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Retinal Hemodynamics in Early Diabetic Macular Edema

2006· article· en· W2156800020 on OpenAlexaff
Kit Guan, Chris Hudson, Tien Yin Wong, M. Kisilevsky, Ravi K. Nrusimhadevara, Wai‐Ching Lam, Mark S. Mandelcorn, Robert G. Devenyi, John G. Flanagan

Bibliographic record

VenueDiabetes · 2006
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsMedicineHemodynamicsDiabetes mellitusDiabetic retinopathyRetinalBlood pressureCardiologyInternal medicineOphthalmologyBlood flowEdemaAnesthesiaEndocrinology

Abstract

fetched live from OpenAlex

The objective of this study was to establish the baseline retinal hemodynamic characteristics of stratified groups of diabetic patients at increasing risk for the development of diabetic macular edema (DME). Group 1 had 50 control subjects, group 2 had 56 diabetic patients without clinically visible retinopathy, group 3 had 54 diabetic patients with microaneurysms and/or hard exudates within two disc diameters of the fovea in the absence of clinically manifest DME, and group 4 had 40 patients with clinically manifest DME. Retinal hemodynamics (diameter, velocity, maximum-to-minimum velocity ratio, and flow) were assessed. Intraocular pressure, blood pressure, and relevant systemic markers of diabetes control and complications were also undertaken. The maximum-to-minimum velocity ratio was elevated with increasing risk of clinically significant DME (P < 0.0001). No significant differences were found between the groups with respect to diameter, velocity, or flow. The maximum-to-minimum velocity ratio was correlated to age, duration of diabetes, blood pressure, pulse rate, intraocular pressure, and serum potassium levels. In conclusion, the maximum-to-minimum velocity ratio was significantly increased with increasing risk of development of DME. Retinal arteriolar hemodynamics were positively correlated to age, duration of diabetes, and blood pressure. These findings suggest a reduction in the compliance (i.e., an increase of vascular rigidity) of the arteriolar circulation with increasing risk of DME.

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 score0.005
Threshold uncertainty score0.459

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 head0.005
GPT teacher head0.229
Teacher spread0.224 · 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

Citations76
Published2006
Admission routes1
Has abstractyes

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