Synkinesis following recurrent laryngeal nerve injury: A computer simulation.

Synkinesis following recurrent laryngeal nerve injury: A computer simulation.

Laryngoscope. 2015 Nov 24;

Authors: Paniello RC

Abstract
OBJECTIVES/HYPOTHESIS: When the recurrent laryngeal nerve (RLN) is injured, functional recovery may be limited by the number of axons that regrow across the site of injury, and by the proportions of these axons that reinnervate the antagonistic muscle (synkinesis). This process was investigated in a computer model of RLN recovery.
STUDY DESIGN: Computer simulation.
METHODS: The developed computer program accepted as inputs: number of RLN axons; proportions of axons originally innervating adductor versus abductor, fraction of axons transected, fraction of axons that grow back, and width of 1 standard deviation about the mean. The program employed random sampling from a normal distribution to model various degrees of recovery, using random numbers to assign each axon to the correct muscle, an incorrect muscle, or no recovery. Each simulation was run 1,000×, and the mean, highest, and lowest degrees of synkinesis were determined.
RESULTS: More severe injuries were associated with greater degrees of synkinesis. Extremes of synkinesis were possible but were rare. One example result, for a 50% injury with a 50% recovery rate, found: in the adductor muscles, 74.8% of axons will be innervated, of which 49.2% are the original uninjured axons, 19.4% are recovered adductor axons, and 6.2% are misdirected abductor axons. In the posterior cricoarytenoid (PCA), these values were 75.7%, 50.8%, 6.1%, and 18.8%, respectively. Results of many such simulations are plotted.
CONCLUSIONS: Laryngeal synkinesis can be simulated based on known anatomic ratios and estimated recovery rates. The PCA is invariably much more affected by synkinetic reinnervation than are the adductor muscles.
LEVEL OF EVIDENCE: NA Laryngoscope, 2015.

PMID: 26600293 [PubMed - as supplied by publisher]

from #PubMed 1 via ola Kala on Inoreader http://ift.tt/1MCMzOx
via IFTTT

from #Med Blogs by Alexandros G.Sfakianakis via paythelady61 on Inoreader http://ift.tt/1MCN1fB
via IFTTT