Bibliographic record
Abstract
Introduction: Acute respiratory distress syndrome (ARDS) presents a diagnostic and therapeutic challenge. Although most cases of ARDS are due to well known clinical entities, there is a subset of patients who present to an intensive care unit with hypoxic respiratory failure and pulmonary infiltrates of unknown etiology. It is unclear weather open lung biopsy is of any value in this patient population. Methods: We determined the yield and safety of open lung biopsy in patients with hypoxic respiratory failure of undetermined origin admitted to an intensive care units from 2000 to 2012. Baseline demographic, clinical, physiological and outcome data were collected by a trained data collector. Results: Seventy five patients admitted to three intensive care units underwent an open lung biopsy. The mean age of the cohort was 61 years with a mean APACH II score of 21. The biopsies were obtained after a median of 2 days of being admitted to the intensive care unit. The overall hospital mortality rate in the cohort was 44%. Biopsy results led to a specific diagnosis in 60% of patients and a change in therapy in 66% of patients. The most common pathological diagnosis was Diffuse alveolar damage with over a third of patients displaying it. Procedural complications consisted of ventilator associated pneumonia (20%), Bleeding (16%) and hemorrhagic shock (3%). Conclusions: open lung biopsy in patients with hypoxic respiratory failure admitted to an intensive care unit had a high diagnostic yield leading to change in therapy with a relatively low complication rate.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.393 | 0.233 |
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".