Search

Cross-validation (CV) is a resampling approach to evaluate machine learning models when sample size is limited. The number of all possible combinations of folds for the training data, known as CV rounds, are often very small in leave-one-out CV. Alternatively, Monte Carlo cross-validation (MCCV) can be performed with a flexible number of simulations when computational resources are feasible for a study with limited sample size. We conduct extensive simulation studies to compare accuracy between MCCV and CV with the same number of simulations for a study with binary outcome (e.g., disease progression or not). Accuracy of MCCV is generally higher than CV although the gain is small. They have similar performance when sample size is large. Meanwhile, MCCV is going to provide reliable performance metrics as the number of simulations increases. Two real examples are used to illustrate the comparison between MCCV and CV.

Purpose To determine the relationship of advanced pharmacy practice experience (APPE) grading schemes and other pharmacy program variables (ie, program age and funding) with pharmacy residency match rates. Summary A 12-question survey was disseminated to experiential administrators of pharmacy programs in October 2018. Respondents identified their program’s APPE grading scheme (pass/fail, letter grades, or other) and associated pros and cons. Responding programs were categorized by age and funding status. Survey responses were correlated with the American Society of Health-System Pharmacists residency match rates for 2016 through 2018. Data were analyzed using descriptive statistics and logistic regression models as well as by attributes via thematic analysis. Most pharmacy programs (62%) reported using letter grades for APPEs compared to pass/fail (30%) or other (8%) schemes. Pharmacy programs using pass/fail grading were more likely to have students match to postgraduate year 1 (PGY1) (P < 0.001) and postgraduate year 2 (PGY2) (P = 0.0074) residencies. Older pharmacy programs for each grading scheme were more likely to have higher match rates; however, for PGY1 match rates, older programs utilizing letter grades correlated to lower match rates than those utilizing pass/fail grading (P < 0.0001). Likewise, both public and private pharmacy programs using pass/fail grading had higher PGY1 match rates than those using letter grades (P = 0.0006 and P = 0.0014). Conclusion Pass/fail grading in APPEs does not hinder PGY1 or PGY2 residency placement compared to other grading schemes both overall and in combination with certain pharmacy program variables. Grading scheme strengths and weaknesses should be considered when deciding on optimal assessment strategies for APPEs and when evaluating candidates for residencies.

Introduction This study sought to assess the impact student pharmacist-led health outreach events had on participants in the Health Belief Model domains of perceived severity of disease, perceived barriers, perceived benefits, and self-efficacy. Methods This study was an observational pre‐/post-survey design conducted between January and December 2019 at student pharmacist-led community health outreach events in the Salt Lake City, Utah metropolitan area. The survey was developed partially based on the Health Belief Model and consisted of seven items with a five-point Likert scale (1 = strongly disagree to 5 = strongly agree). The survey was completed by participants before and immediately after engaging in the outreach event. Results A total of 31 participants across a variety of demographics and educational backgrounds completed the study. The surveys from the outreach events showed statistically significant increases in the participants' perceived severity of disease, perceived barriers, and self-efficacy. Perceived benefits was not significantly changed. Conclusions Student pharmacist-led community health outreach events significantly increase participants' perceived severity of disease, perceived barriers, and self-efficacy, which may indicate increased willingness to adopt the recommended health behavior.

Amyloid-$$\beta$$ β (A$$\beta$$ β ) is the target in many clinical trials for Alzheimer’s disease (AD). Preclinical AD patients are heterogeneous with regards to different backgrounds and diagnosis. Accurately predicting A$$\beta$$ β status of participants by using machine learning (ML) models based on easily accessible data, could improve the effectiveness of AD clinical trials. We will develop optimal ML models for each subpopulation stratified by sex and disease stages using sub scores from screening neurological tests. Data from the AD Neuroimaging Initiative (ADNI) were used to build the ML models, for three groups: individuals with significant memory concern, early mild cognitive impairment (MCI), and late MCI. Data were further separated into 6 groups by disease stage (3 levels) and sex (2 categories). The outcome was defined as the A$$\beta$$ β status confirmed by the PET imaging, and the features include demographic data, newly identified risk factors, screening tests, and the domain scores from screening tests. Monte Carlo simulation studies were used together with k-fold cross-validation technique to compute model performance metric. We also develop a new feature selection method based on the stochastic ordering to avoiding searching all possible combinations of features. Accuracy of the identified optimal model for SMC male was over 90% by using domain scores, and accuracy for LMCI female was above 86%. Domain scores can improve the ML model prediction as compared to the total scores. Accurate ML prediction models can identify the proper population for AD clinical trials.

Objectives: Determine, through video reviews, how often concussions occur in combat sport matches, what influence they have on the outcome, and how well non-physician personnel can be trained to recognize concussions.Methods: This is a retrospective video analysis by an 8-person panel of 60 professional fights (30 boxing and 30 mixed martial arts). Through video review, physician and non-physician personnel recorded details about each probable concussion and determined if and when they would have stopped the fight compared to the official stoppage time.Results: A concussion was recorded in 47/60 fights. The mean number of concussions per minute of fight time was 0.061 (0.047 for boxers and 0.085 for MMA). When stratifying by outcome of the bout, the mean number of concussions per minute for the winner was 0.010 compared to the loser at 0.111 concussions per minute. The fighter that sustained the first concussion ultimately lost 98% of the time. The physician and non-physician raters had high agreement regarding the number of concussions that occurred to each fighter per match. The physician raters judged that 24 of the 60 fights (11 boxing [37%]; 13 MMA [43%]) should have been stopped sooner than what occurred.Conclusion: Recognizing that the concussions often occur in combat sport matches, that the losing fighter almost always is concussed first and tends to sustain more concussions during the fight, along with the demonstration that non-physician personnel can be taught to recognize concussion, may guide policy changes that improve brain health in combat sports.

