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Record W4389229472 · doi:10.1182/blood-2023-189763

Risk of Developing Post Thrombotic Syndrome after Deep Vein Thrombosis with Different Anticoagulant Regimens, a Systematic Review and Pooled Analysis

2023· review· en· W4389229472 on OpenAlexaff
Cameron Brown, Lauren Tokessy, Aurélien Delluc, Marc Carrier

Bibliographic record

VenueBlood · 2023
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsUniversity of OttawaOttawa Hospital
Fundersnot available
KeywordsMedicineDeep veinThrombosisInternal medicineIncidence (geometry)AnticoagulantPost-thrombotic syndromeLow molecular weight heparinRivaroxabanSurgeryWarfarinAtrial fibrillation

Abstract

fetched live from OpenAlex

Background Post-thrombotic syndrome (PTS) is a chronic condition that arises in up to 20-50% of patients with deep vein thrombosis (DVT) of the lower extremity. Symptoms range from skin color changes and limb heaviness to edema, chronic pain and ulcers. PTS has a significant impact on patients' quality of life. Hence, it is important to optimize DVT management to minimize the incidence and severity of PTS. It is unclear if different anticoagulant therapies (e.g. vitamin K antagonists (VKA), direct oral anticoagulants (DOACs) or low molecular weight heparin (LMWH)) are associated with different risks of PTS. Objective We sought to assess the incidence rates of PTS development after a proximal DVT of the lower extremity managed with different anticoagulation regimens. Methods A systematic search of MEDLINE, EMBASE and PubMed as well as conference proceedings (inception to June 2023) was performed. Studies were screened and selected if they met the criteria for patients (age ≥18) receiving anticoagulation therapy for a minimum of 3 months after the diagnosis of a proximal DVT of the lower extremity. The primary outcome was development of PTS defined by the Villalta or PRV score of ≥ 5, or as defined by the individual studies. Incidence rates (overall and per type of anticoagulant regimens) were pooled using the random effects model and expressed as event per 100 patient-years with its associated 95% confidence intervals (CI) using R software. Results Out of the 2837 identified studies, 77 were reviewed in full text and 21 (n= 4342 patients) were included in the analysis (7 randomized controlled trials, 14 observational studies). There were 17 studies (2834 patients), 12 studies (1212 patients) and 2 studies (296 patients) reporting the outcomes for VKA, DOAC and LMWH, respectively. The crude incidence rates for PTS development are depicted in Figure 1. After adjusting for duration of anticoagulation, the overall incidence of PTS was 16.3 per 100 patient-years (95% CI: 11.1-24.12). The incidence of PTS was 15.1 per 100-patient-years (95% CI: 8.7-26.1), 18.2 per 100 patient-years (95% CI: 9.4-35.1), 24.6 per 100 patient-years (95% CI: 9.2-65.5) for VKA, DOAC and LMWH, respectively. The most used DOAC was rivaroxaban (incidence rate of 12.3 per 100 patient-years (95% CI: 1.6-96.4)). Conclusions PTS is a common complication among patients with proximal DVT of the lower extremity. Incidence of PTS development may differ based on the anticoagulant regimen. DOACs seems to be associated with lower incidence PTS development compared to VKA and LMWH. Future clinical trials are needed to confirm these findings.

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)0.009
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0130.018
Bibliometrics0.0100.012
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.023
GPT teacher head0.292
Teacher spread0.269 · 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 designMeta-analysis
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

Citations0
Published2023
Admission routes1
Has abstractyes

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