Evidence map›Paper›PMID 38362277›Full record

ArticleFrontiers in endocrinology2024

Optimizing robotic thyroid surgery: lessons learned from an retrospective analysis of 104 cases.

Bo Wang, Jia-Fan Yu, Wei Ao, Jun Wang, Xin-Yi Guo, Meng-Yao Li, Wen-Yu Huang, Chi-Peng Zhou, Shou-Yi Yan, Li-Yong Zhang and 4 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
4.0field-weighted citation impact, top 7% 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, 2 syntheses or guidelines pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Learning Curves in Robotic Thyroid Surgery: A Systematic Review Comparing Transoral, Axillary, and Facelift Approaches.Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale
    Pooled it
  3. Article
  4. Article
  5. 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

14 authors at 2 institutions in 1 country.

Bo Wang *Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China.
Jia-Fan Yu *Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China.
Wei Ao *Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China.
Jun WangDepartment of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China.
Xin-Yi GuoDepartment of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China.
Meng-Yao LiDepartment of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China.
Wen-Yu HuangDepartment of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China.
Chi-Peng ZhouDepartment of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China.
Shou-Yi YanDepartment of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China.
Li-Yong ZhangDepartment of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China.
Si-Si WangDepartment of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China.
Shao-Jun CaiDepartment of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China.
Si-Ying LinDepartment of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China.
Wen-Xin ZhaoDepartment of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China.
Union Hospital · CNFujian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Robotic assistance in thyroidectomy is a developing field that promises enhanced surgical precision and improved patient outcomes. This study investigates the impact of the da Vinci Surgical System on operative efficiency, learning curve, and postoperative outcomes in thyroid surgery. Methods: We conducted a retrospective cohort study of 104 patients who underwent robotic thyroidectomy between March 2018 and January 2022. We evaluated the learning curve using the Cumulative Sum (CUSUM) analysis and analyzed operative times, complication rates, and postoperative recovery metrics. Results: The cohort had a mean age of 36 years, predominantly female (68.3%). The average body mass index (BMI) was within the normal range. A significant reduction in operative times was observed as the series progressed, with no permanent hypoparathyroidism or recurrent laryngeal nerve injuries reported. The learning curve plateaued after the 37th case. Postoperative recovery was consistent, with no significant difference in hospital stay duration. Complications were minimal, with a noted decrease in transient vocal cord palsy as experience with the robotic system increased. Conclusion: Robotic thyroidectomy using the da Vinci system has demonstrated a significant improvement in operative efficiency without compromising safety. The learning curve is steep but manageable, and once overcome, it leads to improved surgical outcomes and high patient satisfaction. Further research with larger datasets and longer follow-up is necessary to establish the long-term benefits of robotic thyroidectomy.

Indexed as

RoboticsRobotic Surgical ProceduresThyroid NeoplasmsAdultFemaleHumansMaleRetrospective Studiesda Vinci surgical systemlearning curveoperative efficiencypostoperative outcomesrobotic thyroidectomythyroid surgery

Identifiers

PMID38362277
PMCPMC10867960
OpenAlexW4391359194

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.