Are Interstitial Lung Abnormalities a Prognostic Factor of Worse Outcome in COVID-19 Pneumonia?

PURPOSE: To assess the association between interstitial lung abnormalities (ILAs) and worse outcome in patients affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19)-related pneumonia. MATERIALS AND METHODS: The study included patients older than 18 years, who were admitted at the emergency department between February 29 and April 30, 2020 with findings of COVID-19 pneumonia at chest computed tomography (CT), with positive reverse-transcription polymerase chain reaction nasal-pharyngeal swab for SARS-CoV-2, and with the availability of prepandemic chest CT. Prepandemic CTs were reviewed for the presence of ILAs, categorized as fibrotic in cases with associated architectural distortion, bronchiectasis, or honeycombing. Worse outcome was defined as intensive care unit (ICU) admission or death. Cox proportional hazards regression analysis was used to test the association between ICU admission/death and preexisting ILAs. RESULTS: The study included 147 patients (median age 73 y old; 95% CIs: 71-76-y old; 29% females). On prepandemic CTs, ILA were identified in 33/147 (22%) of the patients, 63% of which were fibrotic ILAs. Fibrotic ILAs were associated with higher risk of ICU admission or death in patients with COVID-19 pneumonia (hazard ratios: 2.73, 95% CIs: 1.50-4.97, P =0.001). CONCLUSIONS: In patients affected by COVID-19 pneumonia, preexisting fibrotic ILAs were an independent predictor of worse prognosis, with a 2.7 times increased risk of ICU admission or death. Chest CT scans obtained before the diagnosis of COVID-19 pneumonia should be carefully reviewed for the presence and characterization of ILAs.

A "Post-mortem" of COVID-19-associated stroke: a case-control study.

OBJECTIVES: To assess whether COVID-19 could be a concurrent factor in the genesis and/or worsening of stroke and to provide data on COVID-19 -associated stroke patients during the first pandemic wave and comparative data on COVID-19 negative stroke patients in the same period. MATERIALS AND METHODS: This is a retrospective, observational, case-control, single centre study, carried out in a General Hospital in northern Italy. Sixty-three consecutive stroke patients were included, COVID-19-associated stroke was classified as cases and non COVID-19-associated stroke as controls. RESULTS: A total of 19/63 (28.8%) had a COVID-19-associated stroke, 11 /63 (17.5%) were haemorrhagic and 52/63 (82.5%) ischaemic. COVID-19-associated strokes were more severe (p-value 0.019) and had a higher risk of severe disability and/or death (OR 3.79, CI 95%: 1.21-11.93, p-value 0.19). The COVID-19-associated stroke patients with onset during hospitalization for COVID-19 had a more severe stroke than patients with COVID-19 onset during hospitalization for stroke (p-value 0.019). CONCLUSION: Although no relationship was observed between the stroke aetiology and COVID-19, intriguingly, COVID-associated stroke turned out to be more severe and disabling. Hopefully, further studies will provide more data and help in the management of this emerging population.

Multiple Sclerosis Treatment in the COVID-19 Era: A Risk-Benefit Approach.

The COVID-19 pandemic poses an ongoing global challenge, and several risk factors make people with multiple sclerosis (pwMS) particularly susceptible to running a severe disease course. Although the literature does report numerous articles on the risk factors for severe COVID-19 and vaccination response in pwMS, there is a scarcity of reviews integrating both these aspects into strategies aimed at minimizing risks. The aim of this review is to describe the risk of vulnerable pwMS exposed to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the issues related to the SARS-CoV-2 vaccine and to evidence possible future strategies in the clinical management of pwMS. The authors searched for papers on severe COVID-19 risk factors, SARS-CoV-2 vaccination and people with multiple sclerosis in support of this narrative literature review. We propose a multilevel strategy aimed at: the evaluation of risk factors for severe COVID-19 in people with multiple sclerosis, identifying the most appropriate vaccination schedule that is safe for people on disease-modifying drugs (DMDs) and a strict follow-up of high-risk people with multiple sclerosis to allow for the prompt administration of monoclonal antibodies to manage COVID-19 risks in this patient population.

