Determinants of acute irreversible electroporation lesion characteristics after pulsed field ablation: the role of voltage, contact, and adipose interference.

AIMS: Pulsed field ablation (PFA) is a non-thermal ablative approach in which cardiomyocyte death is obtained through irreversible electroporation (IRE). Data correlating the biophysical characteristics of IRE and lesion characteristics are limited. The aim of this study was to assess the effect of different procedural parameters [voltage, number of cycles (NoCs), and contact] on lesion characteristics in a vegetal and animal model for IRE. METHODS AND RESULTS: Two hundred and four Russet potatoes were used. Pulsed field ablation lesions were delivered on 3 cm cored potato specimens using a multi-electrode circular catheter with its dedicated IRE generator. Different voltage (from 300 to 1200 V) and NoC (from 1 to 5×) protocols were used. The impact of 0.5 and 1 mm catheter-to-specimen distances was tested. A swine animal model was then used to validate the results observed in the vegetable model. The association between voltage, the NoCs, distance, and lesion depth was assessed through linear regression. An almost perfect linear association between lesion depth and voltage was observed (R2 = 0.95; P < 0.001). A similarly linear relationship was observed between the NoCs and the lesion depth (R2 = 0.73; P < 0.001). Compared with controls at full contact, a significant dampening on lesion depth was observed at 0.5 mm distance (1000 V 2×: 2.11 ± 0.12 vs. 0.36 ± 0.04, P < 0.001; 2.63 ± 0.10 vs. 0.43 ± 0.08, P < 0.001). No lesions were observed at 1.0 mm distance. CONCLUSION: In a vegetal and animal model for IRE assessment, PFA lesion characteristics were found to be strongly dependent on voltage settings and the NoCs, with a quasi-linear relationship. The lack of catheter contact was associated with a dampening in lesion depth.

Electrocardiogram Monitoring Wearable Devices and Artificial-Intelligence-Enabled Diagnostic Capabilities: A Review.

Worldwide, population aging and unhealthy lifestyles have increased the incidence of high-risk health conditions such as cardiovascular diseases, sleep apnea, and other conditions. Recently, to facilitate early identification and diagnosis, efforts have been made in the research and development of new wearable devices to make them smaller, more comfortable, more accurate, and increasingly compatible with artificial intelligence technologies. These efforts can pave the way to the longer and continuous health monitoring of different biosignals, including the real-time detection of diseases, thus providing more timely and accurate predictions of health events that can drastically improve the healthcare management of patients. Most recent reviews focus on a specific category of disease, the use of artificial intelligence in 12-lead electrocardiograms, or on wearable technology. However, we present recent advances in the use of electrocardiogram signals acquired with wearable devices or from publicly available databases and the analysis of such signals with artificial intelligence methods to detect and predict diseases. As expected, most of the available research focuses on heart diseases, sleep apnea, and other emerging areas, such as mental stress. From a methodological point of view, although traditional statistical methods and machine learning are still widely used, we observe an increasing use of more advanced deep learning methods, specifically architectures that can handle the complexity of biosignal data. These deep learning methods typically include convolutional and recurrent neural networks. Moreover, when proposing new artificial intelligence methods, we observe that the prevalent choice is to use publicly available databases rather than collecting new data.

Rapid prediction of secondary neurologic decline after traumatic brain injury: a data analytic approach.

Secondary neurologic decline (ND) after traumatic brain injury (TBI) is independently associated with outcome, but robust predictors of ND are lacking. In this retrospective analysis of consecutive isolated TBI admissions to the R. Adams Cowley Shock Trauma Center between November 2015 and June 2018, we aimed to develop a triage decision support tool to quantify risk for early ND. Three machine learning models based on clinical, physiologic, or combined characteristics from the first hour of hospital resuscitation were created. Among 905 TBI cases, 165 (18%) experienced one or more ND events (130 clinical, 51 neurosurgical, and 54 radiographic) within 48 h of presentation. In the prediction of ND, the clinical plus physiologic data model performed similarly to the physiologic only model, with concordance indices of 0.85 (0.824-0.877) and 0.84 (0.812-0.868), respectively. Both outperformed the clinical only model, which had a concordance index of 0.72 (0.688-0.759). This preliminary work suggests that a data-driven approach utilizing physiologic and basic clinical data from the first hour of resuscitation after TBI has the potential to serve as a decision support tool for clinicians seeking to identify patients at high or low risk for ND.

