Evidence map›Paper›PMID 39161409›Full record

ArticleFrontiers in medicine2024

Learning curve of ovarian cystectomy by vaginal natural orifice transluminal endoscopic surgery: a cumulative sum analysis.

Kailiang Tan, Liufei Wei, Zengmei Deng, Desheng Yao, Li Jiang

Abstract read
In one paragraph

Article in Frontiers in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Review
  4. 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

5 authors.

Kailiang TanDepartment of Gynecological Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China.
Liufei WeiDepartment of Obstetrics and Gynecology, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Zengmei DengDepartment of Obstetrics and Gynecology, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Desheng YaoDepartment of Gynecological Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China.
Li JiangDepartment of Obstetrics and Gynecology, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To identify the learning curve in ovarian cystectomy by vaginal natural orifice transluminal endoscopic surgery. Methods: Data consist of consecutively ordered patients who underwent ovarian cystectomy via vaginal natural orifice transluminal endoscopic surgery between May 2020 and June 2023. The learning curve of ovarian cystectomy via vaginal natural orifice transluminal endoscopic surgery was measured in terms of the operating time adjusted by multivariate linear regression. A cumulative sum analysis was performed to establish the learning curve. Patients' characteristics and surgical outcomes were compared based on the inflection points of this curve. Results: The learning curve was divided into two unique phases: phase 1 (1-26 patients), and phase 2 (27-40 patients). The expected operating time in phase 2 was shorter than in phase 1 (86.4 ± 11.2 min vs. 102.0 ± 22.7 min, Conclusion: Proficiency in ovarian cystectomy by vaginal natural orifice transluminal endoscopic surgery was achieved after 26 surgeries based on cumulative sum analysis. These findings may provide insight for structured training programs of ovarian cystectomy via vaginal natural orifice transluminal endoscopic surgery.

Indexed as

cumulative sum analysisendoscopylearning curveovarian cystectomyvNOTES

Identifiers

PMID39161409
PMCPMC11330758

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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.