Lung perfusion assessed by SPECT/CT after a minimum of three months anticoagulation therapy in patients with SARS-CoV-2-associated acute pulmonary embolism: a retrospective observational study.

BACKGROUND: Anticoagulant treatment is recommended for at least three months after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related acute pulmonary embolism (PE), but the persistent pulmonary clot burden after that time is unknown. METHODS: Lung perfusion was assessed by ventilation-perfusion (V/Q) SPECT/CT in 20 consecutive patients with SARS-CoV-2-associated acute PE after a minimum of three months anticoagulation therapy in a retrospective observational study. RESULTS: Remaining perfusion defects after a median treatment period of six months were observed in only two patients. All patients (13 men, seven women, mean age 55.6 ± 14.5 years) were on non-vitamin K direct oral anticoagulants (DOACs). No recurrent venous thromboembolism or anticoagulant-related bleeding complications were observed. Among patients with partial clinical recovery, high-risk PE and persistent pulmonary infiltrates were significantly more frequent (p < 0.001, respectively). INTERPRETATION: Temporary DOAC treatment seems to be safe and efficacious for resolving pulmonary clot burden in SARS-CoV-2-associated acute PE. Partial clinical recovery is more likely caused by prolonged SARS-CoV-2-related parenchymal lung damage rather than by persistent pulmonary perfusion defects.

Artificial Intelligence-Based Detection of Pneumonia in Chest Radiographs.

Artificial intelligence is gaining increasing relevance in the field of radiology. This study retrospectively evaluates how a commercially available deep learning algorithm can detect pneumonia in chest radiographs (CR) in emergency departments. The chest radiographs of 948 patients with dyspnea between 3 February and 8 May 2020, as well as 15 October and 15 December 2020, were used. A deep learning algorithm was used to identify opacifications associated with pneumonia, and the performance was evaluated by using ROC analysis, sensitivity, specificity, PPV and NPV. Two radiologists assessed all enrolled images for pulmonal infection patterns as the reference standard. If consolidations or opacifications were present, the radiologists classified the pulmonal findings regarding a possible COVID-19 infection because of the ongoing pandemic. The AUROC value of the deep learning algorithm reached 0.923 when detecting pneumonia in chest radiographs with a sensitivity of 95.4%, specificity of 66.0%, PPV of 80.2% and NPV of 90.8%. The detection of COVID-19 pneumonia in CR by radiologists was achieved with a sensitivity of 50.6% and a specificity of 73%. The deep learning algorithm proved to be an excellent tool for detecting pneumonia in chest radiographs. Thus, the assessment of suspicious chest radiographs can be purposefully supported, shortening the turnaround time for reporting relevant findings and aiding early triage.

Impact of the COVID-19 Pandemic on In-Patient Treatment of Peripheral Artery Disease in Germany during the First Pandemic Wave.

Patients with peripheral artery disease (PAD) belong to a vulnerable population with relevant comorbidity. Appropriate care and timely treatment are imperative, but not readily assured in the current pandemic. What impact did the first wave have on in-hospital treatment in Germany? Nationwide healthcare remuneration data for inpatient care of the years 2019 and 2020 were used to compare demographic baseline data including the assessment of comorbidity (van Walraven score), as well as the encoded treatments. A direct comparison was made between the first wave of infections in 2020 and the reference period in 2019. The number of inpatient admissions decreased by 10.9%, with a relative increase in hospitalizations due to PAD Fontaine IV (+13.6%). Baseline demographics and comorbidity showed no relevant differences. The proportion of emergency admissions increased from 23.4% to 28.3% during the first wave to the reference period in 2019, and in-hospital mortality increased by 21.9% from 2.5% to 3.1%. Minor and major amputations increased by 24.5% and 18.5%. Endovascular and combined surgical/endovascular treatment strategies increased for all stages. Already in the first, comparatively mild wave of the pandemic, significantly fewer patients with predominantly higher-grade PAD stages were treated as inpatients. Consecutively, in-hospital mortality and amputation rates increased.

Typical Imaging Patterns in COVID-19 Infections of the Lung on Plain Chest Radiographs to Aid Early Triage.

PURPOSE: To evaluate imaging patterns of a COVID-19 infection of the lungs on chest radiographs and their value in discriminating this infection from other viral pneumonias. MATERIALS AND METHODS: All 321 patients who presented with respiratory impairment suspicious for COVID-19 infection between February 3 and May 8, 2020 and who received a chest radiograph were included in this analysis. Imaging findings were classified as typical for COVID-19 (bilateral, peripheral opacifications/consolidations), non-typical (findings consistent with lobar pneumonia), indeterminate (all other distribution patterns of opacifications/consolidations), or none (no opacifications/consolidations). The sensitivity, specificity, as well as positive and negative predictive value for the diagnostic value of the category "typical" were determined. Chi² test was used to compare the pattern distribution between the different types of pneumonia. RESULTS: Imaging patterns defined as typical for COVID-19 infections were documented in 35/111 (31.5 %) patients with confirmed COVID-19 infection but only in 4/210 (2 %) patients with any other kind of pneumonia, resulting in a sensitivity of 31.5 %, a specificity of 98.1 %, and a positive and negative predictive value of 89.7 % or 73 %, respectively. The sensitivity could be increased to 45.9 % when defining also unilateral, peripheral opacifications/consolidations with no relevant pathology contralaterally as consistent with a COVID-19 infection, while the specificity decreases slightly to 93.3 %. The pattern distribution between COVID-19 patients and those with other types of pneumonia differed significantly (p < 0.0001). CONCLUSION: Although the moderate sensitivity does not allow the meaningful use of chest radiographs as part of primary screening, the specific pattern of findings in a relevant proportion of those affected should be communicated quickly as additional information and trigger appropriate protective measures. KEY POINTS: · COVID-19 infections show specific X-ray image patterns in 1/3 of patients.. · Bilateral, peripheral opacities and/or consolidations are typical imaging patterns.. · Unilateral, peripheral opacities and/or consolidations should also raise suspicion of COVID-19 infection.. CITATION FORMAT: · Kasper J, Decker J, Wiesenreiter K et al. Typical Imaging Patterns in COVID-19 Infections of the Lung on Plain Chest Radiographs to Aid Early Triage. Fortschr Röntgenstr 2021; 193: 1189 - 1196.