Updated Trends in Valvular Heart Disease-Related Heart Failure in G20-the Group of Twenty Countries: Insights From the Global Burden of Disease Study 2021
Bibliographic record
Abstract
Background: Valvular heart disease (VHD), including both non-rheumatic valvular heart disease (NRVHD) and rheumatic valvular heart disease (RVHD), is a major global health concern. Moreover, the progression of VHD to heart failure (HF) poses substantial clinical and public health challenges. In light of the global population aging, alongside increasing cardiovascular risk factors, and the additional strain imposed by the COVID-19 pandemic, a timely reassessment of the VHD-related HF burden is urgently needed. Using the most recent data from the Global Burden of Disease (GBD) Study 2021, this study aimed to evaluate the distribution of VHD-related HF burden in 2021, examining the long-term trends from 1990 to 2021, and short-term changes between 2019 and 2021, to provide updated insights to inform future prevention and management strategies. Methods: Using GBD 2021 data, we analyzed the distribution of VHD-related HF burden in age-standardized prevalence rates across the Group of Twenty (G20) countries. Results: The highest NRVHD-related HF burden in 2021 was observed in the United States (US), Italy, and Russia, while the highest RVHD-related HF burden was noted in India, France, and China. Over the past 30 years (1990-2021), the NRVHD-related HF burden decreased in developed countries (e.g., the US, Canada, Japan) but increased in emerging economies (e.g., India, Brazil, South Africa), with significant increases also observed in Argentina, Mexico, Brazil, among other countries. Notably, nearly all G20 countries exhibited a downward trend in RVHD-related HF burden, with Germany and Australia being the exceptions. During the COVID-19 pandemic (2019-2021), the NRVHD-related HF burden declined in most G20 nations, except for South Africa, India, and a few others, while the RVHD-related HF burden increased slightly in countries such as Mexico, Russia, and Indonesia. Conclusions: Trends in NRVHD- and RVHD-related HF burden across G20 countries exhibited notable variations, and these became more pronounced under the impact of the COVID-19 pandemic. These findings underscore the importance of developing long-term strategies to enhance the resilience of healthcare systems, improve chronic disease management, and optimize resource allocation to promote cardiovascular health and preparedness for public health challenges.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".