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Record W4311978181 · doi:10.12974/2312-5411.2022.09.03

Multiple Myeloma Presenting as Acute Kidney Failure Secondary to Lambda Light Chain Deposition

2022· article· en· W4311978181 on OpenAlexaff
Marie-Eve Emond-Boisjoly, Émilie Lemieux‐Blanchard, Antonia Maietta, Stéphanie Forté

Bibliographic record

VenueJournal of Hematology Research · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAmyloidosis: Diagnosis, Treatment, Outcomes
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversité de Montréal
Fundersnot available
KeywordsPlasma cell dyscrasiaMultiple myelomaImmunoglobulin light chainMedicineRenal biopsyKidneyMonoclonalMonoclonal gammopathy of undetermined significanceRenal functionBortezomibPathologySerum protein electrophoresisBiopsyNephropathyMonoclonal antibodyInternal medicineImmunologyAntibodyEndocrinologyDiabetes mellitus

Abstract

fetched live from OpenAlex

Renal monoclonal immunoglobulin deposition disease (MIDD) is a rare disease defined by deposition of monoclonal light chains and/or heavy chains on basement membranes and vascular walls of the kidney. We describe a case of a 71-year-old woman with kidney failure secondary to monoclonal immunoglobulin deposition disease lambda in association with plasma cell dyscrasia. Her initial serum protein electrophoresis did not demonstrate a monoclonal protein, and classic cast nephropathy was absent on renal biopsy. However, lambda light chain deposits and associated changes confirmed MIDD. She achieved a very good partial response (VGRP) after 8 cycles of CyBorD (cyclophosphamide, bortezomib, dexamethasone) and her kidney function improved. This case highlights the importance of an early diagnostic with renal biopsy to prevent end-stage renal disease. A review of the existing literature and a discussion on the management of the disease is presented.

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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.017
GPT teacher head0.333
Teacher spread0.316 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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