Lung ultrasound to predict gas-exchange response to prone positioning in COVID-19 patients: A prospective study in pilot and confirmation cohorts.

PURPOSE: To examine whether lung ultrasound prior to prone positioning can predict the resulting gas-exchange response. MATERIALS AND METHODS: This is a prospective observational study on critically-ill COVID-19 patients with a pilot and confirmation cohort. Lung ultrasound examinations were performed before prone positioning and gas-exchange parameters were recorded before and after position change. RESULTS: A total of 79 patients, 36 in the pilot cohort and 43 in the confirmation cohort, were included. In the pilot cohort, a moderate correlation between pre-turn lung ultrasound score index (LUSI) and change in PaO2/FiO2 after prone positioning was found. These findings were corroborated and extended upon in the confirmation cohort. The confirmation cohort found that anterior LUSI had the strongest correlation with follow-up time-points 1, 6, 12, and 24 h after prone positioning, with strength of correlation gradually increasing up to 24 h. In a multivariate model anterior aeration loss (odds ratio 0.035; 95%CI 0.003-0.319 for anterior LUSI >50%) and higher pre-turn PaCO2 (odds ratio 0.479 95% CI 0.235-0.979) were negatively predictive of a PaO2/FiO2 increase ≥20 mmHg. CONCLUSIONS: Anterior LUSI, in addition to other clinical parameters, may be used to aid COVID-19 respiratory strategy and a clinician's decision to prone.

Dynamic prediction of mortality in COVID-19 patients in the intensive care unit: A retrospective multi-center cohort study.

Background: The COVID-19 pandemic continues to overwhelm intensive care units (ICUs) worldwide, and improved prediction of mortality among COVID-19 patients could assist decision making in the ICU setting. In this work, we report on the development and validation of a dynamic mortality model specifically for critically ill COVID-19 patients and discuss its potential utility in the ICU. Methods: We collected electronic medical record (EMR) data from 3222 ICU admissions with a COVID-19 infection from 25 different ICUs in the Netherlands. We extracted daily observations of each patient and fitted both a linear (logistic regression) and non-linear (random forest) model to predict mortality within 24 h from the moment of prediction. Isotonic regression was used to re-calibrate the predictions of the fitted models. We evaluated the models in a leave-one-ICU-out (LOIO) cross-validation procedure. Results: The logistic regression and random forest model yielded an area under the receiver operating characteristic curve of 0.87 [0.85; 0.88] and 0.86 [0.84; 0.88], respectively. The recalibrated model predictions showed a calibration intercept of -0.04 [-0.12; 0.04] and slope of 0.90 [0.85; 0.95] for logistic regression model and a calibration intercept of -0.19 [-0.27; -0.10] and slope of 0.89 [0.84; 0.94] for the random forest model. Discussion: We presented a model for dynamic mortality prediction, specifically for critically ill COVID-19 patients, which predicts near-term mortality rather than in-ICU mortality. The potential clinical utility of dynamic mortality models such as benchmarking, improving resource allocation and informing family members, as well as the development of models with more causal structure, should be topics for future research.

Multi-organ point-of-care ultrasound for detection of pulmonary embolism in critically ill COVID-19 patients - A diagnostic accuracy study.

PURPOSE: Critically ill COVID-19 patients have an increased risk of developing pulmonary embolism (PE). Diagnosis of PE by point-of-care ultrasound (POCUS) might reduce the need for computed tomography pulmonary angiography (CTPA), while decreasing time-to-diagnosis. MATERIALS & METHODS: This prospective, observational study included adult ICU patients with COVID-19. Multi-organ (lungs, deep vein, cardiac) POCUS was performed within 24 h of CTPA, looking for subpleural consolidations, deep venous thrombosis (DVT), and right ventricular strain (RVS). We reported the scan time, and calculated diagnostic accuracy measures for these signs separately and in combination. RESULTS: 70 consecutive patients were included. 23 patients (32.8%) had a PE. Median scan time was 14 min (IQR 11-17). Subpleural consolidations' diagnostic accuracy was: 42.9% (95%CI [34.1-52.0]). DVT's and RVS' diagnostic accuracy was: 75.6% (95%CI [67.1-82.9]) and 74.4% (95%CI [65.8-81.8]). Their sensitivity was: 24.0% (95%CI [9.4-45.1]), and 40.0% (95%CI [21.3-61.3]), while their specificity was: 88.8% (95%CI [80.8-94.3]), and: 83.0% (95%CI [74.2-89.8]), respectively. Multi-organ POCUS sensitivity was: 87.5% (95%CI [67.6-97.3]), and specificity was: 25% (95%CI [16.9-34.7]). CONCLUSIONS: Multi-organ rather than single-organ POCUS can be of aid in ruling out PE in critically ill COVID-19 and help select patients for CTPA. In addition, finding RVS can make PE more likely, while a DVT would preclude the need for a CTPA. REGISTRATION: www.trialregister.nl: NL8540.

POCUS series: point-of-care lung ultrasound in patients with COVID-19

This article is part of the point-of-care ultrasound (POCUS) series. During the Coronavirus Disease 2019 (COVID-19) pandemic, we have been managing large numbers of infected patients whilst maintaining high-quality healthcare. In this article we aim to provide a short and practical description on how point-of-care lung ultrasound can be of use to facilitate diagnosis and treatment in critically ill patients diagnosed with COVID-19.