Improved early risk stratification of deep sternal wound infection risk after coronary artery bypass grafting.

BACKGROUND: Deep sternal wound infection (DSWI) following open heart surgery is associated with excessive morbidity and mortality. Contemporary DSWI risk prediction models aim at identifying high-risk patients with varying complexity and performance characteristics. We aimed to optimize the DSWI risk factor set and to identify additional risk factors for early postoperative detection of patients prone to DSWI. METHODS: Single-centre retrospective analysis of patients with isolated multivessel coronary artery disease undergoing myocardial revascularization at Paracelsus Medical University Nuremberg between 2007 and 2022 was performed to identify risk factors for DSWI. Three data sets were created to examine preoperative, intraoperative, and early postoperative parameters, constituting the "Baseline", the "Improved Baseline" and the "Extended" models. The "Extended" data set included risk factors that had not been analysed before. Univariable and stepwise forward multiple logistic regression analyses were performed for each respective set of variables. RESULTS: From 5221 patients, 179 (3.4%) developed DSWI. The "Extended" model performed best, with the area under the curve (AUC) of 0.80, 95%-CI: [0.76, 0.83]. Pleural effusion requiring intervention, postoperative delirium, preoperative hospital stay > 24 h, and the use of fibrin sealant were new independent predictors of DSWI in addition to age, Diabetes Mellitus on insulin, Body Mass Index, peripheral artery disease, mediastinal re-exploration, bilateral internal mammary harvesting, acute kidney injury and blood transfusions. CONCLUSIONS: The "Extended" regression model with the short-term postoperative complications significantly improved DSWI risk discrimination after surgical revascularization. Short preoperative stay, prevention of postoperative delirium, protocols reducing the need for evacuation of effusion and restrictive use of fibrin sealant for sternal closure facilitate DSWI reduction. TRIAL REGISTRATION: The registered retrospective study was registered at the study centre and approved by the Institutional Review Board of Paracelsus Medical University Nuremberg (IRB-2019-005).

Automatic detection of Gibbs artefact in MR images with transfer learning approach.

BACKGROUND: Quality control of magnetic resonance imaging includes image validation, which covers also artefact detection. The daily manual review of magnetic resonance images for possible artefacts can be time-consuming, so automated methods for computer-assisted quality assessment of magnetic resonance imaging need to be developed. OBJECTIVE: The aim of this study was to develop automatic detection of Gibbs artefacts in magnetic resonance imaging using a deep learning method called transfer learning, and to demonstrate the potential of this approach for the development of an automatic quality control tool for the detection of such artefacts in magnetic resonance imaging. METHODS: The magnetic resonance image dataset of the scanned phantom for quality assurance was created using a turbo spin-echo pulse sequence in the transverse plane. Images were created to include Gibbs artefacts of varying intensities. The images were annotated by two independent reviewers. The annotated dataset was used to develop a method for Gibbs artefact detection using the transfer learning approach. The VGG-16, VGG-19, and ResNet-152 convolutional neural networks were used as pre-trained networks for transfer learning and compared using 5-fold cross-validation. RESULTS: All accuracies of the classification models were above 97%, while the AUC values were all above 0.99, confirming the high quality of the constructed models. CONCLUSION: We show that transfer learning can be successfully used to detect Gibbs artefacts on magnetic resonance images. The main advantages of transfer learning are that it can be applied on small training datasets, the procedures to build the models are not so complicated, and they do not require much computational power. This shows the potential of transfer learning for the more general task of detecting artefacts in magnetic resonance images of patients, which consequently can improve and speed up the process of quality assessment in medical imaging practice.

Final adult height in children with central precocious puberty - a retrospective study.

