Complement activation predicts negative outcomes in COVID-19: The experience from Northen Italian patients.

Coronavirus disease 19 (COVID-19) may present as a multi-organ disease with a hyperinflammatory and prothrombotic response (immunothrombosis) in addition to upper and lower airway involvement. Previous data showed that complement activation plays a role in immunothrombosis mainly in severe forms. The study aimed to investigate whether complement involvement is present in the early phases of the disease and can be predictive of a negative outcome. We enrolled 97 symptomatic patients with a positive RT-PCR for SARS-CoV-2 presenting to the emergency room. The patients with mild symptoms/lung involvement at CT-scan were discharged and the remaining were hospitalized. All the patients were evaluated after a 4-week follow-up and classified as mild (n. 54), moderate (n. 17) or severe COVID-19 (n. 26). Blood samples collected before starting any anti-inflammatory/immunosuppressive therapy were assessed for soluble C5b-9 (sC5b-9) and C5a plasma levels by ELISA, and for the following serum mediators by ELLA: IL-1ß, IL-6, IL-8, TNFα, IL-4, IL-10, IL-12p70, IFNγ, IFNα, VEGF-A, VEGF-B, GM-CSF, IL-2, IL-17A, VEGFR2, BLyS. Additional routine laboratory parameters were measured (fibrin fragment D-dimer, C-reactive protein, ferritin, white blood cells, neutrophils, lymphocytes, monocytes, platelets, prothrombin time, activated partial thromboplastin time, and fibrinogen). Fifty age and sex-matched healthy controls were also evaluated. SC5b-9 and C5a plasma levels were significantly increased in the hospitalized patients (moderate and severe) in comparison with the non-hospitalized mild group. SC5b9 and C5a plasma levels were predictive of the disease severity evaluated one month later. IL-6, IL-8, TNFα, IL-10 and complement split products were higher in moderate/severe versus non-hospitalized mild COVID-19 patients and healthy controls but with a huge heterogeneity. SC5b-9 and C5a plasma levels correlated positively with CRP, ferritin values and the neutrophil/lymphocyte ratio. Complement can be activated in the very early phases of the disease, even in mild non-hospitalized patients. Complement activation can be observed even when pro-inflammatory cytokines are not increased, and predicts a negative outcome.

Active screening of COVID-19-associated pulmonary aspergillosis with serum beta-glucan and endotracheal aspirates galactomannan and fungal culture.

BACKGROUND: Since February 2021 active screening of COVID-19-associated pulmonary aspergillosis (CAPA) has been implemented in our institution. OBJECTIVES: To evaluate CAPA incidence in our centre and evaluate performance of our screening protocol. METHODS: We screened once per week, collecting endotracheal aspirates for fungal culture and galactomannan (GM) and serum for 1,3-ß-D-glucan (BG). In case of positivity (GM more than 4.5, platelia assay, and/or BG >7 pg/ml, wako and/or positive fungal culture), second-level investigations were performed to pursue CAPA diagnosis according to ECMM/ISHAM criteria: bronchoalveolar lavage (BAL) fungal culture and GM, chest computed tomography (CT), serum GM. RESULTS: A total of 102 patients were screened (median age 64 years, range 39-79; 28 (27.4%) females). Twenty-two patients were diagnosed with CAPA (21%). 12 patients were positive for serum BG, 17 patients were positive for endotracheal aspirates GM and 27 patients were positive for endotracheal aspirates fungal culture. Thirty-two BALs were performed, and 26 patients underwent CT chest. Following the second level investigations 61% of the patients with positive screening tests were diagnosed with CAPA. Serum BG above 20 pg/ml or positive serum GM were always associated with typical CT chest signs of aspergillosis. Compared with 1 single positive test, having 2 positive screening test was significantly more associated with CAPA diagnosis (p = .0004). CONCLUSIONS: Active CAPA screening with serum 1,3-ß-D-glucan and endotracheal aspirates galactomannan and fungal cultures and consequent second level investigations led to high number of CAPA diagnosis. Combining more positive fungal biomarkers was more predictive of CAPA diagnosis.

High-dose glucocorticoids pulse-therapy for beta-coronaviridae pneumonia: a systematic literature review and case-series of Coronavirus disease-2019.

