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Record W2341490834 · doi:10.1371/journal.pone.0140463

Effectiveness of Haemodiafiltration with Heat Sterilized High-Flux Polyphenylene HF Dialyzer in Reducing Free Light Chains in Patients with Myeloma Cast Nephropathy

2015· article· en· W2341490834 on OpenAlexafffund
Mathieu Rousseau‐Gagnon, Mohsen Agharazii, Sacha A. De Serres, Simon Desmeules

Bibliographic record

VenuePLoS ONE · 2015
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsHôtel-Dieu de QuébecUniversité Laval
FundersKidney Foundation of CanadaCanadian Institutes of Health ResearchCanadian Society of NephrologyUniversité Laval
KeywordsMultiple myelomaMaterials scienceImmunoglobulin light chainMedicineInternal medicineImmunology

Abstract

fetched live from OpenAlex

INTRODUCTION: In cases of myeloma cast nephropathy in need of haemodialysis (HD), reduction of free light chains using HD with High-Cut-Off filters (HCO-HD), in combination with chemotherapy, may be associated with better renal recovery. The aim of the present study is to evaluate the effectiveness of haemodiafiltration (HDF) in reducing free light chain levels using a less expensive heat sterilized high-flux polyphenylene HF dialyzer (HF-HDF). METHODS: In a single-centre prospective cohort study, 327 dialysis sessions were performed using a 2.2 m2 heat sterilized high-flux polyphenylene HF dialyzer (Phylther HF22SD), a small (1.1m2) or large (2.1 m2) high-cut-off (HCO) dialyzer (HCOS and HCOL) in a cohort of 16 patients presenting with dialysis-dependent acute cast nephropathy and elevated free light chains (10 kappa, 6 lambda). The outcomes of the study were the mean reduction ratio (RR) of kappa and lambda, the proportion of treatments with an RR of at least 0.65, albumin loss and the description of patient outcomes. Statistical analysis was performed using linear and logistic regression through generalized estimating equation analysis so as to take into account repeated observation within subjects and adjust for session duration. RESULTS: There were no significant differences in the estimated marginal mean of kappa RR, which were respectively 0.67, 0.69 and 0.70 with HCOL-HD, HCOS-HDF and HF-HDF (P = 0.950). The estimated marginal mean of the proportions of treatments with a kappa RR ≥0.65 were 68%, 63% and 71% with HCOL-HD, HCOS-HDF and HF-HDF, respectively (P = 0.913). The estimated marginal mean of lambda RR were higher with HCOL-HDF (0.78), compared to HCOL-HD and HF-HDF (0.62, and 0.61 respectively). The estimated marginal mean proportion of treatments with a lambda RR ≥0.65 were higher with HCOL-HDF (81%), compared to 57% in HF-HDF (P = 0.042). The median albumin loss were 7, 21 and 63 g/session with HF-HDF, HCOL-HD and HCOL-HDF respectively (P = 0.044). Among survivors, 9 out of 10 episodes of acute kidney injuries became dialysis-independent following a median time of renal replacement therapy of 40 days (range 7-181). CONCLUSION: Therefore, in patients with acute dialysis-dependent myeloma cast nephropathy, in addition to chemotherapy, HDF with a heat sterilized high-flux polyphenylene HF dialyzer could offer an alternative to HCO dialysis for extracorporeal kappa reduction with lower albumin loss.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.029
GPT teacher head0.240
Teacher spread0.211 · 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 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".

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Citations18
Published2015
Admission routes2
Has abstractyes

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