Hypothalamic imaging in Alzheimer’s disease and Lewy body dementia: A systematic review and meta-analysis
Bibliographic record
Abstract
Symptoms related to sleep, weight, and endocrine dysfunction are common in Alzheimer’s disease (AD) and Lewy body dementia (LBD). The cause of these symptoms is not known, but they may be related to hypothalamic neurodegeneration. We performed a systematic search of MEDLINE and EMBASE for studies using MRI or PET imaging to examine the hypothalamus in AD or LBD. The Newcastle-Ottawa scale was used to assess the risk of bias. A random-effects meta-analysis was conducted using the standardised mean difference (SMD) in hypothalamic volume, and a narrative synthesis was used to examine associations between hypothalamic imaging and sleep, weight, and endocrine function. We screened 8891 articles which identified 22 studies for inclusion in the narrative synthesis of which 6 were suitable for meta-analysis. 86 % had a low to moderate risk of bias. People with mild-moderate AD had a smaller hypothalamus compared to controls (SMD=-0.49[-0.86,-0.13],p = 0.018;I 2 =67 %[21.5 %-86.1 %];n = 454(AD),715(controls)), and had differences in hypothalamic metabolism and connectivity. Two studies in LBD found lower grey matter and serotonin transporter binding in the hypothalamus compared to controls. Hypothalamic differences in AD were associated with male sex, worse sleep, lower bone mineral density and plasma levels of sex hormones. Body mass index was not associated with hypothalamic volume in AD, although further studies are needed. Lower hypothalamic volume is seen in AD and this may influence sleep and endocrine function. A better understanding of hypothalamic degeneration may help elucidate how pathology relates to symptoms in AD and LBD and reveal new targets for intervention. • Alzheimer’s disease is associated with a smaller hypothalamus. • Some studies suggests hypothalamic volume is lower in men with AD. • Hypothalamic structure may be associated with sleep, sex hormones and bone density.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.027 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".