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      Factors affecting spirometry reference range in growing children

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          Abstract

          Objectives:

          To find out the association of weight, height and age with spirometry variables and to generate a regression equation by taking weight as an independent variable beside age and height among children and adolescents of Karachi.

          Methods:

          A modified form of ISSAC questionnaire was used. The spirometry variables recorded were Forced vital capacity (FVC), Forced expiratory volume in 1 second (FEV 1), FEV 1/FVC, Peak expiratory flow rate (PEF), Forced expiratory flow between 25% and 75% expired volume (FEF 25-75). A person’s correlation coefficient among boys and girls were calculated for all spirometry variable considering age, height and weight as independent variables. The linear regression models were calculated.

          Results:

          The results reported a linear correlation of lung function variables with all three independent variables (i.e. p-value = 0.000), in which age and height manifested a strong positive correlation while weight reported a moderately significant correlation. All spirometry variables such as FVC, FEV 1, PEF and FEF 25-75 reported a significant coefficient of dependency and coefficient of correlation individually with age, height and weight.

          Conclusion:

          It is concluded that beside age, height and weight both also have significant correlation with lung volumes so these should be taken into account when using spirometry as a diagnostic test.

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          Most cited references19

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          Respiratory health and disease in Europe: the new European Lung White Book.

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            Genetic ancestry in lung-function predictions.

            Self-identified race or ethnic group is used to determine normal reference standards in the prediction of pulmonary function. We conducted a study to determine whether the genetically determined percentage of African ancestry is associated with lung function and whether its use could improve predictions of lung function among persons who identified themselves as African American. We assessed the ancestry of 777 participants self-identified as African American in the Coronary Artery Risk Development in Young Adults (CARDIA) study and evaluated the relation between pulmonary function and ancestry by means of linear regression. We performed similar analyses of data for two independent cohorts of subjects identifying themselves as African American: 813 participants in the Health, Aging, and Body Composition (HABC) study and 579 participants in the Cardiovascular Health Study (CHS). We compared the fit of two types of models to lung-function measurements: models based on the covariates used in standard prediction equations and models incorporating ancestry. We also evaluated the effect of the ancestry-based models on the classification of disease severity in two asthma-study populations. African ancestry was inversely related to forced expiratory volume in 1 second (FEV(1)) and forced vital capacity in the CARDIA cohort. These relations were also seen in the HABC and CHS cohorts. In predicting lung function, the ancestry-based model fit the data better than standard models. Ancestry-based models resulted in the reclassification of asthma severity (based on the percentage of the predicted FEV(1)) in 4 to 5% of participants. Current predictive equations, which rely on self-identified race alone, may misestimate lung function among subjects who identify themselves as African American. Incorporating ancestry into normative equations may improve lung-function estimates and more accurately categorize disease severity. (Funded by the National Institutes of Health and others.) 2010 Massachusetts Medical Society
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              Reference values for lung function: past, present and future.

              Reliable interpretation of pulmonary function results relies on the availability of appropriate reference data to help distinguish between health and disease and to assess the severity and nature of any functional impairment. The overwhelming number of published reference equations, with at least 15 published for spirometry alone in the past 3 yrs, complicates the selection of an appropriate reference. The use of inappropriate reference equations and misinterpretation, even when potentially appropriate equations are used, can lead to serious errors in both under and over diagnosis, with its associated burden in terms of financial and human costs. Further misdiagnosis occurs when fixed cut-offs, such as 80% predicted forced expiratory volume in 1 s (FEV(1)) or 0.70 FEV(1)/forced vital capacity, are used; particularly in young children and elderly adults. While per cent predicted has historically been used to interpret lung function results, z-scores are more appropriate as they take into account the predicted value, as well as the between-subject variability of measurements. We aim to highlight some of the main issues in selecting and using reference equations and discuss how recent developments may improve interpretation of pulmonary function results.
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                Author and article information

                Journal
                Pak J Med Sci
                Pak J Med Sci
                Pakistan Journal of Medical Sciences
                Professional Medical Publications (Pakistan )
                1682-024X
                1681-715X
                Nov-Dec 2019
                : 35
                : 6
                : 1587-1591
                Affiliations
                [1 ]Sara Sadiq, MBBS, M.Phil. Department of Physiology, CMH Institute of Medical Sciences, Bahawalpur, Pakistan
                [2 ]Prof. Nadeem Ahmed Rizvi, MBBS, MCPS, MRCP, FRCP. Head of Chest Medicine, Jinnah Postgraduate Medical Centre Karachi, Pakistan
                [3 ]Fahad Khalid Soleja, Undergraduate MBBS Student, Ziauddin University, Karachi, Pakistan
                [4 ]Muaz Abbasi, Undergraduate MBBS Student, Ziauddin University, Karachi, Pakistan
                Author notes
                Correspondence: Dr. Sara Sadiq, H.No: 2146/81 Kamora Colony, Nawabshah, Sindh, Pakistan. E-mail: dr.sarabhatti@ 123456gmail.com
                Article
                PJMS-35-1587
                10.12669/pjms.35.6.1212
                6861488
                31777498
                554b11fa-b64c-433b-823b-485dd857cba0
                Copyright: © Pakistan Journal of Medical Sciences

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 19 December 2018
                : 11 June 2019
                : 01 July 2019
                : 31 August 2019
                : 04 September 2019
                Categories
                Original Article

                pulmonary function test,spirometry,forced vital capacity,regression analysis

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