Publications

BACKGROUND: The Essential Tremor Rating Assessment Scale (TETRAS) is a popular scale for essential tremor (ET), but its activities of daily living (ADL) and performance (P) subscales are based on a structured interview and physical exam. No patient-reported outcome (PRO) scale for ET has been developed according to US regulatory guidelines.

OBJECTIVE: Develop and validate a TETRAS PRO subscale.

METHODS: Fourteen items, rated 0-4, were derived from TETRAS ADL and structured cognitive interviews of 18 ET patients. Convergent validity analyses of TETRAS PRO versus TETRAS ADL, TETRAS-P, and the Quality of Life in Essential Tremor Questionnaire (QUEST) were computed for 67 adults with ET or ET plus. Test-retest reliability was computed at intervals of 1 and 30 days. The influence of mood (Hospital Anxiety and Depression Scale, HADS) and coping behaviors (Essen Coping Questionnaire, ECQ) was examined with multiple linear regression.

RESULTS: TETRAS PRO was strongly correlated (r > 0.7) with TETRAS ADL, TETRAS-P, and QUEST and exhibited good to excellent reliability (Cronbach alpha 95%CI = 0.853-0.926; 30-day test-retest intraclass correlation 95%CI = 0.814-0.921). The 30-day estimate of minimum detectable change (MDC) was 6.6 (95%CI 5.2-8.0). TETRAS-P (rsemipartial = 0.607), HADS depression (rsemipartial = 0.384), and the coping strategy of information seeking and exchange of experiences (rsemipartial = 0.176) contributed statistically to TETRAS PRO in a multiple linear regression (R2 = 0.67).

CONCLUSIONS: TETRAS PRO is a valid and reliable scale that is influenced strongly by tremor severity, moderately by mood (depression), and minimally by coping skills. The MDC for TETRAS PRO is probably sufficient to detect clinically important change.

OBJECTIVE: Previous studies have suggested a link between peripheral inflammation and cognitive outcomes in the general population and individuals with Parkinson's disease (PD). We sought to test the association between peripheral inflammation, measured by the neutrophil-to-lymphocyte ratio (NLR), cognitive performance, and mild cognitive impairment (MCI) status in individuals with PD.

METHODS: A retrospective, longitudinal analysis was carried out using data from the Parkinson's Progression Markers Initiative (PPMI), including 422 participants with PD followed over 5 years. Cognitive performance was assessed using a neuropsychological battery including the Montreal Cognitive Assessment (MoCA) and tests of verbal learning, visuospatial function, processing speed, and executive function. Mixed-effect regression models were used to analyze the association between NLR, cognitive performance, and MCI status, controlling for age, sex, education, APOE genotype, and motor severity.

RESULTS: There was a negative association between NLR and MoCA, even after adjusting for covariates (b = -0.12, p = 0.033). MoCA scores for individuals in the high NLR category exhibited a more rapid decline over time compared to the low NLR group (b = -0.16, p = 0.012). Increased NLR was associated with decreased performance across all cognitive domains. However, NLR was not associated with MCI status over 5 years of follow-up.

INTERPRETATION: This study demonstrates a link between elevated NLR and cognitive performance in PD, but not with MCI status over 5 years. This suggests that NLR is more strongly associated with day-to-day cognitive performance than with incident MCI, but this requires further study in more heterogeneous cohorts.

BACKGROUND: Smartphone-based cognitive assessments have emerged as promising tools, bridging gaps in accessibility and reducing bias in Alzheimer disease and related dementia research. However, their congruence with traditional neuropsychological tests and usefulness in diverse cohorts remain underexplored.

