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The conditional power prior is a popular method to borrow information from a single prior data source. The amount of borrowing is controlled by the power parameter which is fixed before running the new study. However, fixing this parameter before running a new study is often difficult and may be unwise because if the outcomes in the current study are much different from the prior data outcomes, the power parameter cannot be changed to reflect a more appropriate degree of borrowing. On the other hand, treating the power parameter as a random variable to be updated via Bayes theorem may relinquish control over how much to borrow in cases where regulatory oversight recommends a conservative approach.Previous authors have determined the power parameter at the end of the current study based on "stochastic" similarity in the outcomes between the current study and the prior data. In this paper, we introduce some modifications to those methods. First, we determine the power parameter based on similarity between a percentage of the current study outcome data available at an interim look and the prior outcome data. This may limit potential for operational bias resulting from the determination of the power parameter after the current study is complete. Next, we introduce a new measure of similarity between the current (interim) and prior data that limits similarity by a pre-specified clinical margin. The proposed clinical similarity region may be readily understood by clinicians who need to assess when such borrowing is clinically appropriate. Through simulations, we show that our approach has low bias and good power, while reducing type I error rate in areas outside of the "similarity region". An example of a hypothetical medical device study illustrates its potential use in practice.

With more and more medical device databases being developed, there is an increasing interest in learning the geographical patterns of medical-device-related adverse events (AEs). For a specific medical device and an adverse event (AE) of interest, our aim is to detect a spatial-cluster signal that has a significantly higher AE rate than the AE rates for other regions, when the exposure information is available. We develop a likelihood ratio test (LRT) method incorporating exposure information, by geographical region, for spatial-cluster signal detection when the underlying observed health outcome associated with the medical device of interest is a Poisson-modeled count data (e.g., an outcome of AE count). An extensive simulation study shows that this method has good power, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). The application of the method is demonstrated by two hypothetical case studies regarding a medical device that is used for patients who have reached end-stage heart failure. A methodological framework for exploring geographic patterns in device safety surveillance is discussed, including safety data collection, statistical tools, and display of the analysis results. The proposed statistical method can be used for spatial-cluster signal detection for an AE of interest from medical device registries or other databases that have patient-level geographical information.

Recently, unsupervised learning has made impressive progress on various tasks. Despite the dominance of discriminative models, increasing attention is drawn to representations learned by generative models and in particular, Generative Adversarial Networks (GANs). Previous works on the interpretation of GANs reveal that GANs encode semantics in feature maps in a linearly separable form. In this work, we further find that GAN's features can be well clustered with the linear separability assumption. We propose a novel clustering algorithm, named KLiSH, which leverages the linear separability to cluster GAN's features. KLiSH succeeds in extracting fine-grained semantics of GANs trained on datasets of various objects, e.g., car, portrait, animals, and so on. With KLiSH, we can sample images from GANs along with their segmentation masks and synthesize paired image-segmentation datasets. Using the synthesized datasets, we enable two downstream applications. First, we train semantic segmentation networks on these datasets and test them on real images, realizing unsupervised semantic segmentation. Second, we train image-to-image translation networks on the synthesized datasets, enabling semantic-conditional image synthesis without human annotations.

Meta-analysis of related trials can provide an overall measure of safety-signal accounting for variability across studies. In addition to an overall measure, researchers may often be interested in study-specific measures to assess safety of the product. Likelihood ratio tests (LRT) methods serve this purpose by identifying studies that appear to show a safety concern. In this paper, we present a Bayesian approach. Despite having good statistical properties, the LRT methods may not be suitable for the meta-analysis of randomized controlled trials (RCTs) when there are several studies with zero events in at least one arm.In this article, we describe a Bayesian framework using a Zero-inflated binomial model with spike-and-slab parameterization for the treatment effects. In addition to providing an overall meta-analytic estimate, this method provides posterior probability of a safety-signal for each study.We illustrate the approach using two published data sets comprising several randomized controlled trials (RCTs) each and compare the model performance for different choices of priors for treatment effect.The proposed Bayesian methodological framework is useful to identify potential signal for single adverse event and to determine overall meta-analytic estimate of the magnitude of the signal. Practitioners may consider this approach as an alternative to the frequentist's LRT approach discussed in Jung et al. (J Biopharm Stat 31:47-54, 2020) when there are zero events in either the treatment arm or the control arm. In the future, this approach can be further extended to accommodate multiple adverse events.