Background/Aims: Central precocious puberty (CPP) is due to premature activation of the hypothalamic-pituitary-gonadal axis. It predominantly affects girls. CPP leads to lower final height (FH), yet the treatment benefit in girls between 6 and 8 years is equivocal. Our main goal was to evaluate the effects of gonadotropin-releasing hormone analog (GnRHa) on FH and identify factors that predict FH. Methods: In a retrospective study, children with CPP (12 boys, 81 girls) that reached FH were included. Their clinical data at diagnosis and up to their final height was compared by descriptive statistics among idiopathic (iCPP) (n=68) and non-idiopathic CPP (nCPP) and between GnRHa treated (n=48) and untreated (n=15) girls with iCPP. The treatment effect of body weight (BW) adjusted GnRHa dosing was evaluated. Univariate linear regression and step-wise multivariable regression including 48 girls with iCPP treated with GnRHa were performed to identify predicting factors for FH. Results: Children with idiopathic CPP (iCPP) reached higher FH (p=0.002) than children with non-idiopathic CPP. After the diagnosis, the treated group gained 7.0 cm more than the untreated group. Yet, attributable to individualized decision-making, the FH in both groups was comparable (161.5 cm in treated, 161.0 cm in untreated girls with iCPP), although the onset of menarche was 2.5 years earlier among untreated girls. BW-adjusted dosing suppressed peak luteinizing hormone (LH) below 4.5 IU/L in 95% of children; however, bone age further advanced during therapy in 38% of patients. Predicting factors revealed by multivariable regression were bone age at diagnosis, BMI SDS at diagnosis, LH basal, age at start and cessation of treatment, predicted adult height and target height. (R2 = 0.72). Conclusion: Children with nCPP had worse FH outcome compared to iCPP despite similar CPP onset and therapeutic characteristics. Treatment by GnRHa using BW-adjusted dosing was effective in delaying menarche onset and reaching target height in girls with iCPP. Multiple factors affecting FH outcome indicated individualized decision-making regarding therapeutic intervention remains challenging. In the treated patients, among the factors that can be influenced, height at treatment cessation most significantly influenced the outcome.

Extended compartmental model for modeling COVID-19 epidemic in Slovenia.

In the absence of a systematic approach to epidemiological modeling in Slovenia, various isolated mathematical epidemiological models emerged shortly after the outbreak of the COVID-19 epidemic. We present an epidemiological model adapted to the COVID-19 situation in Slovenia. The standard SEIR model was extended to distinguish between age groups, symptomatic or asymptomatic disease progression, and vaccinated or unvaccinated populations. Evaluation of the model forecasts for 2021 showed the expected behavior of epidemiological modeling: our model adequately predicts the situation up to 4 weeks in advance; the changes in epidemiologic dynamics due to the emergence of a new viral variant in the population or the introduction of new interventions cannot be predicted by the model, but when the new situation is incorporated into the model, the forecasts are again reliable. Comparison with ensemble forecasts for 2022 within the European Covid-19 Forecast Hub showed better performance of our model, which can be explained by a model architecture better adapted to the situation in Slovenia, in particular a refined structure for vaccination, and better parameter tuning enabled by the more comprehensive data for Slovenia. Our model proved to be flexible, agile, and, despite the limitations of its compartmental structure, heterogeneous enough to provide reasonable and prompt short-term forecasts and possible scenarios for various public health strategies. The model has been fully operational on a daily basis since April 2020, served as one of the models for decision-making during the COVID-19 epidemic in Slovenia, and is part of the European Covid-19 Forecast Hub.

Single-Centre Retrospective Evaluation of Intraoperative Hemoadsorption in Left-Sided Acute Infective Endocarditis.

