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Record W2507735282 · doi:10.14740/jocmr2740w

An Overlapping Case of Alport Syndrome and Thin Basement Membrane Disease

2016· article· en· W2507735282 on OpenAlexvenueno aff
Mashriq Alganabi, Ahmad Eter

Bibliographic record

VenueJournal of Clinical Medicine Research · 2016
Typearticle
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAlport syndromeProteinuriaKidney diseaseRenal biopsyPhysical examinationBiopsyDiseaseAbnormalityGlomerulonephritisSurgeryDermatologyPediatricsPathologyKidneyInternal medicine

Abstract

fetched live from OpenAlex

We report a case of a 48-year-old male who presented with hematuria of at least 10 years, and has a daughter with hematuria as well. The patient has a history of degenerative hearing loss, decreased vision and cataract formation, but no diabetes, hypertension or proteinuria. A full serology and urology workup was negative for any abnormality. A kidney biopsy for the patient revealed a diagnosis of Alport syndrome but was unable to rule out thin basement membrane disease. The biopsy was inconclusive in making the diagnosis but the patient's clinical presentation led to the diagnosis of Alport syndrome. The patient's 10-year-old daughter also has hematuria with no clear etiology but now can subsequently be anticipatorily managed for Alport syndrome progression. Due to the rarity of the disease, diagnosis is often missed or delayed by primary care providers especially when no associated proteinuria has yet developed. This can lead to confusion and misdiagnosis with thin basement membrane disease, a generally benign hematuria without kidney failure progression. Additionally, biopsy can be inconclusive in these patients, relying on the physician's history and physical examination findings to diagnose. It is important to appropriately diagnose Alport syndrome not only to manage the patient's rate of kidney failure progression but also allow for a higher degree of suspicion, screening and intervention in the patient's family members. Both the inconclusive nature of kidney biopsies and the usefulness of diagnosis for family member screening are often overlooked in medical literature but are explored in this case.

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)0.000
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0040.002
Scholarly communication0.0020.003
Open science0.0010.004
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.210
GPT teacher head0.549
Teacher spread0.338 · 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 designCase report
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

Citations1
Published2016
Admission routes1
Has abstractyes

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