OBJECTIVE Repetitive head impacts (RHIs) in combat sports are associated with cognitive decline and brain volume reduction. While fighting style differences between boxers, mixed martial artists (MMAs), and martial artists (MAs) have resulted in a broader spectrum of injury, the effects of RHIs on MAs relative to other fighters have not yet been explored. This study aimed to determine a differential effect of fighting style on cognition and brain. SETTING A large outpatient medical center specializing in neurological care. PARTICIPANTS, DESIGN, AND MAIN MEASURES In total, 40 MAs, 188 boxers, and 279 MMAs were compared on baseline measures of subcortical regional brain volumes, after controlling for total brain volumes, and cognitive performance. RESULTS Significant differences between MAs, MMAs, and boxers were observed in subcortical brain structure volumes and cognitive measures. MMAs and MAs consistently had larger volumes and higher scores than boxers. Fighting style significantly moderated the relationship between the number of professional fights and the volumes of various subcortical brain structures and performance on a measure of processing speed at baseline. CONCLUSIONS Differences in RHIs across fighting styles may be of clinical significance. Exploring changes over time within the MA, boxer, and MMA cohorts may provide insight into longer-term discrepancies in subcortical regional brain volumes and cognitive functioning across fighting styles.

Sample size calculation based on normal approximations is often associated with the loss of statistical power for a single-arm trial with a time-to-event endpoint. Recently, Wu (2015) derived the exact variance for the one-sample log-rank test under the alternative and showed that a single-arm one-stage study based on exact variance often has power above the nominal level while the type I error rate is controlled. We extend this approach to a single-arm two-stage design by using exact variances of the one-sample log-rank test for the first stage and the two stages combined. The empirical power of the proposed two-stage optimal designs is often not guaranteed under a two-stage design setting, which could be due to the asymptotic bi-variate normal distribution used to estimate the joint distribution of the test statistics. We adjust the nominal power level in the design search to guarantee the simulated power of the identified optimal design being above the nominal level. The sample size and the study time savings of the proposed two-stage designs are substantial as compared to the one-stage design.

Multidrug-resistantTo assess the efficacy of eravacycline compared with best previously available therapy in adults with difficult-to-treat resistant (DTR)This was a retrospective study of adults hospitalized for pneumonia with DTRNinety-three patients were included, with 27 receiving eravacycline. Eravacycline was associated with higher 30-day mortality (33%Eravacycline-based combination therapy had similar outcomes to best previously available combination therapy for adults with DTR

Interval-censored data occur in a study where the exact event time of each participant is not observed but it is known to be within a certain time interval. Multiple tests were proposed for such data, including the logrank test by Sun, the proportional hazard test by Finkelstein, and the Wilcoxon-type test by Peto and Peto. We propose sample size calculations based on these tests for a parallel one-stage or two-stage design. When the proportional hazard assumption is met, the proportional hazard test and the logrank test need smaller sample sizes than the Wilcoxon-type test, and the sample size savings are substantial. But this trend is reversed when the proportional hazard assumption does not hold, and the sample size savings using the Wilcoxon-type test are sizable. An example from a lung cancer clinical trial is used to illustrate the application of the proposed sample size calculations.

Purpose Pharmacists report high levels of burnout. Mindfulness approaches have been demonstrated to have positive results in the general population and in other healthcare professions. However, limited studies have been performed evaluating mindfulness approaches in student pharmacists. The aim of this study was to evaluate the effectiveness of daily use of a mindfulness mobile application in improving student pharmacists’ perceived stress, burnout, and mindfulness. Methods This study was a randomized, longitudinal, waitlist-controlled trial. The intervention group was asked to meditate using the mindfulness application Headspace daily for at least 6 weeks. The waitlist control group was asked to abstain from using the application for the entire study. Stress, burnout, and mindfulness were assessed using validated survey instruments at baseline, 6 weeks, and 10 weeks. A secondary outcome was to assess the persistence of application use after the intervention period. Results Fifty-six participants completed the study. The intervention group reported significantly lower scores on stress and burnout at 6 weeks compared to the control group. The intervention group also reported significantly higher scores on mindfulness. The differences in stress, burnout, and mindfulness persisted at follow-up. The mean percentage of students in the intervention group who used the application each day was 90% over the intervention period and 62% over the follow-up period. Conclusion A mindfulness mobile application significantly improved student pharmacists’ stress, burnout, and mindfulness with daily use. Most participants continued to use the application for 4 weeks after the end of the intervention. Positive effects on stress and mindfulness persisted even with decreased use.

Objective Acute care physical therapists recommend discharge locations and services in part to help prevent falls during post-discharge recovery. Therapists may use standardized tests to inform their recommendation decisions, but evidence linking test scores with fall risk after discharge is lacking. The primary purpose of this study was to explore the associations between Tinetti Performance-Oriented Mobility Assessment (POMA) and Activity Measure for Post-Acute Care Inpatient Mobility Short Form (AM-PAC IMSF) scores and falls in the first 30 days after hospital discharge. Anticipating that agreement between therapist recommendations and discharge locations and services (discharge agreement), age, and sex could impact those associations, these factors were included in this investigation. Methods In this observational cohort study, 258 hospitalized patients consented to medical record data extraction and answered a phone survey 30 days after discharge to report whether they had experienced a fall since leaving the hospital. POMA and AM-PAC IMSF tests were administered for every patient. Participants’ age, sex, diagnosis, last POMA score, last AM-PAC IMSF score, physical therapist discharge recommendations, actual discharge location and services, discharge date, and phone number were collected from their medical records. Results When analyzed alone, higher POMA scores were associated with lower odds of falling, but the association was not significant after adjustment for other factors. Neither AM-PAC IMSF scores, age, nor sex were associated with falls. Discharge agreement, however, was associated with 59% lower odds of falling after adjustment for other factors. Conclusion Participants, who were discharged to the location with the services recommended by their physical therapist, were less likely to fall. Tinetti POMA and AM-PAC IMSF scores did not discriminate well participants who would fall. Impact Findings in this study inform those involved in discharge planning on the value of implementing physical therapist recommendations in reducing fall risk after hospital discharge. Lay Summary If physical therapist discharge recommendations are implemented, patients are less likely to fall during the month after hospital discharge. Balance and mobility test scores may provide therapists valuable information, but they are limited in their ability to identify who will fall after discharge.

