Diagnosis of idiopathic pulmonary fibrosis by virtual means using "IPFdatabase"- a new software.

BACKGROUND: The diagnostic algorithm for idiopathic pulmonary fibrosis (IPF) guidelines has some shortcomings. The aim of the present study was to develop a novel software, "IPFdatabase", that could readily apply the diagnostic criteria per IPF guidelines and make a 'virtual' diagnosis of IPF. METHODS: Software was developed as a step-by-step compilation of necessary information according to guidelines to enable a diagnosis of IPF. Software accuracy was validated primarily by comparing software diagnoses to those previously made at a Center for Interstitial Lung Diseases. RESULTS: Clinical validation on 98 patients (68 male, age 61.0 ±â€¯8.5 years), revealed high software accuracy for IPF diagnosis when compared to historical diagnoses (sensitivity 95.5%, specificity 96.2%; positive predictive value 95.5%, negative predictive value 96.2%). A general radiologist and a general pathologist reviewed relevant data with and without the new software: interobserver agreement increased when they used the IPFdatabase (kappa 0.18 to 0.64 for radiology, 0.13 to 0.59 for pathology). CONCLUSION: IPFdatabase is a useful diagnostic tool for typical cases of IPF, and potentially restricts the need for MDDs to atypical and complex cases. We propose this web-designed software for instant accurate diagnosis of IPF by virtual means and for educational purposes; the software is readily accessed with mobile apps, allows incorporation of updated version of guidelines, can be utilized for gathering data useful for future studies and give physicians rapid feedback in daily practice.