BACKGROUND: Cardiac surgery in patients with infective endocarditis (IE) is still associated with high mortality and morbidity; an already present inflammation might further be aggravated due to a cardiopulmonary bypass-induced dysregulated immune response. Intraoperative hemoadsorption therapy may attenuate this septic response. Our objective was therefore to assess the efficacy of intraoperative hemoadsorption in active left-sided native- and prosthetic infective endocarditis. METHODS: Consecutive high-risk patients with active left-sided infective endocarditis were enrolled between January 2015 and April 2021. Patients with intraoperative hemoadsorption (Cytosorbents, Princeton, NJ, USA) were compared to patients without hemoadsorption (control). Endpoints were the incidence of postoperative sepsis, sepsis-associated death and in-hospital mortality. Predictors for sepsis-associated mortality and in-hospital mortality were analysed by multivariable logistic regression. RESULTS: A total of 202 patients were included, 135 with active left-sided native and 67 with prosthetic valve infective endocarditis. Ninety-nine patients received intraoperative hemoadsorption and 103 patients did not. Ninety-nine propensity-matched pairs were selected for final analyses. Postoperative sepsis and sepsis-related mortality was reduced in the hemoadsorption group (22.2% vs. 39.4%, p = 0.014 and 8.1% vs. 22.2%, p = 0.01, respectively). In-hospital mortality tended to be lower in the hemoadsorption group (14.1% vs. 26.3%, p = 0.052). Key predictors for sepsis-associated mortality and in-hospital mortality were preoperative inotropic support, lactate-levels 24 h after surgery, C-reactive protein levels on postoperative day 1, chest tube output, cumulative inotropes and white blood cell counts on postoperative day 2, and new onset of dialysis. Multivariate regression analysis revealed intraoperative hemoadsorption to be associated with lower sepsis-associated (OR 0.09, 95% CI 0.013-0.62, p = 0.014) as well as in-hospital mortality (OR 0.069, 95% CI 0.006-0.795, p = 0.032). CONCLUSIONS: Intraoperative hemoadsorption holds promise to reduce sepsis and sepsis-associated mortality after cardiac surgery for active left-sided native and prosthetic valve infective endocarditis.

Enhanced Detection of Cardiac Surgery-Associated Acute Kidney Injury by a Composite Biomarker Panel in Patients with Normal Preoperative Kidney Function.

We have recently shown that minor subclinical creatinine dynamic changes enable the excellent detection of acute kidney injury (AKI) within 6-12 h after cardiac surgery. The aim of the present study was to examine a combination of neutrophil gelatinase-associated lipocalin (NGAL), cystatin C (CysC) and creatinine for enhanced AKI detection early after cardiac surgery. Elective patients with normal renal function undergoing cardiac surgery using cardiopulmonary bypass were enrolled. Concentrations of plasma NGAL, serum CysC and serum creatinine were determined after the induction of general anesthesia, at the termination of the cardiopulmonary bypass and 2 h thereafter. Out of 119 enrolled patients, 51 (43%) developed AKI. A model utilizing an NGAL, CysC and creatinine triple biomarker panel including sequential relative changes provides a better prediction of cardiac surgery-associated acute kidney injury than any biomarker alone already 2 h after the termination of the cardiopulmonary bypass. The area under the receiver-operator curve was 0.77, sensitivity 77% and specificity 68%.

Left Atrial Appendage Amputation for Atrial Fibrillation during Aortic Valve Replacement.

BACKGROUND: Occluding the left atrial appendage (LAA) during cardiac surgery reduces the risk of ischemic stroke; nonetheless, it is currently only softly recommended with "may be considered" by the current guidelines. We aimed to assess thromboembolic risk after LAA amputation in patients with atrial fibrillation (AF) and aortic stenosis undergoing biological aortic valve replacement (AVR) as primary cardiac surgery. METHODS: Two cohorts were generated retrospectively: patients with AF undergoing AVR alone or combined with revascularization either with LAA amputation or without. Data were collected from the hospital-specific data system. Follow-up was completed by telephone interview or in person. Thirty-day and follow-up results were compared in patients with vs. without LAA amputation. RESULTS: One hundred and fifty-seven patients were investigated retrospectively, and seventy-four pairs were matched with regard to baseline characteristics. Patients with LAA amputation exhibited a lower incidence of cumulative and late ischemic stroke (6.4% vs. 25%, p = 0.028 and 3.2% vs. 20%, p = 0.008, respectively; hazard ratio 0.30; 95% confidence interval 0.11; 0.84; p = 0.021) during follow-up of 48 months vs. patients without intervention during follow-up of 45 months, p = 0.494. No significant differences were observed in postoperative stroke, 2 (2.7%) vs. 3 (4.1%), p = 1.000, re-exploration for bleeding 3 (4.1%) vs. 6 (8.1), p = 0.494 or late pericardial effusion 2 (2.7%) vs. 3 (4.1%), p = 1.000, in-hospital 2 (2.7%) vs. 4 (5.4%), p = 0.681 and all-cause mortality 15 (23.8%) vs. 9 (15%), p = 0.315 in patients with vs. without LAA amputation, respectively. CONCLUSIONS: A combination of leading aortic stenosis and AF in patients undergoing isolated or combined biological AVR represents a subpopulation with excessive thromboembolic risk. Concomitant LAA amputation during cardiac surgery reduces the risk of ischemic stroke without posing an additional periprocedural risk for the patient. Therefore, the minimal invasive approach at the expense of omitting LAA amputation should be discouraged to maximize the clinical benefits of AVR in this setting.

