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Record W2115272737 · doi:10.1177/0009922809339385

Prevalence and Severity of Hypertensive Retinopathy in Children

2009· article· en· W2115272737 on OpenAlexafffund
Bethany J. Foster, Huma Ali, Silvia Mamber, Robert C. Polomeno, Andrew S. Mackie

Bibliographic record

VenueClinical Pediatrics · 2009
Typearticle
Languageen
FieldMedicine
TopicRetinal Imaging and Analysis
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsMedicineHypertensive retinopathyRetinopathyInternal medicineOphthalmologyPediatricsEndocrinologyDiabetes mellitus

Abstract

fetched live from OpenAlex

The National High Blood Pressure Education Program (NHBPEP) report recommends a retinal exam seeking evidence of target organ damage in hypertensive children. This study aimed to determine the prevalence and severity of hypertensive retinopathy among hypertensive children, evaluated by pediatric ophthalmologists in the "real world" clinical setting using direct ophthalmoscopy. The authors retrospectively reviewed the medical records of the 83 children diagnosed with hypertension by a pediatric nephrologist between 1999 and 2006. Of the 35 children examined by an ophthalmologist within 12 months of the diagnosis of hypertension, only 3 (8.6%; 95% CI, 1.8%-23.1%) were diagnosed with hypertensive retinopathy. Despite the fact that those selected for retinal examination were likely at higher risk for retinopathy, the prevalence of retinopathy was low, and only mild abnormalities were detected. Given the lack of evidence linking mild retinal abnormalities with adverse outcomes, the NHBPEP recommendation for retinal examinations in hypertensive children should be reconsidered.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.335
Teacher spread0.314 · 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 source (direct Gemma or distilled Codex), 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

Citations30
Published2009
Admission routes2
Has abstractyes

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