A unique method for estimating the reliability learning curve of optic nerve sheath diameter ultrasound measurement

• Published in: Critical ultrasound journal Vol. 8; no. 1; pp. 9 - 5
• Main Authors: Zeiler, Frederick A., Ziesmann, Markus T., Goeres, Patrick, Unger, Bertram, Park, Jason, Karakitsos, Dimitrios, Blaivas, Michael, Vergis, Ashley, Gillman, Lawrence M.
• Format: Journal Article
• Language: English
• Published: Milan Springer Milan 01.12.2016; Springer Nature B.V; SpringerOpen
• Subjects: Critical Care Medicine; Diagnostic Radiology; Diameters; Education; Emergency Medicine; Imaging; Intensive; Interventional Radiology; Intracranial pressure; Knots; Learning curve; Learning curves; Medicine; Medicine & Public Health; Nerves; Optic nerve; Optic nerve sheath diameter; Original; Original Article; Point of Care ultrasound; Polynomials; Radiology; Reliability; Robot learning; Sheaths; Ultrasonic imaging; Ultrasonic methods; Ultrasound; Variability; Variance; Intracranial pressure; Learning curve; Education; Ultrasound; Point of Care ultrasound; Optic nerve sheath diameter
• ISSN: 2036-3176; 2036-7902; 2524-8987
• DOI: 10.1186/s13089-016-0044-x

Background Optic nerve sheath diameter (ONSD) measurement using ultrasound has been proposed as a rapid, non-invasive, point of care technique to estimate intra-cranial pressure (ICP). Ultrasonic measurement of the optic nerve sheath can be quite challenging and there is limited literature surrounding learning curves for this technique. We attempted to develop a method to estimate the reliability learning curve for ONSD measurement utilizing a unique definition of reliability: a plateau in within-subject variability with unchanged between-subject variability. Methods As part of a previously published study, a single operator measured the ONSD in 120 healthy volunteers over a 6-month period. Utilizing the assumption that the four measurements made on each subject during this study should be equal, the relationship of within-subject variance was described using a quadratic-plateau model as assessed by segmental polynomial (knot) regression. Results Segmental polynomial (knot) regression revealed a plateau in within-subject variance after the 21st subject. However, there was no difference in overall mean values [3.69 vs 3.68 mm ( p  = 0.884)] or between-subject variance [14.49 vs 11.92 ( p  = 0.54)] above or below this cutoff. Conclusions This study suggests a significant finite learning curve associated with ONSD measurements. It also offers a unique method of calculating the learning curve associated with ONSD measurement.