Hyperpolarised<sup>129</sup>Xe magnetic resonance imaging to monitor treatment response in children with cystic fibrosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Xe gas (XeMRI) can quantify ventilation inhomogeneity by measuring the percentage of unventilated lung volume (ventilation defect per cent (VDP)). While previous studies have demonstrated its sensitivity for detecting early cystic fibrosis (CF) lung disease, the utility of XeMRI to monitor response to therapy in CF is unknown. The aim of this study was to assess the ability of XeMRI to capture treatment response in paediatric CF patients undergoing inpatient antibiotic treatment for a pulmonary exacerbation.15 CF patients aged 8-18 years underwent XeMRI, spirometry, plethysmography and multiple-breath nitrogen washout at the beginning and end of inpatient treatment of a pulmonary exacerbation. VDP was calculated from XeMRI images obtained during a static breath hold using semi-automated k-means clustering and linear binning approaches.XeMRI was well tolerated. VDP, lung clearance index and the forced expiratory volume in 1 s all improved with treatment; however, response was not uniform in individual patients. Of all outcome measures, VDP showed the largest relative improvement (-42.1%, 95% CI -52.1--31.9%, p<0.0001).These data support further investigation of XeMRI as a tool to capture treatment response in CF lung disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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