METHODS AND RESULTS: A total of 406 FHS (Framingham Heart Study) and 59 BHS (Bogalusa Heart Study) participants with traditional neuropsychological tests and digital assessments using the Defense Automated Neurocognitive Assessment (DANA) smartphone protocol were included. Regression models investigated associations between DANA task digital measures and a neuropsychological global cognitive Z score (Global Cognitive Score [GCS]), and neuropsychological domain-specific Z scores. FHS participants' mean age was 57 (SD, 9.75) years, and 44% (179) were men. BHS participants' mean age was 49 (4.4) years, and 28% (16) were men. Participants in both cohorts with the lowest neuropsychological performance (lowest quartile, GCS1) demonstrated lower DANA digital scores. In the FHS, GCS1 participants had slower average response times and decreased cognitive efficiency scores in all DANA tasks (P<0.05). In BHS, participants in GCS1 had slower average response times and decreased cognitive efficiency scores for DANA Code Substitution and Go/No-Go tasks, although this was not statistically significant. In both cohorts, GCS was significantly associated with DANA tasks, such that higher GCS correlated with faster average response times (P<0.05) and increased cognitive efficiency (all P<0.05) in the DANA Code Substitution task.

CONCLUSIONS: Our findings demonstrate that smartphone-based cognitive assessments exhibit concurrent validity with a composite measure of traditional neuropsychological tests. This supports the potential of using smartphone-based assessments in cognitive screening across diverse populations and the scalability of digital assessments to community-dwelling individuals.

Most research using digital technologies builds on existing methods for staff-administered evaluation, requiring a large investment of time, effort, and resources. Widespread use of personal mobile devices provides opportunities for continuous health monitoring without active participant engagement. Home-based sensors show promise in evaluating behavioral features in near real time. Digital technologies across these methodologies can detect precise measures of cognition, mood, sleep, gait, speech, motor activity, behavior patterns, and additional features relevant to health. As a neurodegenerative condition with insidious onset, Alzheimer disease and other dementias (AD/D) represent a key target for advances in monitoring disease symptoms. Studies to date evaluating the predictive power of digital measures use inconsistent approaches to characterize these measures. Comparison between different digital collection methods supports the use of passive collection methods in settings in which active participant engagement approaches are not feasible. Additional studies that analyze how digital measures across multiple data streams can together improve prediction of cognitive impairment and early-stage AD are needed. Given the long timeline of progression from normal to diagnosis, digital monitoring will more easily make extended longitudinal follow-up possible. Through the American Heart Association-funded Strategically Focused Research Network, the Boston University investigative team deployed a platform involving a wide range of technologies to address these gaps in research practice. Much more research is needed to thoroughly evaluate limitations of passive monitoring. Multidisciplinary collaborations are needed to establish legal and ethical frameworks for ensuring passive monitoring can be conducted at scale while protecting privacy and security, especially in vulnerable populations.

BACKGROUND: The Essential Tremor Rating Assessment Scale (TETRAS) is a popular scale for essential tremor (ET), but its activities of daily living (ADL) and performance (P) subscales are based on a structured interview and physical exam. No patient-reported outcome (PRO) scale for ET has been developed according to US regulatory guidelines.

OBJECTIVE: Develop and validate a TETRAS PRO subscale.

METHODS: Fourteen items, rated 0-4, were derived from TETRAS ADL and structured cognitive interviews of 18 ET patients. Convergent validity analyses of TETRAS PRO versus TETRAS ADL, TETRAS-P, and the Quality of Life in Essential Tremor Questionnaire (QUEST) were computed for 67 adults with ET or ET plus. Test-retest reliability was computed at intervals of 1 and 30 days. The influence of mood (Hospital Anxiety and Depression Scale, HADS) and coping behaviors (Essen Coping Questionnaire, ECQ) was examined with multiple linear regression.

RESULTS: TETRAS PRO was strongly correlated (r > 0.7) with TETRAS ADL, TETRAS-P, and QUEST and exhibited good to excellent reliability (Cronbach alpha 95%CI = 0.853-0.926; 30-day test-retest intraclass correlation 95%CI = 0.814-0.921). The 30-day estimate of minimum detectable change (MDC) was 6.6 (95%CI 5.2-8.0). TETRAS-P (rsemipartial = 0.607), HADS depression (rsemipartial = 0.384), and the coping strategy of information seeking and exchange of experiences (rsemipartial = 0.176) contributed statistically to TETRAS PRO in a multiple linear regression (R2 = 0.67).

