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A young man presents with severe, pressure-like, midsternal, nonradiating pain, rated 10 on a scale of 10.

Purpose Differentiating psychogenic non-epileptic seizures (PNES) from epileptic seizures (ES) can be difficult, even when expert clinicians have video recordings of seizures. Moreover, witnesses who are not trained observers may provide descriptions that differ from the expert clinicians’, which often raises concern about whether the patient has both ES and PNES. As such, quantitative, evidence-based tools to help differentiate ES from PNES based on patients’ and witnesses’ descriptions of seizures may assist in the early, accurate diagnosis of patients. Methods Based on patient- and observer-reported data from 1372 patients with diagnoses documented by video-elect roencephalography (vEEG), we used logistic regression (LR) to compare specific peri-ictal behaviors and seizure triggers in five mutually exclusive groups: ES, PNES, physiologic non-epileptic seizure-like events, mixed PNES plus ES, and inconclusive monitoring. To differentiate PNES-only from ES-only, we retrospectively trained multivariate LR and a forest of decision trees (DF) to predict the documented diagnoses of 246 prospective patients. Results The areas under the receiver operating characteristic curve (AUCs) of the DF and LR were 75% and 74%, respectively (empiric 95% CI of chance 37–62%). The overall accuracy was not significantly higher than the naive assumption that all patients have ES (accuracy DF 71%, LR 70%, naive 68%, p > 0.05). Conclusions Quantitative analysis of patient- and observer-reported peri-ictal behaviors objectively changed the likelihood that a patient’s seizures were psychogenic, but these reports were not reliable enough to be diagnostic in isolation. Instead, our scores may identify patients with “probable” PNES that, in the right clinical context, may warrant further diagnostic assessment.

Objective Psychogenic nonepileptic seizure (PNES) is a common diagnosis after evaluation of medication resistant or atypical seizures with video-electroencephalographic monitoring (VEM), but usually follows a long delay after the development of seizures, during which patients are treated for epilepsy. Therefore, more readily available diagnostic tools are needed for earlier identification of patients at risk for PNES. A tool based on patient-reported psychosocial history would be especially beneficial because it could be implemented in the outpatient clinic. Methods Based on the data from 1375 patients with VEM-confirmed diagnoses, we used logistic regression to compare the frequency of specific patient-reported historical events, demographic information, age of onset, and delay from first seizure until VEM in five mutually exclusive groups of patients: epileptic seizures (ES), PNES, physiologic nonepileptic seizure-like events (PSLE), mixed PNES plus ES, and inconclusive monitoring. To determine the diagnostic utility of this information to differentiate PNES only from ES only, we used multivariate piecewise-linear logistic regression trained using retrospective data from chart review and validated based on data from 246 prospective standardized interviews. Results The prospective area under the curve of our weighted multivariate piecewise-linear by-sex score was 73%, with the threshold that maximized overall retrospective accuracy resulting in a prospective sensitivity of 74% (95% CI: 70–79%) and prospective specificity of 71% (95% CI: 64–82%). The linear model and piecewise linear without an interaction term for sex had very similar performance statistics. In the multivariate piecewise-linear sex-split predictive model, the significant factors positively associated with ES were history of febrile seizures, current employment or active student status, history of traumatic brain injury (TBI), and longer delay from first seizure until VEM. The significant factors associated with PNES were female sex, older age of onset, mild TBI, and significant stressful events with sexual abuse, in particular, increasing the likelihood of PNES. Delays longer than 20 years, age of onset after 31 years for men, and age of onset after 40 years for women had no additional effect on the likelihood of PNES. Discussion Our promising results suggest that an objective score has the potential to serve as an early outpatient screening tool to identify patients with greater likelihood of PNES when considered in combination with other factors. In addition, our analysis suggests that sexual abuse, more than other psychological stressors including physical abuse, is more associated with PNES. There was a trend of increasing frequency of PNES for women during childbearing years and plateauing outside those years that was not observed in men.

