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利用咽高压测量数据的模式识别技术早期和中期帕金森病吞咽障碍的识别。

Identification of swallowing disorders in early and mid-stage Parkinson's disease using pattern recognition of pharyngeal high-resolution manometry data.

机构信息

Division of Otolaryngology - Head and Neck Surgery, Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.

出版信息

Neurogastroenterol Motil. 2018 Apr;30(4):e13236. doi: 10.1111/nmo.13236. Epub 2017 Nov 16.

Abstract

BACKGROUND

Parkinson's disease (PD) can cause severe dysphagia, especially later in disease progression. Early identification of swallowing dysfunction may lead to earlier intervention. Pharyngeal high-resolution manometry (HRM) provides complementary information to videofluoroscopy, with advantages of being quantitative and objective. Artificial neural network (ANN) classification can examine non-linear relationships among multiple variables with relatively low bias. We evaluated if ANN techniques could differentiate between patients with PD and healthy controls.

METHODS

Simultaneous videofluoroscopy and pharyngeal HRM were performed on 31 patients with early to mid-stage PD and 31 age- and sex-matched controls during thin-liquid swallows of 2 cc, 10 cc and comfortable sip volume. We performed multilayer-perceptron analyses on only videofluoroscopic data, only HRM data or a combination of the two. We also evaluated variability-based parameters, representing variability in manometric parameters across multiple swallows. We hypothesized that patients with PD and controls would be classified with at least 80% accuracy, and that combined videofluoroscopic and HRM data would classify participants better than either alone.

KEY RESULTS

Classification rates were highest with all parameters considered. Maximum classification rate was 82.3 ± 5.2%, recorded for 2 cc swallows. Inclusion of variability-based parameters improved classification rates. Classification rates using only manometric parameters were similar to those using all parameters, and rates were substantially lower for the comfortable sip volumes.

CONCLUSIONS & INFERENCES: Results from these classifications highlight the differences between swallowing function in patients with early and mid-stage PD and healthy controls. Early identification of swallowing dysfunction is key to developing preventative swallowing treatments for those with PD.

摘要

背景

帕金森病(PD)可导致严重的吞咽困难,尤其是在疾病进展后期。早期识别吞咽功能障碍可能有助于更早地进行干预。咽部高分辨率测压(HRM)可提供与视频透视相比具有定量和客观优势的补充信息。人工神经网络(ANN)分类可以检查多个变量之间的非线性关系,具有相对较低的偏差。我们评估 ANN 技术是否可以区分 PD 患者和健康对照者。

方法

对 31 例处于早中期 PD 患者和 31 名年龄和性别匹配的健康对照者进行同步视频透视和咽部 HRM 检查,在吞咽 2cc、10cc 及舒适吸吮量稀薄液体时进行。我们仅对视频透视数据、HRM 数据或两者的组合进行多层感知器分析。我们还评估了基于变异性的参数,代表多个吞咽过程中测压参数的变异性。我们假设 PD 患者和对照组的分类准确率至少为 80%,并且联合视频透视和 HRM 数据的分类效果优于单独使用任何一种数据。

主要结果

考虑所有参数时分类率最高。在 2cc 吞咽时,最大分类率为 82.3±5.2%。包含基于变异性的参数可提高分类率。仅使用测压参数的分类率与使用所有参数的分类率相似,而在舒适吸吮量时的分类率则大大降低。

结论

这些分类结果突出了早期和中期 PD 患者与健康对照者吞咽功能的差异。早期识别吞咽功能障碍是为 PD 患者开发预防性吞咽治疗的关键。

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