Not all is COVID19: a case of eclampsia and posterior reversible encephalopathy syndrome in the emergency room.

In the so called COVID19 era, headache, fever and gastrointestinal symptoms are highly suggestive for SARS-CoV-2 infection, but in all the cases presenting to the emergency room, clinicians should always keep in mind alternative diagnoses, particularly if the patient is pregnant.  Life-threatening diseases, such as eclampsia and posterior reversible encephalopathy syndrome (PRES), should be promptly recognized and treated. Eclampsia is defined as a seizure occurring in association with pre-eclampsia, and it represents one of the major and serious obstetric disorders associated with significant maternal and perinatal morbidity and mortality. PRES is a distinctive clinical and imaging syndrome characterized by acute headaches, visual impairment, seizures, and altered sensorium, that can be associated with severe eclampsia. Emergency clinicians should always consider eclampsia in the differential diagnosis of headache in pregnant women. The prompt and accurate diagnosis of eclampsia/PRES is crucial to prevent adverse maternal and perinatal outcomes. Here we describe the case of a young pregnant woman admitted to our emergency department for fever, dyspnea, headache, nausea and vomiting, who developed generalized tonic clonic seizures and a subsequent status epilepticus due to eclampsia and PRES.

Qualitative and quantitative chest CT parameters as predictors of specific mortality in COVID-19 patients.

PURPOSE: To test the association between death and both qualitative and quantitative CT parameters obtained visually and by software in coronavirus disease (COVID-19) early outbreak. METHODS: The study analyzed retrospectively patients underwent chest CT at hospital admission for COVID-19 pneumonia suspicion, between February 21 and March 6, 2020. CT was performed in case of hypoxemia or moderate-to-severe dyspnea. CT scans were analyzed for quantitative and qualitative features obtained visually and by software. Cox proportional hazards regression analysis examined the association between variables and overall survival (OS). Three models were built for stratification of mortality risk: clinical, clinical/visual CT evaluation, and clinical/software-based CT assessment. AUC for each model was used to assess performance in predicting death. RESULTS: The study included 248 patients (70% males, median age 68 years). Death occurred in 78/248 (32%) patients. Visual pneumonia extent > 40% (HR 2.15, 95% CI 1.2-3.85, P = 0.01), %high attenuation area - 700 HU > 35% (HR 2.17, 95% CI 1.2-3.94, P = 0.01), exudative consolidations (HR 2.85-2.93, 95% CI 1.61-5.05/1.66-5.16, P < 0.001), visual CAC score > 1 (HR 2.76-3.32, 95% CI 1.4-5.45/1.71-6.46, P < 0.01/P < 0.001), and CT classified as COVID-19 and other disease (HR 1.92-2.03, 95% CI 1.01-3.67/1.06-3.9, P = 0.04/P = 0.03) were significantly associated with shorter OS. Models including CT parameters (AUC 0.911-0.913, 95% CI 0.873-0.95/0.875-0.952) were better predictors of death as compared to clinical model (AUC 0.869, 95% CI 0.816-0.922; P = 0.04 for both models). CONCLUSIONS: In COVID-19 patients, qualitative and quantitative chest CT parameters obtained visually or by software are predictors of mortality. Predictive models including CT metrics were better predictors of death in comparison to clinical model.

Comparison of admission chest computed tomography and lung ultrasound performance for diagnosis of COVID-19 pneumonia in populations with different disease prevalence.