Artificial intelligence-based early detection of acute kidney injury after cardiac surgery.

OBJECTIVES: This study aims to improve the early detection of cardiac surgery-associated acute kidney injury using artificial intelligence-based algorithms. METHODS: Data from consecutive patients undergoing cardiac surgery between 2008 and 2018 in our institution served as the source for artificial intelligence-based modelling. Cardiac surgery-associated acute kidney injury was defined according to the Kidney Disease Improving Global Outcomes criteria. Different machine learning algorithms were trained and validated to detect cardiac surgery-associated acute kidney injury within 12 h after surgery. Demographic characteristics, comorbidities, preoperative cardiac status and intra- and postoperative variables including creatinine and haemoglobin values were retrieved for analysis. RESULTS: From 7507 patients analysed, 1699 patients (22.6%) developed cardiac surgery-associated acute kidney injury. The ultimate detection model, 'Detect-A(K)I', recognizes cardiac surgery-associated acute kidney injury within 12 h with an area under the curve of 88.0%, sensitivity of 78.0%, specificity of 78.9% and accuracy of 82.1%. The optimal parameter set includes serial changes of creatinine and haemoglobin, operative emergency, bleeding-associated variables, cardiac ischaemic time and cardiac function-associated variables, age, diuretics and active infection, chronic obstructive lung and peripheral vascular disease. CONCLUSIONS: The 'Detect-A(K)I' model successfully detects cardiac surgery-associated acute kidney injury within 12 h after surgery with the best discriminatory characteristics reported so far.

Nonlinear Heart Rate Variability in Patients with Chronic Obstructive Pulmonary Disease and Changes after 4-week Comprehensive Inpatient Pulmonary Rehabilitation.

Cardiovascular disease is among the leading causes of mortality in chronic obstructive pulmonary disease (COPD). Nonlinear heart rate variability (NHRV) measures are markers and predictors of cardiovascular disease, particularly arrhythmias. Our aim was to investigate NHRV in patients with COPD and changes after pulmonary rehabilitation. 20-minute ECGs were used to compare NHRV (a) in 45 healthy individuals and 31 patients with COPD and (b) in 16 patients who completed rehabilitation versus 13 age- and sex-matched control patients. We studied detrended fluctuation analysis (DFA1, DFA2), fractal dimension (low, high, average FD) and sample entropy. Compared to healthy individuals, patients with COPD had lower DFA1 (p=.038). During rehabilitation high FD decreased (p=.018) and DFA2 increased (p=.043). Cluster analysis displayed an increase of DFA1 in the rehabilitation cluster with DFA1 values below 1 (p=.032). NHRV reflects altered autonomic regulation in patients with COPD. Reduced DFA1 in patients with COPD implies a stronger pro-arrhythmic substrate and altered parasympathetic modulation.

Improved creatinine-based early detection of acute kidney injury after cardiac surgery.