CONCLUSIONS: TETRAS PRO is a valid and reliable scale that is influenced strongly by tremor severity, moderately by mood (depression), and minimally by coping skills. The MDC for TETRAS PRO is probably sufficient to detect clinically important change.

OBJECTIVE: Previous studies have suggested a link between peripheral inflammation and cognitive outcomes in the general population and individuals with Parkinson's disease (PD). We sought to test the association between peripheral inflammation, measured by the neutrophil-to-lymphocyte ratio (NLR), cognitive performance, and mild cognitive impairment (MCI) status in individuals with PD.

METHODS: A retrospective, longitudinal analysis was carried out using data from the Parkinson's Progression Markers Initiative (PPMI), including 422 participants with PD followed over 5 years. Cognitive performance was assessed using a neuropsychological battery including the Montreal Cognitive Assessment (MoCA) and tests of verbal learning, visuospatial function, processing speed, and executive function. Mixed-effect regression models were used to analyze the association between NLR, cognitive performance, and MCI status, controlling for age, sex, education, APOE genotype, and motor severity.

RESULTS: There was a negative association between NLR and MoCA, even after adjusting for covariates (b = -0.12, p = 0.033). MoCA scores for individuals in the high NLR category exhibited a more rapid decline over time compared to the low NLR group (b = -0.16, p = 0.012). Increased NLR was associated with decreased performance across all cognitive domains. However, NLR was not associated with MCI status over 5 years of follow-up.

INTERPRETATION: This study demonstrates a link between elevated NLR and cognitive performance in PD, but not with MCI status over 5 years. This suggests that NLR is more strongly associated with day-to-day cognitive performance than with incident MCI, but this requires further study in more heterogeneous cohorts.

BACKGROUND: Initiation of symptomatic therapy in Parkinson disease is a disease progression milestone, and its prediction is important. Previous studies were limited in duration and number of variables included in their predictive models.

OBJECTIVES: To identify predictors of time to initiation of symptomatic therapy in patients with PD not on treatment, using a large pool of candidate variables from the Parkinson's Progression Markers Initiative dataset, analyzed at ten years.

METHODS: Kaplan Meier survival curve was used to estimate time to initiation of symptomatic treatment. Potential predictors included 33 baseline clinical, imaging, biofluid, and genetic biomarkers. Univariate Cox regression was used for variable selection, significant predictors subsequently entering a multivariate Cox proportional hazard model, which was further reduced using the Akaike Information Criterion into a final reduced model.

RESULTS: Of 425 participants with Parkinson's Disease, 406 initiated symptomatic therapy at last follow up. The outcome was censored for 4.5% of the sample. The risk of initiating symptomatic therapy was 65% (95%CI 60-70%) within the first year from enrollment. Predictors included dopamine transporter SPECT, the Movement Disorders Society Unified Parkinson Disease Rating Scale, and anxiety (State Trait Anxiety Inventory).

CONCLUSIONS: Baseline dopamine transporter SPECT specific binding ratio was found to be the most impactful predictor for time to initiation of symptomatic therapy in this 10-year follow up analysis of the Progressive Parkinson Markers Initiative cohort, when treatment status was known for 95.5% of the sample.

Recent advancements in generative artificial intelligence, particularly using large language models (LLMs), are gaining increased public attention. We provide a perspective on the potential of LLMs to analyze enormous amounts of data from medical records and gain insights on specific topics in neurology. In addition, we explore use cases for LLMs, such as early diagnosis, supporting patient and caregivers, and acting as an assistant for clinicians. We point to the potential ethical and technical challenges raised by LLMs, such as concerns about privacy and data security, potential biases in the data for model training, and the need for careful validation of results. Researchers must consider these challenges and take steps to address them to ensure that their work is conducted in a safe and responsible manner. Despite these challenges, LLMs offer promising opportunities for improving care and treatment of various neurologic disorders.