OBJECTIVES: The results of the RECOVERY trial identified dexamethasone as the first pharmacological therapy that reduces mortality in patients with COVID-19. The aim of this paper is to conduct a systematic literature review on safety and efficacy of pulse glucocorticoid therapy for Severe Acute Respiratory Syndrome (SARS)-CoronaVirus (CoV), Middle East Respiratory Syndrome (MERS)-CoV or SARS-CoV-2 infections and describe a case-series of COVID-19 patients treated with off-label pulse doses of methylprednisolone. METHODS: We performed a systematic literature review on safety and efficacy of pulse therapy for betacoronaviridae infections as described in the protocol registered on PROSPERO (CRD42020190183). All consecutive patients admitted to Arcispedale Santa Maria Nuova di Reggio Emilia or Guastalla Hospital with COVID-19 between March 1st and April 30th, 2020 and treated with methylprednisolone 1 gram/day for at least three days were included in the case series. A retrospective review of available computed tomography (CT) scan and chest x-ray was performed independently by two radiologists blinded to clinical data, and discordances were resolved by consensus. RESULTS: Twenty papers were included for SARS, but only two were comparative and were included in the primary endpoint analysis. Likewise, eleven papers were included for COVID-19, four of which were comparative and were considered for the primary outcome analysis. Included studies for both SARS and COVID-19 are mostly retrospective and highly heterogeneous, with lethality ranging from 0% to 100% and ICU admission rate ranging from 9% to 100%. Fourteen patients were included in our case series, 7 males and 7 females. CONCLUSIONS: No randomised controlled trial is available yet for corticosteroids pulse-therapy defined as at least ≥500mg/day methylprednisolone in patients with emerging coronavirus pneumonia. Lethality among our cohort is high (4/14), but this finding should be interpreted with caution due to the fact that in our setting pulse-steroids were used in patients not eligible for other treatments because of comorbidities or as rescue therapy. The incidence of steroid-related adverse events seems low in our cohort. The quality of the evidence on glucocorticoid pulse-therapy in SARS, MERS and COVID-19 is poor. Randomised controlled trials are greatly needed.

Modifications of Chest CT Body Composition Parameters at Three and Six Months after Severe COVID-19 Pneumonia: A Retrospective Cohort Study.

We aimed to describe body composition changes up to 6-7 months after severe COVID-19 and to evaluate their association with COVID-19 inflammatory burden, described by the integral of the C-reactive protein (CRP) curve. The pectoral muscle area (PMA) and density (PMD), liver-to-spleen (L/S) ratio, and total, visceral, and intermuscular adipose tissue areas (TAT, VAT, and IMAT) were measured at baseline (T0), 2-3 months (T1), and 6-7 months (T2) follow-up CT scans of severe COVID-19 pneumonia survivors. Among the 208 included patients (mean age 65.6 ± 11 years, 31.3% females), decreases in PMA [mean (95%CI) -1.11 (-1.72; -0.51) cm2] and in body fat areas were observed [-3.13 (-10.79; +4.52) cm2 for TAT], larger from T0 to T1 than from T1 to T2. PMD increased only from T1 to T2 [+3.07 (+2.08; +4.06) HU]. Mean decreases were more evident for VAT [-3.55 (-4.94; -2.17) cm2] and steatosis [L/S ratio increase +0.17 (+0.13; +0.20)] than for TAT. In multivariable models adjusted by age, sex, and baseline TAT, increasing the CRP interval was associated with greater PMA reductions, smaller PMD increases, and greater VAT and steatosis decreases, but it was not associated with TAT decreases. In conclusion, muscle loss and fat loss (more apparent in visceral compartments) continue until 6-7 months after COVID-19. The inflammatory burden is associated with skeletal muscle loss and visceral/liver fat loss.

Imaging-based indices combining disease severity and time from disease onset to predict COVID-19 mortality: A cohort study.