Objective:To evaluate the sex differences in cognitive course over 4 years in Parkinson’s disease (PD) patients with and without mild cognitive impairment (MCI) compared to controls.Methods:Four-year longitudinal cognitive scores of 257 cognitively intact PD, 167 PD-MCI, and 140 controls from the Parkinson’s Progression Markers Initiative were included. Longitudinal scores of men and women, and PD with and without MCI were compared.Results:Women had better verbal memory, men had better visuospatial function. There was no interaction between sex, diagnostic group, and/or time (4-year follow-up period).Conclusions:Sex differences in cognitive course in de novo PD are similar to healthy aging. Cognitive decline rates in PD with and without MCI are similar for the first 4 years of PD.

It has long been established that fighting sports such as boxing and mixed martial arts can lead to head injury. Prior work from this group on the Professional Fighters Brain Health Study found that exposure to repetitive head impacts is associated with lower brain volumes and decreased processing speed in fighters. Current and previously licensed professional fighters were recruited, divided into active and retired cohorts, and matched with a control group that had no prior experience in sports with likely head trauma. This study examined the relationship between age of first exposure (AFE) to fighting sports and brain structure (MRI regional volume), cognitive performance (CNS Vital Signs, iComet C3), and clinical neuropsychiatric symptoms (PHQ-9, Barratt Impulsiveness Scale). Brain MRI data showed significant correlations between earlier AFE and smaller bilateral hippocampal and posterior corpus callosum volumes for both retired and active fighters. Earlier AFE in active fighters was correlated with decreased processing speed and decreased psychomotor speed. Retired fighters showed a correlation between earlier AFE and higher measures of depression and impulsivity. Overall, the results help to inform clinicians, governing bodies, parents, and athletes of the risks associated with beginning to compete in fighting sports at a young age.

More than half of the patients with Alzheimer’s disease (AD) have comorbidities including TDP-43 and Lewy bodies, which are also associated with frontotemporal lobar degeneration and dementia with Lewy bodies, respectively. These comorbidities may help explain the overlapping neuropsychiatric symptoms between AD and other dementias. Data on 221 AD patients with Neuropsychiatric Inventory-Questionnaire were obtained from the National Alzheimer’s Coordinating Center. TDP-43 was associated with aberrant motor activity, whereas Lewy bodies were associated with anxiety, irritability, sleep behavior, and appetite problems. The associations between these comorbidities and neuropsychiatric symptoms were more significant for patients with sparse diffuse plaques.

Gallbladder cancer (GBC) is a rare, poor-prognosis cancer with unique demographics, comorbidities and a paucity of research. This study investigated inpatient palliative care and its associations with demographics, comorbidities (e.g., obesity), length of stay and hospital charges in GBC in US hospitals (2007-2016).Data were extracted from the National Inpatient Sample (NIS) database that contains deidentified clinical and nonclinical information for each hospitalisation. Inpatient palliative care utilisation was identified using the International Classification of Diseases (ICD-9 and ICD-10) codes (V66.7 and Z51.5). Generalised regression analysis was conducted with adjustment for variations in predictors.Of the 4921 reported GBC hospitalizations, only 10.3% encountered palliative care. Palliative care was associated with reduced hospital charges by $12,405 per hospitalisation (P 0.0001) with no change in length of stay. Palliative care utilisation increased over time (P = 0.004). It was associated with age80 years, with more severe disease, and in-hospital death (P 0.0001). Obesity had a negative association with palliative care utilisation (P = 0.0029).Our novel study found that obese people were less likely to use palliative care services in GBC. Interventions are needed to increase palliative care consultation in GBC patients, particularly in obese patients.

Purpose To examine the financial impact of automatic formulary substitution of nebulization solutions for pressurized metered dose inhalers and dry powder inhalers and the effect of the automatic substitution initiative on respiratory care practitioner (RCP) workload at a community hospital. Methods A retrospective observational study was conducted in a 326-bed nonacademic community hospital. Adult patients who received respiratory medications and had an inpatient stay, were admitted for observation, or had an emergency room visit from December 2016 through February 2017 (the control group) or from December 2017 through February 2018 (the study group) were included in the analysis. The primary outcomes were the cost of respiratory medications per hospital stay and the number of RCP visits per hospital stay. The secondary outcome was the cost of wasted doses per hospital stay. Results A total of 3,766 patients were included in the study: 2,030 in the study group and 1,736 in the control group. The mean cost of respiratory medications per hospital stay was significantly lower in the study group vs the control group ($13.29 vs $36.48, P < 0.001). The mean number of RCP visits per hospital stay was also statistically lower in the study group vs the control group (11.6 vs 12.9, P = 0.04). The mean cost of wasted doses was significantly lower in study group vs the control group ($0.25 vs $22.91, P < 0.001). Conclusion Automatic formulary substitution of nebulization solutions for inhaler medications significantly decreased medication costs without increasing the average number of RCP visits per hospital stay.

Background Guidelines for pneumonia recommend empiric dual antipseudomonal therapy in patients with specific risk factors. However, there is lack of consensus on when to use dual antipseudomonal therapy as the recommendations are rated as weak, based on low-quality evidence. Objectives The objectives of this study were to develop combination antibiograms to assess the susceptibility of Pseudomonas aeruginosa (P. aeruginosa) in respiratory cultures to combinations of empiric antibiotics and to use combination antibiograms to delineate the impact of specific risk factors for which guidelines recommend dual antipseudomonal therapy. Methods A retrospective cohort study was conducted of adults hospitalized with pneumonia with positive respiratory cultures for P. aeruginosa between September 2014 and September 2018. Data collected included demographics, antimicrobial susceptibility results, and risk factors for which guidelines recommend dual antipseudomonal therapy. Combination antibiograms were developed and logistic regression was performed to identify risk factors for nonsusceptibility to beta-lactams. Results Eight hundred nineteen patients were included and 72% received antibiotics. Beta-lactam susceptibility ranged from 58% to 69% and addition of a fluoroquinolone or aminoglycoside resulted in statistically significant increases in susceptibility. However, only addition of tobramycin or amikacin provided susceptibility rates approaching or exceeding 90% stratified by pneumonia type and risk factors. Presence of guideline-based risk factors generally resulted in reduced susceptibility rates. Logistic regression identified three risk factors associated with nonsusceptibility to beta-lactams: intravenous antibiotics in the previous 90 days, nursing home residence, and mechanical ventilation at onset. The cumulative presence of each additional risk factor affected beta-lactam susceptibility rates, which were 93% in the absence of any risk factors and 39% when all three risk factors co-existed. Conclusions Risk factors necessitating dual antipseudomonal therapy for pneumonia should be locally validated. When dual antipseudomonal therapy is indicated, tobramycin or amikacin have the best likelihood of providing adequate in vitro activity.

