Circle of Willis integrity in acute middle cerebral artery occlusion: does the posterior communicating artery matter?

BACKGROUND: Collateral circulation is an important determinant of outcome in people with acute ischemic stroke due to large vessel occlusion (LVO). OBJECTIVE: To explore the impact of the circle of Willis (CW) anatomical characteristics ipsilateral to the occlusion site, particularly the posterior communicating artery (PComA) and the A1-portion of the anterior cerebral artery (A1-ACA), on stroke outcomes in a cohort of patients with LVO and middle cerebral artery (MCA) occlusion, undergoing endovascular thrombectomy (EVT). METHODS: This is a retrospective cohort study performed in a comprehensive tertiary stroke center. The study population consisted of consecutive patients with LVO with proximal MCA occlusion (M1) between June 2016 and April 2021, undergoing EVT. Demographic, clinical, and imaging information was extracted from patient files. Patency and diameters of ipsilateral A1-ACA and PComA were manually measured on admission CT angiography images in the core laboratory. RESULTS: One hundred and five patients with LVO comprised the study cohort, mean age 72.3 years, 43.8% were male, mean National Institutes of Health Stroke Scale score at admission 15.2. The cohort was grouped according to CW vessel characteristics. On univariate analysis, a well-developed PComA was associated with lower rates of hemorrhagic transformation (1.8% vs 14.3%, P=0.01) and a trend towards lower mortality rates (8.9% vs 20.4%, P=0.08).On multivariable regression analysis a well-developed PComA emerged as an independent predictor for survival (aOR=0.09, 95% CI 0.01 to 0.4 for survival at discharge, P=0.009, aOR=0.22, 95% CI 0.05 to 0.8 for survival at 90 days, P=0.02). CONCLUSIONS: In a cohort of patients with LVO due to M1 occlusion undergoing EVT, a well-developed PComA was associated with significantly lower hemorrhagic transformation rates, a trend towards better functional outcomes, and independently predicted survival. Larger studies are needed to understand the differential effect of CW collateral conduits on stroke outcome and evaluate the practicality of incorporating such factors in the clinical decision-making process prior to EVT.

Evaluation of hemodynamically significant pericardial effusion by analysis of cardiac chambers volume by computed tomography.

OBJECTIVE: Pericardial effusion may present clinically as pleuritic chest pain, dyspnea, or hemodynamic compromise and is a frequent finding in computerized tomographic pulmonary angiography (CTPA) exams. We hypothesized that CTPA-based analysis of the cardiac chamber volumes can be used to predict the hemodynamic significance of pericardial effusion (HsPE) as compared with echocardiography. METHODS: Retrospective analysis of consecutive patients who underwent CTPA and echocardiography between January 2009 and November 2017 that ruled-out acute pulmonary embolism was included. Differences in cardiac chamber volumes were investigated in correlation to echocardiographic evidence of HsPE. RESULTS: The final cohort included 208 patients, of whom 22 (11%) were diagnosed with HsPE. The HsPE patients had much smaller right cardiac chamber volumes (Median 78.8 ml (IQR 72.4-89.1)) than patients without HsPE (Median 115.1 ml (IQR 87.4-150). A decision tree for the prediction of HsPE showed multiple cutoff values. Right atrium (RA) volume had the best accuracy (area under the curve 0.851, 95% confidence interval 0.776-0.925, p < .001) for predicting the presence of HsPE. An RA volume ≤86 ml yielded a sensitivity of 95.5%, a specificity of 64%, and a NPV of 99.2% for the presence of HsPE. CONCLUSION: CTPA-based volumetric information with focus on the RA volume may help predict the presence of HsPE. ADVANCES IN KNOWLEDGE: Pericardial effusion is a frequent finding in CTPA exams. Our study shows that CTPA-based volumetric information can predict the presence of HsPE with RA volume as the best indicator.

Presence of Sarcopenia before Kidney Transplantation Is Associated with Poor Outcomes.

INTRODUCTION: Kidney transplantation is the treatment of choice for patients with renal failure. It is crucial to select which patients may benefit from renal transplantation and which are at high risk for post-transplant complications. Sarcopenia is associated with poor outcome in various conditions, including in chronic kidney disease patients. The gold standard for measuring sarcopenia is computed tomography (CT) imaging to estimate muscle mass and quality since it is objective, reproducible, and reflects the overall health condition. The data regarding those measurements among kidney transplant recipients are limited, therefore we aimed to describe it in patients before kidney transplantation, assess the parameters associated with sarcopenia, and evaluate the clinical significance of those markers on outcomes following transplantation. METHODS: We retrospectively analyzed 183 kidney transplant recipients who had a CT scan 90 days prior to transplant. Sarcopenia was assessed by measuring the cross-sectional area (CSA) and mean muscle density of the psoas muscle at the third and fourth lumbar vertebrae levels and paravertebral muscles at the 12th thoracic vertebra level. RESULTS: There was a strong linear correlation between muscle size measured as CSA of the psoas muscle at the L3 and L4 vertebral body level and the CSA of the paravertebral muscles at the D12 vertebra level, and a moderate correlation to muscle density at those levels. Age was independently associated with risk of sarcopenia, defined as psoas CSA in the lowest tertile, with every year of age increasing the risk by 5%. CSA at the L3 level had a significant independent association with post kidney transplantation mortality, with an adjusted hazard ratio of 0.86 per cm2. There was a significantly longer hospitalization period postoperation in kidney recipients in the lower tertile of psoas CSA and density. CONCLUSIONS: Sarcopenia as measured by psoas CSA is associated with poor short- and long-term outcomes following kidney transplantation and should be included as part of the assessment of kidney transplantation candidates.

[ANTIBIOTIC PRESCRIPTION ERRORS IN PATIENTS HOSPITALIZED IN INTERNAL MEDICINE DEPARTMENTS - A PROSPECTIVE COHORT STUDY].

AIMS: To examine the prevalence of antibiotic prescription errors in three medical departments. BACKGROUND: Prescription errors are common and associated with significant adverse drug events (ADEs), morbidity and mortality, and health care expenditures. METHODS: A prospective observational cohort study was conducted in three medical departments, including consecutive patients with suspected or proven infections, and/or antibiotic prescriptions. The primary outcome was the proportion of prescription errors, defined as: contraindications, inadequate dose regimen, and unnecessary antibiotic treatment. Secondary outcomes included incidence of ADEs, proportion of potential drug-drug interactions (DDIs) with clinical relevance, and prevalence of inadequate monitoring for ADEs and therapeutic drug monitoring (TDM). RESULTS: We identified 327 patient-episodes in 295 patients. The most common infectious diagnoses were urinary tract infection and pneumonia. Among 633 prescriptions, 113 (18%) contained errors in 87 (27%) patient-episodes. The most common types of error were inappropriate dose adjustment for renal function and unnecessary treatment. There were 6 prescriptions with contraindications (0.9%). Laboratory monitoring was required in 259 patient-episodes but inadequate in 40 (15%). TDM was required in 40 patient-episodes, but was not performed in 25 (63%). There were 69 ADEs in 61 patient-episodes (19%). Compared to patients without ADEs, patients who developed ADEs had more prescription errors (p=0.055), more potential DDIs (p=0.012), and received more often antibiotics that needed monitoring and TDM. CONCLUSIONS: Antibiotic prescription errors in medical departments are common and may be associated with significant ADEs. Our findings may help in prioritizing the customization of prescription computer decision support systems to improve antibiotic prescription.