Generative Adversarial Networks (GANs) are able to generate high-quality images, but it remains difficult to explicitly specify the semantics of synthesized images. In this work, we aim to better understand the semantic representation of GANs, and thereby enable semantic control in GAN’s generation process. Interestingly, we find that a well-trained GAN encodes image semantics in its internal feature maps in a surprisingly simple way: a linear transformation of feature maps suffices to extract the generated image semantics. To verify this simplicity, we conduct extensive experiments on various GANs and datasets; and thanks to this simplicity, we are able to learn a semantic segmentation model for a trained GAN from a small number (e.g., 8) of labeled images. Last but not least, leveraging our finding, we propose two few-shot image editing approaches, namely Semantic-Conditional Sampling and Semantic Image Editing. Given a trained GAN and as few as eight semantic annotations, the user is able to generate diverse images subject to a user-provided semantic layout, and control the synthesized image semantics. We have made the code publicly available1.

Signal detection methods have been used extensively in post-market surveillance to identify elevated risks of adverse events. However, these statistical methods have not been widely used in detecting AE signals for medical devices. In this paper, we focused on the use of a likelihood ratio test (LRT)-based method in identifying adverse event (AE) signals associated with left ventricular assist devices (LVADs) using Medical Device Reporting (MDR) data. Among 110,927 adverse event entries identified in MDR data for LVADs, the LRT method detected 18 AE signals which included seven bleeding-related AEs such as hemolysis, thrombosis, hematuria, thrombus, blood loss, and hemorrhage. The LRT method was also applied to longitudinal data from 2007 to 2019 where a monotone alpha-spending function was used to ensure the control of type I error at each look and overall for trend analysis. Furthermore, the LRT method was compared to proportional reporting ratios (PRRs), Bayesian confidence propagation neural network (BCPNN), and simplified Bayes methods and found to be the most conservative method when examining the total number of detected signals, given its ability to control type-I error and the false discovery rate.

Effective post-market safety surveillance of medical devices is critical for public health. However, many current statistical methods for safety signal detection do not control for type I error when assessing multiple device and adverse event (AE) combinations. This can result in increased false signals, underscoring the need for more robust statistical methods. Moreover, the duration of medical device use can be an important factor to consider in safety surveillance. In this study, we adapted a likelihood ratio test (LRT) based method, which was initially developed and applied to drugs, to identify safety signals for left ventricular assist devices (LVAD). Among patients with chronic, advanced left ventricular failure, we analyzed AE data for HeartWare and HeartMate II patients during a two-year period and further incorporated person-years (henceforth exposure-time). The novel modified LRT and conventional Z-test with

With more and more medical device databases being developed, there is an increasing interest in learning the geographical patterns of medical-device-related adverse events (AEs). For a specific medical device and an adverse event (AE) of interest, our aim is to detect a spatial-cluster signal that has a significantly higher AE rate than the AE rates for other regions, when the exposure information is available.We develop a likelihood ratio test (LRT) method incorporating exposure information, by geographical region, for spatial-cluster signal detection when the underlying observed health outcome associated with the medical device of interest is a Poisson-modeled count data (e.g., an outcome of AE count).An extensive simulation study shows that this method has good power, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). The application of the method is demonstrated by two hypothetical case studies regarding a medical device that is used for patients who have reached end-stage heart failure.A methodological framework for exploring geographic patterns in device safety surveillance is discussed, including safety data collection, statistical tools, and display of the analysis results. The proposed statistical method can be used for spatial-cluster signal detection for an AE of interest from medical device registries or other databases that have patient-level geographical information.

With a record number of medical devices approved or cleared, it is important to understand the performance of devices once they are on the market. Using data from multiple medical devices and multiple sites, the problem of interest in this article is to detect if a device is a signal; that is, if a device performs significantly different from other devices of the same class, when the outcome of interest is a continuous variable. We develop a normal likelihood ratio test (LRT) method, henceforth referred to as normal-LRT, by incorporating sample size information into the methodological framework, to detect device signals using multi-site and multi-device data. It is shown via extensive simulation that the proposed method controls the type-I error and false discovery rate (FDR), while having good power and sensitivity. This method is applied to a hypothetical case study, in which 6 medical devices of the same class are compared. The normal-LRT method can be considered as a tool for device signal detection using data from multi-site and multi-device when the outcome of interest is a continuous measurement.