Background The etiology of freezing of gait in Parkinson’s disease (PD) is yet to be clarified. Non-motor risk factors including cognitive impairment, sleep disturbance and mood disorders have been shown in freezing of gait. Research question We aimed to determine the predictive value of non-motor features in freezing of gait development. Methods Data were obtained from the Parkinson’s Progression Markers Initiative. Fifty PD patients with self-reported freezing of gait, and 50 PD patients without freezing of gait at the fourth year visit were included. Groups were matched for Movement Disorders Society-Unified Parkinson’s Disease Rating Scale Part III scores. Several cognitive and non-cognitive tests were used for non-motor features at baseline and over time. Executive function, visuospatial function, processing speed, learning and memory tests were used for cognition. Non-cognitive tests included sleepiness, REM sleep behavior disorder, depression and anxiety scales. Results Patients with freezing of gait had higher scores on sleepiness, REM sleep behavior disorder, depression and anxiety scales. However, predictor model analysis revealed that baseline processing speed, learning and sleepiness scores were predictive of self-reported freezing of gait development over time. Significance Our findings suggest that specific cognitive deficits and sleep disorders are predictive of future freezing of gait. These features may be helpful in identifying underlying networks in freezing of gait and should be further investigated with neuroimaging studies.

Background Meta-analysis provides a useful statistical tool to effectively estimate treatment effect from multiple studies. When the outcome is binary and it is rare (e.g., safety data in clinical trials), the traditionally used methods may have unsatisfactory performance. Methods We propose using importance sampling to compute confidence intervals for risk difference in meta-analysis with rare events. The proposed intervals are not exact, but they often have the coverage probabilities close to the nominal level. We compare the proposed accurate intervals with the existing intervals from the fixed- or random-effects models and the interval by Tian et al. (2009). Results We conduct extensive simulation studies to compare them with regards to coverage probability and average length, when data are simulated under the homogeneity or heterogeneity assumption of study effects. Conclusions The proposed accurate interval based on the random-effects model for sample space ordering generally has satisfactory performance under the heterogeneity assumption, while the traditionally used interval based on the fixed-effects model works well when the studies are homogeneous.

The aim of this study is to evaluate longitudinal change in plasma neurofilament light (NF-L) and tau levels in relationship to clinical and radiological measures in professional fighters. Participants (active and retired professional fighters and control group) underwent annual blood sampling, 3-Tesla magnetic resonance imaging (MRI) brain imaging, computerized cognitive testing, and assessment of exposure to traumatic brain injury. Plasma tau and NF-L concentrations were measured using Simoa assays. Multiple linear regression models were used to compare the difference across groups in regard to baseline measurements, whereas mixed linear models was used for the longitudinal data with multiple measurements for each participant. Plasma samples were available on 471 participants. Baseline NF-L measures differed across groups (F3,393 = 6.99; p = 0.0001), with the active boxers having the highest levels. Higher NF-L levels at baseline were correlated with lower baseline MRI regional volumes and lower cognitive scores. The number of sparring rounds completed by the active fighters was correlated with NF-L (95% confidence interval, 0.0116-0.4053; p = 0.0381), but not tau, levels. Among 126 subjects having multiple yearly samples, there was a significant difference in average yearly percentage change in tau across groups (F3,83 = 3.87; p = 0.0121). We conclude that plasma NF-L and tau behave differently in a group of active and retired fighters; NF-L better reflects acute exposure whereas the role of plasma tau levels in signifying chronic change in brain structure over time requires further study.

To compare a new binary diagnostic test with the gold standard, sensitivity and specificity are the two common measurements used to evaluate the new test. When not all the patients are verified by the gold standard due to time, budget, or cost considerations, several approaches have been proposed to compute sample size for such studies under the assumption of missing completely at random. However, the majority of them are based on asymptotic approaches that generally do not guarantee the type I and II error rates, and the remaining approaches use exact binomial distributions in sample size calculation but only the verified samples are used. In this article, for a study with verification bias, we propose computing exact sample sizes by using all the samples. The proposed approach is compared with the existing exact approach that compute sample size by using verified samples only, and the results show that the proposed approach requires fewer participants than the competitor.

This research was motivated by a clinical trial design for a cognitive study. The pilot study was a matched-pairs design where some data are missing, specifically the missing data coming at the end of the study. Existing approaches to determine sample size are all based on asymptotic approaches (e.g., the generalized estimating equation (GEE) approach). When the sample size in a clinical trial is small to medium, these asymptotic approaches may not be appropriate for use due to the unsatisfactory Type I and II error rates. For this reason, we consider the exact unconditional approach to compute the sample size for a matched-pairs study with incomplete data. Recommendations are made for each possible missingness pattern by comparing the exact sample sizes based on three commonly used test statistics, with the existing sample size calculation based on the GEE approach. An example from a real surgeon-reviewers study is used to illustrate the application of the exact sample size calculation in study designs.

Repeated measures are increasingly collected in a study to investigate the trajectory of measures over time. One of the first research questions is to determine the correlation between two measures. The following five methods for correlation calculation are compared: (1) Pearson correlation; (2) correlation of subject means; (3) partial correlation for subject effect; (4) partial correlation for visit effect; and (5) a mixed model approach. Pearson correlation coefficient is traditionally used in a cross-sectional study. Pearson correlation is close to the correlations computed from mixed-effects models that consider the correlation structure, but Pearson correlation may not be theoretically appropriate in a repeated-measure study as it ignores the correlation of the outcomes from multiple visits within the same subject. We compare these methods with regard to the average of correlation and the mean squared error. In general, correlation under the mixed-effects model with the compound symmetric structure is recommended as its correlation is close to the nominal level with small mean square error.

