Correlation between levodopa equivalent daily dose (LEDD) and sleep quality in Parkinson’s disease patient as weighed by Parkinson’s disease sleep scale-2 (PDSS-2)

INTRODUCTION

Parkinson’s disease (PD) is the second most prevalent neurodegenerative disorder, following Alzheimer’s dementia, affecting the central nervous system and signified by the loss of dopaminergic neurons in the substantia nigra.^[1,2] The main symptoms of PD consist of akinesia, rigidity, and resting tremor while non-motor symptoms often consist of sleep disturbances, olfactory dysfunction, constipation, and cognitive behavioral disorders.^[1,3]

In 2016, there were 6.1 million PD cases worldwide, showing a 2.4-fold increment from 2.5 million cases in the 1990s. It continues to rise and is estimated to reach 8.7 million cases worldwide in 2030 because the elderly population is expected to increase. In Indonesia, the latest data showed approximately 876.665 sufferers out of 238.452.952 total population in 2018. Hence, attention to the impact of this disease has become increasingly important.^[3] Notably, sleep disturbances are a significant issue, with a prevalence of 45– 90% among PD patients. The factors contributing to sleep disturbances are multifactorial, including the influence of dopaminergic medications.^[4-6]

MATERIALS AND METHODS

RESULTS

DISCUSSION

This study focuses on exploring the correlation between LEDD and sleep quality in PD patients. It was found that sleep quality can be influenced by various factors, including the effects of dopaminergic treatment. The study by Chang et al. (2019) indicated that patients with poor sleep quality tend to have a longer disease duration, more advanced disease stage, and higher levels of depression and anxiety. This research also noted that although a correlation was expected between disease severity (measured by the Unified Parkinson’s Disease Rating Scale) and sleep quality, the results were not significant (P = 0.65). This aligns with findings from Young et al. (2002), which showed that sleep disturbances could occur in the initial phases of the disease.^[7]

High LEDD may contribute to sleep disturbances in PD patients through multiple mechanisms. First, levodopa stimulates D1 dopamine receptors, which can induce wakefulness. However, in Parkinson’s patients, the number of D1 receptors is reduced, leading to excessive stimulation and poor sleep quality when high doses of levodopa are administered. In addition, levodopa affects melatonin levels, a hormone critical for sleep regulation. While higher LEDD levels can increase melatonin, Parkinson’s patients already have significantly lower melatonin levels compared to the general population. As a result, high LEDD doses mainly exacerbate receptor activation rather than improving melatonin production.^[8,9]

Our study has several limitations that should be considered. First, we did not assess the timing of medication administration before sleep, which could have influenced sleep quality, especially if medications were taken too close to bedtime. In addition, when comparing LEDD dosages, our study found a median LEDD of 422.5, which is lower than the mean LEDD of 617.06 ± 454.73 reported by Chang et al. This suggests that the higher medication doses in their study may have had a more pronounced impact on sleep quality. Finally, our study had a smaller sample size of 50 participants, while Chang et al. included 134 participants. This difference in sample size resulted in insufficient statistical power for our analysis, and based on an r = 0.21, we would have needed approximately 172 participants to achieve adequate statistical power.^[5]

This study has several strengths, such as the ability to compare different types and cumulative doses of anti-Parkinson medications on sleep quality, the use of LEDD, which is not commonly used in clinical practice, and the implementation of the PDSS-2 questionnaire, which is easy and quick for PD patients to complete.

CONCLUSION

There was no correlation found between LEDD and sleep quality in PD patients, as assessed using the PDSS-2 questionnaire, which means that a cutoff value for LEDD could not be determined. To enhance the study, several recommendations could be considered. First, employing a prospective cohort design that follows participants for a month after medication administration would allow for the observation of changes in sleep quality over time. Second, incorporating quantitative plasma levodopa levels as a parameter alongside the LEDD would provide a more precise comparison of the medication’s impact on sleep. Third, excluding patients who take levodopa <4 h before sleep could minimize potential biases related to the timing of medication administration, which may affect sleep quality. Fourth, analyzing the PDSS-2 questionnaire by breaking down the subgroups for each sleep disturbance component would offer a more detailed understanding of specific sleep issues. Finally, using more objective measurement tools, such as polysomnography or actigraphy, would enable a comprehensive assessment of sleep quality and architecture, thus reducing subjective bias associated with self-reported PDSS-2 responses.