OBJECTIVES: This study aims to improve early detection of cardiac surgery-associated acute kidney injury (CSA-AKI) compared to classical clinical scores. METHODS: Data from 7633 patients who underwent cardiac surgery between 2008 and 2018 in our institution were analysed. CSA-AKI was defined according to the Kidney Disease Improving Global Outcomes (KDIGO) criteria. Cleveland Clinical Score served as the reference with an area under the curve (AUC) 0.65 in our cohort. Based on that, stepwise logistic regression modelling was performed on the training data set including creatinine (Cr), estimated glomerular filtration rate (eGFR) levels and deltas (ΔCr, ΔeGFR) at different time points and clinical parameters as preoperative haemoglobin, intraoperative packed red blood cells (units) and cardiopulmonary bypass time (min) to predict CSA-AKI in the early postoperative course. The AUC was determined on the validation data set for each model respectively. RESULTS: Incidence of CSA-AKI in the early postoperative course was 22.4% (n = 1712). The 30-day mortality was 12.5% in the CSA-AKI group (n = 214) and in the no-CSA-AKI group 0.9% (n = 53) (P < 0.001). Logistic regression models based on Cr and its delta gained an AUC of 0.69; 'Model eGFRCKD-EPI' an AUC of 0.73. Finally, 'Model DynaLab' including dynamic laboratory parameters and clinical parameters as haemoglobin, packed red blood cells and cardiopulmonary bypass time improved AUC to 0.84. CONCLUSIONS: Model DynaLab' improves early detection of CSA-AKI within 12 h after surgery. This simple Cr-based framework poses a fundament for further endeavours towards reduction of CSA-AKI incidence and severity.

Serum Klotho as a marker for early diagnosis of acute kidney injury after cardiac surgery.

BACKGROUND: Early diagnosis of acute kidney injury (AKI) after cardiac surgery is based on serum creatinine which is neither a specific nor a sensitive biomarker. In our study, we investigated the role of serum Klotho in early prediction of AKI after cardiac surgery using cardiopulmonary bypass (CPB). METHODS: The included patients were classified into three groups according to AKI stages using KDIGO criteria. The measurements of creatinine and Klotho levels in serum were performed before surgery, at the end of CPB, 2 hours after the end of CPB, 24 hours and 48 hours postoperatively. RESULTS: Seventy-eight patients were included in the study. A significant increase of creatinine levels (p<0.001) was measured on the first day after the surgery in both AKI groups compared to the non-AKI group. However, a significant difference between AKI-2 and AKI-1 groups (p=0.006) was not measured until the second day after the operation. Using decision trees for classification of patients with a higher or lower risk of AKI we found out that Klotho discriminated between the patients at low risk of developing more severe kidney injury in the first hours after surgery and the patients at high risk better than creatinine. Adding also the early measurements of creatinine in the decision tree model further improved the prediction of AKI. CONCLUSIONS: Serum Klotho may be useful to discriminate between the patients at lower and the patients at higher risk of developing severe kidney injury after cardiac surgery using CPB already in the first hours after surgery.

Key Challenges in Modelling an Epidemic - What have we Learned from the COVID-19 Epidemic so Far.

Mathematical modelling can be useful for predicting how infectious diseases progress, enabling us to show the likely outcome of an epidemic and help inform public health interventions. Different modelling techniques have been used to predict and simulate the spread of COVID-19, but they have not always been useful for epidemiologists and decision-makers. To improve the reliability of the modelling results, it is very important to critically evaluate the data used and to check whether or not due regard has been paid to the different ways in which the disease spreads through the population. As building an epidemiological model that is reliable enough and suits the current epidemiological situation within a country or region, certain criteria must be met in the modelling process. It might be necessary to use a combination of two or more different types of models in order to cover all aspects of epidemic modelling. If we want epidemiological models to be a useful tool in combating the epidemic, we need to engage experts from epidemiology, data science and statistics.

Anthropometry and bone mineral density in treated and untreated hyperphenylalaninemia.