INTRODUCTION: Cognitive decline and mood symptoms are common in Parkinson’s disease (PD). Reductions in striatal dopaminergic binding have been associated with worse cognition and mood. We investigated whether this association persists throughout the disease progression in newly diagnosed PD. METHODS: Four-year data from Parkinson Progression Markers Initiative (PPMI) were used. Groups consisted of left and right limb dominantly affected PD patients, and controls. Longitudinal relationships between cognition, mood and striatal binding ratios were assessed by repeated measures correlations. RESULTS: Reduced binding was associated with general cognitive decline in controls; reduced processing speed and increased mood symptoms in PD. Anxiety was associated with striatum only in left limb dominantly affected PD. Dominantly affected limb side did not impact striatum and cognition association. CONCLUSION: There are longitudinal associations between striatum, processing speed and anxiety. Dopamine transporter availability imaging may have some prognostic value for cognition and mood in PD.

Objective Depression, neuropathology, and cognitive decline are commonly observed with repetitive head injuries (RHIs). We examined whether in boxers (a) clinically significant depression is associated with structural brain changes and cognition; (b) minimal symptoms of depression moderate the relations among RHI and brain volumes and cognition; and (c) baseline depression is associated with longitudinal cognitive changes. Setting Clinical Research Center. Participants A total of 205 male professional boxers. Design Cross-sectional and longitudinal (subsample: n = 45; first visit to follow-up range = 1-6 years; mean = 2.61 years). Main measures Patient Health Questionnaire-9 depression; CNS Vital Signs cognitive battery; brain imaging. Results Clinically significant depression was associated with smaller regional volumes in insula, cingulate, orbitofrontal cortex, thalami, and middle corpus-callosum subregions; and with poorer verbal memory and psychomotor speed performance. Depression symptoms moderated the relations between RHI and bilateral thalami, left hippocampus, left medial orbitofrontal cortex, and bilateral insula volumes; but not cognition. Baseline depression was associated with poorer psychomotor speed and reaction time longitudinally and improved verbal memory performance longitudinally. Conclusion Clinical depression is associated with volumetric and cognitive changes occasioning RHI exposure, and even minimal depressive symptoms may moderate the relations between exposure and brain volumes in key regions. Longitudinally, there is preliminary evidence that depression precedes cognitive changes.

In an agreement test between two raters with binary endpoints, existing methods for sample size calculation are always based on asymptotic approaches that use limiting distributions of a test statistic under null and alternative hypotheses. These calculated sample sizes may be not reliable due to the unsatisfactory type I error control of asymptotic approaches. We propose a new sample size calculation based on exact approaches which control for the type I error rate. The two exact approaches are considered: one approach based on maximization and the other based on estimation and maximization. We found that the latter approach is generally more powerful than the one based on maximization. Therefore, we present the sample size calculation based on estimation and maximization. A real example from a clinical trial to diagnose low back pain of patients is used to illustrate the two exact testing procedures and sample size determination.

Background The underlying mechanisms for increased osteopenia and fracture rates in patients with diabetes are not well understood, but may relate to chronic systemic inflammation. We assessed the effect of treating periodontal disease (POD), a cause of chronic inflammation, on inflammatory and bone turnover markers in patients with diabetes. Materials and Methods Using an investigator-administered questionnaire, we screened a cross-section of patients presenting for routine outpatient diabetes care. We recruited 22 subjects with POD. Inflammatory and bone turnover markers were measured at baseline and 3 months following POD treatment (scaling, root planing and subantimicrobial dose doxycycline). Results There were nonsignificant reductions in high-sensitivity C-reactive protein (6.34–5.52 mg/L, P = 0.626) and tumor necrosis factor-alpha (10.37–10.01 pg/mL, P = 0.617). There were nonsignificant increases in urinary C-terminal telopeptide (85.50–90.23 pg/mL, P = 0.684) and bone-specific alkaline phosphatase (7.45–8.79 pg/mL, P = 0.074). Patients with >90% adherence with doxycycline were 6.4 times more likely to experience reduction in tumor necrosis factor-alpha ( P = 0.021) and 2.8 times more likely to experience reductions in high-sensitivity C-reactive protein ( P = 0.133). Conclusions Treatment of POD in patients with diabetes resulted in nonsignificant lowering of inflammatory markers and nonsignificant increase in bone turnover markers. However, adherence to doxycycline therapy resulted in better treatment effects.

ObjectiveThis study tests the hypothesis that certain MRI-based regional brain volumes will show reductions over time in a cohort exposed to repetitive head impacts (RHI).MethodsParticipants were drawn from the Professional Fighters Brain Health Study, a longitudinal observational study of professional fighters and controls. Participants underwent annual 3T brain MRI, computerized cognitive testing, and blood sampling for determination of neurofilament light (NfL) and tau levels. Yearly change in regional brain volume was calculated for several predetermined cortical and subcortical brain volumes and the relationship with NfL and tau levels determined.ResultsA total of 204 participants who had at least 2 assessments were included in the analyses. Compared to controls, the active boxers had an average yearly rate of decline in volumes of the left thalamus (102.3 mm3/y [p = 0.0004], mid anterior corpus callosum (10.2 mm3/y [p = 0.018]), and central corpus callosum (16.5 mm3/y [p = 3/y [p = 0.002]) and right (30.6 mm3/y [p = 0.008]) amygdala and right hippocampus (33.5 mm3/y [p = 0.01]). Higher baseline NfL levels were associated with greater volumetric decline in left hippocampus and mid anterior corpus callosum.ConclusionVolumetric loss in different brain regions may reflect different pathologic processes at different times among individuals exposed to RHI.

