Atrial fibrillation after cardiac surgery: A systematic review and meta-analysis

ObjectiveNew-onset postoperative atrial fibrillation (POAF) after cardiac surgery is common, with rates up to 60%. POAF has been associated with early and late stroke, but its association with other cardiovascular outcomes is less known. The objective was to perform a meta-analysis of the studies reporting the association of POAF with perioperative and long-term outcomes in patients with cardiac surgery.MethodsWe performed a systematic review and a meta-analysis of studies that presented outcomes for cardiac surgery on the basis of the presence or absence of POAF. MEDLINE, EMBASE, and the Cochrane Library were assessed; 57 studies (246,340 patients) were selected. Perioperative mortality was the primary outcome. Inverse variance method and random model were performed. Leave-one-out analysis, subgroup analyses, and metaregression were conducted.ResultsPOAF was associated with perioperative mortality (odds ratio [OR], 1.92; 95% confidence interval [CI], 1.58-2.33), perioperative stroke (OR, 2.17; 95% CI, 1.90-2.49), perioperative myocardial infarction (OR, 1.28; 95% CI, 1.06-1.54), perioperative acute renal failure (OR, 2.74; 95% CI, 2.42-3.11), hospital (standardized mean difference, 0.80; 95% CI, 0.53-1.07) and intensive care unit stay (standardized mean difference, 0.55; 95% CI, 0.24-0.86), long-term mortality (incidence rate ratio [IRR], 1.54; 95% CI, 1.40-1.69), long-term stroke (IRR, 1.33; 95% CI, 1.21-1.46), and longstanding persistent atrial fibrillation (IRR, 4.73; 95% CI, 3.36-6.66).ConclusionsThe results suggest that POAF after cardiac surgery is associated with an increased occurrence of most short- and long-term cardiovascular adverse events. However, the causality of this association remains to be established.     

Orientation and mobility outcome measures

Despite orientation and mobility (O&M) being a significant factor determining quality of life of people with low vision or blindness, there are no gold standard measures or agreement on how to measure O&M performance. In the first part of this systematic review, an inventory of O&M outcome measures used by recent studies to assess the performance of orientation and/or mobility of adults with vision impairment (low vision and blindness) is presented. A wide variety of O&M outcome measures have been implemented in different fields of study, such as epidemiologic research and interventional studies evaluating training, assistive technology, vision rehabilitation and vision restoration. The most frequent aspect of outcome measures is efficiency such as time, distance, speed and percentage of preferred walking speed, followed by obstacle contacts and avoidance, and dis/orientation and veering. Other less commonly used aspects are target identification, safety and social interaction and self-reported outcome measures. Some studies employ sophisticated equipment to capture and analyse O&M performance in a laboratory setting, while others carry out their assessment in real-world indoor or outdoor environments. In the second part of this review, the appropriateness of implementing the identified outcome measures to assess O&M performance in clinical and functional O&M practice is evaluated. Nearly a half of these outcome measures meet all four criteria of face validity (either clinical or functional), responsiveness, reliability and feasibility and have the potential to be implemented in clinical or functional O&M practice. The findings of this review confirm the complicated and dynamic nature of O&M. Multiple measures are required in any evaluation of O&M performance to facilitate holistic assessment of O&M abilities and limitations of each individual.     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.     

Left ventricular and atrial strain imaging with cardiac computed tomography: Validation against echocardiography

BackgroundData on left ventricular (LV) deformation imaging using CT angiography (CTA) are scarce and the feasibility of atrial deformation analysis by CT has not been addressed. We aimed to compare 2D echocardiographic and CT derived LV and left atrial (LA) global longitudinal strain (GLS) obtained by using a novel feature tracking algorithm in patients following transcatheter aortic valve implantation.MethodsTwenty-eight patients were included who underwent retrospectively-gated 256-slice CTA and speckle-tracking echocardiography (STE) on the same day. CT datasets in 10% increments were reconstructed throughout the cardiac cycle. LV GLS and LA global peak reservoir strain (LA GS) was measured.ResultsMedian absolute values for LV GLS were 19.9 [14.8–22.4] vs. 19.9 [16.8–24.7], as measured by CT vs STE, respectively (p = 0.017). We found good inter-modality correlation for LV GLS (ρ = 0.78, p < 0.05) with a mean bias of −1.6. Regarding atrial measurements, the median LA GS was 19.0 [13.5–27.3] for CT vs. 28.0 [17.5–32.6] for STE (p < 0.001) with a mean bias of −5.6 between CT and STE and a correlation coefficient of ρ = 0.87, p < 0.001. CT measurements were highly reproducible: intra-observer intra-class correlation coefficient was 0.96 for LV GLS and 0.95 for LA GS.ConclusionWe detected good correlation between CTA and echocardiography-based LV and LA longitudinal strain parameters. CTA provides accurate strain measurements with high reproducibility. Feature tracking-based deformation analysis could provide a clinically important addition to CT examinations by complementing anatomical information with functional data.