Despite recent improvements in the composition of the diet, lower mineral bone density and overweight tendencies are incoherently described in patients with phenylketonuria (PKU). The impact of dietary factors and plasma phenylalanine levels on growth, BMI, body composition, and bone mineral density was investigated in our cohort of patients with hyperphenylalaninemia (HPA) with or without dietary treatment. The anthropometric, metabolic, BMI and other nutritional indicators and bone mineral density were compared between the group of 96 treated patients with PKU (58 classic PKU (cPKU) and 38 patients with moderate-mild PKU defined as non-classic PKU (non-cPKU)) and the untreated group of 62 patients with benign HPA. Having compared the treated and untreated groups, there were normal outcomes and no statistically significant differences in BMI, body composition, and bone mineral density. Lower body height standard deviation scores were observed in the treated as compared to the untreated group (P < 0.001), but the difference was not significant when analyzing patients older than 18 years; however, cPKU adults were shorter compared to non-cPKU treated adults (P = 0.012). Interestingly, the whole-body fat was statistically higher in non-cPKU as compared to cPKU patients. In conclusion, the dietary treatment ensured adequate nutrition without significant consequences in BMI, body composition, and bone mineral density. A low protein diet may have delayed the growth in childhood, but the treated patients gained a normal final height. Mild untreated hyperphenylalaninemia characteristic for benign HPA had no negative physiological effect on bone mineral density.

Cardiac autonomic regulation and PR interval determination for enhanced atrial fibrillation risk prediction after cardiac surgery.

BACKGROUND: Changes in cardiac autonomic regulation and P-wave characteristics are associated with the occurrence of atrial fibrillation. The purpose of this study was to evaluate whether combined preoperative non-invasive determination of cardiac autonomic regulation and PR interval allows for the identification of patients at risk of new-onset atrial fibrillation after cardiac surgery. METHODS: RR, PR and QT intervals, and linear and non-linear heart rate variability parameters from 20 min high-resolution electrocardiographic recordings were determined one day before surgery in 150 patients on chronic beta blockers undergoing elective coronary artery bypass grafting, aortic valve replacement, or both, electively. RESULTS: Thirty-one patients (21%) developed postoperative atrial fibrillation. In the atrial fibrillation group, more arterial hypertension, a greater age, a higher EuroSCORE II, a higher heart rate variability index (pNN50: 9 ±â€¯20 vs. 4 ±â€¯10, p = 0.050), a short PR interval (156 ±â€¯23 vs. 173 ±â€¯31 ms; p = 0.011), and a reduced short-term scaling exponent of the detrended fluctuation analysis (DFA1, 0.96 ±â€¯0.36 vs. 1.11 ±â€¯0.30 ms; p = 0.032) were found compared to the sinus rhythm group. Logistic regression modeling confirmed PR interval, DFA1 and age as the strongest preoperative predictors of postoperative atrial fibrillation (area under the receiver operating characteristic curve = 0.804). CONCLUSIONS: Patients developing atrial fibrillation after cardiac surgery presented with severe cardiac autonomic derangement and a short PR interval preoperatively. The observed state characterizes both altered heart rate regulation and arrhythmic substrate and is strongly related to an increased risk of postoperative atrial fibrillation.

Biofouling of stainless steel surfaces by four common pathogens: the effects of glucose concentration, temperature and surface roughness.

There is a wide range of factors affecting bacterial adhesion and biofilm formation. However, in both food processing and medical settings, it is very hard to obtain suitably controlled conditions so that the factors that reduce surface colonisation and biofouling can be studied. The aim of this study was to evaluate the effect of glucose concentration, temperature and stainless steel (SS) surface roughness on biofouling by four common pathogens (Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa and L. monocytogenes). Among the tested variables, the untreated SS surface (3C) was shown to be fouled more than 3D polished, brushed or electropolished SS surfaces. Although an array of parameters influenced biofouling, the most promising control measure was the influence of low temperature (4 °C) that reduced biofouling even in the case of the psychrophilic Listeria monocytogenes. The study findings could significantly contribute to the prevention of SS surface contamination and consequential biofouling by food and healthcare associated pathogens.

Creatinine, Neutrophil Gelatinase-Associated Lipocalin, and Cystatin C in Determining Acute Kidney Injury After Heart Operations Using Cardiopulmonary Bypass.

