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BackgroundMedicinal cannabis registries typically report pain as the most common reason for use. It would be clinically useful to identify patterns of cannabis treatment in migraine and headache, as compared to arthritis and chronic pain, and to analyze preferred cannabis strains, biochemical profiles, and prescription medication substitutions with cannabis.MethodsVia electronic survey in medicinal cannabis patients with headache, arthritis, and chronic pain, demographics and patterns of cannabis use including methods, frequency, quantity, preferred strains, cannabinoid and terpene profiles, and prescription substitutions were recorded. Cannabis use for migraine among headache patients was assessed via the ID Migraine™ questionnaire, a validated screen used to predict the probability of migraine.ResultsOf 2032 patients, 21 illnesses were treated with cannabis. Pain syndromes accounted for 42.4% (n = 861) overall; chronic pain 29.4% (n = 598;), arthritis 9.3% (n = 188), and headache 3.7% (n = 75;). Across all 21 illnesses, headache was a symptom treated with cannabis in 24.9% (n = 505). These patients were given the ID Migraine™ questionnaire, with 68% (n = 343) giving 3 “Yes” responses, 20% (n = 102) giving 2 “Yes” responses (97% and 93% probability of migraine, respectively). Therefore, 88% (n = 445) of headache patients were treating probable migraine with cannabis. Hybrid strains were most preferred across all pain subtypes, with “OG Shark” the most preferred strain in the ID Migraine™ and headache groups. Many pain patients substituted prescription medications with cannabis (41.2–59.5%), most commonly opiates/opioids (40.5–72.8%). Prescription substitution in headache patients included opiates/opioids (43.4%), anti-depressant/anti-anxiety (39%), NSAIDs (21%), triptans (8.1%), anti-convulsants (7.7%), muscle relaxers (7%), ergots (0.4%).ConclusionsChronic pain was the most common reason for cannabis use, consistent with most registries. The majority of headache patients treating with cannabis were positive for migraine. Hybrid strains were preferred in ID Migraine™, headache, and most pain groups, with “OG Shark”, a high THC (Δ9-tetrahydrocannabinol)/THCA (tetrahydrocannabinolic acid), low CBD (cannabidiol)/CBDA (cannabidiolic acid), strain with predominant terpenes β-caryophyllene and β-myrcene, most preferred in the headache and ID Migraine™ groups. This could reflect the potent analgesic, anti-inflammatory, and anti-emetic properties of THC, with anti-inflammatory and analgesic properties of β-caryophyllene and β-myrcene. Opiates/opioids were most commonly substituted with cannabis. Prospective studies are needed, but results may provide early insight into optimizing crossbred cannabis strains, synergistic biochemical profiles, dosing, and patterns of use in the treatment of headache, migraine, and chronic pain syndromes.

Objectives/Goals: This study examines prevalence of complete sample size justifications in publications in the top five clinical neurology journals. Secondary goals include comparing study designs and clinical populations to explore whether some may be more likely to include inadequate sample size considerations. Methods/Study Population: Recent studies (n  =  125) in Lancet Neurology , Alzheimer’s and Dementia , JAMA Neurology , Acta Neuropathology , and Brain will be evaluated. For each journal, the 25 most recent empirical articles between 2022 and 2023 will be examined for their inclusion of a justification and reproducible sample size calculation. Inclusion of components of an ideal sample size justification will be evaluated: effect size to be detected (standardized or unstandardized), alpha, power, and from where values were derived. Prevalence and completeness will be compared among study designs, clinical populations, and with regard to journal reporting requirements. Results/Anticipated Results: At the pilot review stage, 17 of 25 included studies had any kind of sample size justification, and only 3 studies had enough information to reproduce their sample size calculations. Retrospective studies included a sample size justification more frequently (81.8% vs. 57.1%), but prospective studies had more complete sample size justifications, when present. We hypothesize that sample size calculations will be more complete in reports of clinical trials and prospective cohort studies, compared to retrospective and cross-sectional designs. Based on our previous research, we do not expect that journal reporting requirements will affect completeness of sample size justifications. Discussion/Significance of Impact: Translational decision-making is informed in part by the robustness of current research. Transparency of sample size considerations in publications can contribute to the formation of less biased opinions of translational readiness and, subsequently, more efficient and effective translation.