The purpose of our study is to assess outcomes following robotic ventral hernia (RVH) repair. The New York Statewide Planning and Research Cooperative System administrative database was used to identify all patients undergoing laparoscopic ventral hernia (LVH) and RVH between 2010 and 2013. Outcome measures including complications, hospital length of stay (HLOS), 30-day readmissions, and 30-day emergency department (ED) visits were compared. Propensity score (PS) analysis was used to estimate the adjusted marginal differences between patients who underwent robotic-assisted and laparoscopic procedures. There were 20,896 LVH and 679 (3.2%) RVH repairs. Initial univariate analysis demonstrated that patients undergoing RVH had worse outcomes in terms of complications (20.18% vs 10.56%, P < 0.0001), longer HLOS (4.32 vs 2.19 days, P = 0.0023), higher rates in 30-day readmissions (9.28% vs 5.06%, P < 0.0001), and 30-day ED visits (14.43% vs 10.46%, P < 0.0001). Following PS analysis, which accounts for all patient associated variables, there was no difference found in 30-day readmission or 30-day ED visits between RVH and LVH (P = 0.2760 and 0.2043, respectively). Patients undergoing RVH had a significantly shorter HLOS (P < 0.0001) and lower rate of complications (P = 0.0134). Following PS analysis, this study demonstrates that RVH may be associated with shorter HLOS and lower complication rate. Further studies are necessary to compare laparoscopic and robotic approaches for ventral hernia.

Investigation of trends and outcomes in heart disease (HD) and pregnancy has been limited. We chose to identify the prevalence, trends, and outcomes of pregnant women with different forms of HD in the United States. Healthcare Cost and Utilization Project's National Inpatient Sample was screened for hospital admissions for delivery in pregnant women with HD from 2003 to 2012. Maternal clinical characteristics and outcomes were identified in women with and without HD, and in HD subtypes: congenital (CHD), valvular HD, cardiomyopathy, and pulmonary hypertension (PH). Primary outcomes of interest were prevalence, trends, and major adverse cardiac events (MACEs), a composite of in-hospital death, acute myocardial infarction, heart failure, arrhythmia, cerebrovascular event, embolic events, or cardiac complications of anesthesia. We studied 81,295 patients with HD and 39,894,032 without. CHD was the most frequent type (41.8%, 33,982 of 81,295 patients), followed by valvular HD (30.9%, 25,138 of 81,295 patients), cardiomyopathy (20.8%, 16,926 of 81,295 patients), and PH (6.5%, 5,250 of 81,295 patients). MACE was highest among women with cardiomyopathy and lowest among women with CHD (44.0%, 7,449 of 16,926 vs 6.2%, 2,102 of 33,982; p

Toll-like receptor (TLR)-mediated inflammation may contribute to neonatal sepsis, for which pentoxifylline (PTX), a phosphodiesterase inhibitor that raises intracellular cAMP, is a candidate adjunctive therapy. We characterized the anti-inflammatory effects of PTX toward TLR-mediated production of inflammatory (tumor necrosis factor (TNF) and interleukin (IL)-1β) and proresolution (IL-6 and IL-10) cytokines in human newborn and adult blood. Newborn cord and adult blood were treated with PTX (50–400 µmol/l) before, during or after stimulation with LPS (TLR4 agonist), R848 (TLR7/8 agonist) or LPS/ATP (inflammasome activation). Cytokines were measured by multiplex assay (supernatants), intracellular cytokines and signaling molecules by flow cytometry, and mRNA by quantitative real-time PCR. Whether added 2 h pre-, simultaneously to, or 2 h post-TLR stimulation, PTX inhibited TLR-mediated cytokine production in a concentration-dependent manner, with greater efficacy and potency in newborn blood, decreasing intracellular TNF and IL-1β with relative preservation of IL-10 and IL-6. PTX decreased TLR-mediated TNF mRNA while increasing IL-10 mRNA. Neonatal plasma factors contributed to the anti-inflammatory effects of PTX in newborn blood that were independent of soluble TNF receptor concentrations, p38 MAPK phosphorylation and IĸB degradation. PTX is a potent and efficacious inhibitor of TLR-mediated inflammatory cytokines in newborn cord blood and a promising neonatal anti-inflammatory agent.

