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Background: Parkinson's disease (PD) represents one of the most frequently seen neurodegenerative disorders, while anxiety accounts for its non-motor symptom (NMS), and it has greatly affected the life quality of PD cases. Bilateral subthalamic nucleus deep brain stimulation (STN-DBS) can effectively treat PD. This study aimed to develop a clinical prediction model for the anxiety improvement rate achieved in PD patients receiving STN-DBS. Methods: The present work retrospectively enrolled 103 PD cases undergoing STN-DBS. Patients were followed up for 1 year after surgery to analyze the improvement in HAMA scores. Univariate and multivariate logistic regression were conducted to select factors affecting the Hamilton Anxiety Scale (HAMA) improvement. A nomogram was established to predict the likelihood of achieving anxiety improvement. Receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA), and calibration curve analysis were conducted to verify nomogram performance. Results: The mean improvement in HAMA score was 23.9% in 103 patients; among them, 68.9% had improved anxiety, 25.2% had worsened (Preop) anxiety, and 5.8% had no significant change in anxiety. Education years, UPDRS-III preoperative score, and HAMA preoperative score were independent risk factors for anxiety improvement. The nomogram-predicted values were consistent with real probabilities. Conclusions: Collectively, a nomogram is built in the present work for predicting anxiety improvement probability in PD patients 1 year after STN-DBS. The model is valuable for determining expected anxiety improvement in PD patients undergoing STN-DBS. [ABSTRACT FROM AUTHOR]

Objective: The Ki-67 index is an indicator of the active proliferation and aggressive behavior of pituitary adenomas (PAs). Appropriate pre- and intra-operatives of the Ki-67 index can help surgeons develop better and more personalized treatment strategies for patients with PAs. This study aimed to investigate the influence factors for predicting the Ki-67 index in PAs. Methods: Data of 178 patients with PAs confirmed by pathology were retrospectively analyzed. According to the Ki-67 index, the patients were divided into the Ki-67 < 3% and Ki-67 ≥ 3% cohorts. Patient data, including age, sex, postoperative immunohistochemical pituitary hormone positive index, Knosp grade, tumor breaking through the sellar floor, rich blood supply to the tumor, tumor located inside the sella, erosion of the dorsum sellae bone, and pituitary-specific transcription factor, were collected. A univariate logistic analysis was used to evaluate the influence factors for a high Ki-67 index. Multiple regression and receiver operating characteristic (ROC) curve were used to analyze the factors with p < 0.05. The mutant status of Ki-67 index was predicted by nomogram. Results: Multivariate regression analysis showed that rich blood supply to the tumor and erosion of the dorsum sellae bone were independent risk factors for the Ki-67 proliferation index. The ROC curves demonstrated that age, rich blood supply to the tumor, and erosion of the dorsum sellae bone can predict the occurrence of a high Ki-67 index. Together, the three risk factors provide a stronger ability to predict the Ki-67 index. The nomogram was developed and validated. Conclusion: Age, rich blood supply to the tumor, and erosion of the dorsum sellae bone are influencing factors for predicting the Ki-67 index. Suitable nomogram prediction models were developed and validated, and there is potential for personalized treatment for PA patients. [ABSTRACT FROM AUTHOR]

Background: Parkinson's disease is a common neurodegenerative disease, with depression being a common non-motor symptom. Bilateral subthalamic nucleus deep brain stimulation is an effective method for the treatment of Parkinson's disease. Thus, this study aimed to establish a nomogram of the possibility of achieving a better depression improvement rate after subthalamic nucleus deep brain stimulation in patients with Parkinson's disease. Methods: We retrospectively analyzed 103 patients with Parkinson's disease who underwent subthalamic nucleus deep brain stimulation and were followed up for the improvement of their Hamilton Depression scale scores 1 year postoperatively. Univariate and multivariate logistic regression analyses were used to select factors affecting the improvement rate of depression. A nomogram was then developed to predict the possibility of achieving better depression improvement. Furthermore, the discrimination and fitting performance was evaluated using a calibration diagram, receiver operating characteristics, and decision curve analysis. Results: The mean and median improvement rates of Hamilton Depression scores were 13.1 and 33.3%, respectively. Among the 103 patients, 70.8% had an improved depression, 23.3% had a worsened depression, and 5.8% remained unchanged. Logistic multivariate regression analysis showed that age, preoperative Parkinson's Disease Questionnaire, Hamilton Anxiety, and Hamilton Depression scores were independent factors for the possibility of achieving a better depression improvement rate. Based on these results, a nomogram model was developed. The nomogram had a C-index of 0.78 (95% confidence interval: 0.69–0.87) and an area under the receiver operating characteristics of 0.78 (95% confidence interval: 0.69–0.87). The calibration plot and decision curve analysis further demonstrated goodness-of-fit between the nomogram predictions and actual observations. Conclusion: We developed a nomogram to predict the possibility of achieving good depression improvement 1 year after subthalamic nucleus deep brain stimulation in patients with Parkinson's disease, which showed a certain value in judging the expected depression improvement of these patients. [ABSTRACT FROM AUTHOR]

