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Record W4414026254 · doi:10.1111/hdi.70026

Recent Progress in Double Filtration Plasmapheresis

2025· review· en· W4414026254 on OpenAlexvenueno aff
Dan Li, Xiaoqiang Liu, Yuhan Wang, Woong Bae Ji

Bibliographic record

VenueHemodialysis International · 2025
Typereview
Languageen
FieldImmunology and Microbiology
TopicComplement system in diseases
Canadian institutionsnot available
Fundersnot available
KeywordsPlasmapheresisFiltration (mathematics)ExtracorporealMedicineUltrafiltration (renal)HemodialysisRefractory (planetary science)Intensive care medicineAlbuminSurgeryChemistryChromatographyInternal medicineImmunologyAntibodyBiology

Abstract

fetched live from OpenAlex

Double-filtration plasmapheresis is an advanced extracorporeal blood purification technique that selectively removes pathogenic macromolecules based on molecular weight. Unlike conventional plasma exchange, double-filtration plasmapheresis uses a two-step filtration process to retain beneficial plasma components such as albumin, while eliminating harmful substances, thereby reducing the need for exogenous plasma replacement. Over the last few decades, double-filtration plasmapheresis has gained prominence in the management of refractory autoimmune, neurological, metabolic, and renal diseases. This review systematically examines the therapeutic mechanisms, recent clinical advances, safety, limitations, and prospects of double-filtration plasmapheresis.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.044
GPT teacher head0.347
Teacher spread0.303 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations3
Published2025
Admission routes1
Has abstractyes

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