Admission Features Associated With Paroxysmal Sympathetic Hyperactivity After Traumatic Brain Injury: A Case-Control Study.

OBJECTIVES: Paroxysmal sympathetic hyperactivity occurs in a subset of critically ill traumatic brain injury patients and has been associated with worse outcomes after traumatic brain injury. The goal of this study was to identify admission risk factors for the development of paroxysmal sympathetic hyperactivity in traumatic brain injury patients. DESIGN: Retrospective case-control study of age- and Glasgow Coma Scale-matched traumatic brain injury patients. SETTING: Neurotrauma ICU at the R. Adams Cowley Shock Trauma Center of the University of Maryland Medical System, January 2016 to July 2018. PATIENTS: Critically ill adult traumatic brain injury patients who underwent inpatient monitoring for at least 14 days were included. Cases were identified based on treatment for paroxysmal sympathetic hyperactivity with institutional first-line therapies and were confirmed by retrospective tabulation of established paroxysmal sympathetic hyperactivity diagnostic and severity criteria. Cases were matched 1:1 by age and Glasgow Coma Scale to nonparoxysmal sympathetic hyperactivity traumatic brain injury controls, yielding 77 patients in each group. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Admission characteristics independently predictive of paroxysmal sympathetic hyperactivity included male sex, higher admission systolic blood pressure, and initial CT evidence of diffuse axonal injury, intraventricular hemorrhage/subarachnoid hemorrhage, complete cisternal effacement, and absence of contusion. Paroxysmal sympathetic hyperactivity cases demonstrated significantly worse neurologic outcomes upon hospital discharge despite being matched for injury severity at admission. CONCLUSIONS: Several anatomical, epidemiologic, and physiologic risk factors for clinically relevant paroxysmal sympathetic hyperactivity can be identified on ICU admission. These features help characterize paroxysmal sympathetic hyperactivity as a clinical-pathophysiologic phenotype associated with worse outcomes after traumatic brain injury.

Safety and Feasibility of a Novel Transnasal Cooling Device to Induce Normothermia in Febrile Cerebrovascular Patients.

BACKGROUND: Inducing normothermia with surface cooling temperature modulating devices (TMDs) is cumbersome and often associated with significant shivering. We tested the safety and feasibility of a novel transnasal evaporative cooling device to induce and maintain normothermia in febrile patients following ischemic and hemorrhagic stroke. METHODS: A single-center study utilizing the CoolStat® transnasal cooling device was used to achieve core temperature reduction in mechanically ventilated stroke patients with fever (T ≥ 38.3 C) refractory to acetaminophen by inducing an evaporative cooling energy exchange in the nasal turbinates thru a high flow of dehumidified air into the nasal cavity and out through the mouth. Continuous temperature measurements were obtained from tympanic and core (esophageal or bladder) temperature monitors. Safety assessments included continuous monitoring for hypertension, tachycardia, and raised intracranial pressure (when monitored). Otolaryngology (ENT) evaluations were monitored for any device-related nasal mucosal injury with a pre- and post-visual examination. Shivering was assessed every 30 min using the Bedside Shivering Assessment Scale (BSAS). Duration of device use was limited to 8 h, at which time patients were transitioned to routine care for temperature management. RESULTS: Ten subjects (median age: 54 years, BMI: 32.5 kg/m2, 60% men) were enrolled with normothermia achieved in 90% of subjects. One subject did not achieve normothermia and was later refractory to other TMDs. Median baseline temperature was 38.5 ± 0.1 C, with a reduction noted by 4 h (38.5 ± 0.1 vs 37.3 ± 0.8, P < 0.001) and sustained at 8 h (38.5 ± 0.1 vs 37.1 ± 0.7, P = 0.001). Time to normothermia was 2.6 ± 1.9 h. The median BSAS was 0 (range 0-1) with only 4 episodes necessitating meperidine across 76 h of study monitoring. No treatment was discontinued due to safety concerns. ENT evaluations noted no device-related adverse findings. CONCLUSIONS: Inducing normothermia with a novel transnasal TMD appears to be safe, feasible and not associated with significant shivering. A multicenter trial testing the ability of the CoolStat to maintain normothermia for 24 h is currently underway.

