Strategies to safely rule out pulmonary embolism in COVID-19 outpatients: a multicenter retrospective study.

OBJECTIVES: The objective was to define a safe strategy to exclude pulmonary embolism (PE) in COVID-19 outpatients, without performing CT pulmonary angiogram (CTPA). METHODS: COVID-19 outpatients from 15 university hospitals who underwent a CTPA were retrospectively evaluated. D-Dimers, variables of the revised Geneva and Wells scores, as well as laboratory findings and clinical characteristics related to COVID-19 pneumonia, were collected. CTPA reports were reviewed for the presence of PE and the extent of COVID-19 disease. PE rule-out strategies were based solely on D-Dimer tests using different thresholds, the revised Geneva and Wells scores, and a COVID-19 PE prediction model built on our dataset were compared. The area under the receiver operating characteristics curve (AUC), failure rate, and efficiency were calculated. RESULTS: In total, 1369 patients were included of whom 124 were PE positive (9.1%). Failure rate and efficiency of D-Dimer > 500 µg/l were 0.9% (95%CI, 0.2-4.8%) and 10.1% (8.5-11.9%), respectively, increasing to 1.0% (0.2-5.3%) and 16.4% (14.4-18.7%), respectively, for an age-adjusted D-Dimer level. D-dimer > 1000 µg/l led to an unacceptable failure rate to 8.1% (4.4-14.5%). The best performances of the revised Geneva and Wells scores were obtained using the age-adjusted D-Dimer level. They had the same failure rate of 1.0% (0.2-5.3%) for efficiency of 16.8% (14.7-19.1%), and 16.9% (14.8-19.2%) respectively. The developed COVID-19 PE prediction model had an AUC of 0.609 (0.594-0.623) with an efficiency of 20.5% (18.4-22.8%) when its failure was set to 0.8%. CONCLUSIONS: The strategy to safely exclude PE in COVID-19 outpatients should not differ from that used in non-COVID-19 patients. The added value of the COVID-19 PE prediction model is minor. KEY POINTS: • D-dimer level remains the most important predictor of pulmonary embolism in COVID-19 patients. • The AUCs of the revised Geneva and Wells scores using an age-adjusted D-dimer threshold were 0.587 (95%CI, 0.572 to 0.603) and 0.588 (95%CI, 0.572 to 0.603). • The AUC of COVID-19-specific strategy to rule out pulmonary embolism ranged from 0.513 (95%CI: 0.503 to 0.522) to 0.609 (95%CI: 0.594 to 0.623).

Attitudes and perceptions of radiologists towards online (virtual) oncologic multidisciplinary team meetings during the COVID-19 pandemic-a survey of the European Society of Oncologic Imaging (ESOI).

OBJECTIVES: To explore radiologists' opinions regarding the shift from in-person oncologic multidisciplinary team meetings (MDTMs) to online MDTMs. To assess the perceived impact of online MDTMs, and to evaluate clinical and technical aspects of online meetings. METHODS: An online questionnaire including 24 questions was e-mailed to all European Society of Oncologic Imaging (ESOI) members. Questions targeted the structure and efficacy of online MDTMs, including benefits and limitations. RESULTS: A total of 204 radiologists responded to the survey. Responses were evaluated using descriptive statistical analysis. The majority (157/204; 77%) reported a shift to online MDTMs at the start of the pandemic. For the most part, this transition had a positive effect on maintaining and improving attendance. The majority of participants reported that online MDTMs provide the same clinical standard as in-person meetings, and that interdisciplinary discussion and review of imaging data were not hindered. Seventy three of 204 (35.8%) participants favour reverting to in-person MDTs, once safe to do so, while 7/204 (3.4%) prefer a continuation of online MDTMs. The majority (124/204, 60.8%) prefer a combination of physical and online MDTMs. CONCLUSIONS: Online MDTMs are a viable alternative to in-person meetings enabling continued timely high-quality provision of care with maintained coordination between specialties. They were accepted by the majority of surveyed radiologists who also favoured their continuation after the pandemic, preferably in combination with in-person meetings. An awareness of communication issues particular to online meetings is important. Training, improved software, and availability of support are essential to overcome technical and IT difficulties reported by participants. KEY POINTS: • Majority of surveyed radiologists reported shift from in-person to online oncologic MDT meetings during the COVID-19 pandemic. • The shift to online MDTMs was feasible and generally accepted by the radiologists surveyed with the majority reporting that online MDTMs provide the same clinical standard as in-person meetings. • Most would favour the return to in-person MDTMs but would also accept the continued use of online MDTMs following the end of the current pandemic.

