Respiratory Mechanics in a Cohort of Critically Ill Subjects With COVID-19 Infection.

BACKGROUND: Patients with coronavirus disease 2019 (COVID-19) often develop acute hypoxemic respiratory failure and receive invasive mechanical ventilation. Much remains unknown about their respiratory mechanics, including the trajectories of pulmonary compliance and [Formula: see text]/[Formula: see text], the prognostic value of these parameters, and the effects of prone positioning. We described respiratory mechanics among subjects with COVID-19 who were intubated during the first month of hospitalization. METHODS: We included patients with COVID-19 who were mechanically ventilated between February and May 2020. Daily values of pulmonary compliance, [Formula: see text], [Formula: see text], and the use of prone positioning were abstracted from electronic medical records. The trends were analyzed separately over days 1-10 and days 1-35 of intubation, stratified by prone positioning use, survival, and initial [Formula: see text]/[Formula: see text]. RESULTS: Among 49 subjects on mechanical ventilation day 1, the mean compliance was 41 mL/cm H2O, decreasing to 25 mL/cm H2O by day 14, the median duration of mechanical ventilation. In contrast, the [Formula: see text]/[Formula: see text] on day 1 was similar to day 14. The overall mean compliance was greater among the non-survivors versus the survivors (27 mL/cm H2O vs 24 mL/cm H2O; P = .005), whereas [Formula: see text]/[Formula: see text] was higher among the survivors versus the non-survivors over days 1-10 (159 mm Hg vs 138 mm Hg; P = .002) and days 1-35 (175 mm Hg vs 153 mm Hg; P < .001). The subjects who underwent early prone positioning had lower compliance during days 1-10 (27 mL/cm H2O vs 33 mL/cm H2O; P < .001) and lower [Formula: see text]/[Formula: see text] values over days 1-10 (139.9 mm Hg vs 167.4 mm Hg; P < .001) versus those who did not undergo prone positioning. After day 21 of hospitalization, the average compliance of the subjects who had early prone positioning surpassed that of the subjects who did not have prone positioning. CONCLUSIONS: Respiratory mechanics of the subjects with COVID-19 who were on mechanical ventilation were characterized by persistently low respiratory system compliance and [Formula: see text]/[Formula: see text], similar to ARDS due to other etiologies. The [Formula: see text]/[Formula: see text] was more tightly associated with mortality than with compliance.

Emergency department characteristics and associations with intensive care admission among patients with coronavirus disease 2019.

OBJECTIVE: There have been few descriptions in the literature to date specifically examining initial coronavirus disease 2019 (COVID-19) patient presentation to the emergency department (ED) and the trajectory of patients who develop critical illness. Here we describe the ED presentation and outcomes of patients with COVID-19 presenting during our initial local surge. METHODS: This is a multicenter, retrospective cohort study using data extracted from the electronic health records at 3 hospitals within a single health system from March 1, 2020 to June 1, 2020. Patients were included in the study if they presented to an ED and had laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection during the study period. Data elements were extracted from the electronic health record electronically and by trained data abstractors and entered into a secure database. We used multivariable regression analysis to examine ED factors associated with the development of critical illness and mortality, with a primary outcome of ICU admission. RESULTS: A total of 330 patients with laboratory-confirmed SARS-CoV-2 infection were admitted during the study period. Of these, 112 (34%) were admitted to the ICU. Among these patients, 20% were female, 50% were White, the median age was 61 (interquartile range [IQR], 52-72), and the median body mass index (BMI) was 28.1 (IQR, 24.3-35.1). On univariable analysis, a doubling of lactate dehydrogenase (LDH) (odds ratio [OR], 3.87; 95% confidence interval [CI], 2.40-6.27) or high-sensitivity C-reactive protein (hsCRP; OR, 1.32; 95% CI, 1.11-1.57) above the reference range or elevated troponin (OR, 12.1; 95% CI, 1.20-121.8) were associated with ICU admission. After adjusting for age, sex, and BMI, LDH was the best predictor of ICU admission (OR, 3.54; 95% CI, 2.12-5.90). Of the patients, 15% required invasive mechanical ventilation during their hospital course, and in-hospital mortality was 19%. CONCLUSIONS: Nearly one-third of ED patients who required hospitalization for COVID-19 were admitted to the ICU, 15% received invasive mechanical ventilation, and 19% died. Most patients who were admitted from the ED were tachypneic with elevated inflammatory markers, and the following factors were associated with ICU admission: elevated hsCRP, LDH, and troponin as well as lower oxygen saturation and increased respiratory rate.

A primer on proning in the emergency department.

Historically, the prone position was used almost exclusively in the ICU for patients suffering from refractory hypoxemia due to acute respiratory distress syndrome (ARDS). Amidst the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, however, this technique has been increasingly utilized in settings outside of the ICU, particularly in the emergency department. With emerging evidence that patients diagnosed with COVID-19 who are not intubated and mechanically ventilated may benefit from the prone position, this strategy should not be isolated to only those with critical illness. This is a review of the pertinent physiology and evidence supporting prone positioning along with a step-by-step guide meant to familiarize those who are not already comfortable with the maneuver. Placing a patient in the prone position helps to improve ventilation-perfusion matching, dorsal lung recruitment, and ultimately gas exchange. Evidence also suggests there is improved oxygenation in both mechanically ventilated patients and those who are awake and spontaneously breathing, further reinforcing the utility of the prone position in non-ICU settings. Given present concerns about resource limitations because of the pandemic, prone positioning has especially demonstrable value as a technique to delay or even prevent intubation. Patients who are able to self-prone should be directed into the ''swimmer's position'' and then placed in reverse Trendelenburg position if further oxygenation is needed. If a mechanically ventilated patient is to be placed in the prone position, specific precautions should be taken to ensure the patient's safety and to prevent any unwanted sequelae of prone positioning.

On-capillary derivatization using a hybrid artificial neural network-genetic algorithm approach.

The first reported hybrid artificial neural network-genetic algorithm (ANN-GA) approach for the optimization of on-capillary dipeptide derivatization is presented. More specifically, genetic optimization proved valuable in the determination of effective network structure with three defined parameter inputs: (i) phthalic anhydride injection volume, (ii) time of injection, and (iii) voltage, for the maximum conversion of the dipeptide D-Ala-D-Ala by phthalic anhydride. Results obtained from the hybrid approach proved superior to an ANN model without GA optimization in terms of training data and predictive ability. The model developed will likely prove useful for the analysis of other organic-based reaction systems.

Application of artificial neural networks in the prediction of product distribution in electrophoretically mediated microanalysis.

The successful application of artificial neural networks toward the prediction of product distribution in electrophoretically mediated microanalysis is presented. To illustrate this concept, we examined the factors and levels required for optimization of reaction conditions for the conversion of nicotinamide adenine dinucleotide to nicotinamide adenine dinucleotide, reduced form by glucose-6-phosphate dehydrogenase in the conversion of glucose-6-phosphate to 6-phosphogluconate. A full factorial experimental design examining the factors voltage, enzyme concentration, and mixing time of reaction was utilized as input-output data sources for suitable artificial neural networks training for prediction purposes. This approach proved successful in predicting optimal values in a reduced number of experiments. Model validation addressing the extent of reaction and product ratios were subsequently determined experimentally in replicate analyses, with results shown to be in good agreement (<10% discrepancy difference) with predicted data.