Lung biopsy in infants with severe bronchopulmonary dysplasia
Bibliographic record
Abstract
INTRODUCTION: Lung biopsy is infrequently performed in the population of infants with severe bronchopulmonary dysplasia (BPD). Yet, its presentation may overlap with other infant diffuse lung diseases, including those within the spectrum of childhood interstitial lung diseases (chILD). Lung biopsy might differentiate between these entities or identify those with an extremely poor prognosis. Both might alter the clinical management of some infants diagnosed with BPD. METHODS: In this tertiary referral center, we drew on a retrospective cohort of 308 preterm infants with severe BPD. Of these, nine underwent lung biopsy between 2012 and 2017. We aimed to assess the indication for lung biopsy, the prior clinical history, safety of the procedure, and describe the biopsy findings. Finally, we considered management decisions in relation to the biopsy results in these patients. RESULTS: All nine infants undergoing biopsy survived the procedure. The mean gestational age and birth weight of the nine patients were 30 ± 3 (range 27-34) weeks and 1421 ± 571 (range 611-2140) grams. All infants received serial echocardiograms to assess pulmonary hypertension, genetic testing, and computed tomography angiography (CTA) before biopsy. In all nine patients moderate to severe alveolar simplification was present and eight had some degree of pulmonary interstitial glycogenosis (PIG) ranging from focal to diffuse. Following biopsy, two infants with PIG received high dose systemic steroids and two separate infants had care redirected. CONCLUSION: In our cohort, lung biopsy was safe and well tolerated. Findings from lung biopsy may aid decision making in selected patients as a part of a step-wise diagnostic algorithm.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".