Table 3.

Factors associated with strain, strain rate, and strain-time integral using multivariable linear regression

	Estimate	95% Confidence Interval	p-value
Log Strain
Male	−0.258	−0.415, −0.101	0.001
Position
Faculty	0
CRNAa	−0.281	−0.490, −0.072	0.009
Resident	0.163	−0.043, 0.368	0.122
Experience (years)b	0.010	−0.002, 0.021	0.103
Blade
Mactinosh	0
Miller	−0.107	−0.301, 0.087	0.282
Macintosh APP	0.013	−0.181, 0.207	0.896
Miller APP	−0.218	−0.413, −0.024	0.028
Log strain rate
Height (cm)	−0.023	−0.042, −0.003	0.024
Blade
Macintosh	0
Miller	−0.179	−0.385, 0.027	0.089
Macintosh APP	0.283	−0.489, −0.077	0.007
Miller APP	−0.399	−0.605, −0.194	<0.001
Log Strain-time Integral
Male	−0.423	−0.649, −0.197	<.001
Position
Faculty	0
CRNAa	−0.268	−0.570, 0.033	0.082
Resident	0.161	−0.162, 0.449	0.273
Experience (years)	0.015	−0.001, 0.031	0.073
Blade Preference
Macintosh	0
Miller	0.465	0.094, 0.836	0.015
No preference	−0.046	−0.287, 0.196	0.712

Table shows the adjusted effect of each item on the amount of log strain, log strain rate, and log strain-time integral using Akaike Information Criteria and multivariable linear regression. For categorical variables, the estimate is the amount that variable increase (or decreases) the log strain, log strain rate, and log strain-time integral by. For continuous variables, the estimate is the amount that one unit of that variable will increase (or decrease) log strain, log strain rate, and log strain-time integral by

^aincludes one 2nd year nurse anesthesia student

^bExperience (years) was calculated from the start of clinical anesthesiology training for resident and faculty anesthesiologists and the start of clinic nurse anesthesia school for certified registered nurse anesthetists