Evidence map›Paper›PMID 27994668›Full record

ArticleJournal of Cancer2016

The learning curves of robotic and three-dimensional laparoscopic surgery in cervical cancer.

Xue-Lian Li, Dan-Feng Du, Hua Jiang

Open access · goldAbstract read
In one paragraph

Article in Journal of Cancer, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-weighted citation impact, top 29% 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

5 citing papers in PubMed, 10 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

3 authors at 1 institution in 1 country.

Xue-Lian LiDepartment of Gynecology, Obstetrics & Gynecology Hospital, Fudan University, Shanghai, China.; Shanghai Key Laboratory of Female Reproductive Endocrine-Related Diseases, Shanghai, China.
Dan-Feng DuDepartment of Gynecology, Obstetrics & Gynecology Hospital, Fudan University, Shanghai, China.; Shanghai Key Laboratory of Female Reproductive Endocrine-Related Diseases, Shanghai, China.
Hua JiangDepartment of Gynecology, Obstetrics & Gynecology Hospital, Fudan University, Shanghai, China.; Shanghai Key Laboratory of Female Reproductive Endocrine-Related Diseases, Shanghai, China.
Obstetrics and Gynecology Hospital of Fudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 3D laparoscopy systems and robotic systems have been introduced into clinical practice for a few years. But the comparison of robotic and 3D laparoscopic gynecologic surgery is still needed.

objectiveTo retrospectively compare the learning curves of robotic and 3D laparoscopic hysterectomy and pelvic lymphadenectomy in cervical cancer. STUDY

designThe operational duration, blood loss, peritoneal drainage of first 24 hours after operation, total hospitalization days, hospitalization days after operation, lymph nodes collected, learning curves and cost of robotic and 3D laparoscopic hysterectomy and pelvic lymphadenectomy in cervical cancer performed by one experienced surgeon were studied.

resultsThere was one surgeon who performed 37 cases of robotic and 24 cases of 3D laparoscopic hysterectomy and pelvic lymphadenectomy, and the turning point of learning curves was case 13

conclusionsThe turning point of the learning curve of 3D laparoscopic hysterectomy and pelvic lymphadenectomy is earlier than that of robotic sugery in patients with cervical cancer, and there is no obvious benefit from robotic surgery than 3D surgery in the terms of short-term medical index and hospitalization cost.

Indexed as

3D laparoscopyhysterectomy and pelvic lymphadenectomy.learning curverobotic laparoscopy

Identifiers

PMID27994668
PMCPMC5166541
OpenAlexW2566527617

What OpenQuestion holds

Textmetadata
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.