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Low‐molecular‐weight heparin for routine hemodialysis

2008· review· en· W1993913487 on OpenAlexvenueno aff
Andrew Davenport

Bibliographic record

VenueHemodialysis International · 2008
Typereview
Languageen
FieldMedicine
TopicHeparin-Induced Thrombocytopenia and Thrombosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHemodialysisHeparinLow molecular weight heparinExtracorporealDialysisPharmacodynamicsPharmacokineticsThrombusIntensive care medicineDrugSurgeryPharmacology

Abstract

fetched live from OpenAlex

Unfractionated heparin (UFH) is a series of molecules, and as such has variable pharmacodynamics. Low-molecular-weight heparins were developed to improve both drug pharmacokinetics and dynamics, so as to provide a reliable clinical effect. These are potent agents, but have an increased half-life compared with UFH in dialysis patients, and also require special laboratory monitoring. We switched our chronic hemodialysis patients from unfractionated to low-molecular-weight heparins. Low-molecular-weight heparins proved to be effective in preventing extracorporeal circuit clotting, and safe with fewer bleeding episodes and heparin-induced thrombocytopenia than standard UFH. Indeed, we stopped routine laboratory monitoring because of the lack of side effects, and simply dosed by clinical inspection of the extracorporeal circuit for thrombus, and the time for fistula needle sites to stop bleeding. These agents have become the anticoagulants of choice in Europe for routine outpatient hemodialysis sessions, not only due to reduced drug costs but also due to the reliability of their clinical effect and ease of administration.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.008

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 head0.053
GPT teacher head0.353
Teacher spread0.300 · 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 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

Citations24
Published2008
Admission routes1
Has abstractyes

Explore more

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