Objectives To examine national trends and contributing factors of cannabis-associated emergency department visits in the United States. Methods This pooled serial cross-sectional study used a hierarchical multivariable analysis on emergency department visit adjusting for year, patient and hospital characteristics. We analyzed 2006 to 2014 National Emergency Department Sample data that identified cannabis-associated emergency department visits among patients aged 12 years or older (n = 265,128). Results Cannabis-associated emergency department visits per 100,000 emergency department discharges increased monotonically (annually by 7%). As compared with privately insured patients, Medicare, and Medicaid, uninsured patients were over 40% more likely to visit emergency department. The age group 12 to 17 had the highest risk of emergency department visits and the risk monotonically declined as the age increased. Hospitals in the South region showed the highest cannabis-associated emergency department utilization, yet trends of cannabis-associated emergency department visits increased in the West region from 15.4% to 26% over time. Conclusions Cannabis-associated emergency department visits increase monotonically over time. Although vulnerable persons were identified, additional policy or regional factors should explore risks of emergency department visits associated with cannabis use.

Background Survival endpoint is frequently used in early phase clinical trials as the primary endpoint to assess the activity of a new treatment. Existing two-stage optimal designs with survival endpoint either over estimate the sample size or compute power outside the alternative hypothesis space. Methods We propose a new single-arm two-stage optimal design with survival endpoint by using the one-sample log rank test based on exact variance estimates. This proposed design with survival endpoint is analogous to Simon’s two-stage design with binary endpoint, having restricted follow-up. Results We compare the proposed design with the existing two-stage designs, including the two-stage design with survival endpoint based on the nonparametric Nelson-Aalen estimate, and Simon’s two-stage designs with or without interim accrual. The new design always performs better than these competitors with regards to the expected total study length, and requires a smaller expected sample size than Simon’s design with interim accrual. Conclusions The proposed two-stage minimax and optimal designs with survival endpoint are recommended for use in practice to shorten the study length of clinical trials.

We examined moderation effects of sex and diagnosis on the effect of positive florbetapir positron emission tomography (PET) amyloid-β (Aβ) scan (A+) on hippocampus subfield volumes in 526 normal control (NC) and early mild cognitive impairment (eMCI) participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI2; ADNI-GO). Regression moderation models showed that women- but not men- with NC designation did not show reduced subiculum volumes despite A+. At the eMCI stage, A+ was detrimental across sexes. Findings were significant while accounting for the effects of age, cognition at screening, education, and APOE4 carrier status. These findings suggest that women with A+ have early neural resistance to Alzheimer's disease-related amyloid burden.

In January 2014, Nevada became 1 of the 32 states that have expanded Medicaid under the Affordable Care Act. As a result of the expansion, 276,400 additional Nevada residents received Medicaid insurance. The objectives of this paper were to examine the impact of Nevada's Medicaid expansion on changes in rates of hospital admissions for ambulatory care-sensitive conditions (ACSCs), which are potentially preventable with good access to outpatient medical care, and to examine the racial/ethnic disparities in such rates.We used complete inpatient discharge data (for the years 2012, 2013, and 2014, and the first 3 quarters of 2015) from all nonfederal acute care community hospitals in Nevada.We employed pooled cross-sectional design with a difference-in-differences approach to identify overall and race/ethnicity-specific changes in admissions for ACSCs, adjusted for secular trends unrelated to expansion. We examined admissions for ACSCs among adults aged 18 to 64 years (those most likely to have been affected by the reform) admitted for overall, acute, and chronic ACSC composites in the 24 months before and 21 months after the date on which expansion was implemented.After adjusting for confounders, we found that Hispanic patients with Medicaid were more likely to be admitted for ACSCs after Nevada's Medicaid expansion (overall quality composite: odds ratio [OR], 1.20; P = .05; chronic quality composite: OR, 1.34; P = .02).This analysis provides evidence that Medicaid expansion may have limited potential to reduce the disparities in rates of hospital admissions for ACSCs. In Nevada, additional efforts might be needed to improve access to outpatient care and reduce preventable admissions.

BACKGROUND: Disease-modifying therapies are urgently needed for the treatment of Alzheimer’s disease (AD). The European Union/United States (EU/US) Task Force represents a broad range of stakeholders including biopharma industry personnel, academicians, and regulatory authorities. OBJECTIVES: The EU/US Task Force represents a community of knowledgeable individuals who can inform views of evidence supporting disease modification and the development of disease-modifying therapies (DMTs). We queried their attitudes toward clinical trial design and biomarkers in support of DMTs. DESIGN/SETTING/PARTICIANTS: A survey of members of the EU/US Alzheimer’s Disease Task Force was conducted. Ninety-three members (87%) responded. The details were analyzed to understand what clinical trial design and biomarker data support disease modification. MEASUREMENTS/RESULTS/CONCLUSIONS: Task Force members favored the parallel group design compared to delayed start or staggered withdrawal clinical trial designs to support disease modification. Amyloid biomarkers were regarded as providing mild support for disease modification while tau biomarkers were regarded as providing moderate support. Combinations of biomarkers, particularly combinations of tau and neurodegeneration, were regarded as providing moderate to marked support for disease modification and combinations of all three classes of biomarkers were regarded by a majority as providing marked support for disease modification. Task Force members considered that evidence derived from clinical trials and biomarkers supports clinical meaningfulness of an intervention, and when combined with a single clinical trial outcome, nearly all regarded the clinical trial design or biomarker evidence as supportive of disease modification. A minority considered biomarker evidence by itself as indicative of disease modification in prevention trials. Levels of evidence (A,B,C) were constructed based on these observations. CONCLUSION: The survey indicates the view of knowledgeable stakeholders regarding evidence derived from clinical trial design and biomarkers in support of disease modification. Results of this survey can assist in designing clinical trials of DMTs.

In Alzheimer’s disease (AD), association of cognition with disease biomarkers is important for accurate diagnosis, prognosis and staging. We studied the value of cerebrospinal fluid (CSF), cortical thickness (CT), and volume (V) measures (in isolation & combination) to predict cognitive ability, as well as cognitive status, in a cross-sectional study of data from Alzheimer’s Disease Neuroimaging Initiative (ADNI). Cognitive status was measured by Mini Mental State Exam (MMSE). Results show that combining biomarkers allows more accurate AD diagnosis. Specifically, combining CSF, CT, and V measures seems promising. In isolation, CSF levels show significant but weak associations with MMSE. Aβ 1– 42 is associated with Mild Cognitive Impairment. CT and V measures of hippocampus and entorhinal cortex are strongly associated with Alzheimer ‘s Disease diagnosis and with ruling out the disease.

