Comparison of years of life lost due to ischemic stroke between two countries with a public health system: 5-year analysis
Notice bibliographique
Résumé
Background: Ischemic stroke occurs when there is arterial obstruction, causing paralysis of brain areas, which prevents the passage of oxygen due to the lack of blood circulation. It is one of the main causes of death worldwide, increasing early mortality in several countries with different realities, such as Brazil and Canada. Objective: To compare the rate of years of life lost (YLLs) due to ischemic stroke between two countries with public health systems over five years, identifying differences and trends in early mortality, providing data to guide public health policies and prevention strategies. Methods: This is an observational, descriptive epidemiological study in which data on years of life lost (YLLs) due to stroke from 2017 to 2021 were obtained from the Institute for Health Metrics and Evaluation (IHME) platform, in the Global Burden of Disease (GBD) section. Information on cerebrovascular disease was selected and data on annual ischemic strokes was filtered out. The YLLs were calculated by multiplying the difference between the country‘s life expectancy and the age at death by the number of people who died from the disease in question. In order to make the appropriate correlation with the years of the fourth decade of life and calculate the rate (per 100,000 inhabitants), the age groups of both sexes, 30 to 34 years and 35 to 39 years, classified as age group 1 and age group 2, respectively, were selected. Results: In both countries, age group 2 had the highest rates in all the years analyzed. In the first year, 2017, men in Canada had a rate of 6.86 and women 7.6. In Brazil, in the same year, the male rate was 37.09 and the female rate was 31.34. In 2018, the second year of analysis, the male rate in Canada was 11.23 and the female rate was 8.77. In Brazil, the rate for men was 40.63 and for women 35.69. In 2019 in Canada, the male rate was 12.02 and the female rate was 9.70. In Brazil, the male rate was 40.99, and the female rate was 38.19. In the penultimate year, 2020, in Canada, the male rate was 12.38, and the female rate was 9.56. This year in Brazil, the male rate remained at 40.99, and the female rate increased slightly to 38.42. Last year, for 2021, in Canada, the male rate was 11.96, and the female rate was 9.10. In Brazil, the male rate was 42.98 and the female rate was 40.16. Conclusion: It was concluded that age group 2 had the highest rates in all the years analyzed in both Canada and Brazil. There was a general increase in rates in both countries over the period analyzed, with an increase of 74.3% in Canadian men, 19.7% in Canadian women, 15.8% in Brazilian men and 28.1% in Brazilian women in 2021 compared to 2017, with Brazil showing significantly higher rates than Canada.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,005 |
| Bibliométrie | 0,005 | 0,006 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».