Neurophysiological Factors Associated with Compression and Reflex Mechanisms of Lower Back Pain

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Abstract

Introduction: Vertebrogenic pain syndromes (PSs) in the lower back (LB) are among the most common neurological disorders in the population. Currently, clinical, neurophysiological and neuroimaging characteristics are used as predictors of the course and effectiveness of the treatment for vertebrogenic PSs in the LB.

Aim: To identify the neurophysiological factors associated with compression and reflex mechanisms of PSs in the LB for their differentiation in complicated diagnostic cases.

Materials and methods: The study included 73 patients, 43 of them men and 30 women of the mean age 46.5 years. Based on the results of clinical neurological examination and the magnetic resonance imaging data, reflex vertebrogenic PSs (lumboischialgia) were verified in 40 cases, and radiculopathy of L5 and/or S1 (compression vertebrogenic PSs) in 33 cases. The patients underwent stimulation electroneuromyography with record of motor and sensory responses from the lower limbs, of F- and H-response, and examination of heart rate variability.

Results: Logit regression analysis was used to create models permitting to divide patients into groups with different mechanisms of PSs based on the neurophysiological parameters. The first model demonstrated high sensitivity in the identification of predominantly compression vertebrogenic disorders with the independent factors being the mean F-wave latency and the sensory response amplitude. The second model was more sensitive in identification of reflex PSs with the main predictors being the F-response amplitude and heart rate variability parameters.

Conclusion: The identified factors reflect the role of conduction disorders in compression PSs, as well as the involvement of segmental motor neuronal apparatus and autonomic regulatory mechanisms in the reaction in reflex PSs, which are additional sources of information in taking medical decisions in complicated diagnostic cases.

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About the authors

Irina A. Barinova

Ryazan Regional Clinical Hospital

Author for correspondence.
Email: barinova-irina-a2@yandex.ru
ORCID iD: 0000-0001-5384-5208
SPIN-code: 4545-1196

Postgraduate Student of the Department of Neurology and Neurosurgery

Russian Federation, Ryazan

Liliya N. Erkhova

Ryazan Regional Clinical Hospital

Email: shu-lilya1@yandex.ru
ORCID iD: 0009-0005-9097-6799
SPIN-code: 3737-7064

MD, Cand. Sci. (Med.)

Russian Federation, Ryazan

Vladimir A. Zhadnov

Ryazan State Medical University

Email: vladimir.zhadnov@mail.ru
ORCID iD: 0000-0002-5973-1196
SPIN-code: 1632-5083

MD, Dr. Sci. (Med.), Professor

Russian Federation, Ryazan

Roman A. Zorin

Ryazan State Medical University

Email: zorin.ra30091980@mail.ru
ORCID iD: 0000-0003-4310-8786
SPIN-code: 5210-5747

MD, Dr. Sci. (Med.), Associate Professor

Russian Federation, Ryazan

Nadezhda N. Kiryukhina

Ryazan Regional Clinical Hospital

Email: centerrsc@mail.ru
ORCID iD: 0000-0003-2561-5960
SPIN-code: 2441-3020

MD, Cand. Sci. (Med.);

Russian Federation, Ryazan

Andrey A. Kosolapov

Ryazan Regional Clinical Hospital

Email: kocolapov2@rambler.ru
ORCID iD: 0000-0001-7593-2353
SPIN-code: 3413-4917

MD, Cand. Sci. (Med.)

Russian Federation, Ryazan

Gennadiy A. Leonov

Ryazan State Medical University

Email: lionlion56.leonov@yandex.com
ORCID iD: 0000-0001-5780-1675
SPIN-code: 5115-3996

MD, Dr. Sci. (Med.), Associate Professor

Russian Federation, Ryazan

Aleksandr O. Burshinov

Ryazan State Medical University

Email: baomz@mail.ru
ORCID iD: 0009-0001-1708-2642
SPIN-code: 8792-9686

MD, Dr. Sci. (Med.), Associate Professor

Russian Federation, Ryazan

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Supplementary files

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2. Fig. 1. Distribution of subjects based on model 2 of logit regression analysis.

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