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Record W2781485779 · doi:10.21776/ub.mnj.2018.004.01.5

DIAGNOSTIC TEST OF TORONTO AND MODIFIED TORONTO SCORING, MONOFILAMENT TEST, AND VIBRATE SENSATION TEST USING 128 HZ TUNING FORK FOR DIABETIC POLINEUROPATHY

2018· article· en· W2781485779 on OpenAlexaboutno aff
Bethasiwi Purbasari, Vivi Laras Anggraini, Made Dinda Pratiwi, Machlusil Husna, Shahdevi Nandar Kurniawan

Bibliographic record

VenueMNJ (Malang Neurology Journal) · 2018
Typearticle
Languageen
FieldMedicine
TopicDiabetic Foot Ulcer Assessment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDiabetes mellitusTuning forkIncidence (geometry)PopulationPolyneuropathyInternal medicinePhysical therapyDiabetic footSurgery

Abstract

fetched live from OpenAlex

Background. The prevalence of diabetes mellitus has been epidemically increasing throughout all the world population, and diabetic polyneuropathy (PNP-DM) is one of the most common neurologic manifestation of this disease. Clinical research has proved that effective bedside screening of PNP-DM can significantly reduce the incidence of foot ulcer and limb amputation. Objective. To measure the diagnostic test of polyneuropathy scoring, monofilament 10-g SemmesWeinstein test, and 128 Hz tuning fork test as an early detection measure for PNP-DM.Methods. This research was conducted using a cross sectional approach from Januari 2016 to Juli 2017.Results. Among the total study population of 43 (23 men and 20 woman), Modified Toronto Score has the highest sensitivity (100%), PPV (93%) and accuracy (93%). Toronto score has the highest NPV (9%).Conclusion. Modified Toronto Score has good diagnostic value as screening tool in PNP-DM.

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)0.001
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 score0.105
Threshold uncertainty score0.878

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.021
GPT teacher head0.282
Teacher spread0.261 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

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