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Record W4385514998 · doi:10.1002/mus.27948

Reliability of confocal corneal microscopy for measurement of dendritic cell density in suspected small fiber neuropathy

2023· article· en· W4385514998 on OpenAlexaff
Juan Idiáquez, Rodrigo Martinez‐Harms, Carolina Barnett, Bruce A. Perkins, Vera Bril

Bibliographic record

VenueMuscle & Nerve · 2023
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsSinai Health SystemDiabetes CanadaUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsIntraclass correlationReliability (semiconductor)ConfocalConfocal microscopyNerve fiberMedicineBasal (medicine)PathologyOphthalmologyAnatomyBiologyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION/AIMS: Dendritic cells (DCs) and their contacts with corneal nerves are described in animal models of nerve damage. Dendritic cell density (DCD) is a potential marker of immune activity in suspected small-fiber neuropathy (SFN). Here, we aim to evaluate the intra- and inter-rater reliability of DCD measurements in suspected SFN. METHODS: This retrospective study collected DCD from confocal microscopy images from the corneal sub-basal epithelium of the eye from 48 patients (mean age 49.6 ± 12.1 y, 61% female). Two examiners, each blinded to the other's examinations and measurements, assessed DCD to evaluate inter-rater reliability. For intra-rater reliability, the first examiner performed a second measurement after 14 days. DCs were classified into two cell morphological subtypes: mature and immature. RESULTS: Test-retest reliability for total DCD showed excellent agreement, with an intraclass correlation coefficient of 0.96 and inter-rater reliability intraclass correlation coefficient of 0.77. The immature cell subtype showed excellent intra-rater reliability but lower inter-rater reliability. DISCUSSION: We found that DCD measurements in the corneal sub-basal epithelium are sufficiently reliable for consideration in clinical studies of patients with suspected SFN.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.028
GPT teacher head0.256
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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations2
Published2023
Admission routes1
Has abstractyes

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