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Role of plasmapheresis in the management of myeloma kidney: A systematic review

2010· review· en· W2108234041 on OpenAlexvenueno aff
Diptesh Gupta, Lohith Bachegowda, Gautam Phadke, E. Diane Johnson, Madhukar Misra

Bibliographic record

VenueHemodialysis International · 2010
Typereview
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePlasmapheresisDialysisRandomized controlled trialNephrologyObservational studyIntensive care medicineMultiple myelomaInternal medicineRenal functionHemodialysisSurgeryImmunology

Abstract

fetched live from OpenAlex

Multiple myeloma complicated by acute renal failure is a diagnosis often encountered by the practicing nephrologist. The role of plasmapheresis in such patients has been of interest for decades. Three randomized controlled trials (RCTs) and multiple observational trials have evaluated the potential role of plasmapheresis in the management of this condition. This systematic review presents the results of these trials regarding survival benefits, recovery from dialysis, and improvement in renal function. A comprehensive search revealed 56 articles. Of these, only 8 articles met our inclusion criteria (3 RCTs, 1 correction of results, and 4 observational trials). Two of the 3 RCTs showed no difference in survival benefit. Two of the 3 RCTs showed a greater percentage of patients stopping dialysis in the intervention group; however, these results were not reproduced in the largest trial. All the studies showed an improvement in renal function for patients receiving plasmapheresis; however, only 2 RCTs and 1 retrospective study showed a statistically significant improvement in renal function among patients who received plasmapheresis in comparison with a control group. Our systematic review does not suggest a benefit of plasmapheresis independent of chemotherapy for multiple myeloma patients with acute renal failure in terms of overall survival, recovery from dialysis, or improvement in renal function.

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)0.001
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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.193
Threshold uncertainty score0.621

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.032
GPT teacher head0.351
Teacher spread0.319 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations32
Published2010
Admission routes1
Has abstractyes

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