Acta medica Indonesiana · 2024
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.
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Widjanantie Siti Chandra, Syam Ari Fahrial, Nusdwinuringtyas Nury, Susanto Agus Dwi, Hidayat Rudy, Kekalih Aria, Rachmawati Maria Regina, Maryastuti Maryastuti, Damayanti Triya, Prathiwi Putri, Choi Won Ah, Kang Seong Woong
Аннотация
BACKGROUND: This study aimed to determine the prediction equations for calculating maximal inspiratory pressure 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 cmH2O. 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.
RESULTS: Sixty-two participants were recruited: mean age 37.23 ± 9.76 years and average MIP 49.85 ± 18.13 cmH2O. 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.