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基于人工神经网络(ANN)分析的变应性湿疹在暴露于空气污染物和天气变化时的严重程度。

Atopic dermatitis severity during exposure to air pollutants and weather changes with an Artificial Neural Network (ANN) analysis.

机构信息

Division Allergy and Clinical Immunology, Department of Medicine ASL Salerno, "Santa Maria della Speranza" Hospital, Salerno, Italy.

Postgraduate Program in Allergy and Clinical Immunology, University of Naples Federico II, Naples, Italy.

出版信息

Pediatr Allergy Immunol. 2020 Nov;31(8):938-945. doi: 10.1111/pai.13314. Epub 2020 Aug 20.

Abstract

BACKGROUND

Epidemiological studies have shown an association between global warming, air pollution, and allergic diseases. Several air pollutants, including volatile organic compounds, formaldehyde, toluene, nitrogen dioxide (NO ), and particulate matter, act as risk factors for the development or aggravation of atopic dermatitis (AD). We evaluated the impact of air pollutants and weather changes on AD patients.

MATERIALS AND METHODS

Sixty AD patients ≥5 years of age (mean age: 23.5 ± 12.5 years), living in the Campania Region (Southern Italy), were followed for 18 months. The primary outcome was the effect of atmospheric and climatic factors on signs and symptoms of AD, assessed using the SCORAD (SCORing Atopic Dermatitis) index. We measured mean daily temperature (TOD), outdoor relative humidity (RH), diurnal temperature range (DTR), precipitation, particulate with aerodynamic diameter ≤ 10 μm (PM ), NO , tropospheric ozone (O ), and total pollen count (TPC). A multivariate logistic regression analysis was used to examine the associations of AD signs and symptoms with these factors. An artificial neural network (ANN) analysis investigated the relationships between weather changes, environmental pollutants, and AD severity.

RESULTS

The severity of AD symptoms was positively correlated with outdoor temperatures (TOD, DTR), RH, precipitation, PM , NO , O , and TPC. The ANN analysis also showed a good discrimination performance (75.46%) in predicting disease severity based on environmental pollution data, but weather-related factors were less predictive.

CONCLUSION

The results of the present study provide evidence that weather changes and air pollutions have a significant impact on skin reactivity and symptoms in AD patients, increasing the severity of the dermatitis. The knowledge of the single variables proportion on AD severity symptoms is important to propose alerts for exacerbations in patients with AD of each age. This finding represents a good starting point for further future research in an area of increasingly growing interest.

摘要

背景

流行病学研究表明,全球变暖、空气污染与过敏性疾病之间存在关联。包括挥发性有机化合物、甲醛、甲苯、二氧化氮(NO )和颗粒物在内的多种空气污染物,是特应性皮炎(AD)发展或恶化的危险因素。我们评估了空气污染物和天气变化对 AD 患者的影响。

材料和方法

60 名年龄≥5 岁(平均年龄:23.5±12.5 岁)的 AD 患者居住在意大利坎帕尼亚地区,随访时间为 18 个月。主要结局是大气和气候因素对 AD 患者的体征和症状的影响,采用 SCORAD(特应性皮炎评分)指数进行评估。我们测量了每日平均气温(TOD)、室外相对湿度(RH)、日温差(DTR)、降水、空气动力学直径≤10μm 的颗粒物(PM )、NO 、对流层臭氧(O )和总花粉计数(TPC)。采用多变量逻辑回归分析来研究 AD 体征和症状与这些因素的关联。人工神经网络(ANN)分析研究了天气变化、环境污染物与 AD 严重程度之间的关系。

结果

AD 症状的严重程度与室外温度(TOD、DTR)、RH、降水、PM 、NO 、O 、TPC 呈正相关。ANN 分析还显示,基于环境污染数据预测疾病严重程度具有良好的区分性能(75.46%),但天气相关因素的预测能力较差。

结论

本研究结果表明,天气变化和空气污染对 AD 患者的皮肤反应和症状有显著影响,加重了皮炎的严重程度。了解各年龄 AD 患者的单一变量对 AD 严重症状的影响比例,对于为 AD 患者提出病情恶化预警具有重要意义。这一发现为该领域进一步的未来研究提供了一个良好的起点,该领域的研究兴趣日益浓厚。

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