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Difference between revisions of "Is dopaminergic medication dose associated with self-reported bruxism in Parkinson's disease? A cross-sectional, questionnaire-based study"
Is dopaminergic medication dose associated with self-reported bruxism in Parkinson's disease? A cross-sectional, questionnaire-based study (view source)
Revision as of 18:17, 27 February 2023
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Aggregation of medication usage per participant was achieved through the use of the levodopa equivalent daily dosage (LEDD) [22, 23]. According to Tomlinson, the LEDD is a ‘summation of the calculated conversion factors of each individual antiparkinsonian drug, aligned to 100 mg immediate release levodopa’ [22] (see Table 1 for an example). All LEDD scores were calculated by two independent examiners (NB and MH). When no consensus was reached between the two examiners (N = 169), a third examiner (MV) calculated the LEDD separately. When consensus was reached, this LEDD score was used. When no consensus was reached or doubt occurred between the three examiners, a neurologist experienced with calculating LEDD scores was contacted (KvD) (N = 35). Most of the time, a conflict occurred because participants did not report that a medicine with slow release was used instead of immediate release. However, based on the dosage and frequency of the intake, it could be determined if immediate release or slow release was taken. Also, handwriting mistakes were made (e.g., 2,75 mg instead of 275 mg a day). The following general agreement was made: when medication usage was ambiguous or the medication list was not completed, participants were excluded from the data analysis (N = 166). Imputation methods were not used because of the amount of missings (> 20%) and the non-random distribution of the missings, which is in line with the recommendations when to use imputation methods [24]. | Aggregation of medication usage per participant was achieved through the use of the levodopa equivalent daily dosage (LEDD) [22, 23]. According to Tomlinson, the LEDD is a ‘summation of the calculated conversion factors of each individual antiparkinsonian drug, aligned to 100 mg immediate release levodopa’ [22] (see Table 1 for an example). All LEDD scores were calculated by two independent examiners (NB and MH). When no consensus was reached between the two examiners (N = 169), a third examiner (MV) calculated the LEDD separately. When consensus was reached, this LEDD score was used. When no consensus was reached or doubt occurred between the three examiners, a neurologist experienced with calculating LEDD scores was contacted (KvD) (N = 35). Most of the time, a conflict occurred because participants did not report that a medicine with slow release was used instead of immediate release. However, based on the dosage and frequency of the intake, it could be determined if immediate release or slow release was taken. Also, handwriting mistakes were made (e.g., 2,75 mg instead of 275 mg a day). The following general agreement was made: when medication usage was ambiguous or the medication list was not completed, participants were excluded from the data analysis (N = 166). Imputation methods were not used because of the amount of missings (> 20%) and the non-random distribution of the missings, which is in line with the recommendations when to use imputation methods [24]. | ||
[[File:Verhoeff 1.jpg|alt= | [[File:Verhoeff 1.jpg|alt=|thumb|'''Table1:''' Anexampleofa medication list, aligned to 100 mg of immediate release levodopa with the use of conversion factors of different types of dopaminergic medication|center|400x400px]] | ||
An example of a medication list, aligned to 100 mg of immediate release levodopa with the use of conversion factors of different types of dopaminergic medication | An example of a medication list, aligned to 100 mg of immediate release levodopa with the use of conversion factors of different types of dopaminergic medication | ||
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=== Results === | === Results === | ||
In Table 2 the demographic characteristics of the participants are presented. The prevalences of possible awake bruxism and sleep bruxism in patients with PD were 46.0% and 24.3%, respectively (see Table2).[[File:Verhoeff 2.jpg|thumb|'''Table 2:''' Demographic information and prevalences of the independent variables (including missings) of the included participants with PD (N = 395)|center]]In this study, the LEDD appeared not to be associated with awake or sleep bruxism (see Tables 3 and 4). The results of the single and multiple logistic regression analyses for possible awake bruxism and sleep bruxism are shown in Tables 3 and and4, respectively. The unadjusted associations for awake bruxism showed a possible association (p < 0.10) with age (odds ratio (OR) 0.94; 95% CI 0.92–0.97), sleep bruxism (OR 11.50; 95% CI 6.02–21.99), TMD pain (OR 6.78; 95% CI 3.97–11.58), jaw locks (OR 3.83; 95% CI 1.91–7.71), and tooth wear (OR 4.98; 95% CI 3.03–8.17). In the multiple regression analysis, only sleep bruxism (OR 8.82; 95% CI 3.56–20.40), TMD pain (OR 4.51; 95% CI 2.31–8.79), and tooth wear (OR 1.87; 95% CI 1.02–3.43) remained significant. The unadjusted associations for sleep bruxism showed a possible association (p < 0.10) with female gender (OR 2.24; 95% CI 1.36–3.68), age (OR 0.94; 95% CI 0.91–0.96), awake bruxism (OR 11.50; 95% CI 6.02–21.99), TMD pain (OR 4.65; 95% CI 2.74–7.88), jaw locks (OR 3.81; 95% CI 1.96–7.41), and tooth wear (OR 16.64; 95% CI 7.26–38.13). According to the multiple regression model, the following variables were significantly associated with the report of sleep bruxism: awake bruxism (OR 9.48; 95% CI 4.24–21.19) and tooth wear (OR 12.49; 95% CI 4.97–31.38). Besides, a trend towards a significant association of sleep bruxism with TMD pain was shown (p-to-exit value 0.057). For both awake and sleep bruxism models, no statistically significant difference was found between the observed and predicted probabilities, according to the Hosmer and Lemeshow test (p = 0.92 and 0.85, respectively), concluding that both models fit the observed data.[[File:Verhoeff 3.jpg|thumb|'''Table 3:''' Single and multiple regression analysis of variables associated with possible sleep bruxism in patients with PD (N = 283). The associated p value and odds ratio (OR) with a 95% confidence interval (CI) are presented|center]] | |||
