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Record W1932338048 · doi:10.1159/000437042

Coupled Plasma Filtration Adsorption in Patients with a History of Kidney Transplantation: Report of Two Cases

2015· article· en· W1932338048 on OpenAlexaff
Quirino Lai, Verdiana Di Pietro, Samuele Iesari, Sofia Amabili, Linda Luca, Katia Clemente, A. Famulari, F Pisani

Bibliographic record

VenueBlood Purification · 2015
Typearticle
Languageen
FieldMedicine
TopicMuscle and Compartmental Disorders
Canadian institutionsBell (Canada)
Fundersnot available
KeywordsMedicineSeptic shockExtracorporealTransplantationHemofiltrationSepsisSurgeryInternal medicineIntensive care medicineUrologyHemodialysis

Abstract

fetched live from OpenAlex

Coupled plasma filtration adsorption (CPFA) is an extracorporeal treatment based on plasma filtration associated with an adsorbent cartridge and hemofiltration. CPFA is able to remove inflammatory mediators and it has been used to treat severe sepsis, septic shock and multiple organ dysfunction syndrome. Limited experience exists on the use of CPFA after solid organ transplantation. We report our experience with CPFA in 2 kidney transplant recipients with post-nephrolithotomy septic shock and severe unexplained rhabdomyolysis. In both the cases, excellent results were observed. In selected cases, CPFA can be safely and effectively used in patients with a solid organ transplant. However, additional studies are needed in this particular setting, to further investigate the potential role of CPFA for the treatment of other conditions associated with excessive inflammation, such as in rheumatologic disorders and delayed graft 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 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)0.005
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0040.003
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.027
GPT teacher head0.249
Teacher spread0.222 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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