PURPOSE: Chest computed tomography (CT) is considered a reliable imaging tool for COVID-19 pneumonia diagnosis, while lung ultrasound (LUS) has emerged as a potential alternative to characterize lung involvement. The aim of the study was to compare diagnostic performance of admission chest CT and LUS for the diagnosis of COVID-19. METHODS: We included patients admitted to emergency department between February 21-March 6, 2020 (high prevalence group, HP) and between March 30-April 13, 2020 (moderate prevalence group, MP) undergoing LUS and chest CT within 12 h. Chest CT was considered positive in case of "indeterminate"/"typical" pattern for COVID-19 by RSNA classification system. At LUS, thickened pleural line with ≥ three B-lines at least in one zone of the 12 explored was considered positive. Sensitivity, specificity, PPV, NPV, and AUC were calculated for CT and LUS against real-time reverse transcriptase polymerase chain reaction (RT-PCR) and serology as reference standard. RESULTS: The study included 486 patients (males 61 %; median age, 70 years): 247 patients in HP (COVID-19 prevalence 94 %) and 239 patients in MP (COVID-19 prevalence 45 %). In HP and MP respectively, sensitivity, specificity, PPV, and NPV were 90-95 %, 43-69 %, 96-72 %, 20-95 % for CT and 94-93 %, 7-31 %, 94-52 %, 7-83 % for LUS. CT demonstrated better performance than LUS in diagnosis of COVID-19, both in HP (AUC 0.75 vs 0.51; P < 0.001) and MP (AUC 0.85 vs 0.62; P < 0.001). CONCLUSIONS: Admission chest CT shows better performance than LUS for COVID-19 diagnosis, at varying disease prevalence. LUS is highly sensitive, but not specific for COVID-19.

COVID-19 outbreak in Italy: Clinical-radiological presentation and outcome in three oncologic patients.

We present three patients affected by pulmonary squamous cell carcinoma, metastatic esophageal cancer and advanced non-Hodgkin lymphoma, who incurred in coronavirus 2019 (COVID-19) infection during the early phase of epidemic wave in Italy. All patients presented with fever. Social contact with subject positive for COVID-19 was declared in only one of the three cases. In all cases, laboratory findings showed lymphopenia and elevated C-reactive protein (CRP). Chest x-ray and computed tomography showed bilateral ground-glass opacities, shadowing, interstitial abnormalities, and "crazy paving" pattern which evolved with superimposition of consolidations in one patient. All patients received antiviral therapy based on ritonavir and lopinavir, associated with hydroxychloroquine. Despite treatment, two patients with advanced cancers died after 39 and 17 days of hospitalization, while the patient with lung cancer was dismissed at home, in good conditions.

Well-aerated Lung on Admitting Chest CT to Predict Adverse Outcome in COVID-19 Pneumonia.

Background CT of patients with severe acute respiratory syndrome coronavirus 2 disease depicts the extent of lung involvement in coronavirus disease 2019 (COVID-19) pneumonia. Purpose To determine the value of quantification of the well-aerated lung (WAL) obtained at admission chest CT to determine prognosis in patients with COVID-19 pneumonia. Materials and Methods Imaging of patients admitted at the emergency department between February 17 and March 10, 2020 who underwent chest CT were retrospectively analyzed. Patients with negative results of reverse-transcription polymerase chain reaction for severe acute respiratory syndrome coronavirus 2 at nasal-pharyngeal swabbing, negative chest CT findings, and incomplete clinical data were excluded. CT images were analyzed for quantification of WAL visually (%V-WAL), with open-source software (%S-WAL), and with absolute volume (VOL-WAL). Clinical parameters included patient characteristics, comorbidities, symptom type and duration, oxygen saturation, and laboratory values. Logistic regression was used to evaluate the relationship between clinical parameters and CT metrics versus patient outcome (intensive care unit [ICU] admission or death vs no ICU admission or death). The area under the receiver operating characteristic curve (AUC) was calculated to determine model performance. Results The study included 236 patients (59 of 123 [25%] were female; median age, 68 years). A %V-WAL less than 73% (odds ratio [OR], 5.4; 95% confidence interval [CI]: 2.7, 10.8; P < .001), %S-WAL less than 71% (OR, 3.8; 95% CI: 1.9, 7.5; P < .001), and VOL-WAL less than 2.9 L (OR, 2.6; 95% CI: 1.2, 5.8; P < .01) were predictors of ICU admission or death. In comparison with clinical models containing only clinical parameters (AUC = 0.83), all three quantitative models showed better diagnostic performance (AUC = 0.86 for all models). The models containing %V-WAL less than 73% and VOL-WAL less than 2.9 L were superior in terms of performance as compared with the models containing only clinical parameters (P = .04 for both models). Conclusion In patients with confirmed coronavirus disease 2019 pneumonia, visual or software quantification of the extent of CT lung abnormality were predictors of intensive care unit admission or death. © RSNA, 2020 Online supplemental material is available for this article.