To study the feasibility of plasma extracellular vesicles (EVs) miRNAs as diagnostic biomarkers for Parkinson's disease (PD). Plasma EVs were isolated from 30 PD patients and 30 age- and sex-matched healthy controls. Plasma EVs miRNAs were analysed by qRT-PCR. SH-SY5Y cells were induced by different concentrations of 1-Methyl-4-phenil-pyridinium (MPP+) to obtain PD cellular model. The levels of miRNAs and α-synuclein (α-syn) in PD cellular model were analysed by qRT-PCR and Western blot. Receiver operating characteristic (ROC) curve analysis was performed to determine the diagnostic usefulness of the miRNAs in plasma EVs for PD. The gene ontology (GO) and KEGG pathways of the target genes of miRNAs were analysed by softwares. The level of hsa-miR-30c-2-3p in plasma EVs was significantly higher in PD patients than that in controls, and the levels of hsa-miR-15b-5p, hsa-miR-138-5p, hsa-miR-338-3p, hsa-miR-106b-3p and hsa-miR-431-5p in plasma EVs were lower in PD patients than that in controls. When compared with the control group, the area under the curve (AUC) values for hsa-miR-15b-5p, hsa-miR-30c-2-3p, hsa-miR-138-5p, hsa-miR-431-5p, hsa-miR-338-3p and hsa-miR-106b-3p were all greater than 0.6. The target genes of hsa-miR-15b-5p, hsa-miR-30c-2-3p, hsa-miR-138-5p and hsa-miR-338-3p were enriched in dopaminergic synapse and PD pathway. The hsa-miR-15b-5p, hsa-miR-30c-2-3p, hsa-miR-138-5p, hsa-miR-106b-3p, hsa-miR-338-3p and hsa-miR-431-5p may be used as potential biomarkers for the diagnosis of PD, and the combined diagnostic accuracy of hsa-miR-15b-5p, hsa-miR-30c-2-3p, hsa-miR-138-5p and hsa-miR-106b-3p was better. The target genes of hsa-miR-15b-5p, hsa-miR-30c-2-3p, hsa-miR-138-5p and hsa-miR-338-3p may regulate the expression of dopamine by dopaminergic synapse and PD pathway. Isolation and identification of plasma EVs. The miRNAs in plasma EVs may be used as potential biomarkers for the diagnosis of PD. When SH-SY5Y cells were induced by different concentrations of MPP+, the levels of miRNAs and α-syn changed gradually. The target genes of miRNAs were enriched in dopaminergic synapse and PD pathway. The target genes of miRNAs may regulate the expression of dopamine. [ABSTRACT FROM AUTHOR]

Purpose: Parkinson's disease (PD) is a common neurodegenerative disease, for which cognitive impairment is a non-motor symptom (NMS). Bilateral subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment for PD. This study established a nomogram to predict cognitive improvement rate after STN-DBS in PD patients. Methods: We retrospectively analyzed 103 PD patients who underwent STN-DBS. Patients were followed up to measure improvement in MoCA scores one year after surgery. Univariate and multivariate logistic regression analyses were used to identify factors affecting improvement in cognitive status. A nomogram was developed to predict this factor. The discrimination and fitting performance were evaluated by receiver operating characteristics (ROC) analysis, calibration diagram, and decision curve analysis (DCA). Results: Among 103 patients, the mean improvement rate of the MoCA score was 37.3% and the median improvement rate was 27.3%, of which 64% improved cognition, 27% worsened cognition, and 8.7% remained unchanged. Logistic multivariate regression analysis showed that years of education, UPDRSIII drug use, MoCA Preop, and MMSE Preop scores were independent factors affecting the cognitive improvement rate. A nomogram model was subsequently developed. The C-index of the nomogram was 0.98 (95%CI, 0.97–1.00), and the area under the ROC was 0.98 (95%CI 0.97–1.00). The calibration plot and DCA demonstrated the goodness-of-fit between nomogram predictions and actual observations. Conclusion: Our nomogram could effectively predict the possibility of achieving good cognitive improvement one year after STN-DBS in patients with PD. This model has value in judging the expected cognitive improvement of patients with PD undergoing STN-DBS. [ABSTRACT FROM AUTHOR]