Search

Amyloid- β (A 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 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 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. [ABSTRACT FROM AUTHOR]

We present sample size determination using exact approaches for testing the ratio of incidence rates from a two-arm non-inferiority trial. The first approach is the exact conditional approach by treating the total number of events from two groups fixed, and the other is the exact unconditional approach based on maximization. Exact approaches guarantee the type I error rate which is often not satisfied in the commonly used asymptotic approaches on the basis of the corresponding limiting distributions of test statistics. We provide tables for sample size determination in commonly used cases in practice, and an example is used to show the application of these exact approaches. Sample size comparison using different exact approaches concludes that the exact unconditional approach based on the Wald-type test statistic has good performance in balanced studies. [ABSTRACT FROM AUTHOR]

Background: Mixed martial arts (MMA) fighters, due to exposure to repetitive head impacts, are at risk for brain atrophy and neurodegenerative sequelae. Simultaneously, motor skills training and cognition-rich activities have been linked with larger regional brain volumes. The majority of an MMA fighter's sporting activity occurs during practice (e.g., sparring) rather than formal competition. This study, therefore, aims to be the first to explore regional brain volumes associated with sparring in MMA fighters. Methods: Ninety-four active, professional MMA fighters from the Professional Fighters Brain Health Study met inclusion criteria for this cross-sectional analysis. Adjusted multivariable regression analyses were utilized to examine the relationship between the number of sparring practice rounds per week during typical training and a select number of regional brain volumes (i.e., caudate, thalamus, putamen, hippocampus, amygdala). Results: A higher number of weekly sparring rounds during training was significantly associated with larger left (beta = 13.5 µL/round, 95% CI 2.26–24.8) and right (beta = 14.9 µL/round, 95% CI 3.64–26.2) caudate volumes. Sparring was not significantly associated with left or right thalamus, putamen, hippocampus, or amygdala volumes. Conclusions: More weekly rounds of sparring was not significantly associated with smaller volumes in any of the brain regions studied in active, professional MMA fighters. Sparring's significant association with larger caudate volume raises questions about whether fighters who spar more experience attenuated trauma-related decreases in caudate volume relative to fighters who spar less, whether fighters who spar more experience minimal or even positive changes to caudate volume, whether baseline differences in caudate size may have mediated results, or whether some other mechanism may be at play. Given limitations inherent to the cross-sectional study design, more research is needed to further explore the brain effects of sparring in MMA. [ABSTRACT FROM AUTHOR]

Background: Severe headaches are common after subarachnoid hemorrhage. Guidelines recommend treatment with acetaminophen and opioids, but patient data show that headaches often persist despite multimodal treatment approaches. Considering an overall slim body of data for a common complaint affecting patients with SAH during their intensive care stay, we set out to assess practice patterns in headache management among clinicians who treat patients with SAH. Methods: We conducted an international cross-sectional study through a 37-question Web-based survey distributed to members of five professional societies relevant to intensive and neurocritical care from November 2021 to January 2022. Responses were characterized through descriptive analyses. Fisher's exact test was used to test associations. Results: Of 516 respondents, 329 of 497 (66%) were from North America and 121 of 497 (24%) from Europe. Of 435 respondents, 379 (87%) reported headache as a major management concern for patients with SAH. Intensive care teams were primarily responsible for analgesia during hospitalization (249 of 435, 57%), whereas responsibility shifted to neurosurgery at discharge (233 of 501, 47%). Most used medications were acetaminophen (90%), opioids (66%), corticosteroids (28%), and antiseizure medications (28%). Opioids or medication combinations including opioids were most frequently perceived as most effective by 169 of 433 respondents (39%, predominantly intensivists), followed by corticosteroids or combinations with corticosteroids (96 of 433, 22%, predominantly neurologists). Of medications prescribed at discharge, acetaminophen was most common (303 of 381, 80%), followed by opioids (175 of 381, 46%) and antiseizure medications (173 of 381, 45%). Opioids during hospitalization were significantly more prescribed by intensivists, by providers managing higher numbers of patients with SAH, and in Europe. At discharge, opioids were more frequently prescribed in North America. Of 435 respondents, 299 (69%) indicated no change in prescription practice of opioids with the opioid crisis. Additional differences in prescription patterns between continents and providers and while inpatient versus at discharge were found. Conclusions: Post-SAH headache in the intensive care setting is a major clinical concern. Analgesia heavily relies on opioids both in use and in perception of efficacy, with no reported change in prescription patterns for opioids for most providers despite the significant drawbacks of opioids. Responsibility for analgesia shifts between hospitalization and discharge. International and provider-related differences are evident. Novel treatment strategies and alignment of prescription between providers are urgently needed. [ABSTRACT FROM AUTHOR]