Attitudes and perceptions of radiologists towards online (virtual) oncologic multidisciplinary team meetings during the COVID-19 pandemic—a survey of the European Society of Oncologic Imaging (ESOI)

Objectives To explore radiologists’ opinions regarding the shift from in-person oncologic multidisciplinary team meetings (MDTMs) to online MDTMs. To assess the perceived impact of online MDTMs, and to evaluate clinical and technical aspects of online meetings. Methods An online questionnaire including 24 questions was e-mailed to all European Society of Oncologic Imaging (ESOI) members. Questions targeted the structure and efficacy of online MDTMs, including benefits and limitations. Results A total of 204 radiologists responded to the survey. Responses were evaluated using descriptive statistical analysis. The majority (157/204;77%) reported a shift to online MDTMs at the start of the pandemic. For the most part, this transition had a positive effect on maintaining and improving attendance. The majority of participants reported that online MDTMs provide the same clinical standard as in-person meetings, and that interdisciplinary discussion and review of imaging data were not hindered. Seventy three of 204 (35.8%) participants favour reverting to in-person MDTs, once safe to do so, while 7/204 (3.4%) prefer a continuation of online MDTMs. The majority (124/204, 60.8%) prefer a combination of physical and online MDTMs. Conclusions Online MDTMs are a viable alternative to in-person meetings enabling continued timely high-quality provision of care with maintained coordination between specialties. They were accepted by the majority of surveyed radiologists who also favoured their continuation after the pandemic, preferably in combination with in-person meetings. An awareness of communication issues particular to online meetings is important. Training, improved software, and availability of support are essential to overcome technical and IT difficulties reported by participants. Key Points • Majority of surveyed radiologists reported shift from in-person to online oncologic MDT meetings during the COVID-19 pandemic. • The shift to online MDTMs was feasible and generally accepted by the radiologists surveyed with the majority reporting that online MDTMs provide the same clinical standard as in-person meetings. • Most would favour the return to in-person MDTMs but would also accept the continued use of online MDTMs following the end of the current pandemic.

Adjusting D-dimer to Lung Disease Extent to Exclude Pulmonary Embolism in COVID-19 Patients (Co-LEAD).

OBJECTIVE: D-dimer measurement is a safe tool to exclude pulmonary embolism (PE), but its specificity decreases in coronavirus disease 2019 (COVID-19) patients. Our aim was to derive a new algorithm with a specific D-dimer threshold for COVID-19 patients. METHODS: We conducted a French multicenter, retrospective cohort study among 774 COVID-19 patients with suspected PE. D-dimer threshold adjusted to extent of lung damage found on computed tomography (CT) was derived in a patient set (n = 337), and its safety assessed in an independent validation set (n = 337). RESULTS: According to receiver operating characteristic curves, in the derivation set, D-dimer safely excluded PE, with one false negative, when using a 900 ng/mL threshold when lung damage extent was <50% and 1,700 ng/mL when lung damage extent was ≥50%. In the derivation set, the algorithm sensitivity was 98.2% (95% confidence interval [CI]: 94.7-100.0) and its specificity 28.4% (95% CI: 24.1-32.3). The negative likelihood ratio (NLR) was 0.06 (95% CI: 0.01-0.44) and the area under the curve (AUC) was 0.63 (95% CI: 0.60-0.67). In the validation set, sensitivity and specificity were 96.7% (95% CI: 88.7-99.6) and 39.2% (95% CI: 32.2-46.1), respectively. The NLR was 0.08 (95% CI; 0.02-0.33), and the AUC did not differ from that of the derivation set (0.68, 95% CI: 0.64-0.72, p = 0.097). Using the Co-LEAD algorithm, 76 among 250 (30.4%) COVID-19 patients with suspected PE could have been managed without CT pulmonary angiography (CTPA) and 88 patients would have required two CTs. CONCLUSION: The Co-LEAD algorithm could safely exclude PE, and could reduce the use of CTPA in COVID-19 patients. Further prospective studies need to validate this strategy.

What level of D-dimers can safely exclude pulmonary embolism in COVID-19 patients presenting to the emergency department?

