Evidence map›Paper›PMID 37658426›Full record

ArticleJournal of orthopaedic surgery and research2023

Learning curve of tibial cortex transverse transport: a cumulative sum analysis.

Jun-Peng Liu, Xing-Chen Yao, Zi-Yu Xu, Xin-Ru Du, Hui Zhao

Abstract read
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Article in Journal of orthopaedic surgery and research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Jun-Peng Liu *Department of Orthopaedic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, China.
Xing-Chen Yao *Department of Orthopaedic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, China.
Zi-Yu XuDepartment of Orthopaedic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, China.
Xin-Ru DuDepartment of Orthopaedic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, China. duxinru@ccmu.edu.cn.
Hui ZhaoDepartment of Orthopaedic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, China. zhaohui_1@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to describe the learning curve of surgeons performing tibial cortex transverse transport (TTT) and explore its safety and effectiveness during the initial stages of surgeon's learning.

methodsThe clinical data of patients with diabetic foot ulcers classified as Wagner grade ≥ 2, who underwent TTT at our hospital from January 2020 to July 2021, were included in this retrospective analysis. The same physician performed all procedures. Patients were numbered according to the chronological order of their surgery dates. The cumulative sum and piecewise linear regression were used to evaluate the surgeon's learning curve, identify the cut-off point, and divide the patients into learning and mastery groups. A minimum follow-up period of 3 months was ensured for all patients. Baseline data, perioperative parameters, complications, and efficacy evaluation indicators were recorded and compared between the two groups.

resultsSixty patients were included in this study based on the inclusion and exclusion criteria. After completing 20 TTT surgeries, the surgeon reached the cut-off point of the learning curve. Compared to the learning group, the mastery group demonstrated a significant reduction in the average duration of the surgical procedure (34.88 min vs. 54.20 min, P < 0.05) along with a notable decrease in intraoperative fluoroscopy (9.75 times vs. 16.9 times, P < 0.05) frequency, while no significant difference was found regarding intraoperative blood loss (P = 0.318). Of the patients, seven (11.7%) experienced complications, with three (15%) and four cases (10%) occurring during the learning phase and the mastery phase, respectively. The postoperative ulcer area was significantly reduced, and the overall healing rate was 94.8%. Significant improvements were observed in postoperative VAS, ABI, and WIFI classification (P < 0.05). There were no significant differences in the occurrence of complications or efficacy indicators between the learning and mastery groups (P > 0.05).

conclusionSurgeons can master TTT after completing approximately 20 procedures. TTT is easy, secure, and highly efficient for treating foot ulcers. Furthermore, TTT's application by surgeons can achieve almost consistent clinical outcomes in the initial implementation stages, comparable to the mastery phase.

Indexed as

Learning CurveSurgeonsBlood Loss, SurgicalCerebral CortexHumansRetrospective StudiesAngiogenesisComplicationDiabetic foot ulcerLearning curveTibial cortex transverse transportUlcer healing

Identifiers

PMID37658426
PMCPMC10474655

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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.