Correlates of quality of life in ALS: Lessons from the minocycline study
Bibliographic record
Abstract
Improving quality of life (QoL) is a major goal in ALS palliative care. Previous studies performed on the general ALS population showed no relationship between QoL and disease progression. ALS subjects participating in clinical trials may differ from those in the general ALS population. We explored the relationship between QoL and disease progression in 412 subjects enrolled in a minocycline trial. We examined correlations between Single Item McGill Quality of Life Scale (MQoL-SIS) score and disease duration, ALS Functional Rating Scale Revised (ALSFRS-R) score, FVC, and survival rate. We also analyzed how NIV and PEG affect QoL. Within subjects, MQoL-SIS scores correlated with ALSFRS-R and FVC (p<0.001). MQoL-SIS declined over time (p<0.001) and correlated with the decline of ALSFRS-R (p<0.001). MQoL-SIS tended to improve after initiation of NIV (p=0.07). There was a significant reduction in the rate of MQoL-SIS decline (p<0.001) after initiation of PEG. Subjects with slower QoL decline survived seven months longer than those with faster QoL decline (p<0.01). Our study demonstrated that QoL does decline with advancing ALS in subjects who participated in a minocycline trial, that the slope of QoL predicts survival, and that both NIV and PEG have beneficial impacts on QoL.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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 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".