Twitter Mentions and Academic Citations in the Urologic Literature.

OBJECTIVE: To quantify the relationship between the number of Twitter mentions and the number of academic citations a urologic publication receives. MATERIALS AND METHODS: Two hundred and thirteen papers from 7 prominent urologic journals were examined 37 months after publication. Articles were evaluated with 2 citation based "bibliometrics" (Scopus, Google Scholar) and Twitter mentions were tracked using the Altmetric Bookmarklet. The number of article citations and Twitter mentions were compared using one-way Analysis of variance (ANOVA) and bivariate fit analysis. RESULTS: Seventy-three percent of articles had at least 1 Twitter mention. Forty-two percent of Twitter mentions occurred within the first week of the online publication date. Articles mentioned on Twitter had 2.0-fold more Scopus citations (P <.01), and 2.3-fold more Google Scholar citations (P <. 01) compared to articles with no Twitter mentions. Female urologic articles had the greatest number of Twitter mentions (5.7 mentions/article) while pediatric urology had the fewest mean number of Twitter mentions (0.8 mentions/article). A total of 8.9% of papers were tweeted by their authors. Author tweeted articles were associated with a 12.3 (2.0-fold) and 15.5 (1.8-fold) mean citation increase for Scopus and Google Scholar (P <. 01 and P = . 01) compared to articles not shared by their authors on Twitter. CONCLUSION: The majority of urologic publications are being shared on Twitter. The number of citations a urologic publication receives up to 3 years after release is positively associated with the number of mentions it has on Twitter. Twitter activity may be an early indicator of ultimate academic impact of an academic urologic paper.

Linking cellular metabolism and metabolomics to risk-stratification of prostate cancer clinical aggressiveness and potential therapeutic pathways.

Prostate cancer treatment is based on the stratification of disease as low-, intermediate- or high-risk. This stratification has been largely based on anatomic pathology of the disease, as well as through the use of prostate specific antigen (PSA). However, despite this stratification, there remains heterogeneity within the current classification schema. Utilizing a metabolic approach may help to further establish novel biomolecular markers of disease aggressiveness. These markers may eventually be useful in not only the diagnosis of disease but in creating tumor specific targeted therapy for improved clinical outcomes.

Pulmonary Hypertension due to Radiofrequency Catheter Ablation (RFCA) for Atrial Fibrillation: The Lungs, the Atrium or the Ventricle?

Atrial fibrillation is the most common heart rhythm disorder in United States, characterised by rapid and irregular beating of both the atria resulting in the similar ventricular response. While rate and rhythm control using pharmacological regimens remain the primary management strategies in these patients, radiofrequency catheter ablation (RFCA) is rapidly rising as an alternative modality of treatment. Increase in the incidence of RFCA has shed light on complications associated with this procedure. Pulmonary hypertension (PH) is one of the long-term complications that has been observed postcatheter ablation. There have been multiple mechanisms which have been proposed to explain these elevated pulmonary pressures. These include the involvement of the lungs due to pulmonary vein stenosis, pulmonary vein occlusion and, rarely, pulmonary embolism. Radiofrequency catheter ablation can also lead to scarring of the atrium which can cause left atrial diastolic dysfunction leading to elevated pulmonary pressures. Recently, it was also proposed that elevated pulmonary pressure was related to the unmasking of left ventricular diastolic dysfunction occurring after this procedure. In this article, we review all the mechanisms that are associated with the development of pulmonary hypertension in patients undergoing RCFA for atrial fibrillation and the approach to diagnosis and management of such patients.

Nivolumab causing painless thyroiditis in a patient with adenocarcinoma of the lung.

Thyroiditis is characterised by transient hyperthyroidism, followed sometimes by hypothyroidism, and then recovery. We report a case of painless drug-induced thyroiditis-in a patient with no history of any thyroid disorder-treated with Nivolumab (an IgG4 monoclonal antibody against Programmed Death Receptor 1). The purpose of this case report is to increase awareness among clinicians regarding this possible adverse effect from Nivolumab, and discuss the possible pathophysiology and management strategies in such patients.