Impact of COPD and anemia on motor and cognitive performance in the general older population: results from the English longitudinal study of ageing
Bibliographic record
Abstract
BACKGROUND: Cognitive and motor-performance decline with age and the process is accelerated by decline in general health. In this study, we aimed to estimate the effects of COPD and HB levels on cognitive and motor performance in the general older population and assess potential interaction. METHODS: The English Longitudinal Study of Aging is a population-based cohort study including measurements of lung-function and HB levels together with cognitive and motor performance testing. Data were collected from 5709 participants including three measurement time over eight years. COPD was defined using lung-function-parameters and clinical symptoms. HB was assessed continuously and low HB was defined using clinical anemia cutoffs. Linear mixed-effects regression models were used to quantify the associations of COPD and HB with outcome measures, both individually and in combination. RESULTS: Participants with both low HB and COPD demonstrated worse motor performance compared to individuals with only one exposure, resulting in up to 1 s (95%CI, 0.04-1.8) longer time needed to complete the five times sit to stand task than what would be expected based on purely additive effects. Additionally in individuals with COPD, the time to complete the motor-performance task per unit decrease in continuous HB levels was longer than in participants without COPD after full adjustment for confounding (up to 1.38 s/unit HB level, 95% CI: 0.65-2.11). CONCLUSION: In persons with COPD low HB levels may contribute to low motor-performance in a supra additive fashion. Further studies should re-evaluate whether earlier treatment of lower HB in these individuals might be beneficial.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".