The link between blood‐based biomarkers and mild cognitive impairment and Alzheimer's disease in a Panamanian sample
Bibliographic record
Abstract
Abstract Background Studies on blood‐based biomarkers associated with age‐related cognitive impairment are key to improve intervention mechanisms and delay the expression of symptoms. The objective of this study was to assess the relationship between blood‐based biomarkers and mild cognitive impairment (MCI) and AD in a sample of elderly Panamanians enrolled from an outpatient geriatric service. Method A descriptive, cross‐sectional, observational study was conducted. Participants were 84 Panamanians (controls, n=41; MCI=32; and AD=11). They were assessed with MMSE and Clock Test. Non‐fasting blood samples were collected to genotype for ApoE4 and to determine a blood‐based biomarker profile. Result CRP levels among AD participants were significantly increased relative to MCI participants (p < 0.05). A2M levels in AD participants were significantly increased compared to normal controls (p < 0.05). SAA levels in AD participants were significantly increased when compared to MCI participants (p < 0.05). Conclusion These results show that in the AD group CRP, A2M and SAA are significantly increased. The link between MCI and AD and inflammatory markers can produce an accurate tool that can aid in early diagnosis of AD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".