Evidence map›Paper›PMID 35781111›Full record

ArticleFacts, views & vision in ObGyn2022

Initial experience with vNOTES hysterectomy for benign conditions in a French university hospital.

C Baron, A Netter, C Tourette, A Pivano, A Agostini, P Crochet

Open access · bronzeAbstract read
In one paragraph

Article in Facts, views & vision in ObGyn, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

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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

6 authors at 1 institution in 2 countries.

C Baron
A Netter
C Tourette
A Pivano
A Agostini
P Crochet
Centre National de la Recherche Scientifique · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Natural orifice transluminal endoscopic surgery by the vaginal route (vNOTES) is a new approach to performing hysterectomy. Clinical outcomes must be evaluated in centres that have started performing this technique. Objectives: To compare operative outcomes between vNOTES hysterectomy and laparoscopic hysterectomy during the introduction of the vNOTES approach in a teaching hospital. Material and Methods: A retrospective study was conducted from November 2019 to May 2021 at a French academic hospital in Marseille. The included patients underwent total hysterectomy for benign indications by vNOTES or conventional laparoscopy. Main outcome measures: Operative time, uterus weight, intraoperative complications, and postoperative complications according to the Clavien-Dindo classification. Results: Eighty-six patients underwent hysterectomy according to the selected criteria: 36 procedures were performed by vNOTES and 50 by laparoscopy. The mean operative time was shorter in the vNOTES group than in the laparoscopy group [116 min versus 149 min; p=0.003]. The mean uterus weight was not different between the vNOTES group and the laparoscopy group (238g versus 281g; p=0.572). Laparo-conversion occurred in one case in the vNOTES group (2.7%) and three cases in the laparoscopy group (3.4%). One Grade III postoperative complication occurred in the laparoscopy group, and no severe complication occurred in the vNOTES group. Conclusion: Operative outcomes of the vNOTES hysterectomy were favourable and support good feasibility without additional morbidity compared to laparoscopy. What is new?: During the introduction period of the vNOTES hysterectomy technique in a teaching hospital, reassuring operative outcomes and a low rate of complications were observed.

Identifiers

PMID35781111
PMCPMC10191712
OpenAlexW4283784555

What OpenQuestion holds

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LicenceCC BY
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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.