Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/8997
Title: Prediction Equations for Calculating Maximal Inspiratory Pressure from Spirometry and Thoracic Ultrasound After COVID-19 with Gastroesophageal Reflux Disease in Indonesian Adults: A Cross-sectional Study
Authors: Widjanantie, Siti Chandra
Syam, Ari Fahrial
Nusdwinuringtyas, Nury
Susanto, Agus Dwi
Hidayat, Rudy
Kekalih, Aria
Keywords: COVID-19
prediction equation
maximum inspiratory pressure
spirometry
thoracic ultrasound
Issue Date: Jul-2024
Publisher: Acta Medica Indosiana
Citation: Original Article
Abstract: sure using spirometry and thoracic ultrasonography (USG) after COVID-19 with gastroesophageal reflux disease (GERD). Methods: This cross-sectional study was conducted from January to December 2022 and included Indonesian adults recruited by consecutive sampling after they developed COVID-19 with GERD symptoms. The following tests were used: spirometry (forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1 ); thoracic USG (left diaphragm excursion (LDE) and right diaphragm excursion (RDE); and respirometry (maximal inspiratory pressure (MIP). The data were analyzed using Pearson correlational analysis and multiple linear regression. Results: Sixty-two participants were recruited: mean age 37.23 ± 9.76 years and average MIP 49.85 ± 18.13 cmH2 O. MIP correlated significantly with FVC (r = 0.307; p = 0.015), LDE (r = 0.249; p = 0.051), FEV1 (r = 0.186; p = 0.147), and RDE (r = 0.156; p = 0.221). We developed two models based on their applicability. Model 1 provides an MIP prediction equation for health facilities that have only spirometry: 23.841 – (20.455 × FEV1 ) + (26.190 × FVC). Model 2 provides an MIP prediction equation for health facilities that have both spirometry and thoracic USG: 3.530 – (20.025 × FEV1 ) + (25.354 × FVC) + (4.819 × LDE). Conclusion: In this study, measures of respiratory function correlated significantly with diaphragm excursion. MIP can be predicted from spirometry and thoracic USG data. Healthcare facilities can choose the prediction equation model that best meets their situation.
URI: http://localhost:8080/xmlui/handle/123456789/8997
Appears in Collections:VOL 56 NO 3 2024

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