MétaCan
Menu
Back to cohort

Comparing Cardiovascular Mortality Estimates From Global Burden of Disease and From the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiological Research

2025· article· en· W4409161976 on OpenAlex
Abdul Mannan Khan Minhas, Sadeer Al‐Kindi, Harriette G.C. Van Spall, Dmitry Abramov

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCirculation Cardiovascular Quality and Outcomes · 2025
Typearticle
Languageen
FieldHealth Professions
TopicMedical Coding and Health Information
Canadian institutionsPopulation Health Research Institute
Fundersnot available
KeywordsMedicineWonderDeath certificateEpidemiologyMortality rateCause of deathDiseaseDemographyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Several sources of data, including the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiological Research (CDC WONDER) and the Global Burden of Disease (GBD) data set, report causes of mortality in the United States. While CDC WONDER contains data based on death certificate codes, the GBD mortality data undergo additional processing, such as cause-of-death reassignment before reporting. Potential differences in reported mortality from cardiovascular disease in the United States between these 2 data sources have not been characterized. METHODS: US nationwide cardiovascular cause-of-death data for each year between 2000 and 2019 were obtained from the GBD and the Multiple Cause-of-Death files using CDC WONDER in this longitudinal study. In addition to mortality from cardiovascular disease, mortality from key components of cardiovascular disease, including ischemic heart disease, stroke, and atrial fibrillation/flutter, was determined from each data set. Absolute and crude mortality rates per 100 000 are reported for each data set. Percent differences in cardiovascular mortality from GBD and CDC WONDER and percent changes in cardiovascular mortality across years were calculated. RESULTS: In 2019, GBD reported 957 455 (95% uncertainty interval, 855 065-1 013 175) cardiovascular deaths, while CDC WONDER reported 859 290 cardiovascular deaths in the United States. Between 2000 and 2019, the reported crude mortality rates from cardiovascular causes in GBD decreased from 327 (297-341) to 292 (261-309), a reduction of 10.7%, and decreased in CDC WONDER from 335 (334-335) to 267 (266-267), a reduction of 20.3%. In 2019, the reported mortality rates for components of cardiovascular disease were higher in GBD compared with CDC WONDER for ischemic heart disease (percent difference, 54.5%), stroke (percent difference, 26.1%), and atrial fibrillation/flutter (percent difference, 25.0%). CONCLUSIONS: There are prominent differences in reported cardiovascular mortality between GBD and CDC WONDER data.

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 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)0.012
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.364
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.567
GPT teacher head0.554
Teacher spread0.013 · 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