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Record W2054962585 · doi:10.1097/mcp.0b013e328216430d

Low molecular weight heparin and bleeding in patients with chronic renal failure

2007· review· en· W2054962585 on OpenAlexaff
Mark Crowther, Wendy Lim

Bibliographic record

VenueCurrent Opinion in Pulmonary Medicine · 2007
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster UniversitySt. Joseph's Hospital
Fundersnot available
KeywordsMedicineChronic renal failureHeparinLow molecular weight heparinInternal medicineIntensive care medicineGastroenterology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Low molecular weight heparin (LMWH) has largely replaced unfractionated heparin (UFH) in patients with venous thromboembolism because of its pharmacokinetic profile, ease of administration and lack of need for monitoring. The pharmacokinetic profile of LMWH is due to lower molecular weight and reduced charge resulting in less nonspecific protein binding than UFH. These same characteristics make LMWH more dependent on renal function compared with UFH. Consequently, care should be employed when LMWH is administered to patients with impaired renal function as reduced clearance and bioaccumulation may cause bleeding. RECENT FINDINGS: LMWHs vary in their likelihood of bioaccumulation in chronic renal failure. Enoxaparin bioaccumulates and causes bleeding if administered in therapeutic doses without dose adjustment to patients with impaired renal function. Less rigorous evidence suggests that tinzaparin does not bioaccumulate. Bioaccumulation appears to be greatest in patients with a creatinine clearance less than 30 ml/min, and when therapeutic LMWH doses are used. SUMMARY: Care should be used when LMWHs are administered to patients with impaired renal function, particularly those with severe impairment (creatinine clearance below 30 ml/min).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.931
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.348
Teacher spread0.308 · 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 teacher head, not a consensus.

Study designOther design
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

Citations58
Published2007
Admission routes1
Has abstractyes

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