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Record W3197621640 · doi:10.1016/j.prdoa.2021.100107

Telephone visit efficacy for Parkinson’s disease during the COVID-19 pandemic

2021· article· en· W3197621640 on OpenAlexaff
Fadi Abu Ahmad, Ronald B. Postuma

Bibliographic record

VenueClinical Parkinsonism & Related Disorders · 2021
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsMcGill University Health CentreMcGill University
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Parkinson's disease2019-20 coronavirus outbreakMedicineVirologySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)DiseaseOutbreakInternal medicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

"1. Introduction There has been growing interest in using telemedicine to expand accessibility of patients with Parkinson’s disease (PD) to clinical care. Efficacy of telemedicine visits continues to be evaluated [1], [2], [3]. During the COVID-19 pandemic, there was an abrupt transition from in-person to remote visits [4]; in our center, due to regulatory and practical barriers, this was conducted by telephone. This abrupt externally-induced and near-complete transition provided an opportunity to directly compare telephone and in-person visits, independent of factors related to patient choice of intervention. Therefore, we explored whether the absence of face-to-face interactions would alter the frequency of changes in medical therapy. We reviewed medical records of 100 PD patients followed at McGill Movement disorders clinic who had a telephone visit March-May 2020 (convenience sample) plus at least one prior in-person visit within 12 months. The project was approved by the local institutional review board; waiver of Informed Consent was granted due to the study’s retrospective nature. The primary outcome was the proportion of visits which ended in a change of therapy. We used the chi-square test and logistic regression for comparison of categorical variables. The population was 40% female, age = 72 ± 10.1 years (Table 1). The average time between the two consecutive visits was similar between telemedicine and in-person visits (5.97 ± 2.1 vs. 6.03 ± 2.3 months). Overall, we observed fewer medication changes during telephone visits; a change was made in 44% of telemedicine visits compared to 59% of the preceding in-person visit [OR 1.83, 95%CI: 1.05–3.21]. This reduction was particularly evident for starting a new medication (new motor medication = OR 3.27[95%CI: 1.02–10.52], new non-motor medication = OR 3.62[95%CI: 1.27–10.3]). Patients in telemedicine visits were less often referred for outside consultation (0% telemedicine vs. 5% in-person, p = 0.024). There was a modest nonsignificant reduction dose changes of existing treatments in telemedicine visits (motor [OR 1.28, 95%CI: 0.73–2.24], non-motor OR 1.83, 95%CI: 0.84–3.99])."@eng

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.046
GPT teacher head0.360
Teacher spread0.314 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2021
Admission routes1
Has abstractno

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