Evidence map›Paper›PMID 35136539›Full record

ReviewJournal of healthcare engineering

Clinical Manifestations of Inferior Vena Cava Injuries and the Progress of Emergency Treatment.

Chao Liu, Hao Zhang, Shaotao Xiang, Liang Liu

RetractedOpen access · hybridAbstract readReviewRetracted Publication
In one paragraph

Review in Journal of healthcare engineering. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 29% 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

5 citing papers in PubMed, 4 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Chao LiuDepartment of General Surgery, Daocheng County People's Hospital, Ganzi Tibetan Autonomous Prefecture, Ganzi 627750, Sichuan, China.
Hao ZhangDepartment of Orthopedics, Second People's Hospital of Yuhang District, Hangzhou 311100, Zhejiang, China.ORCID https://orcid.org/0000-0002-6474-3458
Shaotao XiangDepartment of Cardiovascular Medicine, Xuanhan County Hospital of Traditional Chinese Medicine, Dazhou 636150, Sichuan, China.
Liang LiuDepartment of Urology, Baoding First Central Hospital, Baoding 071000, Hebei, China.
Baoding People's Hospital · CNFirst People's Hospital of Yuhang District · CNTibet Autonomous Region People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, clinical manifestations of inferior vena cava injuries and the progress of emergency treatment are presented. Inferior vena cava (IVC) is the large vein returning venous blood from the lower limbs and pelvic and abdominal cavities to the right atrium of the heart. The clinical manifestations of IVC injuries include shock, progressive hemorrhage, air embolism, retroperitoneal hematoma, active bleeding, and hemoperitoneum. The patients may be combined or not combined with injuries to other organs or even die. Routine examination methods for IVC injuries include general examination, color Doppler ultrasound, abdominal contrast-enhanced CT, magnetic resonance spectroscopic imaging (MRSI), and IVC angiography. These examinations are usually performed to confirm the diagnosis. Surgical treatment is the primary emergency treatment for this condition. Increasing the blood volume and symptomatic treatment are auxiliary treatments. The surgeries and repairs for IVC injuries are currently under investigation. Experimental results have verified the exceptional performance of the proposed scheme.

Indexed as

Vena Cava FiltersAngiographyEmergency TreatmentHumansUltrasonography, Doppler, ColorVena Cava, Inferior

Identifiers

PMID35136539
PMCPMC8818408
OpenAlexW4210287459

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.