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Record W2158810833 · doi:10.2337/diacare.27.1.173

Postural Control Mechanisms During Quiet Standing in Patients With Diabetic Sensory Neuropathy

2004· article· en· W2158810833 on OpenAlexaff
Danik Lafond, Hélène Corriveau, François Prince

Bibliographic record

VenueDiabetes Care · 2004
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsHealth and Social Services Centre University Institute of Geriatrics of SherbrookeUniversité de Montréal
Fundersnot available
KeywordsMedicineCenter of pressure (fluid mechanics)Physical medicine and rehabilitationAnkleSensory systemQUIETProprioceptionSensationForce platformDiabetic neuropathyPhysical therapyDiabetes mellitusSurgeryPsychology

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of the present study was to compare postural mechanisms identified by using dual force platform in healthy elderly community-dwelling subjects and diabetic sensory neuropathy (DSN) patients under different visual conditions. RESEARCH DESIGN AND METHODS: The presence and the severity of the sensory neuropathy was evaluated with a clinical scale. Postural mechanisms and motor strategies of the ankle and hip joints were quantified by testing subjects in quiet stance on a dual force platform under two visual conditions (eyes open and eyes closed). Root mean square (RMS) values of the center of pressure (COP) time-varying signals and normalized cross-correlation function were used to estimate the contribution and the interdependence of postural control mechanisms. RESULTS: DSN patients show larger RMS values of the COP(net) displacement in both anteroposterior and mediolateral (ML) directions. Motor strategies at the ankle joints are altered in DSN patients compared with healthy elderly subjects particularly in the ML direction. CONCLUSIONS: This experiment is the first to highlight that even with vision, postural mechanisms at the ankle joints are impaired in DSN patients during quiet standing. Our results point out the importance of focusing on postural control instability in ML of DSN patients.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.011
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.007
GPT teacher head0.252
Teacher spread0.245 · 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.

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

Citations195
Published2004
Admission routes1
Has abstractyes

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