Bibliographic record
Abstract
BACKGROUND: Single measurements of peak oxygen uptake (VO2) have been shown to predict mortality in patients with cystic fibrosis (CF) although no longitudinal study of serial measurements has been reported in children. A study was undertaken to determine whether the initial, final, or the rate of fall of forced expiratory volume in 1 second (FEV1) or peak VO2 was a better predictor of mortality. METHODS: Twenty eight children aged 8-17 years with CF performed annual pulmonary function and maximal exercise tests over a 5 year period to determine FEV1 and peak VO2, magnitude of their change over time, and survival over the subsequent 7-8 years. Analysis was done using Kaplan-Meier curves and Cox proportional hazard model. RESULTS: Peak VO2 fell during the observation period in 70% of the patients, with a mean annual decline of 2.1 ml/min/kg. Initial peak VO2 was not predictive of mortality but rate of decline and final peak VO2 of the series were significant predictors. Patients with peak VO2 less than 32 ml/min/kg exhibited a dramatic increase in mortality, in contrast to those whose peak VO2 exceeded 45 ml/min/kg, none of whom died. The first, last, and rate of decline in FEV1 over time were all significant predictors of mortality. CONCLUSIONS: Higher peak VO2 is a marker for longer survival in CF patients.
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.
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) | 0.000 | 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) | 0.001 | 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".