Acute kidney injury (AKI) represents frequent complication after cardiac surgery using cardiopulmonary bypass (CPB). In the hope to enhance earlier more reliable characterization of AKI, we tested the utility of neutrophil gelatinase-associated lipocalin (NGAL) and cystatin C (CysC) in addition to standard creatinine for early determination of AKI after cardiac surgery using CPB. Forty-one patients met the inclusion criteria. Arterial blood samples collected after induction of general anesthesia were used as baseline, further sampling occurred at CPB termination, 2 h after CPB, on the first and second day after surgery. According to AKIN classification 18 patients (44%) developed AKI (AKI1-2 groups) and 23 (56%) did not (non-AKI group). Groups were similar regarding demographics and operative characteristics. CysC levels differed already preoperatively (non-AKI vs. AKI2; P = 0.045; AKI1 vs. AKI2; P = 0.011), while postoperatively AKI2 group differed on the first day and AKI1 on the second regarding non-AKI group (P = 0.004; P = 0.021, respectively). NGAL and creatinine showed significant difference already 2 h after CPB between groups AKI2 and non-AKI and later on the first postoperative day between groups AKI1 and AKI2 (P = 0.028; P = 0.014, respectively). This study shows similar performance of early plasma creatinine and NGAL in patients with preserved preoperative renal function. It demonstrates that creatinine, as well as NGAL, differentiate subsets of patients developing AKI of clinically more advanced grade early after 2 h, also when used single and uncombined.

Beyond aphasia: Altered EEG connectivity in Broca's patients during working memory task.

Broca's region and adjacent cortex presumably take part in working memory (WM) processes. Electrophysiologically, these processes are reflected in synchronized oscillations. We present the first study exploring the effects of a stroke causing Broca's aphasia on these processes and specifically on synchronized functional WM networks. We used high-density EEG and coherence analysis to map WM networks in ten Broca's patients and ten healthy controls during verbal WM task. Our results demonstrate that a stroke resulting in Broca's aphasia also alters two distinct WM networks. These theta and gamma functional networks likely reflect the executive and the phonological processes, respectively. The striking imbalance between task-related theta synchronization and desynchronization in Broca's patients might represent a disrupted balance between task-positive and WM-irrelevant functional networks. There is complete disintegration of left fronto-centroparietal gamma network in Broca's patients, which could reflect the damaged phonological loop.

Severe Cardiac Autonomic Derangement and Altered Ventricular Repolarization Pave the Way to Postoperative Atrial Fibrillation.

OBJECTIVE: Postoperative atrial fibrillation (POAF) is a frequent complication after heart surgery. It has been shown that cardiac autonomic derangement plays a significant role in the genesis of atrial fibrillation (AF) and that AF might also be promoted by altered repolarization. Thus, the aim of our study was to determine the levels of cardiac autonomic modulation and repolarization properties in patients developing POAF. METHODS: Seventy-nine patients scheduled for aortic and/or coronary artery bypass grafting surgery with cardiopulmonary bypass were enrolled prospectively. High-resolution 20-minute electrocardiogram recordings were obtained day before surgery to determine P, PR, QT, and QTc intervals, as well as linear (time and frequency domain) and nonlinear heart rate variability parameters (fractal dimension and detrended fluctuation analysis). QTc interval was calculated using Framingham correction. RESULTS: Twenty-nine patients developed POAF (AF group), and 50 did not (non-AF group). Groups were similar regarding demographics, surgery type, and perioperative characteristics, except for older age in the AF group. QT and QTc intervals (Framingham) were longer in the AF group [442 (44) vs 422 (28) milliseconds, P = 0.018; and 448 (44) vs 431 (24) milliseconds, P = 0.031 and P = 0.019, respectively]. Time domain heart rate variability parameter PNN50 (percentage of pairs of adjacent NN intervals differing >50 milliseconds) was higher [14% (21%) vs 8% (16%), P = 0.015], and nonlinear parameter detrended fluctuation analysis α2 was lower in the AF group [0.81 (0.21) vs 0.91 (0.20), P = 0.031]. CONCLUSIONS: Profound cardiac autonomic derangement, suggestive of parasympathetic excessive modulation, exists preoperatively in patients inclined to POAF after cardiac surgery, whereby parameters PNN50 and α2 differentiated the AF from the non-AF group. Prolonged QTc intervals are associated with an increased risk of POAF.

The electrophysiological correlates of the working memory subcomponents: evidence from high-density EEG and coherence analysis.

