Global, regional, and national burden of hypertensive intracerebral hemorrhage, 1990 to 2021 and projections to 2050: Results from the Global Burden of Disease Study 2021
Bibliographic record
Abstract
OBJECTIVE: Hypertensive intracerebral hemorrhage (HICH) is characterized by high morbidity, mortality, disability, and recurrence. According to the current study, there have been no targeted studies exploring the epidemiology and trends of HICH since the Global Burden of Disease (GBD) study report in 2021. The aim of this study was to assess deaths and disability-adjusted life years (DALYs) of patients with HICH globally from 1990 to 2021, with projections to 2050. METHODS: We analyzed age-standardized death rates (ASDR) and age-standardized DALYs for HICH across various countries, geographic regions, age groups, sexes, and the sociodemographic index (SDI) using data from the 2021 GBD study. In addition, we used a Bayesian age-period-cohort (BAPC) model to project the burden of HICH from 2021 to 2050. RESULTS: In 2021, the ASDR for HICH was 22.641 per 100,000 people, reflecting a 31.418% decrease from 1990. Similarly, the age-standardized DALYs rate was 521.085 per 100,000 people, marking a 32.163% reduction since 1990. Country and regional patterns showed stark contrasts: Nauru and Mozambique had the highest ASDRs and age-standardized DALY rates, while Switzerland and Canada reported the lowest. Regionally, Central Africa, South Africa, Central Asia, East Asia, and Southeast Asia had the highest rates, whereas the Americas, Europe, and Oceania had the lowest. Age and gender trends indicated global peaks in the ASDRs (90-94 age group) and age-standardized DALY rates (85-89 age group), with men having higher rates across all age groups. Additionally, both ASDRs and age-standardized DALY rates were negatively associated with SDI levels. Projections from 2021 to 2050 suggest a continued overall decline in global ASDRs and age-standardized DALYs rates for HICH. CONCLUSION: From 1990 to 2021, and projected from 2021 to 2050, the global ASDR and age-standardized DALYs rate for HICH have shown an overall decline. However, significant disparities persist between countries and regions, with less developed areas facing a disproportionately higher burden. In these regions, the early implementation of targeted prevention and treatment strategies, alongside continuous improvements in healthcare resources and services, is crucial to mitigating the global burden of HICH.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".