کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5594035 | 1571283 | 2018 | 41 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
“Spirometric” lung age reference equations: A narrative review
ترجمه فارسی عنوان
یک اسپیرموتریک؟ معادله مرجع سن ریه: یک بررسی روایت
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کلمات کلیدی
ATSMMEFFEV6Reference equationULNLLNFEV1FVCERSSLAPEFBSA - BSALung function test - آزمایش عملکرد ریهEuropean Respiratory Society - انجمن تنفسی اروپاAmerican Thoracic Society - انجمن قلب آمریکاCOPD - بیماری مزمن انسدادی ریهChronic obstructive pulmonary disease - بیماری مزمن انسدادی ریهPeak expiratory flow - جریان انقباض قلهUpper limit of normal - حد بالای طبیعیLower limit of normal - حد پایین عادیAgeing - سالخوردهbody surface area - سطح بدنbody mass index - شاخص توده بدنBMI - شاخص توده بدنیforced vital capacity - ظرفیت حیاتی اجباریNorms - مقررات
موضوعات مرتبط
علوم زیستی و بیوفناوری
بیوشیمی، ژنتیک و زیست شناسی مولکولی
فیزیولوژی
چکیده انگلیسی
The aim of the present paper was to conduct a narrative review of the published norms of the “spirometric” lung-age (SLA). A literature search which covered the period 1970 to June 2017, was conducted using the Pubmed. The search strategy had used the following MeSH words: “Spirometry”[Majr]) AND “Aging”[Majr]. Six original studies have reported equations predicting SLA for adults aged 18-90 years [USA (n = 2), Japan (n = 2); Australia (n = 1) and Tunisia (n = 1)]. Their sample sizes varied from 125 to 15238, with a total of 32334 volunteers (11788 men). Several models of norms were developed. They included one (often, FEV1) or more spirometric data in addition to one (often, height) or more anthropometric data. All studies have validated their norms in additional one or more groups, with satisfactory results. Only three authors have proposed algorithms to interpret SLA. All studies presented several limitations concerning the sample size and/or representation, the age distribution, the use of old spirometric data and/or equipment, the application of old spirometric methods, and especially mathematical and statistical flaws.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Respiratory Physiology & Neurobiology - Volume 247, January 2018, Pages 31-42
Journal: Respiratory Physiology & Neurobiology - Volume 247, January 2018, Pages 31-42
نویسندگان
Mouna Ben Khelifa, Halima Ben Salem, Raoudha Sfaxi, Souheil Chatti, Sonia Rouatbi, Helmi Ben Saad,