Citations

AbstractObjectiveHigh‐frequency oscillations are considered among the most promising interictal biomarkers of the epileptogenic zone in patients suffering from pharmacoresistant focal epilepsy. However, there is no clear definition of pathological high‐frequency oscillations, and the existing detectors vary in methodology, performance, and computational costs. This study proposes relative entropy as an easy‐to‐use novel interictal biomarker of the epileptic tissue.MethodsWe evaluated relative entropy and high‐frequency oscillation biomarkers on intracranial electroencephalographic data from 39 patients with seizure‐free postoperative outcome (Engel Ia) from three institutions. We tested their capability to localize the epileptogenic zone, defined as resected contacts located in the seizure onset zone. The performance was compared using areas under the receiver operating curves (AUROCs) and precision‐recall curves. Then we tested whether a universal threshold can be used to delineate the epileptogenic zone across patients from different institutions.ResultsRelative entropy in the ripple band (80–250 Hz) achieved an average AUROC of .85. The normalized high‐frequency oscillation rate in the ripple band showed an identical AUROC of .85. In contrast to high‐frequency oscillations, relative entropy did not require any patient‐level normalization and was easy and fast to calculate due to its clear and straightforward definition. One threshold could be set across different patients and institutions, because relative entropy is independent of signal amplitude and sampling frequency.SignificanceAlthough both relative entropy and high‐frequency oscillations have a similar performance, relative entropy has significant advantages such as straightforward definition, computational speed, and universal interpatient threshold, making it an easy‐to‐use promising biomarker of the epileptogenic zone.

PURPOSE This randomized, open-label trial compared the efficacy and safety of adjuvant nab-paclitaxel + gemcitabine with those of gemcitabine for resected pancreatic ductal adenocarcinoma (ClinicalTrials.gov identifier: NCT01964430 ). METHODS We assigned 866 treatment-naive patients with pancreatic ductal adenocarcinoma to nab-paclitaxel (125 mg/m 2 ) + gemcitabine (1,000 mg/m 2 ) or gemcitabine alone to one 30-40 infusion on days 1, 8, and 15 of six 28-day cycles. The primary end point was independently assessed disease-free survival (DFS). Additional end points included investigator-assessed DFS, overall survival (OS), and safety. RESULTS Two hundred eighty-seven of 432 patients and 310 of 434 patients completed nab-paclitaxel + gemcitabine and gemcitabine treatment, respectively. At primary data cutoff (December 31, 2018; median follow-up, 38.5 [interquartile range [IQR], 33.8-43 months), the median independently assessed DFS was 19.4 ( nab-paclitaxel + gemcitabine) versus 18.8 months (gemcitabine; hazard ratio [HR], 0.88; 95% CI, 0.729 to 1.063; P = .18). The median investigator-assessed DFS was 16.6 (IQR, 8.4-47.0) and 13.7 (IQR, 8.3-44.1) months, respectively (HR, 0.82; 95% CI, 0.694 to 0.965; P = .02). The median OS (427 events; 68% mature) was 40.5 (IQR, 20.7 to not reached) and 36.2 (IQR, 17.7-53.3) months, respectively (HR, 0.82; 95% CI, 0.680 to 0.996; P = .045). At a 16-month follow-up (cutoff, April 3, 2020; median follow-up, 51.4 months [IQR, 47.0-57.0]), the median OS (511 events; 81% mature) was 41.8 ( nab-paclitaxel + gemcitabine) versus 37.7 months (gemcitabine; HR, 0.82; 95% CI, 0.687 to 0.973; P = .0232). At the 5-year follow-up (cutoff, April 9, 2021; median follow-up, 63.2 months [IQR, 60.1-68.7]), the median OS (555 events; 88% mature) was 41.8 versus 37.7 months, respectively (HR, 0.80; 95% CI, 0.678 to 0.947; P = .0091). Eighty-six percent ( nab-paclitaxel + gemcitabine) and 68% (gemcitabine) of patients experienced grade ≥ 3 treatment-emergent adverse events. Two patients per study arm died of treatment-emergent adverse events. CONCLUSION The primary end point (independently assessed DFS) was not met despite favorable OS seen with nab-paclitaxel + gemcitabine.