Carotid artery stenting (CAS) and carotid artery endarterectomy (CEA) are complementary techniques for management of patients with carotid artery stenosis. This study investigates the impact of chronic kidney disease (CKD) and age on outcomes after carotid artery revascularization.National Inpatient Sample was surveyed for CAS and CEA among stage 3 and 4 CKD and stage 5/end stage renal disease (ESRD) patients from 2004 to 2012. Primary endpoint was in-hospital major adverse cardiovascular and cerebrovascular events (MACCE) stratified by kidney function and age. Regression analysis and propensity score matching were utilized.There were 3299 patients that underwent CEA and 652 underwent CAS with stage 3 and 4 CKD. Whereas, 1630 patients underwent CEA and 511 patients underwent CAS with stage 5 CKD/ESRD. Patients undergoing CAS had more in-hospital MACCE. Coronary artery disease (OR1.35, 95%CI:1.07-1.70) and CAS (OR1.35, 95%CI:1.02-1.77) were independently associated with MACCE for stage 3 and 4 CKD patients. For the stage 5 CKD/ESRD cohort, CAS (OR1.75, 95%CI:1.29-2.37) was independently associated with MACCE. Stratifying by age, showed no difference in event rates except for higher MACCE among patients60years old with stage 5 CKD/ESRD undergoing CAS (p0.001). Propensity score matching showed that treatment type had no significant effect on MACCE rates.Among CKD cohorts studied nationally, in-hospital MACCE were higher for patients that underwent CAS. Overall, age group analyses showed that there was no difference in MACCE rates between CAS and CEA. Although CAS was independently associated with MACCE, propensity score matching showed no risk difference of MACCE between CAS and CEA for either CKD cohort.

Since the introduction of laparoscopic cholecystectomy (LC), there has been continued evolution in technique, instrumentation and postoperative management. With increased experience, LC has migrated to the outpatient setting. We asked whether increased availability and experience has impacted incidence of and indications for LC.The New York (NY) State Planning and Research Cooperative System longitudinal administrative database was utilized to identify patients who underwent cholecystectomy between 1995 and 2013. ICD-9 and CPT procedure codes were extracted corresponding to laparoscopic and open cholecystectomy and the associated primary diagnostic codes. Data were analyzed as relative change in incidence (normalized to 1000 LC patients) for respective diagnoses.From 1995 to 2013, 711,406 cholecystectomies were performed in NY State: 637,308 (89.58 %) laparoscopic. The overall frequency of cholecystectomy did not increase (1.23 % increase with a commensurate population increase of 6.32 %). Indications for LC during this time were: 72.81 % for calculous cholecystitis (n = 464,032), 4.88 % for biliary colic (n = 31,124), 8.98 % for acalculous cholecystitis (n = 57,205), 3.01 % for gallstone pancreatitis (n = 19,193), and 1.59 % for biliary dyskinesia (n = 10,110). The incidence of calculous cholecystitis declined (-20.09 %, p 0.0001) between 1995 and 2013; meanwhile, other diagnoses increased in incidence: biliary colic (+54.96 %, p = 0.0013), acalculous cholecystitis (+94.24 %, p 0.0001), gallstone pancreatitis (+107.48 %, p 0.0001), and biliary dyskinesia (+331.74 %, p 0.0001). Outpatient LC incidence catapulted to 48.59 % in 2013, from 0.15 % in 1995, increasing320-fold. Analysis of LC through 2014 revealed increasing rates of digestive, infectious, respiratory, and renal complications, with overall cholecystectomy complication rates of 9.29 %.A shifting distribution of operative indications and increasing rates of complications should prompt careful consideration prior to surgery for benign biliary disease. For what is a common procedure, LC carries substantial risk of complications, thus requiring the patient to be an active participant and to share in the decision-making process.

