Year: 2024
Type: article
Study design: Observational Study
Abstract: Background. Despite the comprehensive study of Parkinson’s disease (PD), studying the quality of life (QoL) of patients, especially the prediction of low QoL, remains an unresolved issue.The aim. To create a prognostic model for low quality of life in patients with Parkinson’s disease by studying the severity of clinical features.Materials and methods. The cross-sectional study included 104 patients diagnosed with PD (56 % of men, 48 % of women); the median age was 67.0 [60.0; 71.0] years; the median duration of the disease was 5.0 [2.0; 8.0] years. We assessed motor and non-motor symptoms of PD in all patients. The PDQ-39 (Parkinson’s Disease Questionnaire) scale was used to assess the patients’ QoL. We conventionally accepted a PDQ-39 score of 50 or more as a low QoL level in a patient. Binary logistic regression using the stepwise exclusion method was used to create a prognostic model for a low QoL level in a patient with PD.Results. To predict the probability of low QoL in patients with PD depending on the studied clinical manifestations, we proposed a function according to which female gender has the greatest impact on low QoL (odds ratio – 20.0; 95% confidence interval (95% CI): 1.82–222.26). An increase in the PD stage according to the Hoehn – Yahr scale by 1 unit causes 8.77 times increase (95% CI: 2.11–36.49) in the probability of low QoL, an increase on the Epworth sleepiness scale by 1 point – 2.33 times increase (95% CI: 1.24–4.38), an increase in the level of depression according to the HADS (Hospital Anxiety and Depression Scale) by 1 point – 1.93 times increase (95% CI: 1.13–3.32). The sensitivity and specificity of the obtained function were 95.9 and 80%, respectively.Conclusion. The proposed prognostic formula can be used in neurologists’ appointments to determine the probability of low quality of life in patients with Parkinson’s disease.
Institution: North-Eastern Federal University
Language: English
Subfield: Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4404704232