Background Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) infection is associated with hypercoagulability caused by direct invasion of endothelial cells and\or proinflammatory cytokine release. Thromboprophylaxis with enoxaparin is recommended by current guidelines, but evidence is still weak. The aim of this study was to assess the impact of thromboprophylaxis with enoxaparin on hospital mortality in patients admitted for Coronavirus disease 2019 (COVID-19). The effects of enoxaparin on intensive care admission and hospital length-of-stay were evaluated as secondary outcomes. Methods Observational cohort study, with data collected from patients admitted to Poliambulanza Foundation with positive real time reverse transcription polymerase chain reaction (RT-PCR) for SARS-CoV-2 from 20th February to 10th May 2020. Multivariate logistic regression with overlap weight propensity score was used to model hospital mortality and intensive care admission, hospital length-of-stay was analyzed with a multivariate Poisson regression. Seven hundred and ninety nine (57%) patients who received enoxaparin at least once during the hospitalization were included in the enoxaparin cohort, 604 (43%) patients who did not were included in the control cohort. Findings At the adjusted analysis enoxaparin was associated with lower in-hospital mortality (Odds Ratio 0·53, 95% C.I. 0·40–0·70) compared with no enoxaparin treatment. Hospital length-of-stay was longer for patients treated with enoxaparin (Incidence Rate Ratios 1·45, 95% C.I. 1·36–1·54). Enoxaparin treatment was associated with reduced risk of intensive care admission at the adjusted analysis (Odds Ratio 0·48, 95% C.I. 0·32–0·69). Interpretation This study shows that treatment with enoxaparin during hospital stay is associated with a lower death rate and, while results from randomized clinical trials are still pending, this study supports the use of thromboprophylaxis with enoxaparin in all patients admitted for COVID-19. Moreover, when enoxaparin is used on the wards, it reduces the risk of Intensive Care Unit admission.

We analyzed ventilation-induced changes in arterial blood pressure and photoplethysmography from waveforms obtained by monitoring 57 patients in the operating room and intensive care unit. Analysis of systolic and pulse pressure variations during positive pressure ventilation, DeltaUp, DeltaDown, and changes in the preejection period on both arterial and photoplethysmographic waveforms were possible in 49 (86%) patients. The pulse pressure variation and preejection period were similar when calculated using both arterial blood pressure and photoplethysmography, whereas the other variables were different. Photoplethysmographic pulse variation >9% identified patients with arterial pulse pressure variation >13% (area under ROC curve = 0.85) or DeltaDown >5 mm Hg (area under ROC curve = 0.85). In hypotensive patients, photoplethysmographic pulse variation >9% remained the best threshold value (pulse pressure variation >13%: area under ROC curve = 0.90; DeltaDown >5 mm Hg: area under ROC curve = 0.93) for predicting fluid responsiveness. In conclusion, this study showed that pulse variations observed in the arterial pressure waveform and photoplethysmogram are similiar in response to positive pressure ventilation. Furthermore, photoplethysmographic pulse variation > 9% identifies patients with ventilation-induced arterial blood pressure variation that is likely to respond to fluid administration.

Both the PLMA and the LMA can be used for mechanical ventilation of obese patients. The patency of the PLMA drainage tube needs to be checked constantly even when an optimal airtight seal is present. In obese patients the LMA requires a greater cuff pressure than the PLMA, but sore throat is not related to the cuff pressure. Sore throat assessment in the recovery room appears as reliable as assessment later.

Background Flow Index, a numerical expression of the shape of the inspiratory flow-time waveform recorded during pressure support ventilation, is associated with patient inspiratory effort. The aim of this study was to assess the accuracy of Flow Index in detecting high or low inspiratory effort during pressure support ventilation and to establish cutoff values for the Flow index to identify these conditions. The secondary aim was to compare the performance of Flow index,of breathing pattern parameters and of airway occlusion pressure (P0.1) in detecting high or low inspiratory effort during pressure support ventilation. Methods Data from 24 subjects was included in the analysis, accounting for a total of 702 breaths. Breaths with high inspiratory effort were defined by a pressure developed by inspiratory muscles (Pmusc) greater than 10 cmH2O while breaths with low inspiratory effort were defined by a Pmusc lower than 5 cmH2O. The areas under the receiver operating characteristic curves of Flow Index and respiratory rate, tidal volume,respiratory rate over tidal volume and P0.1 were analyzed and compared to identify breaths with low or high inspiratory effort. Results Pmusc, P0.1, Pressure Time Product and Flow Index differed between breaths with high, low and intermediate inspiratory effort, while RR, RR/VT and VT/kg of IBW did not differ in a statistically significant way. A Flow index higher than 4.5 identified breaths with high inspiratory effort [AUC 0.89 (CI 95% 0.85–0.93)], a Flow Index lower than 2.6 identified breaths with low inspiratory effort [AUC 0.80 (CI 95% 0.76–0.83)]. Conclusions Flow Index is accurate in detecting high and low spontaneous inspiratory effort during pressure support ventilation.

This study demonstrates greater early postoperative respiratory restrictive syndrome and lower arterial oxygen saturation following tracheal intubation compared to LMA use in patients without respiratory disease.