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

Frederick A. Zeiler, Markus T. Ziesmann, Patrick Goeres, Bertram Unger, Jason Park, Dimitrios Karakitsos, Michael Blaivas, Ashley Vergis, Lawrence M. Gillman
2016 Critical Ultrasound Journal  
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
more » ... ariability 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. which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
doi:10.1186/s13089-016-0044-x pmid:27501699 pmcid:PMC4977242 fatcat:jydilafjmrgdjh7dr5q5une7py