SummaryObjective Low-cost evidence-based tools are needed to facilitate the early identification of patients with possible psychogenic nonepileptic seizures (PNES). Prior to accurate diagnosis, patients with PNES do not receive interventions that address the cause of their seizures and therefore incur high medical costs and disability due to an uncontrolled seizure disorder. Both seizures and comorbidities may contribute to this high cost. Methods Based on data from 1,365 adult patients with video-electroencephalography–confirmed diagnoses from a single center, we used logistic and Poisson regression to compare the total number of comorbidities, number of medications, and presence of specific comorbidities in five mutually exclusive groups of diagnoses: epileptic seizures (ES) only, PNES only, mixed PNES and ES, physiologic nonepileptic seizurelike events, and inconclusive monitoring. To determine the diagnostic utility of comorbid diagnoses and medication history to differentiate PNES only from ES only, we used multivariate logistic regression, controlling for sex and age, trained using a retrospective database and validated using a prospective database. Results Our model differentiated PNES only from ES only with a prospective accuracy of 78% (95% confidence interval =72–84%) and area under the curve of 79%. With a few exceptions, the number of comorbidities and medications was more predictive than a specific comorbidity. Comorbidities associated with PNES were asthma, chronic pain, and migraines (p < 0.01). Comorbidities associated with ES were diabetes mellitus and nonmetastatic neoplasm (p < 0.01). The population-level analysis suggested that patients with mixed PNES and ES may be a population distinct from patients with either condition alone. Significance An accurate patient-reported medical history and medication history can be useful when screening for possible PNES. Our prospectively validated and objective score may assist in the interpretation of the medication and medical history in the context of the seizure description and history.

ObjectiveEarly and accurate diagnosis of patients with psychogenic nonepileptic seizures (PNES) leads to appropriate treatment and improves long-term seizure prognosis. However, this is complicated by the need to record seizures to make a definitive diagnosis. Suspicion for PNES can be raised through knowledge that patients with PNES have increased somatic sensitivity and report more positive complaints on review-of-systems questionnaires (RoSQs) than patients with epileptic seizures. If the responses on the RoSQ can differentiate PNES from other seizure types, then these forms could be an early screening tool.MethodsOur dataset included all patients admitted from January 2006 to June 2016 for video-electroencephalography at UCLA. RoSQs prior to May 2015 were acquired through retrospective chart review (n=405), whereas RoSQs from subsequent patients were acquired prospectively (n=190). Controlling for sex and number of comorbidities, we used binomial regression to compare the total number of symptoms and the frequency of specific symptoms between five mutually exclusive groups of patients: epileptic seizures (ES), PNES, physiologic nonepileptic seizure-like events (PSLE), mixed PNES plus ES, and inconclusive monitoring. To determine the diagnostic utility of RoSQs to differentiate PNES only from ES only, we used multivariate logistic regression, controlling for sex and the number of medical comorbidities.ResultsOn average, patients with PNES or mixed PNES and ES reported more than twice as many symptoms than patients with isolated ES or PSLE (p0.1).DiscussionThis analysis of RoSQs confirms that patients with PNES with and without comorbid ES report more symptoms on a population level than patients with epilepsy or PSLE. While these differences help describe the population of patients with PNES, the consistency of RoSQ responses was neither accurate nor specific enough to be used solely as an early screening tool for PNES. Our results suggest that the RoSQ may help differentiate PNES from ES only when, based on other information, the pre-test probability of PNES is at least 50%.

