Increase in Core Body Temperature of Alzheimer’s Disease Patients as a Possible Indicator of Chronic Neuroinflammation: A Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Neuroinflammation contributes to the pathogenesis of Alzheimer's disease (AD). Increased pro-inflammatory cytokine levels have been reported in the brain and cerebro-spinal fluid of individuals affected by this neurodegenerative disorder. These same cytokines, including interleukin -1, interleukin-6 and tumor necrosis factor-alpha, are also believed to be involved in thermoregulation. Furthermore, their effects are thought to be mediated through the induction of cyclooxygenases resulting in increased production of inflammatory prostaglandins. Such increases have been observed in AD brains. We hypothesized that these increased levels of inflammatory mediators could lead to an increase in core body temperature in AD patients. OBJECTIVE: To determine whether clinical signs of AD are accompanied by an increase in core body temperature. METHODS: Analysis of the scientific literature identified six studies that used continuous rectal measurements of core body temperature in AD and control patients. Meta-analysis was performed on these published data. RESULTS: Meta-analysis showed that the mean core body temperature in AD patients was significantly increased by 0.10 degrees C when compared to healthy elderly subjects. The two-sided p value was 0.0355, and the 95% confidence interval was 0.0068-0.1950. The severity of AD pathology did not appear to contribute significantly (p = 0.235) to the heterogeneity in the core body temperature among different groups of AD patients. CONCLUSION: The significant increase in core body temperature in AD patients could be a direct consequence of local inflammatory reactions in the brain. Although the changes observed are probably too small to be of any diagnostic value, these observations lend further support to the neuroinflammatory hypothesis of AD pathology.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.046 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".