Quantitative assessment of IgG antibodies to<i>Helicobacter pylori</i>and outcome of ischaemic heart disease
Bibliographic record
Abstract
Criticisms of serological studies on Helicobacter pylori and ischaemic heart disease (IHD) include: undiagnosed heart disease in live controls; no assessment of severity or outcome of IHD; and qualitative not quantitative measurements of IgG to the bacteria. The aim was to assess quantitatively IgG levels specific for H. pylori (ng ml(-1)) among patients who survived a myocardial infarction (MI) with those who died of IHD. Sera were from four groups: (1) men who survived one MI; (2) men matched for age and socioeconomic background to group 1; (3) individuals who died suddenly of IHD; (4) accidental deaths matched for age and sex to group 3. Levels of IgG to H. pylori increased with age (P<0.005) but were not associated with smoking or socioeconomic groups. There was a correlation between IgG to the bacteria and decreasing socioeconomic levels only among group 1 (P<0.01). IgG levels were higher for subjects who died of heart disease (median=151 ng ml(-1)) compared with survivors (median=88 ng ml(-1)) (P=0.034) and higher for survivors compared with their controls (median=58 ng ml(-1)) (P=0.039). Future serological studies of H. pylori in relation to IHD should be quantitative and severity of disease considered in analyses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".