RationaleConsideration of lung transplantation in patients with systemic sclerosis (SSc) remains guarded, often due to the concern for esophageal dysfunction and the associated potential for allograft injury and suboptimal post-lung transplantation outcomes.ObjectivesThe purpose of this study was to systematically report our single-center experience regarding lung transplantation in the setting of SSc, with a particular focus on esophageal dysfunction.MethodsWe retrospectively reviewed all lung transplants at our center from January 1, 2000 through August 31, 2012 (n = 562), comparing the SSc group (n = 35) to the following lung transplant diagnostic subsets: all non-SSc (n = 527), non-SSc diffuse fibrotic lung disease (n = 264), and a non-SSc matched group (n = 109). We evaluated post-lung transplant outcomes, including survival, primary graft dysfunction, acute rejection, bronchiolitis obliterans syndrome, and microbiology of respiratory isolates. In addition, we defined severe esophageal dysfunction using esophageal manometry and esophageal morphometry criteria on the basis of chest computed tomography images. For patients with SSc referred for lung transplant but subsequently denied (n = 36), we queried the reason(s) for denial with respect to the concern for esophageal dysfunction.Measurements and main resultsThe 1-, 3-, and 5-year post-lung transplant survival for SSc was 94, 77, and 70%, respectively, and similar to the other groups. The remaining post-lung transplant outcomes evaluated were also similar between SSc and the other groups. Approximately 60% of the SSc group had severe esophageal dysfunction. Pre-lung transplant chest computed tomography imaging demonstrated significantly abnormal esophageal morphometry for SSc when compared with the matched group. Importantly, esophageal dysfunction was the sole reason for lung transplant denial in a single case.ConclusionsRelative to other lung transplant indications, our SSc group experienced comparable survival, primary graft dysfunction, acute rejection, bronchiolitis obliterans syndrome, and microbiology of respiratory isolates, despite the high prevalence of severe esophageal dysfunction. Esophageal dysfunction rarely precluded active listing for lung transplantation.

Lung transplant recipients (LTR) are at high risk of cutaneous squamous cell carcinoma (SCC). Voriconazole exposure after lung transplant has recently been reported as a risk factor for SCC. We sought to study the relationship between fungal prophylaxis with voriconazole and the risk of SCC in sequential cohorts from a single center. We evaluated 400 adult LTR at UCLA between 7/1/2005 and 12/22/2012. On 7/1/2009, our center instituted a protocol switch from targeted to universal antifungal prophylaxis for at least 6 months post-transplant. Using Cox proportional hazards models, time to SCC was compared between targeted (N = 199) and universal (N = 201) prophylaxis cohorts. Cox models were also used to assess SCC risk as a function of time-dependent cumulative exposure to voriconazole and other antifungal agents. The risk of SCC was greater in the universal prophylaxis cohort (HR 2.02, P < 0.01). Voriconazole exposure was greater in the universal prophylaxis cohort, and the cumulative exposure to voriconazole was associated with SCC (HR 1.75, P < 0.01), even after adjustment for other important SCC risk factors. Voriconazole did not increase the risk of advanced tumors. Exposure to other antifungal agents was not associated with SCC. Voriconazole should be used cautiously in this population.

Current laboratory methods used to assess neonatal and adult cardiocyte function include measurement of gene and protein expression levels, calcium transients, and contractility. Our goal was to develop simple tools to analyze such data readily. We created two MATLAB®-based toolboxes; the Contraction Video Processing (CVP) and the Cardiocyte Functional Response Analysis (CFRA) Toolbox. Videos of contracting cultured cardiocytes are acquired using a digital camera attached to an inverted phase microscope. Video frames are analyzed using digital imaging processing techniques along with several contraction assessment methods available through the CVP toolbox. The CVP offers direct correlation, pixel intensity tracking and Polar Fourier transform methods for the analysis of neonatal cardiocyte contraction. Analysis of adult cardiocytes includes those implemented on neonatal cardiocytes in addition to area boundary tracking, Fourier descriptor analysis, and cell length tracking methods. The resulting contraction records are processed using the CFRA toolbox to provide quantitative analyses of cardiocyte contractility and calcium transient responses. Transient data are obtained by measuring the calcium fluxes using the fluorescent dye Fluo-3, and a Photon Technology fluorometer system running Felix software. Data analysis routines have been created and tailored exclusively to the characteristics and needs of cellular cardiovascular research investigators. The analytical methods created are used to find the onset of contraction, perform signal averaging, and acquire statistical information of functional data. CFRA toolbox contractility processing yields onset time, time-to-peak, duration, and fast and slow recovery times. CFRA toolbox calcium transient signal processing yields onset time, signal intensity, and fast and slow exponential recovery rates associated with SERCA and NCX channels respectively. The toolboxes allow examination of beat-to-beat contractility and calcium transient variations within the same cardiocyte as well as from cell population to population. Supported by NIH/NIGMS SDSU MARC Program 5T34GM008303-22