Longitudinal lung function assessment of patients hospitalised with COVID-19 using <sup>1</sup> H and <sup>129</sup> Xe lung MRI
Bibliographic record
Abstract
Abstract Introduction Microvascular abnormalities and impaired gas transfer have been observed in patients with COVID-19. The progression of pathophysiological pulmonary changes during the post-acute period in these patients remains unclear. Methods Patients who were hospitalised due to COVID-19 pneumonia underwent a pulmonary 1 H and 129 Xe MRI protocol at 6, 12, 25 and 51 weeks after hospital admission. The imaging protocol included: ultra-short echo time, dynamic contrast enhanced lung perfusion, 129 Xe lung ventilation, 129 Xe diffusion weighted and 129 Xe 3D spectroscopic imaging of gas exchange. Results 9 patients were recruited and underwent MRI at 6 (n=9), 12 (n=9), 25 (n=6) and 51 (n=8) weeks after hospital admission. Patients with signs of interstitial lung damage at 3 months were excluded from this study. At 6 weeks after hospital admission, patients demonstrated impaired 129 Xe gas transfer (RBC:M) but normal lung microstructure (ADC, Lm D ). Minor ventilation abnormalities present in four patients were largely resolved in the 6–25 week period. At 12 week follow up, all patients with lung perfusion data available (n=6) showed an increase in both pulmonary blood volume and flow when compared to 6 weeks, though this was not statistically significant. At 12 week follow up, significant improvements in 129 Xe gas transfer were observed compared to 6-week examinations, however 129 Xe gas transfer remained abnormally low at weeks 12, 25 and 51. Changes in 129 Xe gas transfer correlated significantly with changes in pulmonary blood volume and TL CO Z-score. Conclusions This study demonstrates that multinuclear MRI is sensitive to functional pulmonary changes in the follow up of patients who were hospitalised with COVID-19. Impairment of xenon transfer may indicate damage to the pulmonary microcirculation.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 teacher head, 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".