P1‐260: Relationship between <i>helicobacter pylori</i> infection and cognitive performance in elders
Bibliographic record
Abstract
Dementia ranked the 6 leading cause of death in the elders in USA, which has become an important health issue around the world. Mild cognitive impairment (MCI) is a prodromal phase of Alzheimer's disease (AD), which is the leading subtype of dementia. Chronic infection caused by pathogens, e.g., herpes simplex virus and Chlamydia pneumonia, have known to induce neuroinflammation and the following cognitive impairment, including AD and MCI. Recently, some studies explored the association between Helicobacter pylori infection and cognitive impairment. However, their findings were inconsistent. Six hundred and four participants aged 65 years or older were recruited from the annual Elderly Health Checkup at National Taiwan University Hospital from March 2011 to December 2013. Montreal cognitive assessment (MoCA) was used to assess cognition with a score<24 indicates cognitive impairment. Blood sample was collected to determine serum anti- Helicobacter pylori IgG level. Multivariable logistic regression analysis was performed to explore the relationship between serum anti- Helicobacter pylori IgG level and cognitive impairment adjusting for age, sex, educational level, APOE ε4 status, renal function, stroke, and depressive symptoms. Helicobacter pylori seropositivity was 46.6 and 44.0% for cognitive impaired and normal elders, respectively (p < 0.61). Serum anti- Helicobacter pylori IgG level was significantly associated with cognitive impairment in the elders (adjusted odds ratio = 1.09, 95% confidence interval = 1.01-1.18, p = 0.04). As compared with the model including Helicobacter pylori alone (c-statistic of receiver operating curve = 0.54), multivariable regression model adjusting for potential confounders above showed ideal prediction ability (c-statistic= 0.78). This study found that previous Helicobacter pylori infection was associated with the risk of cognitive impairment probably via the enhancement of systemic inflammation and neurodegeneration.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".