Feasibility of multidisciplinary telehealth evaluations in atypical dementia
Bibliographic record
Abstract
INTRODUCTION: While cognitive assessment by videoconference has become possible over the past decade, the COVID-19 pandemic underscores the critical need for expansion and examination of these methods, their appropriateness for various patient populations, and their benefits and limitations. Validity and reliability studies of tele-neuropsychological testing have been conducted in MCI or mild AD dementia patients (e.g., MMSE=25+); few studies have assessed the feasibility of neurologic examination by video, and none in atypical dementias, assuming that patients with some types (e.g., language, comportment) or greater severity of cognitive-behavioral impairment would be unable to participate. Here we report the feasibility of telehealth services for a multi-disciplinary dementia subspecialty clinic that include cognitive-behavioral and neurologic assessment with patients with atypical neurodegenerative syndromes. METHODS: 104 patient-carepartner (P-C) dyads met with providers in the MGH FTD Unit by videoconference (March-December, 2020) for routine clinical care. P-Cs completed validated questionnaires assessing cognition-mood/behavior/function on REDCap prior to video clinical interview and cognitive assessment, including the MoCA and Boston Cognitive Exam (BCE2.0), a newly revised brief cognitive assessment battery adapted for telehealth. P-Cs met with a neurologist for a basic neurologic examination (including eye-movement examination), review of assessment results, and discussion of care plan. P-Cs completed a satisfaction survey. RESULTS: The 104 P-Cs included a range of atypical neurodegenerative disorders (bvFTD, PCA, PPA, CBS, PSP, eoAD, Multidomain syndrome) mild-to-severe impairment (CDR range: 0-3). 76% completed the MoCA (25% had CDR=2). 36% also completed the BCEv2. Comparison of remote assessment data to previous in-person testing is ongoing. Of P-Cs who completed a satisfaction survey, all reported being "very satisfied" with the appointment, with 93% open to participating in a remote visit again. 87% found the telehealth visit comparable to an in-person visit. 66% preferred a future combination of remote and in-person visits. CONCLUSIONS: Multi-disciplinary telehealth visits appear to be feasible with patients with atypical cognitive-behavioral syndromes of across the severity spectrum. P-Cs report a high degree of satisfaction with the telehealth visit and an openness to ongoing telehealth visits. Results have implications for increasing accessibility of multidisciplinary medical services for patients and families living with complex forms of dementia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".