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Record W2915672143 · doi:10.1177/2399369318824975

A rare case of crystalglobulinemia

2019· article· en· W2915672143 on OpenAlexaff
Bhanu Prasad, Rajni Chibbar, Muhammad Salim, Sanjeev Sethi

Bibliographic record

VenueJournal of Onco-Nephrology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAmyloidosis: Diagnosis, Treatment, Outcomes
Canadian institutionsRoyal University HospitalRegina General Hospital
Fundersnot available
KeywordsMicrohematuriaMedicinePathologyRenal biopsyProteinuriaImmunofixationMicroscopic hematuriaAcute kidney injuryKidneyBiopsyNephrotic syndromeUrologyInternal medicineMonoclonalAntibodyImmunologyMonoclonal antibody

Abstract

fetched live from OpenAlex

Crystalglobulinemia is an extremely rare complication of monoclonal gammopathy. We report a 49-year-old female who presented with acute kidney injury, microhematuria, and non-nephrotic range proteinuria. Eight weeks prior to presentation, she developed a lower urinary tract infection and acute kidney injury, but her creatinine failed to resolve after resolution of her symptoms with antibiotics. Kidney biopsy revealed a membranoproliferative pattern of injury, and numerous crystals were noted in the glomerular capillaries on electron microscopy. On immunofluorescence, positive staining for immunoglobulin G and kappa was demonstrated in the capillary lumen along the capillary walls. Based on the biopsy, a diagnosis of crystalglobulinemia was made. On serum protein electrophoresis, there was presence of a monoclonal band, which was too small to quantify. Urine immunofixation was negative. Patient was treated with cyclophosphamide, bortezomib, and dexamethasone regime and made a remarkable renal recovery.

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)0.003
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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.008
GPT teacher head0.272
Teacher spread0.264 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Onco-NephrologySame topicAmyloidosis: Diagnosis, Treatment, OutcomesFrench-language works237,207