Evidence map›Paper›PMID 35111494›Full record

ArticleFujita medical journal2019

Efficacy and risks of fondaparinux 7.5 mg for deep vein thrombosis after total knee arthroplasty.

Sho Nojiri, Kazue Hayakawa, Hideki Date, Harumoto Yamada

Open access · greenAbstract read
In one paragraph

Article in Fujita medical journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 90% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Sho NojiriDepartment of Orthopedic Surgery, Fujita Health University School of Medicine, Toyoake, Aichi, Japan.
Kazue HayakawaDepartment of Orthopedic Surgery, Fujita Health University School of Medicine, Toyoake, Aichi, Japan.
Hideki DateDepartment of Orthopedic Surgery, Fujita Health University School of Medicine, Toyoake, Aichi, Japan.
Harumoto YamadaDepartment of Orthopedic Surgery, Fujita Health University School of Medicine, Toyoake, Aichi, Japan.
Fujita Health University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesHigh-dose fondaparinux therapy at 7.5 mg/day (FPX 7.5 mg) for deep vein thrombosis (DVT) may increase the risk of hemorrhage. We investigated the efficacy and safety of FPX 7.5 mg to treat DVT after total knee arthroplasty.

methodsThis study included 101 patients (91 with osteoarthritis, 10 with rheumatoid arthritis; mean age at total knee arthroplasty: 72.9 years) with asymptomatic postoperative DVT. Medical prophylaxis for DVT was started on postoperative day 1. Vascular ultrasound was conducted within 2 days postoperatively; patients were switched to FPX 7.5 mg after DVT diagnosis. Ultrasound was repeated to monitor DVT resolution. Adverse reactions were assessed.

resultsDVT resolved in 72 patients (71.3%) receiving FPX 7.5 mg. There were no significant differences between patients with versus without DVT resolution in the timing of FPX 7.5 mg therapy, treatment period, age, body mass index, or D-dimer or hemoglobin levels. There was no significant difference in DVT outcome between patients starting FPX 7.5 mg within 4 days postoperatively versus on day 5 or later, or between patients treated for ≤7 versus ≥8 days. Hemoglobin decreased to ≤7 g/dL in three patients (2.9%).

conclusionsFPX 7.5 mg can be expected to resolve DVT in 71.3% of patients; however, the risk of associated hemorrhagic complications may be higher than the risk of pulmonary embolism. To treat DVT with FPX 7.5 mg without compromising safety, patients should be selected carefully and the timing of treatment should be adjusted appropriately.

Indexed as

Deep vein thrombosisFondaparinuxPulmonary thromboembolismTotal knee arthroplasty

Identifiers

PMID35111494
PMCPMC8766234
OpenAlexW2947757167

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.