Convalescent plasma therapy for coronavirus disease 2019 in ambulatory versus hospitalized patients: Efficacy and risk of thromboembolism.

Background: Although early evidence concluded a lack of clinical benefit of convalescent plasma therapy (CPT) in COVID-19 management, recent trials have demonstrated the therapeutic potential of CPT in ambulatory care. CPT may also potentiate thromboembolic events, given the presence of coagulation factors and the prothrombotic state of COVID-19. Objectives: The present study aimed to assess and compare the clinical efficacy and the risk of venous thromboembolism (VTE)/arterial thromboembolism (ATE) of CPT in ambulatory versus hospitalized patients with COVID-19. Methods: MEDLINE, Embase, and Cochrane CENTRAL were searched from December 2019 to December 2022 for randomized controlled trials that investigated the use of CPT against placebo or standard of care in adult patients with COVID-19. The primary outcome was nonmortality disease progression. Secondary outcomes include VTE, ATE, 28-day mortality, clinical improvement, length of hospitalization, sepsis/fever, and major adverse cardiovascular events. Results: Twenty randomized controlled trials, with 21,340 patients, were included. CPT significantly reduced nonmortality disease progression in ambulatory patients (odds ratio [OR], 0.72; 95% CI, 0.56-0.92; P = .009) but not in hospitalized patients (OR, 1.03; 95% CI, 0.94-1.12; P = .58). The risk of VTE and ATE did not differ between the CPT and the control group (OR, 1.16; 95% CI, 0.82-1.66; P = .40; and OR, 1.01; 95% CI, 0.37-2.79; P = .98, respectively). No conclusive differences between CPT and control groups were noted in 28-day mortality, clinical improvement, length of hospitalization, risk of sepsis/fever, and major adverse cardiovascular events. Conclusion: In conclusion, treatment of COVID-19 with CPT prevents the progression of COVID-19 in the ambulatory care. It is not associated with an increased risk of VTE, ATE, or other adverse events.

Convalescent Plasma Therapy for COVID-19 in Ambulatory vs Hospitalized Patients: Efficacy and Risk of Thromboembolism

Background While early evidence concluded a lack of clinical benefit of convalescent plasma therapy (CPT) in COVID-19 management, recent trials demonstrate the therapeutic potential of CPT in ambulatory care. CPT may also potentiate thromboembolic events given the presence of coagulation factors and the prothrombotic state of COVID-19. Objective The present study aims to assess and compare the clinical efficacy and the risk of venous/arterial thromboembolism (VTE, ATE) of CPT in ambulatory vs hospitalized COVID-19 patients. Methods MEDLINE, Embase, and Cochrane CENTRAL were searched from December 2019 to December 2022 for randomized controlled trials that investigated the use of CPT against placebo or standard of care in adult COVID-19 patients. The primary outcome was non-mortality disease progression. Secondary outcomes include VTE, ATE, 28-day mortality, clinical improvement, length of hospitalization (LOH), sepsis/fever, and major adverse cardiovascular events (MACE). Results Twenty randomized controlled trials, with 21340 patients, were included. CPT significantly reduced non-mortality disease progression in ambulatory patients (OR 0.72, 0.56-0.92, P = 0.009) but not in hospitalized patients (1.03, 0.94-1.12, P = 0.58). The risk of VTE and ATE did not differ between the CPT and the control group (1.15, 0.81 to 1.64, P = 0.44;1.01, 0.37 to 2.79, P = 0.98). No conclusive differences between CPT and control were noted in 28-day mortality, clinical improvement, LOH, risk of sepsis/fever, and MACE. Conclusions In conclusion, treatment of COVID-19 with CPT prevents the progression of COVID-19 in the ambulatory care. It is not associated with an increased risk of VTE, ATE, or other adverse events.

Detection of COVID-19 Using Deep Learning Algorithms on Chest Radiographs.

PURPOSE: To evaluate the performance of a deep learning (DL) algorithm for the detection of COVID-19 on chest radiographs (CXR). MATERIALS AND METHODS: In this retrospective study, a DL model was trained on 112,120 CXR images with 14 labeled classifiers (ChestX-ray14) and fine-tuned using initial CXR on hospital admission of 509 patients, who had undergone COVID-19 reverse transcriptase-polymerase chain reaction (RT-PCR). The test set consisted of a CXR on presentation of 248 individuals suspected of COVID-19 pneumonia between February 16 and March 3, 2020 from 4 centers (72 RT-PCR positives and 176 RT-PCR negatives). The CXR were independently reviewed by 3 radiologists and using the DL algorithm. Diagnostic performance was compared with radiologists' performance and was assessed by area under the receiver operating characteristics (AUC). RESULTS: The median age of the subjects in the test set was 61 (interquartile range: 39 to 79) years (51% male). The DL algorithm achieved an AUC of 0.81, sensitivity of 0.85, and specificity of 0.72 in detecting COVID-19 using RT-PCR as the reference standard. On subgroup analyses, the model achieved an AUC of 0.79, sensitivity of 0.80, and specificity of 0.74 in detecting COVID-19 in patients presented with fever or respiratory systems and an AUC of 0.87, sensitivity of 0.85, and specificity of 0.81 in distinguishing COVID-19 from other forms of pneumonia. The algorithm significantly outperforms human readers (P<0.001 using DeLong test) with higher sensitivity (P=0.01 using McNemar test). CONCLUSIONS: A DL algorithm (COV19NET) for the detection of COVID-19 on chest radiographs can potentially be an effective tool in triaging patients, particularly in resource-stretched health-care systems.