Effect of Pain on Quality of Life in Patients with Parkinson's Disease

Objective: To analyze the impact of pain on the quality of life of patients with Parkinson's disease. Methods: 200 patients with primary Parkinson's disease admitted in the Shaanxi Provincial People's Hospital from August 2019 to November 2020 were selected for the experiment, and these patients were divided into pain group and non-pain group in turn. Among them, there were 98 patients in the pain group and 102 patients in the non-pain group. King's Parkinson's disease pain scale was used to evaluate the severity and type of pain, and then ess and HAMD-17 were used to evaluate patients' depression and daytime sleepiness. Results: the incidence of pain in patients with Parkinson's disease was about 49%, including 38% of wave related pain and 74% of musculoskeletal pain. The score of quality-of-life Scale-39 in the pain group was higher than that in the non-pain group, and the difference was statistically significant (P < 0.01). Conclusion: musculoskeletal pain is a common type of pain in patients with Parkinson's disease, followed by nocturnal pain and fluctuation related pain. Its pain will have a direct impact on the quality of life of patients with Parkinson's disease

Effect of Vestibular Rehabilitation Training on Residual Dizziness in Patients with Benign Paroxysmal Positional Vertigo

Objective: To study the effect of vestibular rehabilitation training on residual dizziness in patients with benign paroxysmal positional vertigo (BPPV). Methods: 70 patients with residual dizziness diagnosed as BPPV in Shaanxi Provincial People's hospital were divided into observation group and control group. The observation group was treated with manual reduction + vestibular function rehabilitation training, and the control group was treated with manual reduction. There were 35 patients in the two groups. Within two weeks before and after training, the patients' vertigo Disability Rating Scale score (DHI), vestibular dysfunction rating scale score (vADL) and vestibular symptom index score (vADL) were effectively evaluated. Results: before training, there was no significant difference in DHI, vADL and vADL scores between the observation group and the control group (P > 0.05). After training, there was significant difference in DHI, vADL and vADL scores (P < 0.05). Conclusion: vestibular rehabilitation training can effectively change the residual dizziness symptoms of patients with BPPV, and the treatment effect is significantly higher than that of patients with simple manual reduction. The treatment of residual dizziness symptoms of patients with BPPV can greatly promote and apply vestibular rehabilitation training

Effect of Rehabilitation Training on Limb Function and Self-Care Ability of Patients with Parkinson's Disease

Objective: This study mainly analyzes the effect of rehabilitation training on limb function and self-care ability of Parkinson's disease patients. Methods: 50 patients with Parkinson's disease who were diagnosed and treated in a Shaanxi Provincial People's Hospital in China from February 2, 2018 to July 2, 2021 were tested. These patients were divided into two groups randomly with 25 patients in each group. The control group should adopt routine treatment and nursing intervention, and the experimental group should take the control group as the benchmark and apply rehabilitation exercise training, The limb function and self-care ability of patients in the experimental group were compared with control group before and after the intervention. Results: after the intervention, the patients in the control group, whether Berg balance scale or UPDRS - â…¢ score, will be lower than the patients in the observation group. And after the intervention, the Barthel score of both groups will be better than that before the intervention (P < 0.01). Conclusion: rehabilitation training has a great impact on the limb function and self-care ability of patients with Parkinson's disease. Through the form of rehabilitation exercise training, we can further improve the limb function of current patients, make the self-care ability of patients become higher, and delay the development of the disease

GumDrop at the DISRPT2019 Shared Task: A Model Stacking Approach to Discourse Unit Segmentation and Connective Detection

In this paper we present GumDrop, Georgetown University's entry at the DISRPT 2019 Shared Task on automatic discourse unit segmentation and connective detection. Our approach relies on model stacking, creating a heterogeneous ensemble of classifiers, which feed into a metalearner for each final task. The system encompasses three trainable component stacks: one for sentence splitting, one for discourse unit segmentation and one for connective detection. The flexibility of each ensemble allows the system to generalize well to datasets of different sizes and with varying levels of homogeneity.Comment: Proceedings of Discourse Relation Parsing and Treebanking (DISRPT2019

Quantifying Individual Risk for Binary Outcome: Bounds and Inference

Understanding treatment heterogeneity is crucial for reliable decision-making in treatment evaluation and selection. While the conditional average treatment effect (CATE) is commonly used to capture treatment heterogeneity induced by covariates and design individualized treatment policies, it remains an averaging metric within subpopulations. This limitation prevents it from unveiling individual-level risks, potentially leading to misleading results. This article addresses this gap by examining individual risk for binary outcomes, specifically focusing on the fraction negatively affected (FNA) conditional on covariates -- a metric assessing the percentage of individuals experiencing worse outcomes with treatment compared to control. Under the strong ignorability assumption, FNA is unidentifiable, and we find that previous bounds are wide and practically unattainable except in certain degenerate cases. By introducing a plausible positive correlation assumption for the potential outcomes, we obtain significantly improved bounds compared to previous studies. We show that even with a positive and statistically significant CATE, the lower bound on FNA can be positive, i.e., in the best-case scenario many units will be harmed if receiving treatment. We establish a nonparametric sensitivity analysis framework for FNA using the Pearson correlation coefficient as the sensitivity parameter, thereby exploring the relationships among the correlation coefficient, FNA, and CATE. We also present a practical and tractable method for selecting the range of correlation coefficients. Furthermore, we propose flexible estimators for refined FNA bounds and prove their consistency and asymptotic normality

Numerical simulation of clouds and precipitation depending on different relationships between aerosol and cloud droplet spectral dispersion

The aerosol effects on clouds and precipitation in deep convective cloud systems are investigated using the Weather Research and Forecast (WRF) model with the Morrison two-moment bulk microphysics scheme. Considering positive or negative relationships between the cloud droplet number concentration (Nc) and spectral dispersion (ɛ), a suite of sensitivity experiments are performed using an initial sounding data of the deep convective cloud system on 31 March 2005 in Beijing under either a maritime (‘clean’) or continental (‘polluted’) background. Numerical experiments in this study indicate that the sign of the surface precipitation response induced by aerosols is dependent on the ɛ−Nc relationships, which can influence the autoconversion processes from cloud droplets to rain drops. When the spectral dispersion ɛ is an increasing function of Nc, the domain-average cumulative precipitation increases with aerosol concentrations from maritime to continental background. That may be because the existence of large-sized rain drops can increase precipitation at high aerosol concentration. However, the surface precipitation is reduced with increasing concentrations of aerosol particles when ɛ is a decreasing function of Nc. For the ɛ−Nc negative relationships, smaller spectral dispersion suppresses the autoconversion processes, reduces the rain water content and eventually decreases the surface precipitation under polluted conditions. Although differences in the surface precipitation between polluted and clean backgrounds are small for all the ɛ−Nc relationships, additional simulations show that our findings are robust to small perturbations in the initial thermal conditions. Keywords: aerosol indirect effects, cloud droplet spectral dispersion, autoconversion parameterization, deep convective systems, two-moment bulk microphysics schem