Predictors to quality of life improvements after subthalamic stimulation in Parkinson's disease

Quality of life predicts rehabilitation prognosis in Parkinson's disease patients: Factors influence rehabilitation prognosis: Factors influence rehabilitation prognosis

BACKGROUND

Rehabilitation has been reported to improve the quality of life (QoL) of patients with Parkinson's disease (PD). Nevertheless, not all patients are satisfied with rehabilitation outcomes and could achieve a significant improvement in QoL.

OBJECTIVE

To detect possible predictors of QoL improvement in patients with PD after rehabilitation.

METHODS

A total of 86 PD patients were included and followed up for 3 months with a 39-item Parkinson's Disease Questionnaire summary index (PDQ-39 SI) as the primary endpoint. All patients received 2 weeks of multidisciplinary intensive rehabilitation treatment (MIRT). Changes in patients' QoL were assessed using the PDQ-39 at baseline and at the 3-month follow-up. The reliable change index (RCI) was adapted to determine the individual QoL outcome. The predictors of QoL outcome were detected using logistic regression analysis.

RESULTS

After a 3-month follow-up, PDQ-39 SI decreased significantly from 22.95 ± 9.75 to 18.73 ± 10.32 (P < 0.001). Scores for QoL improved (RCI>10.9) after rehabilitation for 18.6% of the patients, and 74.4% of patients reported an unchanged QoL (-10.9≤RCI≤10.9), while 7.0% of patients reported a worsening of QoL (RCI<-10.9). Among the baseline parameters, the PDQ-39 SI was a baseline predictor for changes in QoL in the logistic regression model (OR: 1.15, CI: 1.07-1.24, P < 0.001).

CONCLUSIONS

MIRT could improve QoL for some patients with PD, and PDQ-39 score at baseline is the most important predictor for QoL improvements after rehabilitation for this patients.

Deep Brain Stimulation in Parkinson Disease: A Meta-analysis of the Long-term Neuropsychological Outcomes

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) or globus pallidum internus (GPi) improves motor functions in patients with Parkinson's disease (PD) but may cause a decline in specific cognitive domains. The aim of this systematic review and meta-analysis was to assess the long-term (1-3 years) effects of STN or GPi DBS on four cognitive functions: (i) memory (delayed recall, working memory, immediate recall), (ii) executive functions including inhibition control (Color-Word Stroop test) and flexibility (phonemic verbal fluency), (iii) language (semantic verbal fluency), and (iv) mood (anxiety and depression). Medline and Web of Science were searched, and studies published before July 2021 investigating long-term changes in PD patients following DBS were included. Random-effects model meta-analyses were performed using the R software to estimate the standardized mean difference (SMD) computed as Hedges' g with 95% CI. 2522 publications were identified, 48 of which satisfied the inclusion criteria. Fourteen meta-analyses were performed including 2039 adults with a clinical diagnosis of PD undergoing DBS surgery and 271 PD controls. Our findings add new information to the existing literature by demonstrating that, at a long follow-up interval (1-3 years), both positive effects, such as a mild improvement in anxiety and depression (STN, Hedges' g = 0,34, p = 0,02), and negative effects, such as a decrease of long-term memory (Hedges' g = -0,40, p = 0,02), verbal fluency such as phonemic fluency (Hedges' g = -0,56, p < 0,0001), and specific subdomains of executive functions such as Color-Word Stroop test (Hedges' g = -0,45, p = 0,003) were observed. The level of evidence as qualified with GRADE varied from low for the pre- verses post-analysis to medium when compared to a control group.

Can Levodopa Challenge Testing Predict the Effect of Deep Brain Stimulation? One-Year Outcomes in a Chinese Cohort

Objective: Our study examined whether levodopa challenge test (LCT) results could predict quality of life (QoL) outcomes after surgery to implant subthalamic nucleus deep brain stimulation (STN-DBS) electrodes to treat advanced Parkinson’s disease (PD).

Methods: Forty patients with STN-DBS underwent a follow-up 1 year after implantation surgery to analyze the correlation between preoperative levodopa impact test results and postoperative Unified Parkinson’s Disease Rating Scale (UPDRS) III motor score, postoperative PD Questionnaire-39 (PDQ-39) score, and PDQ-39 improvement.

Results: Improvements in QoL were associated with several preoperative characteristics including preoperative UPDRS-III tremor, UPDRS-III tremor (off-60) (p = 0.049), UPDRS-III tremor (off-120) (p = 0.012), Mini-Mental State Examination (p = 0.012), and PDQ-39 (p = 0.012) before surgery. Multiple linear regression model using preoperative MMSE [odds ratio (OR) = 0.342, 95% confidence interval (CI) = 0.051–2.297], preoperative UPDRS-III tremor (OR = 2.099, 95% CI = 0.585–7.535), UPDRS-III tremor (off-60) [OR = 1.316, 95% CI = 0.804–2.154, UPDRS-III tremor (off-120) OR = 0.913, 95% CI = 0.691–1.207], correctly classified 88.5% of patients.

Conclusion: Levodopa challenge test results cannot predict the effect of DBS. However, the test can be incorporated into a regression prediction model to the quality of life of PD patients after DBS with other preoperative factors.

