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Record W1964682425 · doi:10.1159/000088215

Plasma Exchange Using a Continuous Venovenous Hemofiltration Machine in Children

2005· article· en· W1964682425 on OpenAlexaff
Ewa Ciechanska, Lauren Segal, Hubert Wong, Christine Chretien, Guido Filler

Bibliographic record

VenueBlood Purification · 2005
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
FundersEdwards Lifesciences
KeywordsPlasma volumeHemofiltrationHeparinMedicineBolus (digestion)AnesthesiaActivated clotting timeChemistryUrologySurgeryInternal medicineHemodialysis

Abstract

fetched live from OpenAlex

BACKGROUND: There is considerable interest in using continuous venovenous hemofiltration machines for plasma exchange therapy in children. METHODS: Retrospective study of 7 patients and 61 plasma exchange treatments using the Baxter/Edwards Lifesciences BM25 machine with commercially available plasma filters (mostly Asahi Plasmaflo). RESULTS: The average total exchange volume was 1.5 times the plasma volume, achieved at a blood flow rate of 100 ml/m(2) (3.5 ml/kg/min) and a turnover rate of 25 ml/kg/h over a 3-hour duration. Fifty-six percent of the time, a mean heparin bolus of 29 units/kg resulted in subtherapeutic activated clotting times. Mean heparin infusion rates of 35 units of heparin/kg/h achieved effective anticoagulation. A calcium infusion rate of 0.11 +/- 0.05 mmol/kg/h avoided hypocalcemia. One patient experienced the serious complication of membrane reaction. CONCLUSIONS: This setup provides a safe approach to plasma exchange in children. A similar method could be implemented in other centers.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.288
Teacher spread0.263 · 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

Citations9
Published2005
Admission routes1
Has abstractyes

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