OBJECTIVES: To identify which level of D-dimer would allow the safe exclusion of pulmonary embolism (PE) in COVID-19 patients presenting to the emergency department (ED). METHODS: This retrospective study was conducted on the COVID database of Assistance Publique - Hôpitaux de Paris (AP-HP). COVID-19 patients who presented at the ED of AP-HP hospitals between March 1 and May 15, 2020, and had CTPA following D-dimer dosage within 48h of presentation were included. The D-dimer sensitivity, specificity, and positive and negative predictive values were calculated for different D-dimer thresholds, as well as the false-negative and failure rates, and the number of CTPAs potentially avoided. RESULTS: A total of 781 patients (mean age 62.0 years, 53.8% men) with positive RT-PCR for SARS-Cov-2 were included and 60 of them (7.7%) had CTPA-confirmed PE. Their median D-dimer level was significantly higher than that of patients without PE (4,013 vs 1,198 ng·mL-1, p < 0.001). Using 500 ng·mL-1, or an age-adjusted cut-off for patients > 50 years, the sensitivity and the NPV were above 90%. With these thresholds, 17.1% and 31.5% of CTPAs could have been avoided, respectively. Four of the 178 patients who had a D-dimer below the age-adjusted cutoff had PE, leading to an acceptable failure rate of 2.2%. Using higher D-dimer cut-offs could have avoided more CTPAs, but would have lowered the sensitivity and increased the failure rate. CONCLUSION: The same D-Dimer thresholds as those validated in non-COVID outpatients should be used to safely rule out PE. KEY POINTS: • The median D-dimer level was significantly higher in COVID-19 patients with PE as compared to those without PE (4,013 ng·mL-1 vs 1,198 ng·mL-1 respectively, p < 0.001). • Using 500 ng·mL-1, or an age-adjusted D-dimer cut-off to exclude pulmonary embolism, the sensitivity and negative predictive value were above 90%. • Higher cut-offs would lead to a reduction in the sensitivity below 85% and an increase in the failure rate, especially for patients under 50 years.

Study of Thoracic CT in COVID-19: The STOIC Project.

Background There are conflicting data regarding the diagnostic performance of chest CT for COVID-19 pneumonia. Disease extent at CT has been reported to influence prognosis. Purpose To create a large publicly available data set and assess the diagnostic and prognostic value of CT in COVID-19 pneumonia. Materials and Methods This multicenter, observational, retrospective cohort study involved 20 French university hospitals. Eligible patients presented at the emergency departments of the hospitals involved between March 1 and April 30th, 2020, and underwent both thoracic CT and reverse transcription-polymerase chain reaction (RT-PCR) testing for suspected COVID-19 pneumonia. CT images were read blinded to initial reports, RT-PCR, demographic characteristics, clinical symptoms, and outcome. Readers classified CT scans as either positive or negative for COVID-19 based on criteria published by the French Society of Radiology. Multivariable logistic regression was used to develop a model predicting severe outcome (intubation or death) at 1-month follow-up in patients positive for both RT-PCR and CT, using clinical and radiologic features. Results Among 10 930 patients screened for eligibility, 10 735 (median age, 65 years; interquartile range, 51-77 years; 6147 men) were included and 6448 (60%) had a positive RT-PCR result. With RT-PCR as reference, the sensitivity and specificity of CT were 80.2% (95% CI: 79.3, 81.2) and 79.7% (95% CI: 78.5, 80.9), respectively, with strong agreement between junior and senior radiologists (Gwet AC1 coefficient, 0.79). Of all the variables analyzed, the extent of pneumonia at CT (odds ratio, 3.25; 95% CI: 2.71, 3.89) was the best predictor of severe outcome at 1 month. A score based solely on clinical variables predicted a severe outcome with an area under the curve of 0.64 (95% CI: 0.62, 0.66), improving to 0.69 (95% CI: 0.6, 0.71) when it also included the extent of pneumonia and coronary calcium score at CT. Conclusion Using predefined criteria, CT reading is not influenced by reader's experience and helps predict the outcome at 1 month. ClinicalTrials.gov identifier: NCT04355507 Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Rubin in this issue.

Prevalence and characteristics of pulmonary embolism in 1042 COVID-19 patients with respiratory symptoms: A nested case-control study.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) has been associated with cardiovascular complications and coagulation disorders. Previous studies reported pulmonary embolism (PE) in severe COVID-19 patients. Aim of the study was to estimate the prevalence of symptomatic PE in COVID-19 patients and to identify the clinical, radiological or biological characteristics associated with PE. PATIENTS/METHODS: We conducted a retrospective nested case-control study in 2 French hospitals. Controls were matched in a 1:2 ratio on the basis of age, sex and center. PE patients with COVID-19 were compared to patients in whom PE was ruled out (CTPA controls) and in whom PE has not been investigated (CT controls). RESULTS: PE was suspected in 269 patients among 1042 COVID-19 patients, and confirmed in 59 patients (5.6%). Half of PE was diagnosed at COVID-19 diagnosis. PE patients did not differ from CT and CTPA controls for thrombosis risk factors. PE patients more often required invasive ventilation compared to CTPA controls (odds ratio (OR) 2.79; 95% confidence interval (CI) 1.33-5.84) and to CT controls (OR 8.07; 95% CI 2.70-23.82). PE patients exhibited more extensive parenchymal lesions (>50%) than CT controls (OR 3.90; 95% CI 1.54-9.94). D-dimer levels were 5.1 (95% CI 1.90-13.76) times higher in PE patients than CTPA controls. CONCLUSIONS: Our results suggest a PE prevalence in COVID-19 patients close to 5% in the whole population and to 20% of the clinically suspected population. PE seems to be associated with more extensive lung damage and to require more frequently invasive ventilation.