BACKGROUND: COVID-19 prognostic factors include age, sex, comorbidities, laboratory and imaging findings, and time from symptom onset to seeking care. PURPOSE: The study aim was to evaluate indices combining disease severity measures and time from disease onset to predict mortality of COVID-19 patients admitted to the emergency department (ED). MATERIALS AND METHODS: All consecutive COVID-19 patients who underwent both computed tomography (CT) and chest X-ray (CXR) at ED presentation between 27/02/2020 and 13/03/2020 were included. CT visual score of disease extension and CXR Radiographic Assessment of Lung Edema (RALE) score were collected. The CT- and CXR-based scores, C-reactive protein (CRP), and oxygen saturation levels (sO2) were separately combined with time from symptom onset to ED presentation to obtain severity/time indices. Multivariable regression age- and sex-adjusted models without and with severity/time indices were compared. For CXR-RALE, the models were tested in a validation cohort. RESULTS: Of the 308 included patients, 55 (17.9%) died. In multivariable logistic age- and sex-adjusted models for death at 30 days, severity/time indices showed good discrimination ability, higher for imaging than for laboratory measures (AUCCT = 0.92, AUCCXR = 0.90, AUCCRP = 0.88, AUCsO2 = 0.88). AUCCXR was lower in the validation cohort (0.79). The models including severity/time indices performed slightly better than models including measures of disease severity not combined with time and those including the Charlson Comorbidity Index, except for CRP-based models. CONCLUSION: Time from symptom onset to ED admission is a strong prognostic factor and provides added value to the interpretation of imaging and laboratory findings at ED presentation.

Prognostic Role of the Pectoralis Musculature in Patients with COVID-19. A Multicenter Study.

RATIONALE AND OBJECTIVES: To evaluate the impact of low skeletal muscle mass in patients with COVID-19 on relevant outcomes like 30-day mortality, need for intubation and need for intensive care unit admission. MATERIALS AND METHODS: For this study, data from six centers were acquired. The acquired sample comprises 1138 patients. There were 547 women (48.1%) and 591 men (51.9%) with a mean age of 54.5 ± 18.8 years; median age, 55 years; range, 18-84 years). In every case, thoracic CT without intravenous application of contrast medium was performed. The following parameters of the pectoralis muscles were estimated: muscle area as a sum of the bilateral areas of the pectoralis major and minor muscles, muscle density, muscle index (PMI) (pectoralis muscle area divided by the patient's body height square) as a ratio pectoralis major and minor muscles divided by the patient's body height2, and muscle gauge as PMI x muscle density. RESULTS: Overall, 220 patients (19.33%) were admitted to the intensive care unit. In 171 patients (15.03%), mechanical lung ventilation was performed. Finally, 154 patients (13.53%) died within the observation time of 30-day. All investigated parameters of pectoralis muscle were lower in the patients with unfavorable courses of Covid-19. All pectoralis muscle parameters were associated with 30-day mortality in multivariate analyses adjusted for age and sex: pectoralis muscle area, HR = 0.93 CI 95% (0.91-0.95) p < 0.001; pectoralis muscle density, HR = 0.94 CI 95% (0.93-0.96) p < 0.001; pectoralis muscle index, HR = 0.79 CI 95% (0.75-0.85) p < 0.001, pectoralis muscle gauge, HR = 0.995 CI 95% (0.99-0.996) p < 0.001. CONCLUSION: in COVID-19, survivors have larger areas and higher index, gauge and density of the pectoralis muscles in comparison to nonsurvivors. However, the analyzed muscle parameters cannot be used for prediction of disease courses.

Rehabilitation Interventions for Post-Acute COVID-19 Syndrome: A Systematic Review.

Increasing numbers of individuals suffer from post-acute COVID-19 syndrome (PACS), which manifests with persistent symptoms, the most prevalent being dyspnea, fatigue, and musculoskeletal, cognitive, and/or mental health impairments. This systematic review investigated the effectiveness of rehabilitation interventions for individuals with PACS. We searched the MEDLINE, Embase, Cochrane Register of Controlled Trials, CINHAL, Scopus, Prospero, and PEDro databases and the International Clinical Trials Registry Platform for randomized controlled trials (RCTs) up to November 2021. We screened 516 citations for eligibility, i.e., trials that included individuals with PACS exposed to exercise-based rehabilitation interventions. Five RCTs were included, accounting for 512 participants (aged 49.2-69.4 years, 65% males). Based on the revised Cochrane risk-of-bias tool (RoB 2.0), two RCTs had "low risk of bias", and three were in the "some concerns" category. Three RCTs compared experimental rehabilitation interventions with no or minimal rehabilitation, while two compared two active rehabilitation interventions. Rehabilitation seemed to improve dyspnea, anxiety, and kinesiophobia. Results on pulmonary function were inconsistent, while improvements were detected in muscle strength, walking capacity, sit-to-stand performance, and quality of life. Pending further studies based on qualitatively sound designs, these first findings seem to advocate for rehabilitation interventions to lessen disability due to PACS.

