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.

ObjectiveTo estimate the predictive role of faecal haemoglobin (f-Hb) concentration among subjects with faecal immunochemical test (FIT) results below the positivity cut-off for the subsequent risk of advanced neoplasia (AN: colorectal cancer—CRC—or advanced adenoma).DesignProspective cohort of subjects aged 50–69 years, undergoing their first FIT between 1 January 2004 and 31 December 2010 in four population-based programmes in Italy.MethodsAll programmes adopted the same analytical procedure (OC Sensor, Eiken Japan), performed every 2 years, on a single sample, with the same positivity cut-off (20 µg Hb/g faeces). We assessed the AN risk at subsequent exams, the cumulative AN detection rate (DR) over the 4-year period following the second FIT and the interval CRC (IC) risk following two negative FITs by cumulative amount of f-Hb concentration over two consecutive negative FITs, using multivariable logistic regression models and the Kaplan-Meier method.ResultsThe cumulative probability of a positive FIT result over the subsequent two rounds ranged between 7.8% (95% CI 7.5 to 8.2) for subjects with undetectable f-Hb at the initial two tests (50% of the screenees) and 48.4% (95% CI 44.0 to 53.0) among those (0.7% of the screenees) with a cumulative f-Hb concentration ≥20 µg/g faeces. The corresponding figures for cumulative DR were: 1.4% (95% CI 1.3 to 1.6) and 25.5% (95% CI 21.4 to 30.2) for AN; 0.17% (95% CI 0.12 to 0.23) and 4.5% (95% CI 2.8 to 7.1) for CRC. IC risk was also associated with cumulative f-Hb levels.ConclusionThe association of cumulative f-Hb concentration with subsequent AN and IC risk may allow to design tailored strategies to optimise the utilisation of endoscopy resources: subjects with cumulative f-Hb concentration ≥20 µg/g faeces over two negative tests could be referred immediately for total colonoscopy (TC), while screening interval might be extended for those with undetectable f-Hb.

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. Supplementary Information The online version contains supplementary material available at 10.1007/s00330-021-07993-9.