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• W4317491772 startingPage "100996" @default.
• W4317491772 abstract "Diagnosing interstitial lung disease (ILD) remains challenging. Guidelines recommend utilizing a multidisciplinary discussion (MDD) to review clinical and radiographic data and if diagnostic uncertainty persists, then to obtain histopathology. Surgical lung biopsy and transbronchial lung cryobiopsy (TBLC) are acceptable methods, but risks of complications may be prohibitive. The Envisia genomic classifier (EGC) represents another option to determine a molecular usual interstitial pneumonia (UIP) signature to facilitate an ILD diagnosis at MDD with high sensitivity and specificity. We evaluated the concordance between TBLC and EGC at MDD and the safety of this procedure.Demographic data, pulmonary function values, chest imaging pattern, procedural information, and MDD diagnosis were recorded. Concordance was defined as agreement between the molecular EGC results and histopathology from TBLC in the context of the patient's High Resolution CT pattern.49 patients were enrolled. Imaging demonstrated a probable (n = 14) or indeterminate (n = 7) UIP pattern in 43% and an alternative pattern in 57% (n = 28). EGC results were positive for UIP in 37% (n = 18) and negative in 63% (n = 31). MDD diagnosis was obtained in 94% (n = 46) with fibrotic hypersensitivity pneumonitis (n = 17, 35%) and IPF (n = 13, 27%) most common. The concordance between EGC and TBLC at MDD was 76% (37/49) with discordant results seen in 24% (12/49) of patients.There appears to be reasonable concordance between EGC and TBLC results at MDD. Efforts clarifying the contributions of these tools to an ILD diagnosis may help identify specific patient populations that may benefit from a tailored diagnostic approach." @default.
• W4317491772 created "2023-01-20" @default.
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• W4317491772 date "2023-06-01" @default.
• W4317491772 modified "2023-10-01" @default.
• W4317491772 title "Real-world utility of a genomic classifier in establishing a diagnosis of newly identified interstitial lung disease" @default.
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• W4317491772 doi "https://doi.org/10.1016/j.resmer.2023.100996" @default.
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