Effect of age and sex on echocardiographic left ventricular diastolic function parameters in patients with preserved ejection fraction and normal valvular function
Bibliographic record
Abstract
BACKGROUND: We conducted a retrospective study to specify the effect of age and gender on echocardiographic left ventricular diastolic function parameters. METHODS: We included echocardiograms done in our institution between 1995 and 2007, for which data on diastolic function were available. In order to target a population as close aspossible to healthy subjects, echocardiograms reporting abnormal contraction, valvulopathy or extreme data were excluded. RESULTS: A total of 14,298 patients (mean age 58.53 years; men 49.1%) were included in the study. Sex did not influence E/A ratio (p = 0.298) but age decreased it significantly (p < 0.001). E/e ratio increased significantly with age (p < 0.001) and was higher in women than in men (p < 0.001). After the age of 40, more than 10% of the patients had an E/e ratio superior than 8. CONCLUSIONS: To our knowledge, this is the most imposing study - in terms of number of patients from first to tenth decade of life that were included - addressing the effect of age and gender on diastolic function. Our results stress the need for future prospective trials to establishnormal diastolic function parameters according to age and gender, notably for the E/e ratio for which a significant proportion of our population had a ratio superior of what is actually considered normal.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".