Follow-Up CT Patterns of Residual Lung Abnormalities in Severe COVID-19 Pneumonia Survivors: A Multicenter Retrospective Study.

Prior studies variably reported residual chest CT abnormalities after COVID-19. This study evaluates the CT patterns of residual abnormalities in severe COVID-19 pneumonia survivors. All consecutive COVID-19 survivors who received a CT scan 5-7 months after severe pneumonia in two Italian hospitals (Reggio Emilia and Parma) were enrolled. Individual CT findings were retrospectively collected and follow-up CT scans were categorized as: resolution, residual non-fibrotic abnormalities, or residual fibrotic abnormalities according to CT patterns classified following standard definitions and international guidelines. In 225/405 (55.6%) patients, follow-up CT scans were normal or barely normal, whereas in 152/405 (37.5%) and 18/405 (4.4%) patients, non-fibrotic and fibrotic abnormalities were respectively found, and 10/405 (2.5%) had post-ventilatory changes (cicatricial emphysema and bronchiectasis in the anterior regions of upper lobes). Among non-fibrotic changes, either barely visible (n = 110/152) or overt (n = 20/152) ground-glass opacities (GGO), resembling non-fibrotic nonspecific interstitial pneumonia (NSIP) with or without organizing pneumonia features, represented the most common findings. The most frequent fibrotic abnormalities were subpleural reticulation (15/18), traction bronchiectasis (16/18) and GGO (14/18), resembling a fibrotic NSIP pattern. When multiple timepoints were available until 12 months (n = 65), residual abnormalities extension decreased over time. NSIP, more frequently without fibrotic features, represents the most common CT appearance of post-severe COVID-19 pneumonia.

Mortality Prediction of COVID-19 Patients Using Radiomic and Neural Network Features Extracted from a Wide Chest X-ray Sample Size: A Robust Approach for Different Medical Imbalanced Scenarios

Aim: The aim of this study was to develop robust prognostic models for mortality prediction of COVID-19 patients, applicable to different sets of real scenarios, using radiomic and neural network features extracted from chest X-rays (CXRs) with a certified and commercially available software. Methods: 1816 patients from 5 different hospitals in the Province of Reggio Emilia were included in the study. Overall, 201 radiomic features and 16 neural network features were extracted from each COVID-19 patient's radiography. The initial dataset was balanced to train the classifiers with the same number of dead and survived patients, randomly selected. The pipeline had three main parts: balancing procedure;three-step feature selection;and mortality prediction with radiomic features through three machine learning (ML) classification models: AdaBoost (ADA), Quadratic Discriminant Analysis (QDA) and Random Forest (RF). Five evaluation metrics were computed on the test samples. The performance for death prediction was validated on both a balanced dataset (Case 1) and an imbalanced dataset (Case 2). Results: accuracy (ACC), area under the ROC-curve (AUC) and sensitivity (SENS) for the best classifier were, respectively, 0.72 ±0.01, 0.82 ±0.02 and 0.84 ±0.04 for Case 1 and 0.70 ±0.04, 0.79 ±0.03 and 0.76 ±0.06 for Case 2. These results show that the prediction of COVID-19 mortality is robust in a different set of scenarios. Conclusions: Our large and varied dataset made it possible to train ML algorithms to predict COVID-19 mortality using radiomic and neural network features of CXRs.

Clinical and imaging characteristics of patients with COVID-19 predicting hospital readmission after emergency department discharge: a single-centre cohort study in Italy.