Abstract BACKGROUND Deformity reconstruction surgery has been shown to improve quality of life (QOL) in cases of adult spinal deformity (ASD) but is associated with significant morbidity. OBJECTIVE To create a preoperative predictive nomogram to help risk-stratify patients and determine which would likely benefit from corrective surgery for ASD as measured by patient-reported health-related quality of life (HRQoL). METHODS All patients aged 25-yr and older with radiographic evidence of ASD and QOL data that underwent thoracolumbar fusion between 2008 and 2014 were identified. Demographic and clinical parameters were obtained. The EuroQol 5 dimensions questionnaire (EQ-5D) was used to measure HRQoL preoperatively and at 12-mo postoperative follow-up. Logistic regression of preoperative variables was used to create the prognostic nomogram. RESULTS Our sample included data from 191 patients. Fifty-one percent of patients experienced clinically relevant postoperative improvement in HRQoL. Seven variables were included in the final model: preoperative EQ-5D score, sex, preoperative diagnosis (degenerative, idiopathic, or iatrogenic), previous spinal surgical history, obesity, and a sex-by-obesity interaction term. Preoperative EQ-5D score independently predicted the outcome. Sex interacted with obesity: obese men were at disproportionately higher odds of improving than nonobese men, but obesity did not affect odds of the outcome among women. Model discrimination was good, with an optimism-adjusted c-statistic of 0.739. CONCLUSION The predictive nomogram that we developed using these data can improve preoperative risk counseling and patient selection for deformity correction surgery.

Towards the end of life (EOL), persons with parkinsonism (PwP) have complex needs and can present with unique palliative care (PC) challenges. There are no widely accepted guidelines to aid neurologists, hospitalists, or PC clinicians in managing the symptoms of PwP at EOL. We examined a population of PwP at EOL, aiming to describe trends of in-hospital management and utilization of PC services.BackgroundTowards the end of life (EOL), persons with parkinsonism (PwP) have complex needs and can present with unique palliative care (PC) challenges. There are no widely accepted guidelines to aid neurologists, hospitalists, or PC clinicians in managing the symptoms of PwP at EOL. We examined a population of PwP at EOL, aiming to describe trends of in-hospital management and utilization of PC services.All PwP admitted to two hospitals during 2018 (N = 727) were examined retrospectively, assessing those who died in hospital or were discharged with hospice (EOL group, N = 35) and comparing them to the main cohort. Their demographics, clinical data, engagement of multidisciplinary and palliative services, code status changes, invasive care, frequency of admissions, and medication administration were assessed.MethodsAll PwP admitted to two hospitals during 2018 (N = 727) were examined retrospectively, assessing those who died in hospital or were discharged with hospice (EOL group, N = 35) and comparing them to the main cohort. Their demographics, clinical data, engagement of multidisciplinary and palliative services, code status changes, invasive care, frequency of admissions, and medication administration were assessed.Among the EOL group, 8 expired in hospital, and 27 were discharged to hospice. Forty-six percent of EOL patients received a PC consultation during their admission. The median interval from admission to death was 37 days. Seventy-seven percent had a full code status on admission. Compared to hospice patients, those who expired in hospital had higher rates of invasive procedures and intensive care unit transfers (41% vs. 75%, in both variables), and lower rates of PC involvement (52% vs. 25%). The transition of code status change for the EOL group from Full code to Do Not Resuscitate (DNR) occurred at a median 4-5 days from admission. For patients that passed in the hospital, the median days from transition of code status to death was 0(IQR 0-1). Levodopa dose deviations were frequent in both EOL and non-EOL group, but contraindicated medications were infrequently administered (11% in EOL group vs. 9% in non-EOL group).ResultsAmong the EOL group, 8 expired in hospital, and 27 were discharged to hospice. Forty-six percent of EOL patients received a PC consultation during their admission. The median interval from admission to death was 37 days. Seventy-seven percent had a full code status on admission. Compared to hospice patients, those who expired in hospital had higher rates of invasive procedures and intensive care unit transfers (41% vs. 75%, in both variables), and lower rates of PC involvement (52% vs. 25%). The transition of code status change for the EOL group from Full code to Do Not Resuscitate (DNR) occurred at a median 4-5 days from admission. For patients that passed in the hospital, the median days from transition of code status to death was 0(IQR 0-1). Levodopa dose deviations were frequent in both EOL and non-EOL group, but contraindicated medications were infrequently administered (11% in EOL group vs. 9% in non-EOL group).Our data suggest a low utilization of PC services and delayed discussions of goals of care. More work is needed to raise awareness of inpatient teams managing PwP regarding the unique but common challenges facing PwP with advanced disease. A brief narrative review summarizing the suggested management of symptoms common to hospitalized PwP near EOL is provided.ConclusionOur data suggest a low utilization of PC services and delayed discussions of goals of care. More work is needed to raise awareness of inpatient teams managing PwP regarding the unique but common challenges facing PwP with advanced disease. A brief narrative review summarizing the suggested management of symptoms common to hospitalized PwP near EOL is provided.

