Evidence map›Paper›PMID 42211918›Full record

ArticleGynecology and pelvic medicine2025

Single port laparoscopic layered processing technique for large hysterectomy.

Ping Cheng, Mei Kong, Junzi Wei

Abstract read
In one paragraph

Article in Gynecology and pelvic medicine, 2025. 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
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.

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

3 authors.

Ping ChengGynecology Department, Urumqi Maternal and Child Health Hospital, Urumqi, China.
Mei KongGynecology Department, Urumqi Maternal and Child Health Hospital, Urumqi, China.
Junzi WeiGynecology Department, Urumqi Maternal and Child Health Hospital, Urumqi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article introduces a case of successful single port laparoscopic hysterectomy using layered technique (layered technique refers to the technique of cutting open the peritoneal layer and the connective tissue below it layer by layer, fully exposing the blood vessels, ureters, and other organs and tissues below). The patient is a 44-year-old female with continuous worsening of dysmenorrhea for 4 years and an increase in menstrual flow for 3 months. Upon examination, it was found that the uterus was 16 weeks pregnant and diagnosed with adenomyosis with moderate anemia. After sufficient preparation, the patient underwent single port laparoscopic total hysterectomy, bilateral salpingectomy, and pelvic adhesion separation surgery. During the surgery, the doctor used a layered technique, which involves cutting open the peritoneal layer and its underlying connective tissue layer by layer, fully exposing blood vessels, ureters, and other organs and tissues to ensure the safety and accuracy of the surgery. The surgery took 1 hour, with a blood loss of approximately 20 mL, and the process went smoothly. Patients can eat and move around 6-8 hours after surgery. For patients who need to have their uterus removed, single port laparoscopic technology is a new surgical option that can ensure surgical effectiveness, reduce postoperative discomfort, shorten recovery time, and improve patient satisfaction. This layered technique is safe, effective, and feasible, with the advantages of reducing surgical difficulty, ensuring safety, and beauty. It is worth promoting clinical practice, and the team will further explore more surgical techniques in the future.

Indexed as

complete hysterectomy for giant uteruslayered technologySingle port laparoscope

Identifiers

PMID42211918
PMCPMC13215076

What OpenQuestion holds

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Registered trials

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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.