Prediction of spirometry outcome in Croatian patients with chronic obstructive pulmonary disease.

IF 1.1 Q4 RESPIRATORY SYSTEM
Erim Bešić, Davorka Muršić, Tajana Jalušić Glunčić, Jelena Ostojić, Sanda Škrinjarić-Cincar, Martina Dokoza, Nataša Karamarković Lazarušić, Miroslav Samaržija, Andrea Vukić Dugac
{"title":"Prediction of spirometry outcome in Croatian patients with chronic obstructive pulmonary disease.","authors":"Erim Bešić, Davorka Muršić, Tajana Jalušić Glunčić, Jelena Ostojić, Sanda Škrinjarić-Cincar, Martina Dokoza, Nataša Karamarković Lazarušić, Miroslav Samaržija, Andrea Vukić Dugac","doi":"10.4081/monaldi.2024.3099","DOIUrl":null,"url":null,"abstract":"<p><p>The current study offers an extensive examination of the influence of 29 diverse parameters on spirometry measurement variables in a cohort of 534 patients with chronic obstructive pulmonary disease (COPD) from five different centers in Croatia. The study elucidates both the magnitude and direction of the effect exerted by the 29 predictors on forced vital capacity (FVC), forced expiratory volume in one second (FEV1), the ratio FEV1/FVC, and predicted forced expiratory flow at 50% of FVC. Additionally, the development of prediction models for these parameters has been undertaken using several statistical methods. The study identifies fat-free mass index, 6-minute walk distance, predicted diffusing capacity of the lung for carbon monoxide, arterial partial pressure of oxygen, and both arterial and tissue hemoglobin oxygen saturation percentage as robust positive predictors for all four spirometry parameters. Body mass index is recognized as a weak positive predictor for FEV1 and FEV1/FVC, commonly observed in COPD patients. As expected, smoking years is identified as a strong negative predictor for all four spirometry parameters, while age and illness duration exhibit strong predictive negative associations. Furthermore, modified medical research council, arterial partial pressure carbon dioxide, St George's respiratory questionnaire, COPD assessment test, depression anxiety stress scales, and nutritional risk screening are identified as weak negative predictors. Charlson comorbidity index, phase angle, and number of comorbidities do not exhibit a significant impact on spirometry variables. Ultimately, the performed factorial analysis categorized the 29 parameters into five groups, which were identified as relating to lung function, health status, nutritional status, age, and smoking. Multiple regression analysis, including four newly derived parameters based on the results of factorial analysis, identified nutritional status as a positive predictor for spirometry readings, while smoking, poor health status, and age were identified as negative predictors in successive order.</p>","PeriodicalId":51593,"journal":{"name":"Monaldi Archives for Chest Disease","volume":" ","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Monaldi Archives for Chest Disease","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4081/monaldi.2024.3099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"RESPIRATORY SYSTEM","Score":null,"Total":0}
引用次数: 0

Abstract

The current study offers an extensive examination of the influence of 29 diverse parameters on spirometry measurement variables in a cohort of 534 patients with chronic obstructive pulmonary disease (COPD) from five different centers in Croatia. The study elucidates both the magnitude and direction of the effect exerted by the 29 predictors on forced vital capacity (FVC), forced expiratory volume in one second (FEV1), the ratio FEV1/FVC, and predicted forced expiratory flow at 50% of FVC. Additionally, the development of prediction models for these parameters has been undertaken using several statistical methods. The study identifies fat-free mass index, 6-minute walk distance, predicted diffusing capacity of the lung for carbon monoxide, arterial partial pressure of oxygen, and both arterial and tissue hemoglobin oxygen saturation percentage as robust positive predictors for all four spirometry parameters. Body mass index is recognized as a weak positive predictor for FEV1 and FEV1/FVC, commonly observed in COPD patients. As expected, smoking years is identified as a strong negative predictor for all four spirometry parameters, while age and illness duration exhibit strong predictive negative associations. Furthermore, modified medical research council, arterial partial pressure carbon dioxide, St George's respiratory questionnaire, COPD assessment test, depression anxiety stress scales, and nutritional risk screening are identified as weak negative predictors. Charlson comorbidity index, phase angle, and number of comorbidities do not exhibit a significant impact on spirometry variables. Ultimately, the performed factorial analysis categorized the 29 parameters into five groups, which were identified as relating to lung function, health status, nutritional status, age, and smoking. Multiple regression analysis, including four newly derived parameters based on the results of factorial analysis, identified nutritional status as a positive predictor for spirometry readings, while smoking, poor health status, and age were identified as negative predictors in successive order.

克罗地亚慢性阻塞性肺病患者肺活量测定结果的预测。
本研究对来自克罗地亚五个不同中心的 534 名慢性阻塞性肺病(COPD)患者进行了广泛研究,探讨了 29 种不同参数对肺活量测量变量的影响。研究阐明了 29 个预测因子对用力肺活量 (FVC)、一秒钟内用力呼气量 (FEV1)、FEV1/FVC 比值和 50%FVC时的预测用力呼气流量的影响程度和方向。此外,还采用多种统计方法为这些参数建立了预测模型。研究发现,去脂体重指数、6 分钟步行距离、肺部对一氧化碳的预测弥散能力、动脉血氧分压以及动脉和组织血红蛋白氧饱和度百分比是所有四个肺活量参数的可靠的正向预测因子。体重指数被认为是慢性阻塞性肺病患者常见的 FEV1 和 FEV1/FVC 的微弱正向预测因子。正如预期的那样,吸烟年限被认为是所有四个肺活量参数的强负预测因子,而年龄和病程则表现出强预测负相关。此外,改良医学研究委员会、动脉二氧化碳分压、圣乔治呼吸问卷、慢性阻塞性肺病评估测试、抑郁焦虑压力量表和营养风险筛查被认为是弱的负预测因子。夏尔森合并症指数、相位角和合并症数量对肺活量变量没有显著影响。最终,因子分析将 29 个参数分为五组,分别与肺功能、健康状况、营养状况、年龄和吸烟有关。多元回归分析(包括根据因子分析结果新得出的四个参数)确定营养状况是肺活量读数的正向预测因素,而吸烟、健康状况差和年龄依次被确定为负向预测因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
3.60
自引率
0.00%
发文量
1
审稿时长
12 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信