Evidence map›Paper›PMID 37342406›Full record

ArticleInternational journal of general medicine2023

Clinical Observation of Uninterrupted Thrombolytic Therapy via Indwelling Catheter for Lower Limb Deep Vein Thrombosis.

Haoyuan Liu, Rurong Wang, Liang Zhang, Jingming Shi, Jiaxi Yao

Open access · goldAbstract read
In one paragraph

Article in International journal of general medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 33% 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Observational
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

5 authors at 1 institution in 1 country.

Haoyuan LiuDepartment of Intervention, Hexi University Affiliated Zhangye People's Hospital, Zhangye City, Gansu Province, 734000, People's Republic of China.
Rurong WangDepartment of Intervention, Hexi University Affiliated Zhangye People's Hospital, Zhangye City, Gansu Province, 734000, People's Republic of China.
Liang ZhangDepartment of Intervention, Hexi University Affiliated Zhangye People's Hospital, Zhangye City, Gansu Province, 734000, People's Republic of China.
Jingming ShiDepartment of Intervention, Hexi University Affiliated Zhangye People's Hospital, Zhangye City, Gansu Province, 734000, People's Republic of China.
Jiaxi YaoInstitute of Urology, Hexi University, Zhangye City, Gansu Province, 734000, People's Republic of China.ORCID 0000-0002-8023-4338
Hexi University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Observe uninterrupted thrombolytic therapy via indwelling catheter for lower limb deep vein thrombosis. Methods: We retrospectively studied data from 32 patients with lower extremity deep vein thrombosis who received comprehensive treatment, consisting of general treatment, inferior vena cava filter implantation, interventional thrombolysis, angioplasty, stenting, and post-operative monitoring. Results: The efficacy and safety of the comprehensive treatment were observed for a follow-up period of 6-12 months. The treatment was 100% effective; patient results indicated no serious bleeding, acute pulmonary embolism, or death after surgery. Conclusion: The combination of intravenous and healthy side femoral vein puncture and directed thrombolysis to treat acute lower limb deep vein thrombosis is safe, effective, and minimally invasive while still achieving a good therapeutic effect.

Indexed as

deep vein thrombosisinterventionalstent implantationuninterrupted thrombolytic

Identifiers

PMID37342406
PMCPMC10278963
OpenAlexW4380997015

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.