Detection of secondary causes of spontaneous pneumothorax: Comparison between computed tomography and chest X-ray
Bibliographic record
Abstract
PURPOSE: The aim of this study was to compare the effectiveness of chest X-ray to that of thoracic computed tomography (CT) for the detection of the causes of secondary spontaneous pneumothorax (SP). METHODS: A prospective cohort of patients with SP was studied. All chest X-ray and CT examinations of the patients were reviewed retrospectively by an expert radiologist blinded to clinical data. The concordance between the CT examination and chest X-ray was assessed using the Cohen Kappa coefficient (κ), based on a bootstrap resampling method. RESULTS: A total of 105 patients with SP were included. There were 78 men and 27 women, with a mean age of 34.5 years±14.2 (SD) (range: 16-87 years). Of these, 44/105 (41%) patients had primary SP and 61/105 (59%) had secondary SP due to emphysema (47/61; 77%), tuberculosis (3/61, 5%), lymphangioleiomyomatosis (3/61; 5%), lung cancer (2/61, 3%) or other causes (6/61; 10%). Apart from pneumothorax, CT showed abnormal findings in 85/105 (81%) patients and chest X-ray in 29/105 (28%). Clinically relevant abnormalities were detected on 62/105 (59%) CT examinations. The concordance between chest X-ray and CT was fair for detecting emphysema (κ=0.39; 95% CI: 0.2420-0.55), moderate for a mass or nodule (κ=0.60; 95% CI: 0.28-0.90), fair for alveolar opacities (κ=0.39; 95% CI: -0.02-1.00), and slight for interstitial syndrome (κ=0.20; 95% CI: -0.02-0.85). CONCLUSION: Chest X-ray is not sufficient for detecting the cause of secondary SP. As the detection of the cause of secondary SP may alter the therapeutic approach and long-term follow-up in patients with SP, the usefulness of a systematic CT examination should be assessed in a prospective trial.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".