Spouse bereavement and brain pathologies: A propensity score matching study
Bibliographic record
Abstract
AIM: Spouse bereavement is one of life's greatest stresses and has been suggested to trigger or accelerate cognitive decline and dementia. However, little information is available about the potential brain pathologies underlying the association between spouse bereavement and cognitive decline. We aimed to investigate that lifetime spouse bereavement is associated with in vivo human brain pathologies underlying cognitive decline. METHODS: F] fluorodeoxyglucose-PET, and magnetic resonance imaging. Participants were classified as experiencing no spouse bereavement or spouse bereavement, and comparisons using propensity score matching (59 cases and 59 controls) were performed. RESULTS: Spouse bereavement was significantly associated with higher cerebral white matter hyperintensity (WMH) volume compared with no spouse bereavement. Interaction and subsequent subgroup analyses showed that spouse bereavement was significantly associated with higher WMH in the older (>75 years) subgroup and among those with no- or low-skill occupations. In addition, spouse bereavement at 60 years or older affects WMH volume compared with no spouse bereavement, whereas spouse bereavement at younger than 60 years did not. No group differences were observed in other brain pathologies between spouse bereavement categories. CONCLUSIONS: The findings suggest that the spouse bereavement may contribute to dementia or cognitive decline by increasing cerebrovascular injury, particularly in older individuals and those with no- or low-skill occupations.
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How this classification was reachedexpand
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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".