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Record W4391929124 · doi:10.1002/mdc3.13999

Remote Deep Brain Stimulation Programming in Canada

2024· letter· en· W4391929124 on OpenAlex
Wilson Fung, Maria Belen Justich, Michelle Hamani, Renato P. Munhoz, Suneil K. Kalia, Andrés M. Lozano, Alfonso Fasano

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMovement Disorders Clinical Practice · 2024
Typeletter
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsKrembil FoundationUniversity of TorontoToronto Western Hospital
Fundersnot available
KeywordsDeep brain stimulationStimulationNeuroscienceComputer sciencePsychologyCognitive scienceMedicineParkinson's disease

Abstract

fetched live from OpenAlex

Over the recent past, telemedicine in movement disorders has played an increasingly important role in improving patient access to specialist care, particularly for individuals living in remote areas or those suffering from significant disability due to chronic neurological illnesses.1 When the healthcare landscape changed further during the early stages of the pandemic owing to many movement disorders services needing to reduce or cancel non-urgent care in order to prioritize resources, this inevitably led to a surge in telemedicine use.2 The Canadian healthcare system is particularly suitable for telemedicine due to the presence of few tertiary centers distributed within a large geographical area spanning three time zones, billing codes, and telemedicine infrastructures that have been in place well before the COVID-19 pandemic. Accordingly, in 2018, we published the first experience with the use of the Ontario Telemedicine Network in DBS patients in our center. In this study, stimulation adjustments were performed by the patient, caregiver or nurse, by means of a patient controller that was pre-programmed by the clinician, thus a paucity of stimulation options were available.3 Such approach comes with challenges as self-adjustments made by means of the aforementioned patient's controller can lead to a delay in programming optimization as well as increased side effects.4 Telemedicine in DBS therefore needed change and the pandemic has auspiciously expedited the utilization of innovative technology, namely remote programming. As of July 26, 2022, healthcare professionals in Canada trained in providing DBS care have been able to program patients’ DBS devices remotely via a secure virtual platform called NeuroSphere™ Virtual Clinic Remote Care (Abbott, Austin, Texas, USA). To date, we have enrolled 18 patients, 10 of whom have successfully undergone remote programming for the first time in Canada, either during the post-operative phase (n = 5) or subsequent follow-up evaluations (n = 5). All patients needed at least one in-person visit, usually the first programming session after surgery, in order to enroll them into the program and to carry out a “monopolar review” of the electrodes. Patients included five women with an average age of 64.6 ± 6.2 years (range: 52–74). All patients but two had Parkinson's disease (PD) while remaining cases included generalized dystonia and tremor (one case each) for a mean disease duration of 17.3 ± 13.1 years (range: 7–42). They underwent an average of 2.8 ± 2.3 (range: 1–7) remote programming sessions, each lasting 60 min in duration and carried out by a DBS neurologist. Similar to in-person reviews, PD patients were provided weekly appointments (for 4–6 weeks) during the initial programming phase, and monthly for dystonia and tremor cases. Follow-up appointments were 3–6 months. Four patients attended their remote sessions alone and 6 patients were accompanied by their caregiver. Figure S1 shows the geographical distribution of these patients, who lived on average 2197.2 ± 1488.0 km (range: 122.5–4059) from our center with an average travel time of 250.8 ± 100.4 min (range: 93–423), all but three patients usually require to come by flight. Sessions were arranged routinely (except one) with all patients reporting clinical improvement, and the majority (70%) rating the improvement as at least moderate. One patient required an urgent follow-up appointment following their in-person review to have the upper amplitude limit increased remotely (for self-adjustment). Stimulation changes varied between patients, ranging from no change (n = 1) to new programs created (n = 6) (Table 1). No extra visits were performed on the same day or urgent appointments afterwards. Clinical markers, such as bradykinesia and/or tremor (eg, UPDRS-III for PD), were used to guide remote programming. No significant adverse effect or technical issue related to the platform was reported. Remote programming addresses an important gap in DBS care by removing the geographical barrier. It is a great step forward toward universal access to DBS services by offering patients quick and flexible access to the DBS clinic, especially those who were previously excluded due poor access to specialist care. It also has the potential to redistribute resources by cutting down waiting lists, improving patient flow as well as potentially reducing last-minute appointment cancellations. It is important to note however that virtual care cannot replace in-person consultations altogether as there are important aspects of the neurological examination that need to be carried out physically, such as assessing rigidity or performing a pull test to look for postural instability. As remote programming gathers momentum, there will be an even greater need to develop clinical guidelines on the use of telemedicine in DBS to ensure that virtual DBS care becomes an integral part of practice. (1) Research project: A. Conception, B. Organization, C. Execution; (2) Statistical Analysis: A. Design, B. Execution, C. Review and Critique; (3) Manuscript Preparation: A. Writing of the first draft, B. Review and Critique. W.F.: 1B, 1C, 2B, 3A M.J.: 1B, 2C, 3B M.H.: 1B, 3B R.M.: 1B, 2C, 3B S.K.: 3B A.L.: 3B A.F.: 1A, 1B, 1C, 2A, 2B, 2C, 3B Ethical Compliance Statement: The authors confirm that the approval of an institutional review board was not required for this work. Informed consent was obtained for videos/photographs. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this work is consistent with those guidelines. Funding Sources and Conflicts of Interest: This study was partly funded by the University of Toronto and University Health Network Chair in Neuromodulation to AF. AF received honoraria from Abbott for work unrelated to the content of this publication. WF was partly funded by Abbott during the Movement Disorders Surgical Fellowship. Financial Disclosures for the Previous 12 Months: WF, MJ, MH and RM declare that there are no additional disclosures to report. SK is a consultant to Abbott, Boston Scientific, Medtronic and Novo Nordisk. SK received honoraria from Abbott, Boston Scientific and Medtronic. AL is a consultant to Abbott, Boston Scientific, Insightec, Medtronic. AL is a Scientific Director at Functional Neuromodulation. AF is a consultant to Abbvie, Abbott, Boston Scientific, Inbrain, Ipsen, Medtronic, Sunovion, Syneos Health. AF is on the advisory board for Abbvie, Boston Scientific, Ceregate and Ipsen. AF received Honoraria from Abbvie, Abbott, AAN, Boston Scientific, Brainlab, Ipsen, Medtronic, Merz, Movement Disorders Society, Sunovion, Paladin Labs, UCB. Figure S1. Map illustrating the locations of the 10 patients undergoing remote programming carried out from Toronto Western Hospital, Ontario. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.229
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.370
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it