[[File:Verhoeff | |||
In this study, the LEDD appeared not to be associated with awake or sleep bruxism (see Tables 3 and 4). The results of the single and multiple logistic regression analyses for possible awake bruxism and sleep bruxism are shown in Tables 3 and and4, respectively. The unadjusted associations for awake bruxism showed a possible association (p < 0.10) with age (odds ratio (OR) 0.94; 95% CI 0.92–0.97), sleep bruxism (OR 11.50; 95% CI 6.02–21.99), TMD pain (OR 6.78; 95% CI 3.97–11.58), jaw locks (OR 3.83; 95% CI 1.91–7.71), and tooth wear (OR 4.98; 95% CI 3.03–8.17). In the multiple regression analysis, only sleep bruxism (OR 8.82; 95% CI 3.56–20.40), TMD pain (OR 4.51; 95% CI 2.31–8.79), and tooth wear (OR 1.87; 95% CI 1.02–3.43) remained significant. The unadjusted associations for sleep bruxism showed a possible association (p < 0.10) with female gender (OR 2.24; 95% CI 1.36–3.68), age (OR 0.94; 95% CI 0.91–0.96), awake bruxism (OR 11.50; 95% CI 6.02–21.99), TMD pain (OR 4.65; 95% CI 2.74–7.88), jaw locks (OR 3.81; 95% CI 1.96–7.41), and tooth wear (OR 16.64; 95% CI 7.26–38.13). According to the multiple regression model, the following variables were significantly associated with the report of sleep bruxism: awake bruxism (OR 9.48; 95% CI 4.24–21.19) and tooth wear (OR 12.49; 95% CI 4.97–31.38). Besides, a trend towards a significant association of sleep bruxism with TMD pain was shown (p-to-exit value 0.057). For both awake and sleep bruxism models, no statistically significant difference was found between the observed and predicted probabilities, according to the Hosmer and Lemeshow test (p = 0.92 and 0.85, respectively), concluding that both models fit the observed data. | |||
=== Discussion === | === Discussion === | ||
The first aim of the present study was to determine the prevalence of possible awake bruxism and sleep bruxism in a population of PD patients. The results showed a respective prevalence of 46.0% and 24.3% for these conditions. The second aim was to investigate possible associations between the dose of dopaminergic medication and the presence of awake and sleep bruxism. The results showed that in a PD population, the levodopa equivalent daily dosage (LEDD) was not associated with the self-reports of awake and sleep bruxism. Hence, the hypothesis formulated in the introduction, viz., that there is an association between awake bruxism/sleep bruxism and dopaminergic medication, could not be accepted. Furthermore, this study examined whether other factors were significantly associated with self-reported awake and sleep bruxism. Co-occurrence of both awake bruxism and sleep bruxism was observed. Besides, there was an association with tooth wear and both circadian manifestations of bruxism. Finally, awake bruxism was also found to be associated with TMD pain.[[File:Verhoeff 4.jpg|thumb|'''Table 4:''' ''R''<sup>2</sup> = .48(Nagelkerke), 0.32 (Cox and Snell). ''X''<sup>2</sup> (2) = 109.5, ''p'' < 0.001|center|400x400px]] | |||
==== Prevalence of awake and sleep bruxism ==== | ==== Prevalence of awake and sleep bruxism ==== | ||
In the studied population, awake bruxism and sleep bruxism were reported much more often (46% and 24.3%, respectively) than in the general population of the same age (3% and 8.3%, respectively) [6]. While this suggests a large discrepancy with the results of our study, as earlier stated in the hypothesis, it is not that surprising. It is known that populations with neurological conditions show a higher prevalence of awake bruxism [26]. Moreover, some risk factors for bruxism are more prevalent in patients with PD [27]. Examples of risk factors for bruxism are, amongst others, the presence of stress and depressive thoughts [28–31] and the use of specific types of medication, such as selective serotonin reuptake inhibitors (SSRI) [11, 12]. All of these risk factors are more prevalent in patients with PD than in the general population [27]. Finally, it has been demonstrated that patients with PD have an increased prevalence of sleep problems, resulting in an increased occurrence of arousals from sleep which is in turn related to higher numbers of sleep bruxism events [32, 33]. | In the studied population, awake bruxism and sleep bruxism were reported much more often (46% and 24.3%, respectively) than in the general population of the same age (3% and 8.3%, respectively) [6]. While this suggests a large discrepancy with the results of our study, as earlier stated in the hypothesis, it is not that surprising. It is known that populations with neurological conditions show a higher prevalence of awake bruxism [26]. Moreover, some risk factors for bruxism are more prevalent in patients with PD [27]. Examples of risk factors for bruxism are, amongst others, the presence of stress and depressive thoughts [28–31] and the use of specific types of medication, such as selective serotonin reuptake inhibitors (SSRI) [11, 12]. All of these risk factors are more prevalent in patients with PD than in the general population [27]. Finally, it has been demonstrated that patients with PD have an increased prevalence of sleep problems, resulting in an increased occurrence of arousals from sleep which is in turn related to higher numbers of sleep bruxism events [32, 33]. | ||