Lung thermography during the initial reperfusion period to assess pulmonary function in cellular ex vivo lung perfusion
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Bibliographic record
Abstract
BACKGROUND: Thermography is a noninvasive technology to detect low temperatures in poorly circulated areas. In ex vivo lung perfusion (EVLP), lungs are rewarmed to body temperature during the initial 1 h. Currently, the effect of graft thermal changes during the rewarming phase on pulmonary function is unknown. In this study, we evaluated the correlation of lung surface temperature with physiological parameters, wet/dry ratio, and transplant suitability in Lund-type EVLP. METHODS: Fifteen pigs were divided into three groups: control group (no warm ischemia) or donation after circulatory death groups with 60 or 90 min of warm ischemia (n = 5, each). Thermal images of the lower lobes were continuously collected from the bottom of an organ chamber using infrared thermography throughout EVLP. RESULTS: At 8 min, lung surface temperatures of nonsuitable cases were significantly lower than in suitable cases (25.1 ± 0.6 vs. 27.8 ± 1.2°C, p < 0.001), while there was no difference in lung surface temperatures between the two groups at 0-4 min and 12-120 min. There was a significant negative correlation between lung surface temperatures at 8 min and wet/dry ratio at 2 h in the lower lobes (R = -0.769, p < 0.001, cutoff = 26°C, area under the curve = 1.0). A lung surface temperature of <26°C was significantly correlated with poor pulmonary function and transplant nonsuitability. CONCLUSION: A lung surface temperature of ≥26°C at 8 min is a good early predictor of transplant suitability in cellular EVLP and might be applicable in clinical EVLP.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it