MétaCan
Menu
Back to cohort
Record W1932640386 · doi:10.1001/jama.2015.7008

Association of Cardiometabolic Multimorbidity With Mortality

2015· article· en· W1932640386 on OpenAlexaff
Emanuele Di Angelantonio, Stephen Kaptoge, David Wormser, Peter Willeit, Adam S. Butterworth, Narinder Bansal, Linda M. O’Keeffe, Pei Gao, Angela Wood, Stephen Burgess, Daniel F. Freitag, Lisa Pennells, Sanne A. E. Peters, Carole Hart, Lise Lund Håheim, Richard F. Gillum, Børge G. Nordestgaard, Bruce M. Psaty, Bu B. Yeap, Matthew Knuiman, Paul J. Nietert, Jussi Kauhanen, Jukka T. Salonen, Lewis H. Kuller, Leon A. Simons, Yvonne T. van der Schouw, Elizabeth Barrett‐Connor, Randi Selmer, Carlos J. Crespo, Beatriz L. Rodríguez, W. M. Monique Verschuren, Veikko Salomaa, Kurt Svärdsudd, Pim van der Harst, Cecilia Björkelund, Lars Wilhelmsen, Robert B. Wallace, Hermann Brenner, Philippe Amouyel, Elizabeth Barr, Hiroyasu Iso, Altan Onat, Maurizio Trevisan, Ralph B. D’Agostino, Cyrus Cooper, Maryam Kavousi, Lennart Welin, Ronan Roussel, Frank B. Hu, Shinichi Sato, Karina W. Davidson, Barbara V. Howard, Maarten J.G. Leening, Annika Rosengren, Marcus Dörr, Dorly J. H. Deeg, Stefan Kiechl, Coen D.A. Stehouwer, Aulikki Nissinen, Simona Giampaoli, Chiara Donfrancesco, Daan Kromhout, Jackie F. Price, Annette Peters, Tom Meade, Edoardo Casiglia, Debbie A. Lawlor, John Gallacher, Dorothea Nagel, Oscar H. Franco, Gerd Assmann, Gilles R. Dagenais, J. Wouter Jukema, Johan Sundström, Mark Woodward, Eric J. Brunner, Kay-Tee Khaw, Nicholas J. Wareham, Eric A. Whitsel, Inger Njølstad, Bo Hedblad, Sylvia Wassertheil‐Smoller, Gunnar Engström, Wayne D. Rosamond, Elizabeth Selvin, Naveed Sattar, Simon G. Thompson, John Danesh

Bibliographic record

VenueJAMA · 2015
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de Québec
FundersNational Center for Advancing Translational SciencesNational Institute for Health and Care ResearchNational Institute of Environmental Health SciencesMedical Research CouncilBritish Heart FoundationWellcome Trust
KeywordsMedicineMultimorbidityAssociation (psychology)MEDLINEGerontologyComorbidityInternal medicine

Abstract

fetched live from OpenAlex

IMPORTANCE: The prevalence of cardiometabolic multimorbidity is increasing. OBJECTIVE: To estimate reductions in life expectancy associated with cardiometabolic multimorbidity. DESIGN, SETTING, AND PARTICIPANTS: Age- and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689,300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128,843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499,808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates. EXPOSURES: A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI). MAIN OUTCOMES AND MEASURES: All-cause mortality and estimated reductions in life expectancy. RESULTS: In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95% CI, 2.0-2.2) in those with stroke, 2.0 (95% CI, 1.9-2.2) in those with MI, 3.7 (95% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy. CONCLUSIONS AND RELEVANCE: Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.069
GPT teacher head0.340
Teacher spread0.271 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1,119
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJAMASame topicChronic Disease Management StrategiesFrench-language works237,207