OBJECTIVES\ud Cardiac arrest is associated with morbidity and mortality because of cerebral ischemia. Therefore, we tested the hypothesis that higher regional cerebral oxygenation during resuscitation is associated with improved return of spontaneous circulation, survival, and neurologic outcomes at hospital discharge. We further examined the validity of regional cerebral oxygenation as a test to predict these outcomes.\ud \ud DESIGN\ud Multicenter prospective study of in-hospital cardiac arrest.\ud \ud SETTING\ud Five medical centers in the United States and the United Kingdom.\ud \ud PATIENTS\ud Inclusion criteria are as follows: in-hospital cardiac arrest, age 18 years old or older, and prolonged cardiopulmonary resuscitation greater than or equal to 5 minutes. Patients were recruited consecutively during working hours between August 2011 and September 2014. Survival with a favorable neurologic outcome was defined as a cerebral performance category 1-2.\ud \ud INTERVENTIONS\ud Cerebral oximetry monitoring.\ud \ud MEASUREMENTS AND MAIN RESULTS\ud Among 504 in-hospital cardiac arrest events, 183 (36%) met inclusion criteria. Overall, 62 of 183 (33.9%) achieved return of spontaneous circulation, whereas 13 of 183 (7.1%) achieved cerebral performance category 1-2 at discharge. Higher mean ± SD regional cerebral oxygenation was associated with return of spontaneous circulation versus no return of spontaneous circulation (51.8% ± 11.2% vs 40.9% ± 12.3%) and cerebral performance category 1-2 versus cerebral performance category 3-5 (56.1% ± 10.0% vs 43.8% ± 12.8%) (both p < 0.001). Mean regional cerebral oxygenation during the last 5 minutes of cardiopulmonary resuscitation best predicted the return of spontaneous circulation (area under the curve, 0.76; 95% CI, 0.69-0.83); regional cerebral oxygenation greater than or equal to 25% provided 100% sensitivity (95% CI, 94-100) and 100% negative predictive value (95% CI, 79-100); regional cerebral oxygenation greater than or equal to 65% provided 99% specificity (95% CI, 95-100) and 93% positive predictive value (95% CI, 66-100) for return of spontaneous circulation. Time with regional cerebral oxygenation greater than 50% during cardiopulmonary resuscitation best predicted cerebral performance category 1-2 (area under the curve, 0.79; 95% CI, 0.70-0.88). Specifically, greater than or equal to 60% cardiopulmonary resuscitation time with regional cerebral oxygenation greater than 50% provided 77% sensitivity (95% CI,:46-95), 72% specificity (95% CI, 65-79), and 98% negative predictive value (95% CI, 93-100) for cerebral performance category 1-2.\ud \ud CONCLUSIONS\ud Cerebral oximetry allows real-time, noninvasive cerebral oxygenation monitoring during cardiopulmonary resuscitation. Higher cerebral oxygenation during cardiopulmonary resuscitation is associated with return of spontaneous circulation and neurologically favorable survival to hospital discharge. Achieving higher regional cerebral oxygenation during resuscitation may optimize the chances of cardiac arrest favorable outcomes.

Appendix_S1 for Statistical Methods for Clinical Study Site Selection by Jianjin Xu, Lan Huang, Zhihao Yao, Zhiheng Xu, Jyoti Zalkikar, and Ram Tiwari in Therapeutic Innovation & Regulatory Science

Appendix_S3 for Statistical Methods for Clinical Study Site Selection by Jianjin Xu, Lan Huang, Zhihao Yao, Zhiheng Xu, Jyoti Zalkikar, and Ram Tiwari in Therapeutic Innovation & Regulatory Science

Appendix_S2 for Statistical Methods for Clinical Study Site Selection by Jianjin Xu, Lan Huang, Zhihao Yao, Zhiheng Xu, Jyoti Zalkikar, and Ram Tiwari in Therapeutic Innovation & Regulatory Science

The purpose of our study is to assess outcomes following robotic ventral hernia (RVH) repair. The New York Statewide Planning and Research Cooperative System administrative database was used to identify all patients undergoing laparoscopic ventral hernia (LVH) and RVH between 2010 and 2013. Outcome measures including complications, hospital length of stay (HLOS), 30-day readmissions, and 30-day emergency department (ED) visits were compared. Propensity score (PS) analysis was used to estimate the adjusted marginal differences between patients who underwent robotic-assisted and laparoscopic procedures. There were 20,896 LVH and 679 (3.2%) RVH repairs. Initial univariate analysis demonstrated that patients undergoing RVH had worse outcomes in terms of complications (20.18% vs 10.56%, P0.0001), longer HLOS (4.32 vs 2.19 days, P = 0.0023), higher rates in 30-day readmissions (9.28% vs 5.06%, P0.0001), and 30-day ED visits (14.43% vs 10.46%, P0.0001). Following PS analysis, which accounts for all patient associated variables, there was no difference found in 30-day readmission or 30-day ED visits between RVH and LVH (P = 0.2760 and 0.2043, respectively). Patients undergoing RVH had a significantly shorter HLOS (P0.0001) and lower rate of complications (P = 0.0134). Following PS analysis, this study demonstrates that RVH may be associated with shorter HLOS and lower complication rate. Further studies are necessary to compare laparoscopic and robotic approaches for ventral hernia.