OBJECTIVE: We aimed at identifying baseline predictive factors for emergency department (ED) readmission, with hospitalisation/death, in patients with COVID-19 previously discharged from the ED. We also developed a disease progression velocity index. DESIGN AND SETTING: Retrospective cohort study of prospectively collected data. The charts of consecutive patients with COVID-19 discharged from the Reggio Emilia (Italy) ED (2 March 2 to 31 March 2020) were retrospectively examined. Clinical, laboratory and CT findings at first ED admission were tested as predictive factors using multivariable logistic models. We divided CT extension by days from symptom onset to build a synthetic velocity index. PARTICIPANTS: 450 patients discharged from the ED with diagnosis of COVID-19. MAIN OUTCOME MEASURE: ED readmission within 14 days, followed by hospitalisation/death. RESULTS: Of the discharged patients, 84 (18.7%) were readmitted to the ED, 61 (13.6%) were hospitalised and 10 (2.2%) died. Age (OR=1.05; 95% CI 1.03 to 1.08), Charlson Comorbidity Index 3 versus 0 (OR=11.61; 95% CI 1.76 to 76.58), days from symptom onset (OR for 1-day increase=0.81; 95% CI 0.73 to 0.90) and CT extension (OR for 1% increase=1.03; 95% CI 1.01 to 1.06) were associated in a multivariable model for readmission with hospitalisation/death. A 2-day lag velocity index was a strong predictor (OR for unit increase=1.21, 95% CI 1.08 to 1.36); the model including this index resulted in less information loss. CONCLUSIONS: A velocity index combining CT extension and days from symptom onset predicts disease progression in patients with COVID-19. For example, a 20% CT extension 3 days after symptom onset has the same risk as does 50% after 10 days.

Inflammatory burden and persistent CT lung abnormalities in COVID-19 patients.

Inflammatory burden is associated with COVID-19 severity and outcomes. Residual computed tomography (CT) lung abnormalities have been reported after COVID-19. The aim was to evaluate the association between inflammatory burden during COVID-19 and residual lung CT abnormalities collected on follow-up CT scans performed 2-3 and 6-7 months after COVID-19, in severe COVID-19 pneumonia survivors. C-reactive protein (CRP) curves describing inflammatory burden during the clinical course were built, and CRP peaks, velocities of increase, and integrals were calculated. Other putative determinants were age, sex, mechanical ventilation, lowest PaO2/FiO2 ratio, D-dimer peak, and length of hospital stay (LOS). Of the 259 included patients (median age 65 years; 30.5% females), 202 (78%) and 100 (38.6%) had residual, predominantly non-fibrotic, abnormalities at 2-3 and 6-7 months, respectively. In age- and sex-adjusted models, best CRP predictors for residual abnormalities were CRP peak (odds ratio [OR] for one standard deviation [SD] increase = 1.79; 95% confidence interval [CI] = 1.23-2.62) at 2-3 months and CRP integral (OR for one SD increase = 2.24; 95%CI = 1.53-3.28) at 6-7 months. Hence, inflammation is associated with short- and medium-term lung damage in COVID-19. Other severity measures, including mechanical ventilation and LOS, but not D-dimer, were mediators of the relationship between CRP and residual abnormalities.

Tocilizumab or glucocorticoids treatment for patients with SARS-CoV-2 pneumonia: An observational study.

OBJECTIVE: To estimate the effect of tocilizumab or glucocorticoids in preventing death and intubation in patients hospitalized with SARS-CoV-2 pneumonia. METHODS: This was a retrospective cohort study enrolling all consecutive patients hospitalized at Reggio Emilia AUSL between February the 11th and April 14th 2020 for severe COVID-19 and treated with tocilizumab or glucocorticoids (at least 80 mg/day of methylprednisolone or equivalent for at least 3 days). The primary outcome was death within 30 days from the start of the considered therapies. The secondary outcome was a composite outcome of death and/or intubation. All patients have been followed-up until May 19th 2020, with a follow-up of at least 30 days for every patient. To reduce confounding due to potential non-comparability of the two groups, those receiving tocilizumab and those receiving glucocorticoids, a propensity score was calculated as the inverse probability weighting of receiving treatment conditional on the baseline covariates. RESULTS AND CONCLUSION: Therapy with tocilizumab alone was associated with a reduction of deaths (OR 0.49, 95% CI 0.21-1.17) and of the composite outcome death/intubation (OR 0.35, 95% CI 0.13-0.90) compared to glucocorticoids alone. Nevertheless, this result should be cautiously interpreted due to a potential prescription bias.