Quality of Life in Newly Diagnosed Patients With Parkin-Related Parkinson's Disease

Introduction: Mutations in the Parkin gene are the most common cause of autosomal recessive early-onset Parkinson's disease (PD). However, little is known about the quality of life (QoL) in Parkin-related PD. Here, we investigated the patterns of QoL in newly diagnosed Parkin-related PD patients.

Methods: Newly diagnosed PD patients (diagnosis made within 12 months) who had an age of onset (AOO) below 40 and underwent a PD-related genetic testing, were recruited (n = 148). Among them, 24 patients carried bi-allelic variants in Parkin (PD-Parkin) and 24 patients did not have any known causative PD mutations, or risk variants (GU-EOPD). The clinical materials, relevant factors and determinants of QoL were analyzed.

Results: PD-Parkin patients had a younger AOO (p = 0.003) and longer disease duration (p = 0.005). After adjustment for AOO and disease duration, more dystonia (p = 0.034), and worse scores of non-motor symptoms including Beck depression inventory (BDI, p = 0.035), Epworth sleepiness scale (ESS, p = 0.044), and subdomains of depression/anxiety (p = 0.015) and sleep disorders (p = 0.005) in Non-motor symptoms questionnaire, were found in PD-Parkin comparing with GU-EOPD. PD-Parkin patients had poorer QoL (adjusted p = 0.045), especially in the mobility (adjusted p = 0.025), emotional well-being (adjusted p = 0.015) and bodily discomfort dimensions (adjusted p = 0.016). BDI scores (p = 0.005) and ESS scores (p = 0.047) were significant determinants of QoL in PD-Parkin.

Conclusion: Newly diagnosed PD-Parkin patients showed worse QoL. More depression and excessive daytime sleepiness predicted worse QoL. For clinicians, management of depression and excessive daytime sleepiness is suggested to better improve QoL in patients with Parkin mutations.

Machine learning prediction of motor response after deep brain stimulation in Parkinson's disease-proof of principle in a retrospective cohort

INTRODUCTION

Despite careful patient selection for subthalamic nucleus deep brain stimulation (STN DBS), some Parkinson's disease patients show limited improvement of motor disability. Innovative predictive analysing methods hold potential to develop a tool for clinicians that reliably predicts individual postoperative motor response, by only regarding clinical preoperative variables. The main aim of preoperative prediction would be to improve preoperative patient counselling, expectation management, and postoperative patient satisfaction.

METHODS

We developed a machine learning logistic regression prediction model which generates probabilities for experiencing weak motor response one year after surgery. The model analyses preoperative variables and is trained on 89 patients using a five-fold cross-validation. Imaging and neurophysiology data are left out intentionally to ensure usability in the preoperative clinical practice. Weak responders (n = 30) were defined as patients who fail to show clinically relevant improvement on Unified Parkinson Disease Rating Scale II, III or IV.

RESULTS

The model predicts weak responders with an average area under the curve of the receiver operating characteristic of 0.79 (standard deviation: 0.08), a true positive rate of 0.80 and a false positive rate of 0.24, and a diagnostic accuracy of 78%. The reported influences of individual preoperative variables are useful for clinical interpretation of the model, but cannot been interpreted separately regardless of the other variables in the model.

CONCLUSION

The model's diagnostic accuracy confirms the utility of machine learning based motor response prediction based on clinical preoperative variables. After reproduction and validation in a larger and prospective cohort, this prediction model holds potential to support clinicians during preoperative patient counseling.

Brain Metabolisms Involved in Self-Reported Quality of Mobility in Parkinson's Disease

Background

Objective motor ratings and subjective motor complaints are both widely used in Parkinson’s disease (PD). However, the objective basis to the self-perceived mobility quality is still not well elucidated.

Purposes

We aimed to figure out the relevancy between the UPDRS motor scores and PDQ39 mobility sub-scores, and further explore whether physician-assessed motor dysfunctions and patients-reported mobility deficits have some shared mechanisms.

Methods

49 patients with PD who completed the PDQ39 scale were retrospectively included. The relevancy between mobility quality and UPDRS scores was assessed, as well as the related presynaptic dopaminergic binding (¹¹C-CFT) and glucose metabolism (¹⁸F-FDG) in this dual-tracer PET imaging study.

Results

Modest correlation was found between UPDRS motor score and the PDQ39 mobility sub-score (r = 0.440, p = 0.002). No correlation was found between PDQ39 mobility SI and the dopaminergic lesions in putamen; however, the strict correlation was found with the UPDRS motor scores. In terms of global PD related pattern (PDRP) scores, the two motor scores both correlated strictly. In the further regional metabolism exploration, cerebellum correlated positively with PDQ39 mobility sub-scores, and the frontal and parietal regions mainly correlated negatively with the motor quality scores.

Conclusion

UPDRS motor scores and PDQ39 mobility scores were only modestly correlated. The mechanisms involved under mobility quality were beyond dopaminergic deficiency, including motor related cerebellum hyper-metabolism and non-motor related frontal hypo-metabolism. Conclusively, the self-reported mobility experience may have the neurophysiological basis related to both motor and non-motor manifestations in PD.