Determining extent of COVID-19 pneumonia on CT based on biological variables.

INTRODUCTION: Covid-19 pneumonia CT extent correlates well with outcome including mortality. However, CT is not widely available in many countries. This study aimed to explore the relationship between Covid-19 pneumonia CT extent and blood tests variations. The objective was to determine for the biological variables correlating with disease severity the cut-off values showing the best performance to predict the parenchymal extent of the pneumonia. METHODS: Bivariate correlations were calculated between biological variables and grade of disease extent on CT. Receiving Operating Characteristic curve analysis determined the best cutoffs for the strongest correlated biological variables. The performance of these variables to predict mild (<10%) or severe pneumonia (>50% of parenchyma involved) was evaluated. RESULTS: Correlations between biological variables and disease extent was evaluated in 168 patients included in this study. LDH, lymphocyte count and CRP showed the strongest correlations (with 0.67, -0.41 and 0.52 correlation coefficient, respectively). Patients were split into a training and a validation cohort according to their centers. If one variable was above/below the following cut-offs, LDH>380, CRP>80 or lymphocyte count <0.8G/L, severe pneumonia extent on CT was detected with 100% sensitivity. Values above/below all three thresholds were denoted in 73% of patients with severe pneumonia extent. The combination of LDH<220 and CRP<22 was associated with mild pneumonia extent (<10%) with specificity of 100%. DISCUSSION: LDH showed the strongest correlation with the extent of Covid-19 pneumonia on CT. Combined with CRP±lymphocyte count, it helps predicting parenchymal extent of the pneumonia when CT scan is not available.

AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia.

Coronavirus disease 2019 (COVID-19) emerged in 2019 and disseminated around the world rapidly. Computed tomography (CT) imaging has been proven to be an important tool for screening, disease quantification and staging. The latter is of extreme importance for organizational anticipation (availability of intensive care unit beds, patient management planning) as well as to accelerate drug development through rapid, reproducible and quantified assessment of treatment response. Even if currently there are no specific guidelines for the staging of the patients, CT together with some clinical and biological biomarkers are used. In this study, we collected a multi-center cohort and we investigated the use of medical imaging and artificial intelligence for disease quantification, staging and outcome prediction. Our approach relies on automatic deep learning-based disease quantification using an ensemble of architectures, and a data-driven consensus for the staging and outcome prediction of the patients fusing imaging biomarkers with clinical and biological attributes. Highly promising results on multiple external/independent evaluation cohorts as well as comparisons with expert human readers demonstrate the potentials of our approach.

Socio-economic and psychological impact of the COVID-19 outbreak on private practice and public hospital radiologists.

PURPOSE: The COVID-19 pandemic has led to an urgent reorganisation of the healthcare system to prevent hospitals from overflowing and the virus from spreading. Our objective was to evaluate the socioeconomic and psychological impact of the COVID-19 outbreak on radiologists. MATERIAL AND METHODS: French radiologists were invited to answer an online survey during the pandemic through mailing lists. The questionnaire was accessible for nine days. It covered socio-demographic information, exposure to COVID-19 at work and impact on work organisation, and included the Insomnia Severity Index and Hospital Anxiety and Depression Scale. Outcomes were moderate to severe insomnia, definite symptoms of depression or anxiety. Risk and protective factors were identified through multivariate binary logistic regression. RESULTS: 1515 radiologists answered the survey. Overall, 674 (44.5 %) worked in a highCOVID-19 density area, 671 (44.3 %) were women, and 809 (53.4 %) worked in private practice. Among responders, 186 (12.3 %) expressed insomnia, 222 (14.6 %) anxiety, and 189 (12.5 %) depression symptoms. Lack of protective equipment, increased teleradiology activity and negative impact on education were risk factors for insomnia (respectively OR [95 %CI]:1.7[1.1-2.7], 1.5[1.1-2.2], and 2.5[1.8-3.6]). Female gender, respiratory history, working in COVID-19 high density area, increase of COVID-19 related activity, and impacted education were risk factors for anxiety (OR[95 %CI]:1.7[1.2-2.3], 2[1.1-3.4], 1.5[1.1-2], 1.2[1-1.4], and 2.1[1.5-3]). Conversely, working in a public hospital was a protective factor against insomnia, anxiety, and depression (OR[95 %CI]:0.4[0.2-0.7], 0.6[0.4-0.9], and 0.5[0.3-0.8]). CONCLUSIONS: During COVID-19 pandemic, many radiologists expressed depression, anxiety and insomnia symptoms. Working in a public hospital was a protective factor against every psychological symptom. Socio-economic impact was also major especially in private practice.