Synchronization between prefrontal (executive) and posterior (association) cortices seems a plausible mechanism for temporary maintenance of information. However, while EEG studies reported involvement of (pre)frontal midline structures in synchronization, functional neuroimaging elucidated the importance of lateral prefrontal cortex (PFC) in working memory (WM). Verbal and spatial WM rely on lateralized subsystems (phonological loop and visuospatial sketchpad, respectively), yet only trends for hemispheric dissociation of networks supporting rehearsal of verbal and spatial information were identified by EEG. As oscillatory activity is WM load dependent, we applied an individually tailored submaximal load for verbal (V) and spatial (S) task to enhance synchronization in the relevant functional networks. To map these networks, we used high-density EEG and coherence analysis. Our results imply that the synchronized activity is limited to highly specialized areas that correspond well with the areas identified by functional neuroimaging. In both V and S task, two independent networks of theta synchronization involving dorsolateral PFC of each hemisphere were revealed. In V task, left prefrontal and left parietal areas were functionally coupled in gamma frequencies. Theta synchronization thus provides the necessary interface for storage and manipulation of information, while left-lateralized gamma synchronization could represent the EEG correlate of the phonological loop.

Characterization of spatiotemporal changes for the classification of dynamic contrast-enhanced magnetic-resonance breast lesions.

OBJECTIVE: The early detection of breast cancer is one of the most important predictors in determining the prognosis for women with malignant tumours. Dynamic contrast-enhanced magnetic-resonance imaging (DCE-MRI) is an important imaging modality for detecting and interpreting the different breast lesions from a time sequence of images and has proved to be a very sensitive modality for breast-cancer diagnosis. However, DCE-MRI exhibits only a moderate specificity, thus leading to a high rate of false positives, resulting in unnecessary biopsies that are stressful and physically painful for the patient and lead to an increase in the cost of treatment. There is a strong medical need for a DCE-MRI computer-aided diagnosis tool that would offer a reliable support to the physician's decision providing a high level of sensitivity and specificity. METHODS: In our study we investigated the possibility of increasing differentiation between the malignant and the benign lesions with respect to the spatial variation of the temporal enhancements of three parametric maps, i.e., the initial enhancement (IE) map, the post-initial enhancement (PIE) map and the signal enhancement ratio (SER) map, by introducing additional methods along with the grey-level co-occurrence matrix, i.e., a second-order statistical method already applied for quantifying the spatiotemporal variations. We introduced the grey-level run-length matrix and the grey-level difference matrix, representing two additional, second-order statistical methods, and the circular Gabor as a frequency-domain-based method. Each of the additional methods is for the first time applied to the DCE-MRI data to differentiate between the malignant and the benign breast lesions. We applied the least-square minimum-distance classifier (LSMD), logistic regression and least-squares support vector machine (LS-SVM) classifiers on a total of 115 (78 malignant and 37 benign) breast DCE-MRI cases. The performances were evaluated using ten experiments of a ten-fold cross-validation. RESULTS: Our experimental analysis revealed the PIE map, together with the feature subset in which the discriminating ability of the co-occurrence features was increased by adding the newly introduced features, to be the most significant for differentiation between the malignant and the benign lesions. That diagnostic test - the aforementioned combination of parametric map and the feature subset achieved the sensitivity of 0.9193 which is statistically significantly higher compared to other diagnostic tests after ten-experiments of a ten-fold cross-validation and gave a statistically significantly higher specificity of 0.7819 for the fixed 95% sensitivity after the receiver operating characteristic (ROC) curve analysis. Combining the information from all the three parametric maps significantly increased the area under the ROC curve (AUC) of the aforementioned diagnostic test for the LSMD and logistic regression; however, not for the LS-SVM. The LSMD classifier yielded the highest area under the ROC curve when using the combined information, increasing the AUC from 0.9651 to 0.9755. CONCLUSION: Introducing new features to those of the grey-level co-occurrence matrix significantly increased the differentiation between the malignant and the benign breast lesions, thus resulting in a high sensitivity and improved specificity.