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Abstract 17828: Sex Differences in Mortality Trends of Rheumatic Heart Disease in High-Income Countries

2023· article· en· W4389945053 on OpenAlexaffabout
Makoto Hibino, Junichi Shimamura, Raj Verma, Nitish K. Dhingra, Bobby Yanagawa, Deepak L. Bhatt, Subodh Verma

Bibliographic record

VenueCirculation · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineDemographyMortality rateSex ratioHeart diseaseStatistical significanceDiseaseEpidemiologyPopulationInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Introduction: Rheumatic heart disease has traditionally been considered to be more prevalent among females; however, current trends in mortality in each sex are unclear in high-income countries. Hypothesis: We hypothesized that mortality from rheumatic heart disease is higher among females but has improved in both sexes in high-income countries. Methods: We analyzed the WHO mortality database to determine trends in mortality from rheumatic heart disease in the UK, Germany, France, Italy, Japan, Australia, the USA, and Canada from 2000 to 2020. Sex-specific age-standardized mortality rates per 100,000 persons were calculated and compared by using female-to-male ratio. Annual percentage change was analyzed using joinpoint regression. Results: In the most recent year, female sex-specific age-standardized mortality rates were significantly higher in the UK (0.60 vs 0.44), Italy (1.24 vs 0.98), the USA (0.63 vs 0.47) and Canada (0.79 vs 0.57). Over the observation period, there was a trend to deceasing sex-specific age-standardized mortality rates in both sexes in the UK, France, Japan, and USA (p<0.01, respectively) and only in female sex in Italy and Australia (p<0.01, respectively), while the mortality rates in both sexes were constant in Canada and demonstrated increasing trends in Germany. Average female-to-male mortality rates ranged from 1.07 (95% CI, 1.02, 1.11) in France to 1.59 (95% CI, 1.51, 1.67) in the UK and were decreasing toward 1 with statistical significance in all countries (average annual change ranged from -1.6% to -0.6%) except for France. Conclusions: Mortality from rheumatic heart disease in females exhibited a decreasing trend in the 6 studied high-income countries while increasing in Germany and constant in Canada. Female-dominated mortality was becoming less pronounced in the studied high-income countries, with the exception of France, which already had the lowest average female-dominant mortality rates.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.288
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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