Cerebral hypoperfusion and future falls risk among community dwelling older adults with orthostatic hypotension
Bibliographic record
Abstract
BACKGROUND: Falls are a major health concern for older adults, affecting one-third of those over 65 years annually, with 10%-20% leading to injury or hospitalisation. Whilst falls are often multifactorial, unexplained falls may overlap with syncope. Orthostatic hypotension (OH), characterised by a significant drop in blood pressure (BP) upon standing, is a potent falls risk factor, likely due to cerebral hypoperfusion. While the association between OH and falls is well established, few studies have examined the combined role of OH and real-time cerebral perfusion measures in predicting future unexplained falls. METHODS: Frontal lobe cerebral oxygenation (Tissue Saturation Index, TSI) was measured using near-infrared spectroscopy alongside continuous beat-to-beat BP monitoring (Finometer) during active standing in 2478 participants (≥55 years) from Wave 3 of The Irish Longitudinal Study on Ageing. OH was defined as a sustained SBP drop ≥20 mmHg and/or DBP drop ≥10 mmHg at 30, 60 or 90 seconds post-standing. A TSI drop ≥75th centile at 30 seconds was classified as 'greater TSI drop.' Associations between TSI change and OH were analysed using multilevel mixed-effects regression, and longitudinal relationships with unexplained falls were assessed over four years. RESULTS: One-fifth of participants had OH, associated with older age and cardiovascular disease. OH was associated with significantly greater TSI change from baseline at 30, 60 and 90 seconds (p < .001) in adjusted models. The combination of OH and greater TSI drops predicted future unexplained falls (OR 2.16, p = .003), whereas OH and lower TSI drops did not (OR 1.25, p = .288). CONCLUSION: The risk of falls associated with OH appears to be modified by the extent of cerebral hypoperfusion upon standing. These findings suggest that integrating cerebral perfusion measures with OH assessment may help refine risk stratification in older adults, particularly for unexplained falls.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".