Trigeminal reflex testing abnormalities as a predictive model for distinguishing classical and idiopathic trigeminal neuralgia

•Trigeminal reflex latency asymmetry longer than 0.5 ms between the affected and unaffected sides is predictive of classical TN.•The latency asymmetry in trigeminal reflexes probably reflects the association of classical TN with neurovascular compression.•In idiopathic TN the impairment in large-mye...

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Veröffentlicht in:Clinical neurophysiology 2025-03, Vol.171, p.61-66
Hauptverfasser: De Stefano, Gianfranco, Mollica, Cristina, Leone, Caterina, Galosi, Eleonora, Di Pietro, Giuseppe, Falco, Pietro, Esposito, Nicoletta, Litewczuk, Daniel, Evangelisti, Enrico, Caramia, Francesca, Truini, Andrea, Di Stefano, Giulia
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container_end_page 66
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container_title Clinical neurophysiology
container_volume 171
creator De Stefano, Gianfranco
Mollica, Cristina
Leone, Caterina
Galosi, Eleonora
Di Pietro, Giuseppe
Falco, Pietro
Esposito, Nicoletta
Litewczuk, Daniel
Evangelisti, Enrico
Caramia, Francesca
Truini, Andrea
Di Stefano, Giulia
description •Trigeminal reflex latency asymmetry longer than 0.5 ms between the affected and unaffected sides is predictive of classical TN.•The latency asymmetry in trigeminal reflexes probably reflects the association of classical TN with neurovascular compression.•In idiopathic TN the impairment in large-myelinated fibers is undetectable. Primary trigeminal neuralgia (TN) is a representative neuropathic facial pain condition classified into classical (associated with neurovascular compression), and idiopathic (unknown etiology). Differentiating between classical and idiopathic TN based on clinical and neurophysiological findings remains challenging. In this clinical and neurophysiological study, we aimed to identify predictive clinical and neurophysiological variables that may distinguish between the two types of TN. We retrospectively analyzed clinical records and neurophysiological data from 114 patients with primary TN (84 classical TN, 30 idiopathic TN). We implemented a logistic regression model to identify predictive variables for classical and idiopathic TN. The logistic regression model showed that a trigeminal reflex latency asymmetry longer than 0.5 ms between the affected and unaffected sides was predictive of classical TN (p 
doi_str_mv 10.1016/j.clinph.2024.12.025
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Primary trigeminal neuralgia (TN) is a representative neuropathic facial pain condition classified into classical (associated with neurovascular compression), and idiopathic (unknown etiology). Differentiating between classical and idiopathic TN based on clinical and neurophysiological findings remains challenging. In this clinical and neurophysiological study, we aimed to identify predictive clinical and neurophysiological variables that may distinguish between the two types of TN. We retrospectively analyzed clinical records and neurophysiological data from 114 patients with primary TN (84 classical TN, 30 idiopathic TN). We implemented a logistic regression model to identify predictive variables for classical and idiopathic TN. The logistic regression model showed that a trigeminal reflex latency asymmetry longer than 0.5 ms between the affected and unaffected sides was predictive of classical TN (p &lt; 0.05). Additionally, combined involvement of the second and third trigeminal divisions was predictive of idiopathic TN (p &lt; 0.05). Our findings suggesting that latency asymmetry in trigeminal reflexes differentiate between classical and idiopathic TN probably reflects the association of classical TN with neurovascular compression, while idiopathic TN may involve other factors affecting trigeminal nerve fibers. 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Primary trigeminal neuralgia (TN) is a representative neuropathic facial pain condition classified into classical (associated with neurovascular compression), and idiopathic (unknown etiology). Differentiating between classical and idiopathic TN based on clinical and neurophysiological findings remains challenging. In this clinical and neurophysiological study, we aimed to identify predictive clinical and neurophysiological variables that may distinguish between the two types of TN. We retrospectively analyzed clinical records and neurophysiological data from 114 patients with primary TN (84 classical TN, 30 idiopathic TN). We implemented a logistic regression model to identify predictive variables for classical and idiopathic TN. The logistic regression model showed that a trigeminal reflex latency asymmetry longer than 0.5 ms between the affected and unaffected sides was predictive of classical TN (p &lt; 0.05). Additionally, combined involvement of the second and third trigeminal divisions was predictive of idiopathic TN (p &lt; 0.05). Our findings suggesting that latency asymmetry in trigeminal reflexes differentiate between classical and idiopathic TN probably reflects the association of classical TN with neurovascular compression, while idiopathic TN may involve other factors affecting trigeminal nerve fibers. 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subjects Neurovascular compression
Primary trigeminal afferents
Trigeminal neuralgia
Trigeminal reflex testing
title Trigeminal reflex testing abnormalities as a predictive model for distinguishing classical and idiopathic trigeminal neuralgia
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