Gaussian network model (GNM), regarded as the simplest and most representative coarse-grained model, has been widely adopted to analyze and reveal protein dynamics and functions. Designing a variation of the classical GNM, by defining a new Kirchhoff matrix, is the way to improve the residue flexibility modeling. We combined information arising from local relative solvent accessibility (RSA) between two residues into the Kirchhoff matrix of the parameter-free GNM. The undetermined parameters in the new Kirchhoff matrix were estimated by using particle swarm optimization. The usage of RSA was motivated by the fact that our previous work using RSA based linear regression model resulted out higher prediction quality of the residue flexibility when compared with the classical GNM and the parameter free GNM. Computational experiments, conducted based on one training dataset, two independent datasets and one additional small set derived by molecular dynamics simulations, demonstrated that the average correlation coefficients of the proposed RSA based parameter-free GNM, called RpfGNM, were significantly increased when compared with the parameter-free GNM. Our empirical results indicated that a variation of the classical GNMs by combining other protein structural properties is an attractive way to improve the quality of flexibility modeling.

Background Recently, several adaptive one-arm two-stage designs have been developed by fully using the information from previous stages to reduce the expected sample size in clinical trials with binary endpoints as primary outcome. It is important to compute exact confidence limits for these studies. Methods In this article, we propose three new one-sided limits by ordering the sample space based on p-value, average response rate at each stage, and asymptotic lower limit, as compared to another three existing sample size ordering approaches based on average response rate. Among the three proposed approaches, the one based on the average response rate at each stage is not exact, and the remaining two approaches are exact with the coverage probability guaranteed. Results We compare these exact intervals by using the two commonly used criteria: simple average length and expected length. The existing three approaches based on average response rate have similar performance, and they have shorter expected lengths than the two proposed exact approaches although the gain is small, while this trend is reversed under the simple average criterion. Conclusions We would recommend the two exact proposed approaches based on p-value and asymptotic lower limit under the simple average length criterion, and the approach based on average response rate under the expected length criterion.

Objective: To examine the association between patient race/ethnicity, insurance status, and their interaction with patient safety indicators among hospitalized patients. Methods: Cross-sectional study was conducted. Data were extracted from the 2009 National Inpatient Sample. A total of 3,052,268 patient safety indicator-related discharges were identified. Dependent variables were 11 patient safety indicators (PSI) whereas independent variables included race/ethnicity and insurance status. Results: As compared with White patients, African American patients were more likely to experience pressure ulcer, postoperative hemorrhage or hematoma, and post-operative pulmonary embolism (PE) or deep vein thrombosis (DVE); Asian/Pacific Islander patients were more likely to experience pressure ulcer, post-operative PE or DVT, and two obstetric care PSIs; whereas Hispanic/Latino patients were more likely to experience post-operative physiometabolic derangement and accidental puncture/ laceration. As compared with patients with private insurance, Medicaid patients were more likely to experience pressure ulcer, post-operative physiological metabolic derangement, post-operative PE or DVT, post-operative respiratory failure, post-operative wound dehiscence, and death among surgeries. However, both obstetric care PSIs showed that African Americans, Hispanics, and uninsured patients were less likely to incur them in comparison with their respective counterparts. Furthermore, strong interactive effects between African American and Medicaid on PSIs were detected. Conclusions: Although mixed findings in disparities in PSIs were observed in our study, Asian/Pacific Islander patients and Medicaid patients seem to be the most vulnerable. Further, interactive effects between African American and Medicaid indicate that poverty may be a key factor related to disparities in health care. Future research is merited to identify underlying factors that are related to PSIs among Asian/Pacific Islander patients. Strategies are needed to improve PSIs among Medicaid patients, especially during the current Medicaid program expansion due to the implementation of the Affordable Care Act. Ethn Dis. 2016; 26(3):443-452; doi:10.18865/ed.26.3.443

We consider two exact unconditional procedures to test the difference between two multinomials with ordered categorical data. Exact unconditional procedures are compared to other approaches based on the Wilcoxon mid-rank test and the proportional odds model. We use a real example from an arthritis pain study to illustrate the various test procedures and provide an extensive numerical study to compare procedures with regards to type I error rates and power under the unconditional framework. The exact unconditional procedure based on estimation followed by maximization is generally more powerful than other procedures, and is therefore recommended for use in practice.

The activity of a new treatment in clinical trials with binary endpoints can be assessed by comparing the observed response rate to the target response rate. Traditionally, a one-sided hypothesis is used to make statistical inference, and the actual Type I error rate has to be computed over the parameter space of the null hypothesis. The monotonicity property is a fundamental property that guarantees the actual Type I error rate occurring at the boundary. One-arm two-stage designs are considered in this article. We theoretically proved this important property when the final threshold value of a design is less than the first-stage sample size together with another weak condition being satisfied. The method used in this article may finally lead to the final complete proof of this property in the future. We also numerically proved that the monotonicity property is satisfied for designs with the first-stage and the second-stage sample sizes from 10 to 100.

In ophthalmologic studies, measurements obtained from both eyes of an individual are often highly correlated. Ignoring the correlation could lead to incorrect inferences. An asymptotic method was proposed by Tang and others (2008) for testing equality of proportions between two groups under Rosner's model. In this article, we investigate three testing procedures for general g ≥ 2 groups. Our simulation results show the score testing procedure usually produces satisfactory type I error control and has reasonable power. The three test procedures get closer when sample size becomes larger. Examples from ophthalmologic studies are used to illustrate our proposed methods.

In historical clinical trials, the sample size and the number of success in the control group are often considered as given. The traditional method for sample size calculation is based on an asymptotic approach developed by Makuch and Simon (1980). Exact unconditional approaches may be considered as alternative to control for the type I error rate where the asymptotic approach may fail to do so. We provide the sample size calculation using an efficient exact unconditional testing procedure based on estimation and maximization. The sample size using the exact unconditional approach based on estimation and maximization is generally smaller than those based on the other approaches.

