Management and recurrence of spontaneous pneumothorax in children
Bibliographic record
Abstract
OBJECTIVE: No guideline clearly prescribes an approach to management of spontaneous pneumothorax in children. The objectives of this study were to evaluate practice variation in the management of spontaneous pneumothorax in children and its probability of recurrence. METHODS: This study was a retrospective chart review followed by a phone follow-up that included all children who had visited a tertiary care paediatric hospital for a first episode of spontaneous pneumothorax between 2008 and 2017. The primary outcomes were the management of pneumothorax (observation, oxygen, needle aspiration, intercostal chest tube, surgery) and the probability of recurrence. All charts were evaluated by a rater using a standardized report form and 10% of the charts were evaluated in duplicate. All children/families were contacted by phone to assess recurrence. The primary analyses were the proportions of each treatment modalities and recurrence, respectively. RESULTS: During the study period, 76 children were deemed eligible for the study. Among them, 59 had a primary spontaneous pneumothorax while 17 were secondary. The most common first therapeutic approaches were chest tube insertion (31), oxygen alone (27), and observation (14). A total of 54 patients were available for follow-up among whom a recurrence was observed in 28 (37% of the total cohort or 52% of available children). CONCLUSION: Chest tube insertion was the first line of treatment in about 40% of children with a first spontaneous pneumothorax. In this population, the recurrence probability is established between 37 and 52% and the majority occurs in the following months.
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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 | 0.002 | 0.014 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".