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Record W4408313554 · doi:10.14740/jocmr6179

Evaluating Grasp Function in Patients With Chronic Inflammatory Demyelinating Polyneuropathy Using Dynamometers: A Comprehensive Review

2025· review· en· W4408313554 on OpenAlexvenueno aff
Periklis Tsoumanis, Theocharis Chatzoglou, Thomas Iraklis Smyris, Christos Stefanou, Dimitris Tsoumanis, Stefanos K Stefanou, Kostas Tepelenis, Alexandra Barbouti, Aikaterini Marini, Paraskevas Zafeiropoulos, Dimitrios Varvarousis

Bibliographic record

VenueJournal of Clinical Medicine Research · 2025
Typereview
Languageen
FieldMedicine
TopicPeripheral Neuropathies and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineChronic inflammatory demyelinating polyneuropathyGRASPDynamometerPhysical medicine and rehabilitationPhysical therapyBiomedical engineeringImmunologyMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

Chronic inflammatory demyelinating polyneuropathy (CIDP) is a progressive neurological disorder characterized by weakness and impaired sensory function due to damage to peripheral nerves. Evaluating grasp function is critical for understanding the impact of CIDP on patients' daily activities and guiding rehabilitation strategies. This comprehensive review examines the role of dynamometers in quantifying grip strength deficits, tracking disease progression, and assessing treatment outcomes in CIDP patients. Key findings highlight the utility of dynamometers in quantifying grip strength deficits, tracking disease progression, and evaluating treatment outcomes. The review also explores methodological considerations, such as standardizing testing protocols and integrating dynamometric measurements with clinical scales. By providing insights into the functional impairments associated with CIDP and the effectiveness of therapeutic interventions, this review underscores the role of dynamometry in advancing patient care and enhancing the quality of life for individuals living with this condition. Future research directions include the development of more sensitive dynamometric tools and longitudinal studies to better understand the relationship between grip strength and overall disease trajectory in CIDP.

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)0.013
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.872
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.006
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 head0.354
GPT teacher head0.582
Teacher spread0.228 · 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 designOther design
Domainnot available
GenreReview

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

Citations1
Published2025
Admission routes1
Has abstractyes

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