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Record W2031196113 · doi:10.1159/000216901

Therapeutic Use of Low-Molecular-Weight Heparins

2009· review· en· W2031196113 on OpenAlexaff
Russell D. Hull, Graham F. Pineo

Bibliographic record

VenueHaemostasis · 2009
Typereview
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsHeparinMedicineAntithromboticDeep veinThrombosisIntensive care medicineLow molecular weight heparinClinical trialSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Accumulating evidence indicates that certain low-molecular-weight (LMW) heparins administered subcutaneously may replace classic intravenous heparin therapy. LMW heparins do not require monitoring and may be safer and more effective than unfractionated heparin. The decreased mortality rate, evident in two randomized trials, which was particularly striking in patients with metastatic carcinoma, requires confirmation. The simplified care offered by LMW heparin therapy raises the possibility of transferring care from in-hospital to out of hospital in uncomplicated patients with deep-vein thrombosis [Salzman EW: Low-molecular weight heparin and other new antithrombotic drugs. N Engl J Med 1992;326: 1017-1019]. The advantages to the patient of avoiding in-hospital care and its associated hazards are obvious. Outpatient LMW heparin therapy will likely prove to be highly cost-effective. It is uncertain at present whether the findings associated with an individual LMW heparin preparation can be extrapolated to a different LMW heparin. For this reason the findings of clinical trials apply only to the particular LMW heparin evaluated and cannot be generalized to the LMW heparins at large.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.149
GPT teacher head0.419
Teacher spread0.270 · 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

Citations18
Published2009
Admission routes1
Has abstractyes

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