Extracorporeal Lung Support as a Bridge to Diagnosis of Pulmonary Tumor Embolism
Bibliographic record
Abstract
Bridging to diagnosis is an emerging technique used in end-stage cardiorespiratory failure that prolongs a patient's life using various modalities of extracorporeal lung support (ECLS) to achieve antemortem diagnosis. Pulmonary tumor embolism occurs when cell clusters travel from primary malignancies through venous circulation to the lungs, causing respiratory failure through inflammatory and venoocclusive pathways. Due to its nonspecific symptomatology, pulmonary tumor embolism remains an elusive diagnosis antemortem. Herein, we bridge a patient who presented in acute respiratory failure to the diagnosis of pulmonary tumor embolism from a gastric signet-ring cell carcinoma using ECLS modalities including venoarterial extracorporeal membrane oxygenation and centrally cannulated Novalung pumpless extracorporeal lung assist. We demonstrate the utility of this approach in diagnostically uncertain cases in unstable patients who are potentially acceptable ECLS and transplant candidates.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".