3042Gender differences in the prevalence of a normal IMT with increasing severity of carotid disease
Bibliographic record
Abstract
Abstract Background The ARIC group has shown that increasing IMT is only predictive of increased cardiovascular (CV) risk in males (M). Plaque is predictive of increased CV risk in both M and females (F). Purpose To determine the prevalence of a normal IMT (<1.00mm) in M and F with evidence of carotid plaque. Plaque score (PS) was used as a measure of severity of disease. Methods Our database was searched for patients with all the required data, IMT, PS and plaque area. IMT was measured with automatic edge detection software, PS was calculated using the Rotterdam method and plaque area was measured in the carotid bulb and ICA bilaterally. Only the first carotid study was used in the analysis. PS of 0–6 were used to estimate plaque severity. ANOVA and the Fisher's exact test were used to detect differences between groups. A p value of <0.05 was considered significant. Results There were 5981 patients, 3062 M and 2919 F with an average age of 62.1±11.3 years. Table I. indicates that with increasing PS, age, IMT and plaque area all increase, with a reciprocal decrease in the proportion of patients with a normal IMT. Of 3829 patients with carotid plaque 1355 (35.4%) had an IMT <1.00mm. There were clear gender differences with a much higher prevalence of a normal IMT in F with carotid plaque than M, 776 of 1772 (43.8%) versus 579 of 2057 (28.1%), p<0.0001, Fisher's exact test. This gender difference applies to most groups with increasing plaque burden except those with the most severe disease (PS “5–6”). Table 1 PS “0” PS “1” PS “2” PS “3” PS “4” PS “5–6” N 2152 896 1209 792 562 370 ANOVA Age 57.6±12.2 60.4±9.2 63.0±9.5 66.5±9.3 67.8±8.9 71.5±8.8 <0.0001 IMT 0.94±0.32 1.00±0.23 1.08±0.29 1.30±0.55 1.51±0.75 2.77±0.88 <0.0001 Plaque area 0 16.5±11.6 35.1±20.0 58.6±29.9 91.0±43.1 130.4±61.3 <0.0001 Males 1005 424 627 422 331 253 IMT <1.00mm 671 222 226 77 50 4 Percentage 66.8% 52.4% 36.0% 18.2% 15.1% 1.6% Females 1147 472 582 370 231 117 IMT <1.00mm 879 293 288 136 57 2 Percentage 76.6% 62.1% 49.5% 36.8% 24.6% 1.7% Fisher's test <0.0001 <0.005 <0.0001 <0.0001 <0.0001 NS PS = Carotid ÷ 6 segments, assigned “0” or “1” if plaque is absent or present. Conclusions Significantly more women with carotid plaque have a normal IMT. This may explain why IMT fails to be predictive of CV risk in women.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.009 | 0.002 |
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".