The vestibular schwannoma surgery learning curve mapped by the cumulative summation test for learning curve.

Otol Neurotol

Department of Otolaryngology, Westmead Hospital, University of Sydney, Sydney, New South Wales, Australia.

Published: October 2013

Objective: To demonstrate and quantify the learning curve for microsurgical excision of vestibular schwannoma in a newly formed neurootologic team by using the cumulative summation test for learning curve (LC-CUSUM). To secondarily identify the factors influencing postoperative facial nerve outcome.

Study Design: Retrospective review.

Setting: Tertiary referral center.

Patients: Between 1999 and 2011, 153 consecutive cases of vestibular schwannoma excision.

Intervention: One-hundred and fifty-three patients underwent excision of vestibular schwannoma.

Main Outcome Measures: Facial nerve outcomes were assessed using the House-Brackmann (HB) facial nerve grading system. Postoperative facial nerve outcomes at 12 months were analyzed using the LC-CUSUM method with HB Grades I to III being defined as successful outcomes. The factors that influence postoperative facial nerve outcome were analyzed.

Results: The constructed learning curve shows a gradual improvement in facial nerve outcomes. The learning curve crossed the derived LC-CUSUM barrier at the 56th procedure, indicating that sufficient evidence had accumulated to demonstrate that the surgeon had achieved optimal outcomes at this point. Tumor size (p = 0.008) and surgical approach (p = 0.005) were 2 additional significant factors influencing postoperative facial nerve outcome.

Conclusion: The learning curve is evident in this series of microsurgical excisions of vestibular schwannoma. A newly formed team needs to perform at least 56 cases to gain sufficient experience to accomplish optimal results. Position along the learning curve, tumor size, and familiarity with a preferred surgical approach are the factors, which dominated facial nerve outcome. We recommend the use of LC-CUSUM test for learning curve analysis.

Download full-text PDF

Source
http://dx.doi.org/10.1097/MAO.0b013e31829bfc54DOI Listing

Publication Analysis

Top Keywords

learning curve
36
facial nerve
32
vestibular schwannoma
16
postoperative facial
16
test learning
12
nerve outcomes
12
learning
9
curve
9
cumulative summation
8
summation test
8

Similar Publications

Background: Large language models (LLMs) have been proposed as valuable tools in medical education and practice. The Chinese National Nursing Licensing Examination (CNNLE) presents unique challenges for LLMs due to its requirement for both deep domain-specific nursing knowledge and the ability to make complex clinical decisions, which differentiates it from more general medical examinations. However, their potential application in the CNNLE remains unexplored.

View Article and Find Full Text PDF

Background: Falls are among the most prevalent workplace accidents, necessitating thorough screening for susceptibility to falls and customization of individualized fall prevention programs. The aim of this study was to develop and validate a high fall risk prediction model using machine learning (ML) and video-based first three steps in middle-aged workers.

Methods: Train data (n=190, age 54.

View Article and Find Full Text PDF

Background: Neoadjuvant chemotherapy is standard for advanced esophageal squamous cell carcinoma, though often ineffective. Therefore, predicting the response to chemotherapy before treatment is desirable. However, there is currently no established method for predicting response to neoadjuvant chemotherapy.

View Article and Find Full Text PDF

Introduction: A large number of middle-aged and elderly patients have an insufficient understanding of osteoporosis and its harm. This study aimed to establish and validate a convolutional neural network (CNN) model based on unenhanced chest computed tomography (CT) images of the vertebral body and skeletal muscle for opportunistic screening in patients with osteoporosis.

Materials And Methods: Our team retrospectively collected clinical information from participants who underwent unenhanced chest CT and dual-energy X-ray absorptiometry (DXA) examinations between January 1, 2022, and December 31, 2022, at four hospitals.

View Article and Find Full Text PDF

This study applied cumulative sum (CUSUM) analysis to evaluate trends in operative time and blood loss, It aims to identify key milestones in mastering extraperitoneal single-site robotic-assisted radical prostatectomy (ss-RARP). A cohort of 100 patients who underwent ss-RARP, performed by a single surgeon at the First Affiliated Hospital of Guangzhou Medical University between March 2021 and June 2023, was retrospectively analyzed. To evaluate the learning curve, the CUSUM (Cumulative Sum Control Chart) technique was applied, revealing the progression and variability over time.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!