Comparison of Interstitial Lung Disease Between Antineutrophil Cytoplasmic Antibodies Positive and Negative Patients: A Retrospective Cohort Study
Bibliographic record
Abstract
OBJECTIVE: Positive antineutrophil cytoplasmic antibodies (ANCAs) may occur in the setting of interstitial lung disease (ILD), with or without ANCA-associated vasculitis (AAV). We aim to compare the characteristics and clinical course of patients with ILD and positive ANCA (ANCA-ILD) to those with negative ANCA. METHODS: We performed a single-center retrospective cohort study from 2018 to 2021. All patients with ILD and ANCA testing were included. Patient characteristics (symptoms, dyspnea scale, and systemic AAV), test results (pulmonary high-resolution computed tomography and pulmonary function tests), and adverse events were collected from electronic medical records. Descriptive statistics and the Fisher exact test were used to compare the outcomes of patients with ANCA-ILD to those with ILD and negative ANCA. RESULTS: A total of 265 patients with ILD were included. The mean follow-up duration was 69.3 months, 26 patients (9.8%) were ANCA positive, and 69.2% of those with ANCA-ILD had another autoantibody. AAV occurred in 17 patients (65.4%) with ANCA-ILD. In 29.4% of patients, AAV developed following ILD diagnosis. Usual interstitial pneumonia was the most common radiologic pattern in patients with ANCA-ILD. There was no association between ANCA status and the evolution of dyspnea, diffusing capacity of the lungs for carbon monoxide, and lung imaging. Forced vital capacity improved over time in 42% of patients with ANCA-ILD and in 17% of patients with negative ANCA (P = 0.006). Hospitalization occurred in 46.2% of patients with ANCA-ILD and in 21.8% of patients with negative ANCA (P = 0.006). Both groups had similar mortality rates. CONCLUSION: Routine ANCA testing should be considered in patients with ILD. Patients with ANCA-ILD are at risk for AAV. More research is required to better understand and manage patients with ANCA-ILD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".