A practical artificial intelligence system to diagnose COVID-19 using computed tomography: A multinational external validation study.

Computed tomography has gained an important role in the early diagnosis of COVID-19 pneumonia. However, the ever-increasing number of patients has overwhelmed radiology departments and has caused a reduction in quality of services. Artificial intelligence (AI) systems are the remedy to the current situation. However, the lack of application in real-world conditions has limited their consideration in clinical settings. This study validated a clinical AI system, COVIDiag, to aid radiologists in accurate and rapid evaluation of COVID-19 cases. 50 COVID-19 and 50 non-COVID-19 pneumonia cases were included from each of five centers: Argentina, Turkey, Iran, Netherlands, and Italy. The Dutch database included only 50 COVID-19 cases. The performance parameters namely sensitivity, specificity, accuracy, and area under the ROC curve (AUC) were computed for each database using COVIDiag model. The most common pattern of involvement among COVID-19 cases in all databases were bilateral involvement of upper and lower lobes with ground-glass opacities. The best sensitivity of 92.0% was recorded for the Italian database. The system achieved an AUC of 0.983, 0.914, 0.910, and 0.882 for Argentina, Turkey, Iran, and Italy, respectively. The model obtained a sensitivity of 86.0% for the Dutch database. COVIDiag model could diagnose COVID-19 pneumonia in all of cohorts with AUC of 0.921 (sensitivity, specificity, and accuracy of 88.8%, 87.0%, and 88.0%, respectively). Our study confirmed the accuracy of our proposed AI model (COVIDiag) in the diagnosis of COVID-19 cases. Furthermore, the system demonstrated consistent optimal diagnostic performance on multinational databases, which is critical to determine the generalizability and objectivity of the proposed COVIDiag model. Our results are significant as they provide real-world evidence regarding the applicability of AI systems in clinical medicine.

The impact of chest CT body composition parameters on clinical outcomes in COVID-19 patients.

We assessed the impact of chest CT body composition parameters on outcomes and disease severity at hospital presentation of COVID-19 patients, focusing also on the possible mediation of body composition in the relationship between age and death in these patients. Chest CT scans performed at hospital presentation by consecutive COVID-19 patients (02/27/2020-03/13/2020) were retrospectively reviewed to obtain pectoralis muscle density and total, visceral, and intermuscular adipose tissue areas (TAT, VAT, IMAT) at the level of T7-T8 vertebrae. Primary outcomes were: hospitalization, mechanical ventilation (MV) and/or death, death alone. Secondary outcomes were: C-reactive protein (CRP), oxygen saturation (SO2), CT disease extension at hospital presentation. The mediation of body composition in the effect of age on death was explored. Of the 318 patients included in the study (median age 65.7 years, females 37.7%), 205 (64.5%) were hospitalized, 68 (21.4%) needed MV, and 58 (18.2%) died. Increased muscle density was a protective factor while increased TAT, VAT, and IMAT were risk factors for hospitalization and MV/death. All these parameters except TAT had borderline effects on death alone. All parameters were associated with SO2 and extension of lung parenchymal involvement at CT; VAT was associated with CRP. Approximately 3% of the effect of age on death was mediated by decreased muscle density. In conclusion, low muscle quality and ectopic fat accumulation were associated with COVID-19 outcomes, VAT was associated with baseline inflammation. Low muscle quality partly mediated the effect of age on mortality.

The value of computed tomography in assessing the risk of death in COVID-19 patients presenting to the emergency room.