Abstract Background Atrial fibrillation is associated with considerable morbidity and mortality. Real-world reports on the effect of early rhythm control on patient outcomes in patient with recent onset atrial fibrillation are limited. Purpose To assess the effect of early rhythm versus rate control on clinical outcomes in patients with newly diagnosed non-valvular atrial fibrillation. Method The Global Anticoagulant Registry in the FIELD-AF (GARFIELD-AF) is a non-interventional registry of adult (≥18 years) patients with newly diagnosed atrial fibrillation (≤ six weeks' duration) and at least one investigator determined risk factor for stroke. Patients were enrolled in 1317 participating sites in 35 countries between March 2010 and August 2016. Patients with permanent atrial fibrillation were excluded. Stratification to rhythm or rate control was based on treatment strategy initiated at baseline (≤48 days post enrolment). Rhythm control was defined as investigator reported initiation of rhythm control (antiarrhythmic drug(s), cardioversion, or ablation – alone or in combination with rate modifiers). Rate control was defined as investigator reported initiation of rate control and absence of rhythm control therapy. Overlap propensity weighting and Cox proportional-hazards models were used to evaluate effect on outcomes. Results Of 45,382 included patients, 23,858 (52.6%) received rhythm control and 21,524 (47.4%) rate control. Rates of rhythm control were similar throughout the study time period (52.7% in 2010/2011, 54.2% in 2015/2016). Patients in the rhythm control group were younger (median age (Q1; Q3) 68.0 (60.0; 76.0) versus 73.0 (65.0; 79.0)), had lower rates of prior stroke/transitory ischemic attack/systemic embolism (9.4% vs 13.0%), and a lower median GARFIELD death score (4.0 (2.3; 7.5) versus 5.1 (2.8; 9.2)). Median CHA2DS2-VASc Scores were 3.0 (2.0; 4.0) in both groups. Rate of anticoagulation treatment was similar in the rhythm and rate control group (66.0% versus 65.5%). After propensity score overlap weighting, patients of the two groups were well balanced on all observed characteristics. Event rates per 100 person-years (95% confidence interval [CI]) over two years follow-up in the rhythm and rate control group were 2.94 (2.78–3.10) versus 4.43 (4.22–4.64) for mortality, 0.84 (0.75–0.92) versus 1.16 (1.05–1.27) for non-haemorrhagic stroke/systemic embolism and 0.84 (0.76–0.93) versus 1.16 (1.06–1.27) for major bleeding. Adjusted hazard ratios (95% CI) for the same time period were 0.85 (0.79–0.92), 0.84 (0.72–0.97) and 0.9 (0.78–1.04). Conclusion In this large, internation registry, a rhythm control strategy was initiated at baseline in about half of the patients with newly diagnosed non-valvular atrial fibrillation. After adjustment for confounding factors, a significantly lower risk of all-cause mortality and non-haemorrhagic stroke/systemic embolism were observed for patients that received an early rhythm control strategy. Funding Acknowledgement Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): This work was supported by the Thrombosis Research Institute (London, UK).

Abstract Early implantable epilepsy therapy devices provided open-loop electrical stimulation without brain sensing, computing, or an interface for synchronized behavioural inputs from patients. Recent epilepsy stimulation devices provide brain sensing but have not yet developed analytics for accurately tracking and quantifying behaviour and seizures. Here we describe a distributed brain co-processor providing an intuitive bi-directional interface between patient, implanted neural stimulation and sensing device, and local and distributed computing resources. Automated analysis of continuous streaming electrophysiology is synchronized with patient reports using a handheld device and integrated with distributed cloud computing resources for quantifying seizures, interictal epileptiform spikes and patient symptoms during therapeutic electrical brain stimulation. The classification algorithms for interictal epileptiform spikes and seizures were developed and parameterized using long-term ambulatory data from nine humans and eight canines with epilepsy, and then implemented prospectively in out-of-sample testing in two pet canines and four humans with drug-resistant epilepsy living in their natural environments. Accurate seizure diaries are needed as the primary clinical outcome measure of epilepsy therapy and to guide brain-stimulation optimization. The brain co-processor system described here enables tracking interictal epileptiform spikes, seizures and correlation with patient behavioural reports. In the future, correlation of spikes and seizures with behaviour will allow more detailed investigation of the clinical impact of spikes and seizures on patients.

Abstract Aims Patients with obesity frequently present with dyspnoea. Biomarkers that reflect wall stress are often used to evaluate circulatory congestion and help determine whether dyspnoea is of cardiac causes. Patients with obesity display greater external restraint on the heart, which may alter relationships between intravascular pressures and stress markers. Methods and results Subjects with unexplained dyspnoea ( n = 212) underwent cardiac catheterization with simultaneous echocardiography. Blood sampling was performed in a subset ( n = 58). Relationships between echocardiographic and blood biomarkers of circulatory congestion and directly‐measured haemodynamics were compared between participants with severe obesity [body mass index (BMI) ≥35 kg/m 2 , Group B) and those without (BMI <35 kg/m 2 , Group A). Circulatory congestion was assessed by pulmonary capillary wedge pressure (PCWP), and vascular distending pressure was assessed by left ventricular transmural pressure (LVTMP). As compared to Group A, participants in Group B displayed higher PCWP relative to N‐terminal pro‐B‐type natriuretic peptide, mid‐regional pro‐atrial natriuretic peptide, troponin T, and growth differentiation factor‐15 (all p < 0.01). In contrast, the relationships between LVTMP and the biomarkers were superimposable. Echocardiographic biomarkers revealed the same pattern: PCWP was higher for any E/e′ ratio in Group B compared to Group A, but the relationship between LVTMP and E/e′ was similar. In contrast, levels of C‐terminal pro‐endothelin‐1 and mid‐regional pro‐adrenomedullin were more robustly correlated with PCWP (r = 0.67 and r = 0.62, both p < 0.0001), with no differential relationship based upon BMI. Conclusions Non‐invasive haemodynamic markers underestimate circulatory congestion in patients with obesity, an effect that appears related to uncoupling between cardiac wall stress and intravascular pressures. This may lead to systematic under‐recognition of congestion in patients with obesity.