PH in BPD is not always a transient condition; it can be diagnosed at later stages and can have a protracted course. The incidence of associated CVAs is high. Prompt diagnosis, detection, and treatment of CVAs, and specific drug therapy can improve the outcome in these patients, although the mortality rate remains high.

Background The clinical presentation of COVID-19 in patients admitted to hospital is heterogeneous. We aimed to determine whether clinical phenotypes of patients with COVID-19 can be derived from clinical data, to assess the reproducibility of these phenotypes and correlation with prognosis, and to derive and validate a simplified probabilistic model for phenotype assignment. Phenotype identification was not primarily intended as a predictive tool for mortality. MethodsIn this study, we used data from two cohorts: the COVID-19@Spain cohort, a retrospective cohort including 4035 consecutive adult patients admitted to 127 hospitals in Spain with COVID-19 between Feb 2 and March 17, 2020, and the COVID-19@HULP cohort, including 2226 consecutive adult patients admitted to a teaching hospital in Madrid between Feb 25 and April 19, 2020. The COVID-19@Spain cohort was divided into a derivation cohort, comprising 2667 randomly selected patients, and an internal validation cohort, comprising the remaining 1368 patients. The COVID-19@HULP cohort was used as an external validation cohort. A probabilistic model for phenotype assignment was derived in the derivation cohort using multinomial logistic regression and validated in the internal validation cohort. The model was also applied to the external validation cohort. 30-day mortality and other prognostic variables were assessed in the derived phenotypes and in the phenotypes assigned by the probabilistic model. Findings Three distinct phenotypes were derived in the derivation cohort (n=2667)-phenotype A (516 [19%] patients), phenotype B (1955 [73%]) and phenotype C (196 [7%])-and reproduced in the internal validation cohort (n=1368)phenotype A (233 [17%] patients), phenotype B (1019 [74%]), and phenotype C (116 [8%]). Patients with phenotype A were younger, were less frequently male, had mild viral symptoms, and had normal inflammatory parameters. Patients with phenotype B included more patients with obesity, lymphocytopenia, and moderately elevated inflammatory parameters. Patients with phenotype C included older patients with more comorbidities and even higher inflammatory parameters than phenotype B. We developed a simplified probabilistic model (validated in the internal validation cohort) for phenotype assignment, including 16 variables. In the derivation cohort, 30-day mortality rates were 2•5% (95% CI 1•4-4•3) for patients with phenotype A, 30•5% (28•5-32•6) for patients with phenotype B, and 60•7% (53•7-67•2) for patients with phenotype C (log-rank test p<0•0001). The predicted phenotypes in the internal validation cohort and external validation cohort showed similar mortality rates to the assigned phenotypes (internal validation cohort: 5•3% [95% CI 3•4-8•1] for phenotype A, 31•3% [28•5-34•2] for phenotype B, and 59•5% [48•8-69•3] for phenotype C; external validation cohort: 3•7% [2•0-6•4] for phenotype A, 23•7% [21•8-25•7] for phenotype B, and 51•4% [41•9-60•7] for phenotype C).Interpretation Patients admitted to hospital with COVID-19 can be classified into three...

Background Upper-extremity venous thrombosis is associated with the use of peripherally inserted central catheters (PICCs). Few pediatric studies have focused on this issue. Objectives To determine the incidence and risk factors for PICC-related superficial vein thrombosis (SVT) and deep vein thrombosis (DVT) in children. Patients/methods An observational follow-up cohort study was conducted at a single hospital between June 2012 and June 2015. All patients receiving a PICC were enrolled and followed up, with weekly Doppler ultrasound examination of the catheterized limb until PICC removal. Patient, procedural and follow-up data were analyzed. Results In the study period, 265 PICCs were inserted (median age of patients 6.5 years, interquartile range [IQR] 2.4-13 years; median weight 20 kg, IQR 11-38 kg; 54% males; 67.9% chronically ill), and patients were followed up for a total of 9743 days. The median indwelling time was 21 days (IQR 12-37 days). During follow-up, 88 (33.2% of insertions) PICC-related thromboses (incidence rate [IR] 9.03 per 1000 catheter-days) were diagnosed, 66 (24.9%) as isolated SVT, seven (2.6%) as isolated DVT, and 15 (5.7%) as SVT with associated DVT (IR 6.78, 0.71 and 1.54 per 1000 catheter-days, respectively). Only 9.9% of patients with SVT and 18.2% of those with DVT were symptomatic. The main risk factors for PICC-related SVT and DVT were a catheter/vein ratio of > 0.33 and thrombosis of the catheterized superficial vein, respectively. Conclusions PICC-related thrombosis is a common and nearly always asymptomatic complication in children, the SVT rate being approximately three times higher than the DVT rate. Optimal vein and catheter selection, yielding the lowest possible catheter/vein ratio, may decrease the rate of PICC-related thrombosis.

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Bronchospasm appears in up to 4% of patients with obstructive lung disease or respiratory infection undergoing general anesthesia. Clinical examination alone may miss bronchospasm. As a consequence, subsequent (mis)treatment and ventilator settings could lead to pulmonary hyperinflation, hypoxia, hypercapnia, hypotension, patient-ventilator asynchrony, volutrauma, or barotrauma. Electrical impedance tomography (EIT), a new noninvasive technique, can potentially identify bronchospasms by determining regional expiratory time constants (τ) for each one of the pixels of a functional EIT image. We present the first clinical case that highlights the potential of breath-wise EIT-based τ images of the lung to quickly identify bronchospasm at the bedside, which could improve perioperative patient management and safety.