Evidence map›Paper›PMID 35365458›Full record

ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2022

[Robot-assisted laparoscopic total hysterectomy in a patient with giant uterine fibroids and complex pelvic adhesions: a case report].

M Chen, N Wang, Y Ye, M Wang, Z Li, Y Meng, M Ye

Open access · greenAbstract readCase Reports
In one paragraph

Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2022. 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 96% 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

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

7 authors at 1 institution in 1 country.

M ChenDepartment of Obstetrics and Gynecology, General Hospital of PLA, Beijing 100853, China.
N WangDepartment of Obstetrics and Gynecology, General Hospital of PLA, Beijing 100853, China.
Y YeDepartment of Obstetrics and Gynecology, General Hospital of PLA, Beijing 100853, China.
M WangDepartment of Obstetrics and Gynecology, General Hospital of PLA, Beijing 100853, China.
Z LiDepartment of Obstetrics and Gynecology, General Hospital of PLA, Beijing 100853, China.
Y MengDepartment of Obstetrics and Gynecology, General Hospital of PLA, Beijing 100853, China.
M YeDepartment of Obstetrics and Gynecology, General Hospital of PLA, Beijing 100853, China.
Chinese PLA General Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We report a case of giant hysteromyoma and complex pelvic adhesion treated by robotic assisted laparoscopic total hysterectomy and bilateral salpingectomy. The patient was diagnosed with uterine fibroids after physical examination in 1998 but did not receive any treatment, and regular examinations reported progressive growth of the fibroids. Ultrasound suggested multiple uterine fibroids, and pelvic MRI indicated large uterine fibroids with bleeding. Robot-assisted laparoscopic total hysterectomy and bilateral salpingectomy were performed after relevant examinations, and the operation was completed smoothly. The patient was discharged 4 days after surgery with good appearance of the abdominal wall and good recovery during the follow-up. With its unique advantages, robot-assisted laparoscopy provides a minimally invasive surgical approach for giant hysterectomy with complex pelvic adhesions.

Indexed as

LaparoscopyLeiomyomaRoboticsFemaleHumansHysterectomyUterushysterectomyminimally invasive surgeryrobotic surgery

Identifiers

PMID35365458
PMCPMC8983356
OpenAlexW4224090856

What OpenQuestion holds

Textmetadata
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.