Introduction Neonatal inflammation, mediated in part through Toll-like receptor (TLR) and inflammasome signaling, contributes to adverse outcomes including organ injury. Pentoxifylline (PTX), a phosphodiesterase inhibitor which potently suppresses cytokine production in newborn cord blood, is a candidate neonatal anti-inflammatory agent. We hypothesized that combinations of PTX with other anti-inflammatory agents, the steroid dexamethasone (DEX) or the macrolide azithromycin (AZI), may exert broader, more profound and/or synergistic anti-inflammatory activity towards neonatal TLR- and inflammasome-mediated cytokine production. Methods Whole newborn and adult blood was treated with PTX (50–200 μM), DEX (10−10–10−7 M), or AZI (2.5–20 μM), alone or combined, and cultured with lipopolysaccharide (LPS) (TLR4 agonist), R848 (TLR7/8 agonist) or LPS/adenosine triphosphate (ATP) (inflammasome induction). Supernatant and intracellular cytokines, signaling molecules and mRNA were measured by multiplex assay, flow cytometry and real-time PCR. Drug interactions were assessed based on Loewe's additivity. Results PTX, DEX and AZI inhibited TLR- and/or inflammasome-mediated cytokine production in newborn and adult blood, whether added before, simultaneously or after TLR stimulation. PTX preferentially inhibited pro-inflammatory cytokines especially TNF. DEX inhibited IL-10 in newborn, and TNF, IL-1β, IL-6 and interferon-α in newborn and adult blood. AZI inhibited R848-induced TNF, IL-1β, IL-6 and IL-10, and LPS-induced IL-1β and IL-10. (PTX+DEX) synergistically decreased LPS- and LPS/ATP-induced TNF, IL-1β, and IL-6, and R848-induced IL-1β and interferon-α, while (PTX+AZI) synergistically decreased induction of TNF, IL-1β, and IL-6. Synergistic inhibition of TNF production by (PTX+DEX) was especially pronounced in newborn vs. adult blood and was accompanied by reduction of TNF mRNA and enhancement of IL10 mRNA. Conclusions Age, agent, and specific drug-drug combinations exert distinct anti-inflammatory effects towards TLR- and/or inflammasome-mediated cytokine production in human newborn blood in vitro. Synergistic combinations of PTX, DEX and AZI may offer benefit for prevention and/or treatment of neonatal inflammatory conditions while potentially limiting drug exposure and toxicity.

Cognitive impairment affects more than half of all individuals living with multiple sclerosis (MS). We hypothesized that training at home with an adaptive online cognitive training program would have greater cognitive benefit than ordinary computer games in cognitively-impaired adults with MS. This was a double-blind, randomized, active-placebo-controlled trial. Participants with MS were recruited through Stony Brook Medicine and randomly assigned to either the adaptive cognitive remediation (ACR) program or active control of ordinary computer games for 60 hours over 12 weeks. Training was remotely-supervised and delivered through a study-provided laptop computer. A computer generated, blocked stratification table prepared by statistician provided the randomization schedule and condition was assigned by a study technician. The primary outcome, administered by study psychometrician, was measured by change in a neuropsychological composite measure from baseline to study end. An intent-to-treat analysis was employed and missing primary outcome values were imputed via Markov Chain Monte Carlo method. Participants in the ACR (n = 74) vs. active control (n = 61) training program had significantly greater improvement in the primary outcome of cognitive functioning (mean change in composite z score±SD: 0·25±0·45 vs. 0·09±0·37, p = 0·03, estimated difference = 0·16 with 95% CI: 0·02–0·30), despite greater training time in the active control condition (mean±SD:56·9 ± 34·6 vs. 37·7 ±23 ·8 hours played, p = 0·006). This study provides Class I evidence that adaptive, computer-based cognitive remediation accessed from home can improve cognitive functioning in MS. This telerehabilitation approach allowed for rapid recruitment and high compliance, and can be readily applied to other neurological conditions associated with cognitive dysfunction. Trial Registration: Clinicaltrials.gov NCT02141386

Background Pregnant women with pulmonary hypertension ( PH ) are at risk for adverse cardiac outcomes, particularly at the time of labor and delivery. The purpose of this study is to define the impact of PH on pregnancy outcomes and the risk of major adverse cardiac events ( MACE ). Methods and Results The National Inpatient Sample was screened for hospital admissions of women delivering during the years 2003 to 2012. The primary outcome was MACE , a composite of death, cardiac arrest, cardiogenic shock, myocardial infarction, respiratory failure, arrhythmia, stroke, and embolic event. Data on 1519 patients with PH and 6 757 582 without heart disease or PH were available. There were 59.6% with isolated PH ; 10.7% with PH and congenital heart disease; 18.1% with PH and valvular heart disease; 3% with PH and valvular heart disease and congenital heart disease; 6.6% PH and cardiomyopathy; and 1.9% with PH and cardiomyopathy and valvular heart disease. Compared with women without heart disease or PH , women with PH experienced significantly higher MACE (24.8 versus 0.4%, P PH , the highest MACE was noted in women with the combination of PH and cardiomyopathy and valvular heart disease, and PH and cardiomyopathy, primarily because of heart failure and arrhythmia. Women with PH were significantly more likely to experience eclampsia syndromes, preterm delivery, and intrauterine fetal demise ( P PH subtype was significantly associated with MACE in multivariable analysis ( P Conclusions In a contemporary data set of pregnant women in the United States, PH was associated with an increase in MACE during the hospitalization for delivery, with an exceptionally elevated risk among women with associated cardiomyopathy.

