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Incidence of deep vein thrombosis in erysipelas or cellulitis of the lower extremities

2012· review· en· W1918778432 on OpenAlexaff
Mohammadreza Mortazavi, Mitra M. Samiee, Frederick A. Spencer

Bibliographic record

VenueInternational Journal of Dermatology · 2012
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineErysipelasCellulitisIncidence (geometry)SurgeryDeep veinThrombosisCochrane LibraryDermatologyMeta-analysisInternal medicine

Abstract

fetched live from OpenAlex

The incidence of deep vein thrombosis (DVT) in patients with erysipelas and cellulitis of the lower extremities is unknown. As such, the indication and efficacy of prophylactic anticoagulation for prevention of DVT in these patients is unclear. The main goal of this review is to provide an estimate of the incidence of DVT in erysipelas and cellulitis based on existing literature. A comprehensive search of the electronic sources: MEDLINE, EMBASE, CINAHL, LILAC and Cochrane without any language limitation was performed from 1950 to April 2011 for articles focused on the occurrence of DVT in cellulitis or erysipelas of the lower extremities. The selected studies were divided into two groups according to presence or absence of systematic investigation for DVT. Those studies in which the patients received prophylactic or therapeutic anticoagulants before a diagnosis of DVT were excluded. The reported incidence rate of DVT in patients with erysipelas or cellulitis of the lower extremities is highly variable, ranging from 0 to 15%. In this review, the overall incidence rates of DVT in studies with and without systematic investigation for thromboembolism were 2.72% (95% CI: 1.71-3.75%) and 0.68% (95% CI: 0.27-1.07%), respectively. Given the low reported overall incidence of DVT, neither routine prophylactic anticoagulation nor systematic paraclinical investigation for DVT is indicated in low risk patients with erysipelas or cellulitis of the lower extremities. DVT should still be considered in patients with high pretest probability or other thromboembolic risk factors.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.923
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.053
GPT teacher head0.354
Teacher spread0.301 · 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.

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

Citations7
Published2012
Admission routes1
Has abstractyes

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