Longitudinal and behavioral preclinical animal studies generate complex data, which may not be well matched to statistical approaches common in this literature. Analyses that do not adequately account for complexity may result in overly optimistic study conclusions, with consequences for reproducibility and translational decision-making. Recent work interrogating methodological shortcomings in animal research has not yet comprehensively investigated statistical shortcomings in the analysis of complex longitudinal and behavioral data. To this end, the current cross-sectional meta-research study rigorously reviewed published mouse or rat controlled experiments for motor rehabilitation in three neurologic conditions to evaluate statistical choices and reporting. Medline via PubMed was queried in February 2020 for English-language articles published January 1, 2017- December 31, 2019. Included were articles that used rat or mouse models of stroke, Parkinson’s disease, or traumatic brain injury, employed a therapeutic controlled experimental design to determine efficacy, and assessed at least one functional behavioral assessment or global evaluation of function. 241 articles from 99 journals were evaluated independently by a team of nine raters. Articles were assessed for statistical handling of non-independence, animal attrition, outliers, ordinal data, and multiplicity. Exploratory analyses evaluated whether transparency or statistical choices differed as a function of journal factors. A majority of articles failed to account for sources of non-independence in the data (74–93%) and/or did not analytically account for mid-treatment animal attrition (78%). Ordinal variables were often treated as continuous (37%), outliers were predominantly not mentioned (83%), and plots often concealed the distribution of the data (51%) Statistical choices and transparency did not differ with regards to journal rank or reporting requirements. Statistical misapplication can result in invalid experimental findings and inadequate reporting obscures errors. Clinician-scientists evaluating preclinical work for translational promise should be mindful of commonplace errors. Interventions are needed to improve statistical decision-making in preclinical behavioral neurosciences research.

Considerable variability exists in the publication of clinical research study procedures related to study enrollment and participant exit from clinical trials. Despite recent efforts to encourage research data sharing and greater transparency regarding research outcomes, reporting of research procedures remains inconsistent. Transparency about study procedures has important implications for the interpretation of study outcomes and the consistent implementation of best practices in clinical trial design and conduct. This review of publications from clinical trials of deep brain stimulation (DBS) using the MEDLINE database examines the frequency and consistency of publication of research procedures and data related to exit from DBS research. Related considerations, such as device explant or continued use, battery and other device hardware replacements, and post-trial follow-up care are also reviewed. This review finds significant variability in the publication and reporting of study exit procedures. Of the 47 clinical trials included in this review, 19% (9) disclosed procedures related to exit from research. Reporting of other exit-related data and study procedures examined in this review was identified in fewer than half of the included clinical trials. The rate of participant retention and duration of follow-up was reported more than any other category of data included in this review. Results inform efforts to improve consistency in research design, conduct, and publication of results from clinical trials in DBS and related areas of clinical research.

Background Individuals with PTEN hamartoma tumor syndrome (PHTS) demonstrate a distinct neurobehavioral profile suggesting primary disruption of frontal lobe symptoms, with more severe cognitive deficits in those with associated autism spectrum disorder (ASD) that extend to other areas of neurobehavioral function as well (e.g., adaptive behavior, sensory deficits). The current study sought to characterize longitudinal neurobehavioral profiles in individuals with PHTS who completed serial assessments (2–3 evaluations) over a 2-year time period. Methods Comprehensive neurobehavioral evaluations were conducted on 92 participants (age range 6–21) with PHTS and/or ASD. Spaghetti plots and linear mixed effects models were used to visualize the individual patient profiles and group trends and examine the group differences in cognitive/behavioral test scores over time. Practice-adjusted reliable change indices (RCIs) and standardized regression-based change scores (SRBs) were calculated for those measures in the battery with adequate sample sizes and test–retest reliabilities for future use in assessing neurobehavioral change in children and young adults with PHTS. Results Wide individual differences were observed at baseline across all measures. Encouragingly, baseline differences between patient groups persisted at the same magnitude over a 2-year time period with no differences in longitudinal neurobehavioral profiles within any one group. Test–retest reliabilities were generally high, ranging from 0.62 to 0.97, and group mean change from baseline to 12 months was small (range − 3.8 to 3.7). A Microsoft Excel calculator was created that clinicians and researchers can use to automatically calculate RCI and SRB thresholds at both 80% and 90% confidence intervals using test scores from a given child or young adult with PHTS. Conclusions Our results suggest that the neurobehavioral phenotypes observed in individuals with PHTS remain relatively stable over time, even in those with ASD. The RCIs and SRBs provided can be used in future research to examine patient outcomes at the individual level as well as to detect negative deviations from the expected trajectory that can be used to inform intervention strategies.

