Evidence map›Paper›PMID 31892789›Full record

ArticleJSLS : Journal of the Society of Laparoendoscopic Surgeons

Single-Incision Hysterectomy Outcomes With and Without Robotic Assistance.

Yiming Zhang, Jaden R Kohn, Xiaoming Guan

Open access · hybridAbstract read
In one paragraph

Article in JSLS : Journal of the Society of Laparoendoscopic Surgeons. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 17% 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
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 at 2 institutions in 2 countries.

Yiming ZhangDepartment of Obstetrics & Gynecology, Baylor College of Medicine, Houston, Texas, USA.
Jaden R KohnDepartment of Obstetrics & Gynecology, Baylor College of Medicine, Houston, Texas, USA.
Xiaoming GuanDepartment of Obstetrics & Gynecology, Baylor College of Medicine, Houston, Texas, USA.
Baylor College of Medicine · USJinan Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the differences in operative time and postoperative complications for total laparoscopic hysterectomy (TLH) performed using conventional laparoendoscopic single-site surgery (LESS) versus a robotic-assisted LESS approach.

methodsA retrospective study was conducted of all cases of conventional LESS TLH (n = 47) and robotic LESS TLH (n = 129) for benign gynecologic conditions performed from November 2014 to October 2017. Patient characteristics, operative time for hysterectomy, estimated blood loss, duration of hospitalization, and short-term postoperative complications were compared using appropriate parametric and nonparametric statistical tests.

resultsConventional LESS TLH cases had a 16.36-minute longer mean operative time for hysterectomy (

conclusionRobotic single-incision laparoscopy can result in decreased operative time compared to a conventional LESS approach. Robotic-assisted and conventional LESS are similar in rate of postoperative complications, if performed by surgeons with abundant LESS experience.

Indexed as

LaparoscopyRobotic Surgical ProceduresAdultAgedCohort StudiesFemaleHumansHysterectomyMiddle AgedOperative TimePostoperative ComplicationsRetrospective StudiesYoung AdultLaparoendoscopic single-site surgeryOperative timePostoperative complicationsRobotic-assisted surgeryTotal laparoscopic hysterectomy

Identifiers

PMID31892789
PMCPMC6924503
OpenAlexW2998122725

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.