OBJECTIVE: The aims of this study were to develop a multiparametric prognostic model for death in COVID-19 patients and to assess the incremental value of CT disease extension over clinical parameters. METHODS: Consecutive patients who presented to all five of the emergency rooms of the Reggio Emilia province between February 27 and March 23, 2020, for suspected COVID-19, underwent chest CT, and had a positive swab within 10 days were included in this retrospective study. Age, sex, comorbidities, days from symptom onset, and laboratory data were retrieved from institutional information systems. CT disease extension was visually graded as < 20%, 20-39%, 40-59%, or ≥ 60%. The association between clinical and CT variables with death was estimated with univariable and multivariable Cox proportional hazards models; model performance was assessed using k-fold cross-validation for the area under the ROC curve (cvAUC). RESULTS: Of the 866 included patients (median age 59.8, women 39.2%), 93 (10.74%) died. Clinical variables significantly associated with death in multivariable model were age, male sex, HDL cholesterol, dementia, heart failure, vascular diseases, time from symptom onset, neutrophils, LDH, and oxygen saturation level. CT disease extension was also independently associated with death (HR = 7.56, 95% CI = 3.49; 16.38 for ≥ 60% extension). cvAUCs were 0.927 (bootstrap bias-corrected 95% CI = 0.899-0.947) for the clinical model and 0.936 (bootstrap bias-corrected 95% CI = 0.912-0.953) when adding CT extension. CONCLUSIONS: A prognostic model based on clinical variables is highly accurate in predicting death in COVID-19 patients. Adding CT disease extension to the model scarcely improves its accuracy. KEY POINTS: • Early identification of COVID-19 patients at higher risk of disease progression and death is crucial; the role of CT scan in defining prognosis is unclear. • A clinical model based on age, sex, comorbidities, days from symptom onset, and laboratory results was highly accurate in predicting death in COVID-19 patients presenting to the emergency room. • Disease extension assessed with CT was independently associated with death when added to the model but did not produce a valuable increase in accuracy.

The association between clinical laboratory data and chest CT findings explains disease severity in a large Italian cohort of COVID-19 patients.

BACKGROUND: Laboratory data and computed tomography (CT) have been used during the COVID-19 pandemic, mainly to determine patient prognosis and guide clinical management. The aim of this study was to evaluate the association between CT findings and laboratory data in a cohort of COVID-19 patients. METHODS: This was an observational cross-sectional study including consecutive patients presenting to the Reggio Emilia (Italy) province emergency rooms for suspected COVID-19 for one month during the outbreak peak, who underwent chest CT scan and laboratory testing at presentation and resulted positive for SARS-CoV-2. RESULTS: Included were 866 patients. Total leukocytes, neutrophils, C-reactive protein (CRP), creatinine, AST, ALT and LDH increase with worsening parenchymal involvement; an increase in platelets was appreciable with the highest burden of lung involvement. A decrease in lymphocyte counts paralleled worsening parenchymal extension, along with reduced arterial oxygen partial pressure and saturation. After correcting for parenchymal extension, ground-glass opacities were associated with reduced platelets and increased procalcitonin, consolidation with increased CRP and reduced oxygen saturation. CONCLUSIONS: Pulmonary lesions induced by SARS-CoV-2 infection were associated with raised inflammatory response, impaired gas exchange and end-organ damage. These data suggest that lung lesions probably exert a central role in COVID-19 pathogenesis and clinical presentation.

Acute-phase reactants during tocilizumab therapy for severe COVID-19 pneumonia.

OBJECTIVES: To identify predictors of clinical improvement and intubation/death in tocilizumab-treated severe COVID19, focusing on IL6 and CRP longitudinal monitoring. METHODS: 173 consecutive patients with severe COVID-19 pneumonia receiving tocilizumab in Reggio Emilia province Hospitals between 11 March and 3 June 2020 were enrolled in a prospective cohort study. Clinical improvement was defined as status improvement on a six-category ordinal scale or discharge from the hospital, whichever came first. A composite outcome of intubation/death was also evaluated. CRP and IL-6 levels were determined before TCZ administration (T0) and after 3 (T3), and 7 (T7) days. RESULTS: At multivariate analysis T0 and T3 CRP levels were negatively associated with clinical improvement (OR 0.13, CI 0.03-0.55 and OR 0.11, CI 0.0-0.46) (p=0.006 and p=0.003) and positively associated with intubation/death (OR 17.66, CI 2.47-126.14 and OR 5.34, CI: 1.49-19.12) (p=0.01 and p=0.004). No significant associations with IL-6 values were observed. General linear model analyses for repeated measures showed significantly different trends for CRP from day 3 to day 7 between patients who improved and those who did not, and between patients who were intubated or died and those who were not (p<0.0001 for both). ROC analysis identified a baseline CRP level of 15.8 mg/dl as the best cut-off to predict intubation/death (AUC = 0.711, sensitivity = 0.67, specificity = 0.71). CONCLUSIONS: CRP serial measurements in the first week of TCZ therapy are useful in identifying patients developing poor outcomes.

