Literature DB >> 24967763

CUSUM method for construction of trainee spinal ultrasound learning curves following standardised teaching.

A J Deacon1, N S Melhuishi, N C S Terblanche.   

Abstract

Spinal ultrasonography is a promising aid for epidural insertion. We aimed to determine the learning curve of spinal ultrasonography tasks and the number of training scans required to reach competency after undergoing standardised step-wise teaching. Trainees were required to complete a minimum of 60 assessed scans on selected non-pregnant models following attendance at two training sessions, with feedback from an expert after each scan. Learning curves were plotted using the non-risk cumulative summation technique and an acceptable failure rate of 20%. Five trainees completed between 65 and 75 scans each. All trainees were competent at identifying a randomly assigned intervertebral space after a median of five scans (range one to nine) and at measuring the depth from skin to the posterior complex after a median of 10 scans (range 1 to 42). Two trainees were competent at marking an ideal needle insertion point after 55 scans, while three trainees did not attain competency. All trainees were competent after 60 scans if the tolerance was changed from five to eight millimetre for marking the needle insertion point. The average time taken to complete a scan was 163 seconds. Our study showed that after a standardised educational intervention, anaesthetic trainees are able to identify a lumbar interlaminar space easily and can measure the depth to the posterior complex after a reasonable number of additional practice scans, but experienced difficulty accurately marking the needle insertion point whilst using spinal ultrasonography. We confirmed that it was hard to achieve competency in all aspects of spinal ultrasonography, based on assessment using our predefined competency criteria.

Entities:  

Keywords:  education; epidural anaesthesia; feedback; learning curves; lumbar vertebrae; ultrasonography; ultraviolet light

Mesh:

Year:  2014        PMID: 24967763     DOI: 10.1177/0310057X1404200409

Source DB:  PubMed          Journal:  Anaesth Intensive Care        ISSN: 0310-057X            Impact factor:   1.669


  9 in total

Review 1.  Ultrasound diagnosis and therapeutic intervention in the spine.

Authors:  Adil S Ahmed; Raahul Ramakrishnan; Vignesh Ramachandran; Shyam S Ramachandran; Kevin Phan; Erik L Antonsen
Journal:  J Spine Surg       Date:  2018-06

2.  Recommendations on the Use of Ultrasound Guidance for Adult Lumbar Puncture: A Position Statement of the Society of Hospital Medicine.

Authors:  Nilam J Soni; Ricardo Franco-Sadud; Ketino Kobaidze; Daniel Schnobrich; Gerard Salame; Joshua Lenchus; Venkat Kalidindi; Michael J Mader; Elizabeth K Haro; Ria Dancel; Joel Cho; Loretta Grikis; Brian P Lucas
Journal:  J Hosp Med       Date:  2019-06-10       Impact factor: 2.960

3.  Imaging Performance of a Handheld Ultrasound System With Real-Time Computer-Aided Detection of Lumbar Spine Anatomy: A Feasibility Study.

Authors:  Mohamed Tiouririne; Adam J Dixon; F William Mauldin; David Scalzo; Arun Krishnaraj
Journal:  Invest Radiol       Date:  2017-08       Impact factor: 6.016

4.  Feasibility of Spinal Anesthesia Placement Using Automated Interpretation of Lumbar Ultrasound Images: A Prospective Randomized Controlled Trial.

Authors:  Priyanka Singla; Adam J Dixon; Jessica L Sheeran; David Scalzo; Frank W Mauldin; Mohamed Tiouririne
Journal:  J Anesth Clin Res       Date:  2019-02-25

5.  Proper training and use of ultrasonography facilitates lumbar puncture.

Authors:  Geert-Jan van Geffen; Rein Ketelaars; Jörgen Bruhn
Journal:  Scand J Trauma Resusc Emerg Med       Date:  2017-12-20       Impact factor: 2.953

6.  Detection of Rotator Cuff Tears by Ultrasound: How Many Scans Do Novices Need to Be Competent?

Authors:  Dong Min Kim; Jae-Seong Seo; In-Ho Jeon; Changho Cho; Kyoung Hwan Koh
Journal:  Clin Orthop Surg       Date:  2021-11-15

7.  Machine learning approach to needle insertion site identification for spinal anesthesia in obese patients.

Authors:  Jason Ju In Chan; Jun Ma; Yusong Leng; Kok Kiong Tan; Chin Wen Tan; Rehena Sultana; Alex Tiong Heng Sia; Ban Leong Sng
Journal:  BMC Anesthesiol       Date:  2021-10-18       Impact factor: 2.217

8.  Use of artificial intelligence as a didactic tool to improve ejection fraction assessment in the emergency department: A randomized controlled pilot study.

Authors:  Ziv Dadon; Adi Butnaru; David Rosenmann; Liat Alper-Suissa; Michael Glikson; Evan A Alpert
Journal:  AEM Educ Train       Date:  2022-04-01

9.  Ultrasound Block of the Medial Branch: Learning the Technique Using CUSUM Curves.

Authors:  Marta Putzu; Maurizio Marchesini
Journal:  Anesth Essays Res       Date:  2022-03-08
  9 in total

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