Manual aspiration of a pneumothorax after CT-guided lung biopsy: outcomes and risk factors
Bibliographic record
Abstract
OBJECTIVE: Quantify the outcomes following pneumothorax aspiration and influence upon chest drain insertion. METHODS: This was a retrospective cohort study of patients who underwent aspiration for the treatment of a pneumothorax following a CT percutaneous transthoracic lung biopsy (CT-PTLB) from January 1, 2010 to October 1, 2020 at a tertiary center. Patient, lesion and procedural factors associated with chest drain insertion were assessed with univariate and multivariate analyses. RESULTS: < 0.001). On multivariate analysis, larger pneumothorax size and supine position during biopsy remained significant for chest drain insertion. Aspiration of a larger pneumothorax (radial depths ≥3 cm and ≥4 cm) had a 50% rate of success. Aspiration of a smaller pneumothorax (radial depth 2-3 cm and <2 cm) had an 82.6% and 100% rate of success, respectively. CONCLUSION: Aspiration of pneumothorax after CT-PTLB can help reduce chest drain insertion in approximately 50% of patients with larger pneumothoraces and even more so with smaller pneumothoraces (>80%). ADVANCES IN KNOWLEDGE: Aspiration of pneumothoraces up to 3 cm was often associated with avoiding chest drain insertion and allowing for earlier discharge.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".