SARS-CoV-2 Positive Hospitalized Cancer Patients during the Italian Outbreak: The Cohort Study in Reggio Emilia.

In the coronavirus disease (COVID-19) pandemic, cancer patients could be a high-risk group due to their immunosuppressed status; therefore, data on cancer patients must be available in order to consider the most adequate strategy of care. We carried out a cohort study on the risk of hospitalization for COVID-19, oncological history, and outcomes on COVID-19 infected cancer patients admitted to the Hospital of Reggio Emilia. Between 1 February and 3 April 2020, a total of 1226 COVID-19 infected patients were hospitalized. The number of cancer patients hospitalized with COVID-19 infection was 138 (11.3%). The median age was slightly higher in patients with cancers than in those without (76.5 vs. 73.0). The risk of intensive care unit (ICU) admission (10.1% vs. 6.7%; RR 1.23, 95% Confidence Interval (CI) 0.63-2.41) and risk of death (34.1% vs. 26.0%; RR 1.07, 95% CI 0.61-1.71) were similar in cancer and non-cancer patients. In the cancer patients group, 89/138 (64.5%) patients had a time interval >5 years between the diagnosis of the tumor and hospitalization. Male gender, age > 74 years, metastatic disease, bladder cancer, and cardiovascular disease were associated with mortality risk in cancer patients. In the Reggio Emilia Study, the incidence of hospitalization for COVID-19 in people with previous diagnosis of cancer is similar to that in the general population (standardized incidence ratio 98; 95% CI 73-131), and it does not appear to have a more severe course or a higher mortality rate than patients without cancer. The phase II of the COVID-19 epidemic in cancer patients needs a strategy to reduce the likelihood of infection and identify the vulnerable population, both in patients with active antineoplastic treatment and in survivors with frequently different coexisting medical conditions.

Accuracy of CT in a cohort of symptomatic patients with suspected COVID-19 pneumonia during the outbreak peak in Italy.

OBJECTIVE: To assess sensitivity/specificity of CT vs RT-PCR for the diagnosis of COVID-19 pneumonia in a prospective Italian cohort of symptomatic patients during the outbreak peak. METHODS: In this cross-sectional study, we included all consecutive patients who presented to the ER between March 13 and 23 for suspected COVID-19 and underwent CT and RT-PCR within 3 days. Using a structured report, radiologists prospectively classified CTs in highly suggestive, suggestive, and non-suggestive of COVID-19 pneumonia. Ground-glass, consolidation, and visual extension of parenchymal changes were collected. Three different RT-PCR-based reference standard definitions were used. Oxygen saturation level, CRP, LDH, and blood cell counts were collected and compared between CT/RT-PCR classes. RESULTS: The study included 696 patients (41.4% women; age 59 ± 15.8 years): 423/454 (93%) patients with highly suggestive CT, 97/127 (76%) with suggestive CT, and 31/115 (27%) with non-suggestive CT had positive RT-PCR. CT sensitivity ranged from 73 to 77% and from 90 to 94% for high and low positivity threshold, respectively. Specificity ranged from 79 to 84% for high positivity threshold and was about 58% for low positivity threshold. PPV remained ≥ 90% in all cases. Ground-glass was more frequent in patients with positive RT-PCR in all CT classes. Blood tests were significantly associated with RT-PCR and CT classes. Leukocytes, lymphocytes, neutrophils, and platelets decreased, CRP and LDH increased from non-suggestive to suggestive CT classes. CONCLUSIONS: During the outbreak peak (in a high-prevalence setting), CT presented high PPV and may be considered a good reference to recognize COVID-19 patients while waiting for RT-PCR confirmation. KEY POINTS: • During the epidemic peak, CT showed high positive predictive value and sensitivity for COVID-19 pneumonia when compared with RT-PCR. • Blood tests were significantly associated with RT-PCR and CT classes.

Abdominal Visceral Infarction in 3 Patients with COVID-19.

A high incidence of thrombotic events has been reported in patients with coronavirus disease (COVID-19), which is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. We report 3 clinical cases of patients in Italy with COVID-19 who developed abdominal viscera infarction, demonstrated by computed tomography.