| Literature DB >> 29115945 |
Milo Engoren1,2, Lauryn R Rochlen3, Matthew V Diehl4, Sarah S Sherman4, Elizabeth Jewell3, Mary Golinski5, Paul Begeman4, John M Cavanaugh4.
Abstract
BACKGROUND: While most Direct laryngoscopy leads to dental injury in 25-39% of cases. Dental injury occurs when the forces and impacts applied to the teeth exceed the ability of the structures to dissipate energy and stress. The purpose of this study was to measure strain, (which is the change produced in the length of the tooth by a force applied to the tooth) strain rate, and strain-time integral to the maxillary incisors and determine if they varied by experience, type of blade, or use of an alcohol protective pad (APP).Entities:
Keywords: Dental injury; Intubation; Laryngoscopy; Strain
Mesh:
Year: 2017 PMID: 29115945 PMCID: PMC5688811 DOI: 10.1186/s12871-017-0442-z
Source DB: PubMed Journal: BMC Anesthesiol ISSN: 1471-2253 Impact factor: 2.217
Fig. 1Photograph of mannequin showing strain gauges attached to the upper incisors
Fig. 2Photograph of instrumented mannequin
Fig. 3Schematic drawing showing strain, change in length divided by length (ΔL/L), which is dimensionless. If the forces producing tension and compression are the same magnitude, the magnitude of ΔL will be the same, but of opposite sign
Fig. 4Schematic drawing showing the force, F, as the laryngoscope blade contacts the tooth of length. The blade produces tension (stretch) on one side of the tooth and compression on the other side. The amount of tension and compression are measured by strain gauges glued to each side of the tooth
Subject Characteristics
| Factor | Number | Percent |
|---|---|---|
| Right handedness | 82 | 89% |
| Male | 54 | 59% |
| Position | ||
| Resident | 40 | 43% |
| CRNAa | 29 | 32% |
| Faculty Anesthesiologist | 23 | 25% |
| Preferred Blade | ||
| Miller | 8 | 9% |
| Macintosh | 66 | 72% |
| No preference | 18 | 20% |
| Median | Interquartile range | |
| Height (cm) | 173 | 163–180 |
| Years of experienceb | 8 | 5–13 |
| Number of intubations in the previous 30 days | 10 | 2–30 |
There were 13 clinical year (CA) zeroes (interns who haven’t started their intraoperative anesthesia training, 9 CA-1, 7 CA-2, 5 CA-3, 5 CA-4, and 1 CA-5
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
Fig. 5(left) Logarithmic box and whisker plot of strain (median = heavy black line, box = 1st – 3rd interquartile range, Tukey’s whiskers = 150% of the interquartile range above and below the 75th and the 25th percentiles, respectively, and dots = outliers) for Macintosh (Mac) and Miller blades. Alcohol protective pad (APP). Pairwise p’s (by MannWhitney U test): Mac v. Mac with APP (p = .877), Mac v. Miller (p = .280), Mac v. Miller with APP (p = .077); Mac with APP v Miller (p = .251), Mac with APP v, Miller with APP (p = .054), and Miller v. Miller with APP (p = .429). (center) Logarithmic box and whisker plot of strain rate (median = heavy black line, box = 1st – 3rd interquartile range, Tukey’s whiskers = 150% of the interquartile range above and below the 75th and the 25th percentiles, respectively, and dots = outliers) for Macintosh (Mac) and Miller blades. Alcohol protective pad (APP). Pairwise p’s (by MannWhitney U test): Mac v. Mac with APP (p = .001), Mac v. Miller (p = .086), Mac v. Miller with APP (p < .001); Mac with APP v Miller (p = .144), Mac with APP v, Miller with APP (p = .245), and Miller v. Miller with APP (p = .009). (right) Logarithmic box and whisker plot of strain time integral (median = heavy black line, box = 1st – 3rd interquartile range, Tukey’s whiskers = 150% of the interquartile range above and below the 75th and the 25th percentiles, respectively, and dots = outliers) for Macintosh (Mac) and Miller blades. Alcohol protective pad (APP). Pairwise p’s (by MannWhitney U test): Mac v. Mac with APP (p = .110), Mac v. Miller (p = .898), Mac v. Miller with APP (p = .988); Mac with APP v Miller (p = .179), Mac with APP v, Miller with APP (p = .100), and Miller v. Miller with APP (p = .880)
Correlation coefficients of strain by the laryngoscopists
| Macintosh | Miller | Macintosh - APP | Miller - APP | |
|---|---|---|---|---|
| Macintosh | 1 | 0.50 | 0.47 | 0.42 |
| Miller | 0.50 | 1 | 0.51 | 0.56 |
| Macintosh - APP | 0.47 | 0.51 | 1 | 0.63 |
| Miller - APP | 0.42 | 0.56 | 0.63 | 1 |
Correlation coefficients (Spearman’s rho) between the strains generated by the same larygnoscopist using the different blades and techniques. APP alcohol protective pad. All p < .001
Factors associated with strain, strain rate, and strain-time integral using multivariable linear regression
| Estimate | 95% Confidence Interval |
| |
|---|---|---|---|
| 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