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Watkins B, Schuster HM, Gerwin L, Schoser B, Kröger S. The effect of methocarbamol and mexiletine on murine muscle spindle function. Muscle Nerve 2022; 66:96-105. [PMID: 35373353 DOI: 10.1002/mus.27546] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 02/23/2022] [Accepted: 02/25/2022] [Indexed: 11/10/2022]
Abstract
INTRODUCTION/AIMS The muscle relaxant methocarbamol and the antimyotonic drug mexiletine are widely used for the treatment of muscle spasms, myotonia, and pain syndromes. To determine whether these drugs affect muscle spindle function, we studied their effect on the resting discharge and on stretch-induced action potential frequencies of proprioceptive afferent neurons. METHODS Single unit action potential frequencies of proprioceptive afferents from muscle spindles in the murine extensor digitorum longus muscle of adult C57BL/6J mice were recorded under resting conditions and during ramp-and-hold stretches. Maximal tetanic force of the same muscle after direct stimulation was determined. High-resolution confocal microscopy analysis was performed to determine the distribution of Nav 1.4 channels, a potential target for both drugs. RESULTS Methocarbamol and mexiletine inhibited the muscle spindle resting discharge in a dose-dependent manner with IC50 values around 300 μM and 6 μM, respectively. With increasing concentrations of both drugs, the response to stretch was also affected, with the static sensitivity first followed by the dynamic sensitivity. At high concentrations, both drugs completely blocked muscle spindle afferent output. Both drugs also reversibly reduced the specific force of the extensor digitorum longus muscle after tetanic stimulation. Finally, we present evidence for the presence and specific localization of the voltage-gated sodium channel Nav 1.4 in intrafusal fibers. DISCUSSION In this study we demonstrate that both muscle relaxants affect muscle spindle function, suggesting impaired proprioception as a potential side effect of both drugs. Moreover, our results provide additional evidence of a peripheral activity of methocarbamol and mexiletine.
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Affiliation(s)
- Bridgette Watkins
- Department of Physiological Genomics, Biomedical Center, Ludwig-Maximilians-University, Planegg-Martinsried, Germany
| | - Hedwig M Schuster
- Department of Physiological Genomics, Biomedical Center, Ludwig-Maximilians-University, Planegg-Martinsried, Germany
| | - Laura Gerwin
- Department of Physiological Genomics, Biomedical Center, Ludwig-Maximilians-University, Planegg-Martinsried, Germany
| | - Benedikt Schoser
- Department of Neurology, LMU Klinikum, Friedrich-Baur-Institute, Ludwig-Maximilians-University, Munich, Germany
| | - Stephan Kröger
- Department of Physiological Genomics, Biomedical Center, Ludwig-Maximilians-University, Planegg-Martinsried, Germany
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Dawwas GK, Hennessy S, Brensinger CM, Acton EK, Bilker WB, Chung S, Dublin S, Horn JR, Manis MM, Miano TA, Oslin DW, Pham Nguyen TP, Soprano SE, Wiebe DJ, Leonard CE. Signals of Muscle Relaxant Drug Interactions Associated with Unintentional Traumatic Injury: A Population-Based Screening Study. CNS Drugs 2022; 36:389-400. [PMID: 35249204 PMCID: PMC9375100 DOI: 10.1007/s40263-022-00909-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/17/2022] [Indexed: 11/03/2022]
Abstract
BACKGROUND Use of muscle relaxants is rapidly increasing in the USA. Little is understood about the role of drug interactions in the known association between muscle relaxants and unintentional traumatic injury, a clinically important endpoint causing substantial morbidity, disability, and death. OBJECTIVE We examined potential associations between concomitant drugs (i.e., precipitants) taken with muscle relaxants (affected drugs, i.e., objects) and hospital presentation for unintentional traumatic injury. METHODS In a series of self-controlled case series studies, we screened to identify drug interaction signals for muscle relaxant + precipitant pairs and unintentional traumatic injury. We used Optum's de-identified Clinformatics® Data Mart Database, 2000-2019. We included new users of a muscle relaxant, aged 16-90 years, who were dispensed at least one precipitant drug and experienced an unintentional traumatic injury during the observation period. We classified each observation day as precipitant exposed or precipitant unexposed. The outcome was an emergency department or inpatient discharge diagnosis for unintentional traumatic injury. We used conditional Poisson regression to estimate rate ratios adjusting for time-varying confounders and then accounted for multiple estimation via semi-Bayes shrinkage. RESULTS We identified 74,657 people who initiated muscle relaxants and experienced an unintentional traumatic injury, in whom we studied concomitant use of 2543 muscle relaxant + precipitant pairs. After adjusting for time-varying confounders, 16 (0.6%) pairs were statistically significantly and positively associated with injury, and therefore deemed signals of a potential drug interaction. Among signals, semi-Bayes shrunk, confounder-adjusted rate ratios ranged from 1.29 (95% confidence interval 1.04-1.62) for baclofen + sertraline to 2.28 (95% confidence interval 1.14-4.55) for methocarbamol + lamotrigine. CONCLUSIONS Using real-world data, we identified several new signals of potential muscle relaxant drug interactions associated with unintentional traumatic injury. Only one among 16 signals is currently reported in a major drug interaction knowledge base. Future studies should seek to confirm or refute these signals.
