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Record W2300737727 · doi:10.4103/0976-3147.176192

Relationship between resting and action tremors in Parkinson’s disease

2016· article· en· W2300737727 on OpenAlexaff
Abdul Qayyum Rana, Mohamad Saleh

Bibliographic record

VenueJournal of Neurosciences in Rural Practice · 2016
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsParkinson's Clinic of Eastern Toronto & Movement Disorders Centre
Fundersnot available
KeywordsMedicineResting tremorLateralityParkinson's diseaseUpper limbPhysical medicine and rehabilitationPhysical therapyDiseaseInternal medicineAudiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the relationship between resting tremor (RT) and action tremor (AT) in Parkinson's disease (PD) patients. METHODS: A retrospective study of RT and AT severity was conducted in 100 PD patients. The severity rating for each type of tremor in the upper extremities was assessed. The disparity in tremor severity between extremities for each tremor type was compared to that of the other two to identify commonalities in the laterality of the tremor manifestation. RESULTS: Overall, RT is predictive of AT on the same side, but not the opposing side of the body. Patients with less intense resting right upper limb (RRU) tremor and moderately intense RRU tremor were significantly more likely to have an action right upper limb (ARU) tremor (-1.53, P = 0.020; -1.88, P = 0.005, respectively). Similarly, patients with less intense resting left upper limb (RLU) tremor and moderately intense RLU tremors were significantly more likely to have an action left upper limb (ALU) tremor (-3.49, P = 0.000; -1.86, P = 0.017, respectively). In addition, RRU and ALU tremors were associated with an increase in RLU and ARU tremors, respectively. CONCLUSION: Tremors are common findings in PD patients, and often impair quality of life. By identifying and classifying the relationship between resting and ATs in PD patients, our study sheds light onto the importance of better understanding and future management of this debilitating symptomology.

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 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)0.000
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.117
GPT teacher head0.391
Teacher spread0.273 · 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 teacher head, not a consensus.

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
Published2016
Admission routes1
Has abstractyes

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