Medical University of Graz

About: Medical University of Graz is a education organization based out in Graz, Steiermark, Austria. It is known for research contribution in the topics: Population & Medicine. The organization has 5684 authors who have published 12349 publications receiving 417282 citations.

Complications of catheter ablation for atrial fibrillation: incidence and predictors.

Abstract: Introduction: Pulmonary vein (PV) isolation by catheter ablation is an increasingly used strategy to treat atrial fibrillation (AF). Complication rates from AF ablation reported in different case series vary widely. We conducted a retrospective analysis of 641 consecutive ablation procedures to assess complication rates, temporal trends, and clinical predictors of adverse outcomes. Methods: All patients (n = 517) undergoing catheter ablation for AF at Johns Hopkins Hospital between February, 2001 and June, 2007 were prospectively enrolled in a database. Data from 641 consecutive procedures were analyzed and complications considered if they occurred within 30 days of ablation. Major complications were defined as those that required intervention, resulted in long-term disability, or prolonged hospitalization. Results: Thirty-two major complications occurred in 641 procedures (5%). Among the patients with major complications, seven had cerebrovascular accident (CVA), eight had tamponade, one had PV occlusion with hemoptysis, and 11 had vascular injury requiring surgical repair and/or transfusion. No periprocedural deaths occurred, and no instances of esophageal injury were seen. Complication rates were higher during the first 100 cases (9.0%) than during the subsequent 541 (4.3%). Major adverse clinical events were associated with age > 70 years (P = 0.007; odds ratio 3.7, 95% confidence interval 1.4–9.6) and female gender (P = 0.014; odds ratio 3.0, 95% confidence interval 1.3–7.2). No other clinical or procedural predictors of complication were identified. Conclusions: Complication rates from AF ablation remain significant, despite improved techniques and increased awareness of procedural risks. Both advanced age and female gender predict major adverse events, suggesting careful consideration of the risk/benefit profile in these patients prior to ablation.

Progression of regional grey matter atrophy in multiple sclerosis.

Abstract: See Stankoff and Louapre (doi:10.1093/brain/awy114) for a scientific commentary on this article.Grey matter atrophy is present from the earliest stages of multiple sclerosis, but its temporal ordering is poorly understood. We aimed to determine the sequence in which grey matter regions become atrophic in multiple sclerosis and its association with disability accumulation. In this longitudinal study, we included 1417 subjects: 253 with clinically isolated syndrome, 708 with relapsing-remitting multiple sclerosis, 128 with secondary-progressive multiple sclerosis, 125 with primary-progressive multiple sclerosis, and 203 healthy control subjects from seven European centres. Subjects underwent repeated MRI (total number of scans 3604); the mean follow-up for patients was 2.41 years (standard deviation = 1.97). Disability was scored using the Expanded Disability Status Scale. We calculated the volume of brain grey matter regions and brainstem using an unbiased within-subject template and used an established data-driven event-based model to determine the sequence of occurrence of atrophy and its uncertainty. We assigned each subject to a specific event-based model stage, based on the number of their atrophic regions. Linear mixed-effects models were used to explore associations between the rate of increase in event-based model stages, and T2 lesion load, disease-modifying treatments, comorbidity, disease duration and disability accumulation. The first regions to become atrophic in patients with clinically isolated syndrome and relapse-onset multiple sclerosis were the posterior cingulate cortex and precuneus, followed by the middle cingulate cortex, brainstem and thalamus. A similar sequence of atrophy was detected in primary-progressive multiple sclerosis with the involvement of the thalamus, cuneus, precuneus, and pallidum, followed by the brainstem and posterior cingulate cortex. The cerebellum, caudate and putamen showed early atrophy in relapse-onset multiple sclerosis and late atrophy in primary-progressive multiple sclerosis. Patients with secondary-progressive multiple sclerosis showed the highest event-based model stage (the highest number of atrophic regions, P < 0.001) at the study entry. All multiple sclerosis phenotypes, but clinically isolated syndrome, showed a faster rate of increase in the event-based model stage than healthy controls. T2 lesion load and disease duration in all patients were associated with increased event-based model stage, but no effects of disease-modifying treatments and comorbidity on event-based model stage were observed. The annualized rate of event-based model stage was associated with the disability accumulation in relapsing-remitting multiple sclerosis, independent of disease duration (P < 0.0001). The data-driven staging of atrophy progression in a large multiple sclerosis sample demonstrates that grey matter atrophy spreads to involve more regions over time. The sequence in which regions become atrophic is reasonably consistent across multiple sclerosis phenotypes. The spread of atrophy was associated with disease duration and with disability accumulation over time in relapsing-remitting multiple sclerosis.