The US Food and Drug Administration conducts on-site inspections and data audits through Bioresearch Monitoring program for assurance of the quality and integrity of data in the pre- and postapproval processes. It is important to inspect the study sites that are different compared with other sites in clinical studies and identify the problems related to those sites. Usually one cannot inspect all the sites in a clinical study because of limited resources, and statistical tools are needed to help in selecting sites for inspection. We propose two technical approaches, namely Fisher combination approach and likelihood ratio test (LRT) approach, for site selection, with each approach integrating the information obtained from a P value matrix. The proposed approaches produce site rankings, and the sites with highest rankings may be selected for inspection. The application of the approaches is demonstrated through a hypothetical data set reflecting the pattern of the real data in a premarket approval submission for a diagnostic device. The proposed methods are shown, through extensive simulations, to control false discovery rate, while maintaining good sensitivity. The proposed approaches will be useful for site selection process. However, limitations exist when only using the statistical approaches proposed here. In practice, investigators will select the site for inspection by considering the outputs from the statistical approaches along with other important factors. Future research topic is discussed to facilitate practical application of the approaches.

Cognitive impairment affects more than half of all individuals living with multiple sclerosis (MS). We hypothesized that training at home with an adaptive online cognitive training program would have greater cognitive benefit than ordinary computer games in cognitively-impaired adults with MS. This was a double-blind, randomized, active-placebo-controlled trial. Participants with MS were recruited through Stony Brook Medicine and randomly assigned to either the adaptive cognitive remediation (ACR) program or active control of ordinary computer games for 60 hours over 12 weeks. Training was remotely-supervised and delivered through a study-provided laptop computer. A computer generated, blocked stratification table prepared by statistician provided the randomization schedule and condition was assigned by a study technician. The primary outcome, administered by study psychometrician, was measured by change in a neuropsychological composite measure from baseline to study end. An intent-to-treat analysis was employed and missing primary outcome values were imputed via Markov Chain Monte Carlo method. Participants in the ACR (n = 74) vs. active control (n = 61) training program had significantly greater improvement in the primary outcome of cognitive functioning (mean change in composite z score±SD: 0·25±0·45 vs. 0·09±0·37, p = 0·03, estimated difference = 0·16 with 95% CI: 0·02–0·30), despite greater training time in the active control condition (mean±SD:56·9 ± 34·6 vs. 37·7 ±23 ·8 hours played, p = 0·006). This study provides Class I evidence that adaptive, computer-based cognitive remediation accessed from home can improve cognitive functioning in MS. This telerehabilitation approach allowed for rapid recruitment and high compliance, and can be readily applied to other neurological conditions associated with cognitive dysfunction. Trial Registration: Clinicaltrials.gov NCT02141386

Background: Cardiac arrest (CA) is associated with morbidity and mortality due to cerebral ischemia. We therefore tested the hypothesis that higher regional cerebral oxygenation (rSO2) during resuscitation is associated with improved return of spontaneous circulation (ROSC), survival and neurological outcomes at hospital discharge. We further examined the validity of rSO2 as a test to predict these outcomes. Methods: Multicenter prospective study of in-hospital CA (IHCA). Inclusion criteria: IHCA, age≥18 years, Prolonged CPR≥5 minutes. Patients were recruited consecutively during working hours between 08/2011-09/2014. Survival with a favorable neurological outcome was defined as a Cerebral Performance Category (CPC)1-2. Results: Among 504 IHCA events, 183 (36%) met inclusion criteria. Overall 62/183 (33.9%) achieved ROSC, while 13/183(7.1%) achieved CPC1-2 at discharge. Higher mean±SD rSO2 was associated with ROSC vs. no ROSC (51.8±11.2% vs. 40.9±12.3%) and CPC1-2 vs. CPC3-5 (56.1±10.0% vs. 43.8±12.8%), both P50% during CPR best predicted CPC1-2 (AUC=0.79: 95%CI:0.70-0.88). Specifically, ≥60% CPR time with rSO2>50% provided 77% sensitivity (95%CI:46%-95%), 72% specificity (95%CI:65%-79%) and 98% NPV (95%CI: 93%-100%) for CPC1-2. Conclusions: Cerebral oximetry allows real-time non-invasive cerebral oxygenation monitoring during CPR. Higher cerebral oxygenation during CPR is associated with ROSC and neurologically favorable survival to hospital discharge. Achieving higher rSO2 during resuscitation may optimize the chances of CA favorable outcomes.

