical ventilation and the history of ischaemic heart disease are the independent predictors of stroke among SARS-CoV-2 patients. FUNDING: None.


Subject(s)
Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Stroke/diagnosis , Adult , Aged , Betacoronavirus/isolation & purification , COVID-19 , Coronavirus Infections/complications , Coronavirus Infections/virology , Female , Hospitalization , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/complications , Pneumonia, Viral/virology , Risk Factors , SARS-CoV-2 , Stroke/complications , Tertiary Care Centers
12.
Gynecol Oncol Rep ; 33: 100615, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-688921

ABSTRACT

•Chemotherapy resumption after convalescence from COVID-19 is safe and feasible.•No guidelines exist for resumption of chemotherapy in patients with COVID-19.•Cancer patients on chemotherapy may develop SARS-CoV-2 antibodies less frequently.

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