MétaCan
Menu
Back to cohort
Record W4386212890 · doi:10.1093/eurheartj/ehad595

Frailty and outcomes in heart failure patients from high-, middle-, and low-income countries

2023· article· en· W4386212890 on OpenAlexaff
Darryl P. Leong, Philip Joseph, John J.V. McMurray, Jean L. Rouleau, Aldo P. Maggioni, Fernando Laņas, Sanjib Kumar Sharma, Julio Núñez, Bishav Mohan, Ahmet Çelik, Jabir Abdullakutty, Okechukwu S. Ogah, Lisa Mielniczuk, Kumar Balasubramanian, Tara McCready, Alex Grinvalds, Salim Yusuf

Bibliographic record

VenueEuropean Heart Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsUniversity of OttawaPopulation Health Research InstituteUniversité de MontréalMcMaster UniversityHamilton Health SciencesHamilton General Hospital
FundersIonis PharmaceuticalsIntas PharmaceuticalsRegeneron PharmaceuticalsSanofiBayerAstraZenecaPfizer
KeywordsMedicineHazard ratioEjection fractionHeart failureConfidence intervalInternal medicineProportional hazards modelCardiology

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: There is little information on the incremental prognostic importance of frailty beyond conventional prognostic variables in heart failure (HF) populations from different country income levels. METHODS: A total of 3429 adults with HF (age 61 ± 14 years, 33% women) from 27 high-, middle- and low-income countries were prospectively studied. Baseline frailty was evaluated by the Fried index, incorporating handgrip strength, gait speed, physical activity, unintended weight loss, and self-reported exhaustion. Mean left ventricular ejection fraction was 39 ± 14% and 26% had New York Heart Association Class III/IV symptoms. Participants were followed for a median (25th to 75th percentile) of 3.1 (2.0-4.3) years. Cox proportional hazard models for death and HF hospitalization adjusted for country income level; age; sex; education; HF aetiology; left ventricular ejection fraction; diabetes; tobacco and alcohol use; New York Heart Association functional class; HF medication use; blood pressure; and haemoglobin, sodium, and creatinine concentrations were performed. The incremental discriminatory value of frailty over and above the MAGGIC risk score was evaluated by the area under the receiver-operating characteristic curve. RESULTS: At baseline, 18% of participants were robust, 61% pre-frail, and 21% frail. During follow-up, 565 (16%) participants died and 471 (14%) were hospitalized for HF. Respective adjusted hazard ratios (95% confidence interval) for death among the pre-frail and frail were 1.59 (1.12-2.26) and 2.92 (1.99-4.27). Respective adjusted hazard ratios (95% confidence interval) for HF hospitalization were 1.32 (0.93-1.87) and 1.97 (1.33-2.91). Findings were consistent among different country income levels and by most subgroups. Adding frailty to the MAGGIC risk score improved the discrimination of future death and HF hospitalization. CONCLUSIONS: Frailty confers substantial incremental prognostic information to prognostic variables for predicting death and HF hospitalization. The relationship between frailty and these outcomes is consistent across countries at all income levels.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.028
GPT teacher head0.275
Teacher spread0.248 · 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

Citations45
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Heart JournalSame topicFrailty in Older AdultsFrench-language works237,207