Parkinson’s Disease is a neurological disease with cardinal motor signs including bradykinesia and tremor. Although beta-band hypersynchrony in the cortico-basal ganglia network is thought to contribute to disease manifestation, resulting effects on network connectivity are unclear. We examined local field potentials from a non-human primate across the naïve, mild, and moderate disease states (model was asymmetric, left-hemispheric dominant) and probed cortico-cortical and cortico-subthalamic connectivity using Granger causality, a measure of directed effective connectivity, and a subsequent graph-theoretic analysis. Our network included the left subthalamic nucleus (L-STN), bilateral primary motor cortices (L-M1, R-M1) and bilateral premotor cortices (L-PMC, R-PMC). Results showed two distinct Granger causality peaks (Peak A at 5-20 Hz, Peak B at 25-45 Hz). Increases in Peak B connectivity and decreases in Peak A connectivity were associated with disease. Induction of mild disease was associated with several changes in connectivity: 1) the cortico-subthalamic connectivity in the descending direction (L-PMC to L-STN) decreased in the Peak A range while the reciprocal, ascending connectivity (L-STN to L-PMC) increased in the Peak B range; this may play a role in generating beta-band hypersynchrony in the cortex, 2) both L-M1 to L-PMC and R-M1 to R-PMC causalities increased, which may either be compensatory or a pathologic effect of disease, and 3) a decrease in connectivity occurred from the R-PMC to R-M1. The only significant change seen between mild and moderate disease was increased right cortical connectivity, which may reflect compensation for the left-hemispheric dominant moderate disease state. Graph-theory analysis suggested that the network became more “efficient”, or synchronized at both local and global levels, which agrees with our findings of increased beta-band connectivity.

Objectives/Goals: In neurological animal research, statistical misapplication may lead to overoptimism in a therapy’s potential for successful translation. This pilot study investigated whether human clinical trials that fail have higher prevalence of statistical misapplication in preceding animal experiments, compared to human trials that succeed. Methods/Study Population: Phase 2 clinical trials for 3 neurological conditions were identified on ClinicalTrials.gov and classified as successful or failed based on advancement to Phase 3 and/or preplanned efficacy test results. PRISMA guideline methods were used to systematically search for preclinical animal experiments (same indication and intervention) preceding the start of the human trial. Data were gathered from animal articles by collectors blinded to human trial outcome and included items describing reporting transparency, experimental design and sample sizes, and statistical tests applied. Statistical mistakes were coded based on mismatch between test and design. Rates of mistakes were compared between articles preceding successful and non-successful human trials using weighted point estimates and 95% confidence interval. Results/Anticipated Results: The final sample included 24 trials (16 successful) and 70 associated animal studies. Transparency was poor, with infrequent reporting of group allocation method (39%), sample sizes adequate to evaluate attrition ( Discussion/Significance of Impact: Statistical misapplication is common in animal research, and this pilot study has demonstrated that preclinical statistical mistakes may indeed occur more frequently prior to failed human trials. Mistakes and lack of transparency may lead to overoptimism in preclinical experimental findings, with consequences for subsequent human translation.

INTRODUCTION Automated models that predict cognitive risk in older adults can aid decisions about which patients to screen in busy primary care settings. METHODS In this retrospective prediction model development study, we conducted formal cognitive testing on 337 older primary care patients to establish cognitive status. We used up to 5 years of prior discrete‐field electronic health record (EHR) data to develop a multivariable prediction model that differentiates patients with impaired versus intact cognition. RESULTS The final model included seven easily extractable variables with known associations to cognitive decline: age, race, pulse, systolic blood pressure, non‐steroidal anti‐inflammatory use, history of mood disorder, and family history of neurological disease. The model demonstrated good discrimination of cognitive status (concordance statistic = 0.72). DISCUSSION The cognitive risk model may be useful clinically to prompt for objective cognitive screening in high‐risk patients. The use of common, discrete variables ensures relative ease of implementation in EHRs. Highlights 337 older primary care patients completed full neuropsychological assessment. Risk modeling used data available in a typical primary care record. The model successfully differentiated patients with/without cognitive impairment. This EHR model offers a passive workflow to identify patients at cognitive risk.