Objective assessment of cesarean section suturing techniques using a uterine simulator

H Hikari Nakato J Jota Maki C Chiaki Kuriyama S Shujiro Sakata K Keiichi Oishi A Ayano Suemori H Hikaru Ooba T Tomohiro Mitoma M Masakazu Kato S Sakurako Mishima A Akiko Ohira S Satoe Kirino E Eriko Eto H Hisashi Masuyama

Abstract

Abstract Cesarean wound healing is influenced by surgeon experience, suture type, and technique. This study utilized a simulation model to quantify these effects. Obstetricians–gynecologists and junior residents performed two-layer continuous suturing on uterine models, forming eight groups based on experience level (expert, novice), suture type (conventional, barbed), and technique (Albert–Lembert, layer-to-layer). The ideal wound condition was defined as that achieved by an expert using barbed sutures and the layer-to-layer technique. Wound characteristics were quantified and compared to this ideal. Experts using barbed sutures in Albert–Lembert suturing showed higher wound density but greater deformation and larger endometrial openings (both P < 0.01). Novices using barbed sutures in Albert–Lembert suturing showed similar wound density but significantly greater deformation and opening (both P < 0.01). Novices using conventional sutures in layer-to-layer suturing showed the lowest wound density and longest suturing time (both P < 0.01). Notably, novices using barbed sutures achieved wound characteristics comparable to experts using conventional sutures in Albert–Lembert suturing and results closer to the ideal in layer-to-layer suturing. These findings establish a quantifiable standard for cesarean suturing and suggest that optimizing suture types and techniques may help compensate for differences in surgical expertise.

Article Details

Volume / Issue Vol. 16, Issue 1
Published February 05, 2026
ISSN 2045-2322
Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (14)

H

Hikari Nakato

J

Jota Maki

C

Chiaki Kuriyama

S

Shujiro Sakata

K

Keiichi Oishi

A

Ayano Suemori

H

Hikaru Ooba

T

Tomohiro Mitoma

M

Masakazu Kato

S

Sakurako Mishima

A

Akiko Ohira

S

Satoe Kirino

E

Eriko Eto

H

Hisashi Masuyama