Evidence map›Paper›PMID 38400918›Full record

ArticleActa neurochirurgica2024

An objective skill assessment framework for microsurgical anastomosis based on ALI scores.

Soheil Gholami, Anaëlle Manon, Kunpeng Yao, Aude Billard, Torstein R Meling

Abstract read
In one paragraph

Article in Acta neurochirurgica, 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
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  3. Article
  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.

Soheil GholamiLearning Algorithms and Systems Laboratory (LASA), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. soheil.gholami@epfl.ch.ORCID 0000-0001-5050-319X
Anaëlle ManonLearning Algorithms and Systems Laboratory (LASA), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Kunpeng YaoLearning Algorithms and Systems Laboratory (LASA), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0000-0002-5839-081X
Aude BillardLearning Algorithms and Systems Laboratory (LASA), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.ORCID 0000-0002-7076-8010
Torstein R MelingDepartment of Neurosurgery, The National Hospital of Denmark, Rigshospitalet, Copenhagen, Denmark.ORCID 0000-0001-6595-0873

Funding

SNSF 9824
6 · The paper itself

Abstract

introductionThe current assessment and standardization of microsurgical skills are subjective, posing challenges in reliable skill evaluation. We aim to address these limitations by developing a quantitative and objective framework for accurately assessing and enhancing microsurgical anastomosis skills among surgical trainees. We hypothesize that this framework can differentiate the proficiency levels of microsurgeons, aligning with subjective assessments based on the ALI score.

methodsWe select relevant performance metrics from the literature on laparoscopic skill assessment and human motor control studies, focusing on time, instrument kinematics, and tactile information. This information is measured and estimated by a set of sensors, including cameras, a motion capture system, and tactile sensors. The recorded data is analyzed offline using our proposed evaluation framework. Our study involves 12 participants of different ages ([Formula: see text] years) and genders (nine males and three females), including six novice and six intermediate subjects, who perform surgical anastomosis procedures on a chicken leg model.

resultsWe show that the proposed set of objective and quantitative metrics to assess skill proficiency aligns with subjective evaluations, particularly the ALI score method, and can effectively differentiate novices from more proficient microsurgeons. Furthermore, we find statistically significant disparities, where microsurgeons with intermediate level of skill proficiency surpassed novices in both task speed, reduced idle time, and smoother, briefer hand displacements.

conclusionThe framework enables accurate skill assessment and provides objective feedback for improving microsurgical anastomosis skills among surgical trainees. By overcoming the subjectivity and limitations of current assessment methods, our approach contributes to the advancement of surgical education and the development of aspiring microsurgeons. Furthermore, our framework emerges to precisely distinguish and classify proficiency levels (novice and intermediate) exhibited by microsurgeons.

Indexed as

Clinical CompetenceLaparoscopyAnastomosis, SurgicalFemaleHumansMaleMicrosurgeryComputer-assisted skill assessmentMicrosurgeryObjective skill assessmentQuantitative skill assessmentSkill acquisition

Identifiers

PMID38400918
PMCPMC11408545

What OpenQuestion holds

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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.