Meta-analysis of Genome-wide Association Studies Identifies 1q22 as a Susceptibility Locus for Intracerebral Hemorrhage

Abstract: Intracerebral hemorrhage (ICH) is the stroke subtype with the worst prognosis and has no established acute treatment. ICH is classified as lobar or nonlobar based on the location of ruptured blood vessels within the brain. These different locations also signal different underlying vascular pathologies. Heritability estimates indicate a substantial genetic contribution to risk of ICH in both locations. We report a genome-wide association study of this condition that meta-analyzed data from six studies that enrolled individuals of European ancestry. Case subjects were ascertained by neurologists blinded to genotype data and classified as lobar or nonlobar based on brain computed tomography. ICH-free control subjects were sampled from ambulatory clinics or random digit dialing. Replication of signals identified in the discovery cohort with p < 1 × 10(-6) was pursued in an independent multiethnic sample utilizing both direct and genome-wide genotyping. The discovery phase included a case cohort of 1,545 individuals (664 lobar and 881 nonlobar cases) and a control cohort of 1,481 individuals and identified two susceptibility loci: for lobar ICH, chromosomal region 12q21.1 (rs11179580, odds ratio [OR] = 1.56, p = 7.0 × 10(-8)); and for nonlobar ICH, chromosomal region 1q22 (rs2984613, OR = 1.44, p = 1.6 × 10(-8)). The replication included a case cohort of 1,681 individuals (484 lobar and 1,194 nonlobar cases) and a control cohort of 2,261 individuals and corroborated the association for 1q22 (p = 6.5 × 10(-4); meta-analysis p = 2.2 × 10(-10)) but not for 12q21.1 (p = 0.55; meta-analysis p = 2.6 × 10(-5)). These results demonstrate biological heterogeneity across ICH subtypes and highlight the importance of ascertaining ICH cases accordingly.

Association Between Surgical Skin Markings in Dermoscopic Images and Diagnostic Performance of a Deep Learning Convolutional Neural Network for Melanoma Recognition.

Abstract: Importance Deep learning convolutional neural networks (CNNs) have shown a performance at the level of dermatologists in the diagnosis of melanoma. Accordingly, further exploring the potential limitations of CNN technology before broadly applying it is of special interest. Objective To investigate the association between gentian violet surgical skin markings in dermoscopic images and the diagnostic performance of a CNN approved for use as a medical device in the European market. Design and Setting A cross-sectional analysis was conducted from August 1, 2018, to November 30, 2018, using a CNN architecture trained with more than 120 000 dermoscopic images of skin neoplasms and corresponding diagnoses. The association of gentian violet skin markings in dermoscopic images with the performance of the CNN was investigated in 3 image sets of 130 melanocytic lesions each (107 benign nevi, 23 melanomas). Exposures The same lesions were sequentially imaged with and without the application of a gentian violet surgical skin marker and then evaluated by the CNN for their probability of being a melanoma. In addition, the markings were removed by manually cropping the dermoscopic images to focus on the melanocytic lesion. Main Outcomes and Measures Sensitivity, specificity, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve for the CNN’s diagnostic classification in unmarked, marked, and cropped images. Results In all, 130 melanocytic lesions (107 benign nevi and 23 melanomas) were imaged. In unmarked lesions, the CNN achieved a sensitivity of 95.7% (95% CI, 79%-99.2%) and a specificity of 84.1% (95% CI, 76.0%-89.8%). The ROC AUC was 0.969. In marked lesions, an increase in melanoma probability scores was observed that resulted in a sensitivity of 100% (95% CI, 85.7%-100%) and a significantly reduced specificity of 45.8% (95% CI, 36.7%-55.2%,P Conclusions and Relevance This study’s findings suggest that skin markings significantly interfered with the CNN’s correct diagnosis of nevi by increasing the melanoma probability scores and consequently the false-positive rate. A predominance of skin markings in melanoma training images may have induced the CNN’s association of markings with a melanoma diagnosis. Accordingly, these findings suggest that skin markings should be avoided in dermoscopic images intended for analysis by a CNN. Trial Registration German Clinical Trial Register (DRKS) Identifier:DRKS00013570