Burden of heart failure and underlying causes in 195 countries and territories from 1990 to 2017
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIMS: To provide the first systematic analysis of the burden and underlying causes of heart failure (HF) in 195 countries and territories from 1990 to 2017. METHODS AND RESULTS: We collected detailed information on prevalence, years lived with disability (YLDs), and underlying causes of HF from the Global Burden of Disease study 2017. Numbers and age-standardized rates of HF prevalence and YLDs were compared by age, sex, socio-demographic index (SDI), and location. The proportions of HF age-standardized prevalence rates due to 23 underlying causes were also presented. Globally, the age-standardized prevalence and YLD rates of HF in 2017 were 831.0 and 128.2 per 100 000 people, a decrease of -7.2% and -0.9% from 1990, respectively. Nevertheless, the absolute numbers of HF prevalent cases and YLDs have increased by 91.9% and 106.0% from 1990, respectively. There is significant geographic and socio-demographic variation in the levels and trends of HF burden from 1990 to 2017. Among all causes of HF, ischaemic heart disease accounted for the highest proportion (26.5%) of age-standardized prevalence rate of HF in 2017, followed by hypertensive heart disease (26.2%), chronic obstructive pulmonary disease (23.4%). CONCLUSION: HF remains a serious public health problem worldwide, with increasing age-standardized prevalence and YLD rates in countries with relatively low SDI. More geo-specific strategies aimed at preventing underlying causes and improving medical care for HF are warranted to reduce the future burden of this condition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it