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POCUS Allows for Rapid Elucidation of Acute Kidney Injury in a Patient with Progressive Multiple Myeloma

2022· article· en· W4210500075 on OpenAlexvenueno aff
Liann Abu Salman, Nathaniel Reisinger

Bibliographic record

VenuePOCUS Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMultiple myelomaProteinuriaUrinalysisPyuriaUrologyTumor lysis syndromeInternal medicineSurgeryKidneyUrineChemotherapy

Abstract

fetched live from OpenAlex

A 63-year-old man with past history of multiple myeloma recently started on a regimen of daratumumab, carfilzomib, and dexamethasone was referred to our emergency department for a rapidly rising serum creatinine as high as 10 mg/dL. He complained of fatigue, nausea, and poor appetite. Exam revealed hypertension, but no edema or rales. Labs were consistent with AKI without hypercalcemia or evidence of hemolysis or tumor lysis. Urinalysis and urine sediment were bland without proteinuria, hematuria, or pyuria. Initial concern was for hypovolemia or myeloma cast nephropathy. POCUS revealed no overt evidence of volume overload or depletion, instead revealing bilateral hydronephrosis. Bilateral percutaneous nephrostomies were placed with resolution of the AKI. Ultimately, referral imaging revealed interval progression of bulky retroperitoneal extramedullary plasmacytomas compressing the ureters bilaterally related to the underlying multiple myeloma.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.501
Threshold uncertainty score0.477

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 head0.015
GPT teacher head0.298
Teacher spread0.283 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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