Sensitivity and specificity are often used to assess the performance of a diagnostic test with binary outcomes. Wald-type test statistics have been proposed for testing sensitivity and specificity individually. In the presence of a gold standard, simultaneous comparison between two diagnostic tests for noninferiority of sensitivity and specificity based on an asymptotic approach has been studied by Chen et al. (2003). However, the asymptotic approach may suffer from unsatisfactory type I error control as observed from many studies, especially in small to medium sample settings. In this paper, we compare three unconditional approaches for simultaneously testing sensitivity and specificity. They are approaches based on estimation, maximization, and a combination of estimation and maximization. Although the estimation approach does not guarantee type I error, it has satisfactory performance with regard to type I error control. The other two unconditional approaches are exact. The approach based on estimation and maximization is generally more powerful than the approach based on maximization.

This research is motivated by one of our survey studies to assess the potential influence of introducing zebra mussels to the Lake Mead National Recreation Area, Nevada. One research question in this study is to investigate the association between the boating activity type and the awareness of zebra mussels. A chi-squared test is often used for testing independence between two factors with nominal levels. When the null hypothesis of independence between two factors is rejected, we are often left wondering where does the significance come from. Cell residuals, including standardized residuals and adjusted residuals, are traditionally used in testing for cell significance, which is often known as a post hoc test after a statistically significant chi-squared test. In practice, the limiting distributions of these residuals are utilized for statistical inference. However, they may lead to different conclusions based on the calculated p-values, and their p-values could be over- o6r under-estimated due to the unsatisfactory performance of asymptotic approaches with regards to type I error control. In this article, we propose new exact p-values by using Fisher's approach based on three commonly used test statistics to order the sample space. We theoretically prove that the proposed new exact p-values based on these test statistics are the same. Based on our extensive simulation studies, we show that the existing asymptotic approach based on adjusted residual is often more likely to reject the null hypothesis as compared to the exact approach due to the inflated family-wise error rates as observed. We would recommend the proposed exact p-value for use in practice as a valuable post hoc analysis technique for chi-squared analysis.

Objective. To analyze the modifiable predictors of institution-wide residency match rates. Methods. This was a retrospective analysis of colleges and schools of pharmacy data and school-wide PGY-1 pharmacy residency match rates for 2013 through 2015. Independent variables included NAPLEX passing rates, history of ACPE probation, NIH funding, academic health center affiliation, dual-degree availability, program length, admit-to-applicant ratio, class size, tuition, student-driven research, clinically focused academic tracks, residency affiliation, U.S. News & World Report rankings, and minority enrollment. Results. In a repeated measures model, predictors of match results were NAPLEX pass rate, class size, academic health center affiliation, admit-to-applicant ratio, U.S. News & World Report rankings, and minority enrollment. Conclusion. Indicators of student achievement, college/school reputation, affiliations, and class demographics were significant predictors of institution-wide residency match rates. Further research is needed to understand how changes in these factors may influence overall match rates.

For comparison of proportions, there are three commonly used measurements: the difference, the relative risk, and the odds ratio. Significant effort has been spent on exact confidence intervals for the difference. In this article, we focus on the relative risk and the odds ratio when data are collected from a matched-pairs design or a two-arm independent binomial experiment. Exact one-sided and two-sided confidence intervals are proposed for each configuration of two measurements and two types of data. The one-sided intervals are constructed using an inductive order, they are the smallest under the order, and are admissible under the set inclusion criterion. The two-sided intervals are the intersection of two one-sided intervals. R codes are developed to implement the intervals. Supplementary materials for this article are available online.

Tests for trend are important in a number of scientific fields when trends associated with binary variables are of interest. Implementing the standard Cochran–Armitage trend test requires an arbitrary choice of scores assigned to represent the grouping variable. Bartholomew proposed a test for qualitatively ordered samples using asymptotic critical values, but type I error control can be problematic in finite samples. To our knowledge, use of the exact probability distribution has not been explored, and we study its use in the present paper. Specifically we consider an approach based on conditioning on both sets of marginal totals and three unconditional approaches where only the marginal totals corresponding to the group sample sizes are treated as fixed. While slightly conservative, all four tests are guaranteed to have actual type I error rates below the nominal level. The unconditional tests are found to exhibit far less conservatism than the conditional test and thereby gain a power advantage.

Objective. Communities are building or improving trail networks for biking and walking to encourage physical activity, but the relationship between trail environments and physical activity is not well understood. We examined the effect of a trail use intervention in Southern Nevada. Methods. We monitored the usage of urban trails (n = 10) in Southern Nevada before, during, and after an intervention which included a marketing campaign promoting trail use and the addition of way-finding and incremental distance signage to selected trails (October 2011–October 2012). Data were collected with infrared monitors placed on the trails for three periods of 7 days. We compared pre-, mid-, and post-intervention usage rates on the 6 trails where signage was added to usage rates on the 4 control trails. Results. The groups of trails experienced different patterns of increases and decreases over the 1-year study period. Mean users per hour increased 31% for the study trails and 35% for the control trails (p < 0.001), but the total increase did not vary between the groups. Conclusion. Trail use increased about 33% during the 1-year study period for the intervention. Adding wayfinding and incremental distance signage appeared to support the increase in usage which followed the marketing campaign.

Testing involving the intra-class kappa coefficient is commonly performed in order to assess agreement involving categorical ratings. A number of procedures have been proposed, which make use of the limiting null distribution as the sample size goes to infinity in order to compute the observed significance. As with many tests based on asymptotic null distributions, these tests are associated with problematic type I error control for selected sample sizes and points in the parameter space. We propose and study a collection of exact testing approaches for both the one-sample and K-sample scenarios. For the one-sample case, p-values are obtained using the exact distribution of the test statistic conditional on a sufficient statistic. In addition, unconditional approaches are considered on the basis of maximization across the nuisance parameter space. Numerical evaluation reveals advantages with the exact unconditional procedures.