Channelrhodospin-2 (ChR2), a light-sensitive ion channel, and its variants have emerged as new excitatory optogenetic tools not only in neuroscience, but also in other areas, including cardiac electrophysiology. An accurate quantitative model of ChR2 is necessary for in silico prediction of the response to optical stimulation in realistic tissue/organ settings. Such a model can guide the rational design of new ion channel functionality tailored to different cell types/tissues. Focusing on one of the most widely used ChR2 mutants (H134R) with enhanced current, we collected a comprehensive experimental data set of the response of this ion channel to different irradiances and voltages, and used these data to develop a model of ChR2 with empirically-derived voltage- and irradiance- dependence, where parameters were fine-tuned via simulated annealing optimization. This ChR2 model offers: 1) accurate inward rectification in the current-voltage response across irradiances; 2) empirically-derived voltage- and light-dependent kinetics (activation, deactivation and recovery from inactivation); and 3) accurate amplitude and morphology of the response across voltage and irradiance settings. Temperature-scaling factors (Q10) were derived and model kinetics was adjusted to physiological temperatures. Using optical action potential clamp, we experimentally validated model-predicted ChR2 behavior in guinea pig ventricular myocytes. The model was then incorporated in a variety of cardiac myocytes, including human ventricular, atrial and Purkinje cell models. We demonstrate the ability of ChR2 to trigger action potentials in human cardiomyocytes at relatively low light levels, as well as the differential response of these cells to light, with the Purkinje cells being most easily excitable and ventricular cells requiring the highest irradiance at all pulse durations. This new experimentally-validated ChR2 model will facilitate virtual experimentation in neural and cardiac optogenetics at the cell and organ level and provide guidance for the development of in vivo tools., Author Summary Optogenetics, the use of light-sensitive ion channels for stimulation of mammalian cells and tissues, offers specificity and superior precision of control compared to traditional chemical or electrical means of stimulation. In particular, Channelrhodospin-2 (ChR2), a light-sensitive ion channel, originally derived from algae, has found wide-spread application in neuroscience for controlled stimulation of different brain regions. More recently, this work was extended to other organs, including the heart, where it opens the possibility for a new generation of optical pacemakers. The development of new optogenetic tools that allow for more efficient optical stimulation can be guided by computational prediction of the response of different cells and tissues to light. In this report, we provide a new computational model of ChR2 that was empirically validated and can be inserted into different cell types – neurons or heart cells – for virtual optical stimulation and prediction of optimal light-delivery arrangements, minimum energy needs etc. Overall, virtual optogenetics can accelerate the development of new optical stimulation tools for better understanding and control of brain and heart function.

Nitric oxide (NO) has been discovered to be a potent vasodilator. Endogenous NO is produced by many cell types and is important in regulating basal vasomotor tone. Exogenous NO has recently been used very successfully to treat pulmonary hypertension in infants and children. In most cases, these patients receive simultaneous oxygen therapy. Unfortunately, there are few reports on the combined toxicity of NO and hyperoxia, either of which can be toxic alone. Together, the potential for the formation of peroxynitrite(ONOO˙) - an extremely reactive and toxic free radical - is increased. To directly test this potential toxicity, cultured human alveolar epithelial(A549) cells were grown in room air (control), hyperoxia (95% O2), 2 mM SNAP (S-nitroso-N-acetyl penicillamine - an NO donor) and hyperoxia + SNAP. Live cells were counted in each of the groups above daily for the next six days, and media and gasses were refreshed each day. Cells began to die in hyperoxia after 4 to 5 d, but cell counts were relatively unchanged in NO. However, cells exposed to both NO and hyperoxia began to die on day 2, and died rapidly thereafter. This cytotoxic effect was clearly synergistic, the death rate far exceeding any additive effect. Some cells were grown on cover slips for later immunocytochemistry for nitrotyrosine, which is a stable byproduct of peroxynitrite (which is too reactive to detect directly). Immunoreactive nitrotyrosine was most abundant only in cells exposed to NO + hyperoxia. Western blots indicate that a variety of proteins become nitrated under various conditions. However, a unique band appeared on blots only after culture in NO + hyperoxia. These experiments indicate that NO and hyperoxia have a synergistic cytotoxic effect on alveolar cells in culture, which is probably mediated by production of peroxynitrite.(Funded by grants from the NIH-NHLBI, ALA and Winthrop-University Hospital)