Clinical Report: A Case Study of Pleuroparenchymal Fibroelastosis
Overview
This report details a case of pleuroparenchymal fibroelastosis (PPFE) without radiological pleural involvement, highlighting the atypical presentation of this rare interstitial lung disease. The patient, a 66-year-old female, exhibited a progressive decline in lung function despite treatment.
Background
Pleuroparenchymal fibroelastosis (PPFE) is a rare interstitial lung disease characterized by excessive elastosis and fibrosis, primarily affecting the pleura and adjacent lung parenchyma. Its atypical presentations, particularly those without overt pleural involvement, complicate diagnosis and management. Understanding PPFE is crucial due to its association with poor prognosis and progressive lung function decline.
Data Highlights
Replace '
No numerical data available.
' with specific numerical data from the case.
Key Findings
The patient presented with a persistent non-productive cough and no other respiratory symptoms.
Histopathology confirmed an NSIP pattern in the lower lobes and intra-alveolar fibroelastosis in the upper lobes consistent with PPFE.
Initial pulmonary function tests showed preserved lung volumes but a decline in diffusion capacity over time.
The patient was treated with immunosuppressive therapy, including prednisone and mycophenolate mofetil.
Follow-up revealed a progressive pulmonary fibrosis phenotype with declining lung function.
Clinical Implications
Clinicians should be aware of atypical presentations of PPFE, as they may lack classic radiological signs. Early diagnosis and appropriate management are critical to potentially slowing disease progression and improving patient outcomes.
Conclusion
This case underscores the importance of recognizing the heterogeneity of PPFE presentations and the need for a multidisciplinary approach in diagnosis and management.
by Iris A. Simons, Daniel A. Korevaar, Teodora Radonic, Carmen Ariño-Palao, Ralf W. Sprengers, Martijn van Dorp, Marjolein E. M. Lacor, JanWillem Duitman, Esther J. Nossent
A VHA study across 11 vendors finds AI-generated primary care notes score lower than clinician-written notes, with the largest deficits in thoroughness, organization, and usefulness