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Affiliation(s)
- Ghadeer K. Dawwas
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA,Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA,Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA
| | - Sean Hennessy
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA,Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA,Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA,Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Colleen M. Brensinger
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA,Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Emily K. Acton
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA,Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA,Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Warren B. Bilker
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA,Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Sascha Dublin
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA,Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - John R. Horn
- Department of Pharmacy, School of Pharmacy, University of Washington, Seattle, WA, USA
| | - Melanie M. Manis
- Department of Pharmacy Practice, McWhorter School of Pharmacy, Samford University, Birmingham, AL, USA
| | - Todd A. Miano
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA,Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - David W. Oslin
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA,Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA,Mental Illness Research, Education, and Clinical Center, Corporal Michael J. Crescenz Veterans Administration Medical Center, Philadelphia, PA, USA
| | - Thanh Phuong Pham Nguyen
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA,Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA,Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA,Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Samantha E. Soprano
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA,Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Douglas J. Wiebe
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA,Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA,Penn Injury Science Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Charles E. Leonard
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA,Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA,Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA
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Alvarez CA, Mortensen EM, Makris UE, Berlowitz DR, Copeland LA, Good CB, Amuan ME, Pugh MJV. Association of skeletal muscle relaxers and antihistamines on mortality, hospitalizations, and emergency department visits in elderly patients: a nationwide retrospective cohort study. BMC Geriatr 2015; 15:2. [PMID: 25623366 PMCID: PMC4322434 DOI: 10.1186/1471-2318-15-2] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2014] [Accepted: 12/17/2014] [Indexed: 11/10/2022] Open
Abstract
Background High-risk medication exposure in the elderly is common and associated with increased mortality, hospitalizations, and emergency department (ED) visits. Skeletal muscle relaxants and antihistamines are high-risk medications commonly prescribed in elderly patients. The objective of this study was to determine the association between skeletal muscle relaxants or antihistamines and mortality, hospitalizations, and emergency department visits. Methods This study used a new-user, retrospective cohort design using national Veteran Affairs (VA) data from 128 hospitals. Veterans ≥65 years of age on October 1, 2005 who received VA inpatient/outpatient care at least once in each of fiscal year (FY) 2005 and FY 2006 were included. Exposure to skeletal muscle relaxants and antihistamines was defined by the National Committee for Quality Assurance Healthcare Effectiveness Data and Information Set measures for high-risk medications in the elderly. Primary outcomes identified within one year of exposure were death, ED visit, or hospitalization; ED visits or hospitalizations due to falls and fracture were also assessed. Propensity score matching (1 to 1 match) was used to balance covariates between exposed patients and non-exposed patients. Results In this cohort of 1,807,404 patients 55,566 patients were included in the propensity-matched cohort for skeletal muscle relaxants and 60,058 patients were included in the propensity-matched cohort for anti-histamines. Mortality was lower in skeletal muscle relaxants-exposed patients (adjusted odds ratio [AOR] 0.87, 95% CI 0.81-0.94), but risk of emergency care (AOR 2.25, 95% CI 2.16-2.33) and hospitalization (AOR 1.56, 95% CI 1.48-1.65) was higher for patients prescribed skeletal muscle relaxants. Similar findings were observed for emergency and hospital care for falls or fractures. Mortality (AOR 1.93, 95% CI 1.82-2.04), ED visits (AOR 2.35, 95% CI 2.27-2.43), and hospitalizations (AOR 2.21, 95% CI 2.11-2.32) were higher in the antihistamine-exposed group, with similar findings for falls and fractures outcomes. Conclusion Skeletal muscle relaxants and antihistamines are associated with an increased risk of ED visits and hospitalizations in elderly patients. Antihistamines were also associated with an increased risk of death, further validating the classification of these drug classes as “high risk”.
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Affiliation(s)
- Carlos A Alvarez
- Pharmacy Practice Department, Texas Tech University Health Sciences Center, Forest Park Rd, Dallas, TX, USA.
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