Abstract 17840: Impact of Age and Sex on Mortality Trends of Infective Endocarditis in High-Income Countries
Bibliographic record
Abstract
Introduction: Incidence of infective endocarditis may relate to a variety of background conditions which may vary depending on age groups and sex in a country. Its national trends in each age group and sex among high-income countries are still unclear. Hypothesis: We hypothesized that mortality from infective endocarditis is without sex differences and has improved in all age groups in both sexes among high-income countries. Methods: The WHO mortality database was analyzed to determine trends in mortality from infective endocarditis in the UK, Germany, France, Italy, Japan, Australia, the USA, and Canada from 2000 to 2021. Age-standardized and age-specific (≤49, 50-64, 65-79, ≥80 years) mortality rates per 100,000 persons in either sex were compared by using male-to-female ratio. Trends were analyzed using joinpoint regression. Results: Age-standardized mortality rates ranged from 0.40 (95%CI, 0.38, 0.42) in Japan to 1.29 (95%CI, 1.23, 1.35) in France in the most recent year and showed increasing trends in all studied countries except for Japan with decreasing trends and the USA with constant trends. During the studied periods, age-standardized mortality was male-dominant in all countries (p<0.0001). In age-specific analysis, three age groups (≤49, 50-64, 65-79 years) showed male dominancy in all countries while age group ≥80 years showed no sex difference except for France. Different mortality trends were identified between the sexes. In the USA, female mortality rates showed increasing trends in the age group ≤49 years while there were decreasing trends in the other three age groups. Male mortality rates showed constant trends in age groups ≤49 and 50-64 years while there were decreasing trends in the age group 65-79 and ≥80 years. Conclusions: Mortality from infective endocarditis was male-dominant in age groups less than 80 years old in all studied high-income countries. The different mortality trends between sexes among age groups need to be contextualized.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".