Evidence map›Paper›PMID 37160507›Full record

ReviewLangenbeck's archives of surgery2023

Variant anatomy of non-recurrent laryngeal nerve: when and how should it be taught in surgical residency?

Victoria Zheng, Reshma Rajeev, Diluka Pinto, Mechteld Christine de Jong, Dinesh Kumar Sreenivasan, Rajeev Parameswaran

Abstract readReview
PubMed Publisher
In one paragraph

Review in Langenbeck's archives of surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

6 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Presentation of Arteria Lusoria with Non Recurent Laryngeal Nerve.Indian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India · 2024
    Article
  4. Article
  5. Article
  6. 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

6 authors at 4 institutions in 2 countries.

Victoria ZhengYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Reshma RajeevUniversity of Buckingham Medical School, Buckingham, UK.
Diluka PintoDivision of Endocrine Surgery, National University Hospital, Lower Kent Ridge Road, Buckingham, Singapore.
Mechteld Christine de JongDivision of Endocrine Surgery, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
Dinesh Kumar SreenivasanDepartment of Anatomy, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Rajeev ParameswaranDivision of Endocrine Surgery, National University Hospital, Lower Kent Ridge Road, Buckingham, Singapore. surrp@nus.edu.sg.ORCID https://orcid.org/0000-0002-3318-0357
National University of Singapore · SGLeeds Teaching Hospitals NHS Trust · GBNational University Hospital · SGUniversity of Buckingham · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionWhile the performance of a thyroidectomy is generally associated with a low risk of injury to the recurrent laryngeal nerve (RLN), the presence of a non-recurrent nerve (NRLN) increases the risk of this complication. Generally, the intraoperative detection via visual appreciation of variant anatomy of the RLN has been regarded as poor, possibly due to a lack of knowledge of both the normal and aberrant anatomy of the RLN. MATERIALS AND

methodsArticles for the review were searched through PubMed using the search terms and their combinations: "non-recurrent laryngeal nerve," "thyroidectomy," "injury," "palsy," "variant anatomy," and "residency," from January 1, 2000, to December 2022. Papers considered for the review were the articles published in English, with additional classic and articles of surgical importance retrieved from the reference list of papers. Only papers relevant to the scope of the review were considered for this review.

findingsThe NRLN has been found to be associated with concurrent vascular abnormalities, such as the presence of an aberrant right subclavian artery (ARSA) or an arteria lusoria originating from the aortic arch. However, it seems that both the normal as well as aberrant anatomy of the RLN is currently not emphasized enough during postgraduate surgical training. With the increased use of intraoperative neuromonitoring (IONM), detection of NRLN has become possible through appropriate neural mapping during thyroid surgery, besides other pointers such as visualization during surgery, computerised tomography, and duplex ultrasound scans to visualize the variant vascular anatomy. There is also a possible role for cadaveric courses, either during medical school or in a post-graduate setting-adapted to the student's level to teach the variant anatomy. With the development of newer techniques such as artificial intelligence, there are potential new options for teaching and training anatomy in the near future. CONCLUSIONS AND RELEVANCE: Adequate knowledge of the normal and aberrant anatomy of the RLN remains essential for the best outcomes in thyroid surgery, even in the era of the IONM. Moving forward, the knowledge of (aberrant) anatomy should be made an integral part of the core competencies of both medical students and surgical trainees. It is imperative that leaders of the different field work closely together to combine their knowledge towards providing their trainees with the best possible training options.

Indexed as

Artificial IntelligenceInternship and ResidencyCardiovascular AbnormalitiesHumansRecurrent Laryngeal NerveSubclavian ArteryThyroidectomyLaryngeal nerveResidencyTeachingVariant anatomy

Identifiers

PMID37160507
OpenAlexW4376132559

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.