Artificial neural network predicts sex differences of patients with advanced Parkinson’s disease under Levodopa-Carbidopa Intestinal gel

medRxiv (Cold Spring Harbor Laboratory)(2023)

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摘要
Objective Although Levodopa-carbidopa intestinal gel (LCIG) treatment has shown to be efficacious in motor and some non-motor symptoms (NMS), not all the patients with advanced Parkinson’s disease (PD) are ideal candidates. To improve their selection analysis knowledge of prognostic factors is of great importance. We aimed to develop a novel machine learning model to predict the clinical outcomes of patients with advanced PD at 2 years under the LCIG therapy. Methods This was a longitudinal 24-month, observational study of 59 patients with advanced PD of a Greek multicenter registry under LCIG treatment from September 2019 to September 2021. Motor status was assessed with the Unified Parkinson’s Disease Rating Scale (UPDRS) part III (off) and IV. NMS were assessed by the NMS Questionnaire (NMSQ) and the Geriatric Depression Scale (GDS), the quality of life by PDQ-39 and severity by Hoehn &Yahr (HY). Multivariate linear regression, ARIMA, SARIMA, and Long Short-Term Memory-recurrent neural network (LSTM-RNN) models were used. Results Dyskinesia duration and quality of life were significantly improved with LCIG (19% and 10% greater improvement for men than women, respectively). Multivariate linear regression models showed that UPDRS-III was decreased by 1.5 and 4.39 units per one unit of increase of the PDQ-39, UPDRS-IV indexes, respectively. Among all the time series models, the LSTM-RNN model predicts these clinical characteristics with highest accuracy (mean square error =0.0069) Conclusions Τhe LSTM-RNN model predicts with highest accuracy sex dependent clinical outcomes of patients with advanced PD after two years of LCIG therapy. ### Competing Interest Statement Anastasia Bougea is an investigator in studies funded by AbbVie; the Michael J. Fox Foundation for Parkinson Research; the ALAMEDA study (H2020-EU, Grant Agreement 101017558). She has received travel grant, or speaker honoraria from AbbVie. Tajedin Derikvand: has no disclosures. Efthymia Efthymiopoulou is an employee of AbbVie and may hold AbbVie stock and/or stock options. Efthalia Angelopoulou has no disclosures. ### Funding Statement AbbVie Inc.GREECE AbbVie contributed to the design, study conduct and financial support for the study. AbbVie participated in the interpretation of data, review and approval of the publication. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study protocol was approved by ethics committee of AbbVie Greece approval no.:20-6-2019. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors
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关键词
advanced parkinsons,parkinsons disease,artificial neural network,levodopa-carbidopa
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