Evidence map›Paper›PMID 24592096›Full record

ArticleJournal of the Turkish German Gynecological Association2013

Conventional box model training improves laparoscopic skills during salpingectomy on LapSim: a randomized trial.

Ali Akdemir, Ahmet Mete Ergenoğlu, Ahmet Özgür Yeniel, Fatih Sendağ

Abstract read
In one paragraph

Article in Journal of the Turkish German Gynecological Association, 2013. 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
–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

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

  1. Pooled it
  2. Article
  3. Application of virtual reality technology in clinical medicine.American journal of translational research · 2017
    Review
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

4 authors.

Ali AkdemirDepartment of Obstetrics and Gynecology, Ege University Medical Faculty, İzmir, Turkey.
Ahmet Mete ErgenoğluDepartment of Obstetrics and Gynecology, Ege University Medical Faculty, İzmir, Turkey.
Ahmet Özgür YenielDepartment of Obstetrics and Gynecology, Ege University Medical Faculty, İzmir, Turkey.
Fatih SendağDepartment of Obstetrics and Gynecology, Ege University Medical Faculty, İzmir, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveBox model trainers have been used for many years to facilitate the improvement of laparoscopic skills. However, there are limited data available on box trainers and their impact on skill acquisition, assessed by virtual reality systems. MATERIAL AND

methodsTwenty-two Postgraduate Year 1 gynecology residents with no laparoscopic experience were randomly divided into one group that received structured box model training and a control group. All residents performed a salpingectomy on LapSim before and after the training. Performances before and after the training were assessed using LapSim and were recorded using objective parameters, registered by a computer system (time, damage, and economy of motion scores).

resultsThere were initially no differences between the two groups. The box trainer group showed significantly greater improvement in time (p=0.01) and economy of motion scores (p=0.001) compared with the control group post-training.

conclusionThe present study confirmed the positive effect of low cost box model training on laparoscopic skill acquisition as assessed using LapSim. Novice surgeons should obtain practice on box trainers and teaching centers should make efforts to establish training laboratories.

Indexed as

box trainerLaparoscopyLapSimskill

Identifiers

PMID24592096
PMCPMC3928414

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.