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Record W4390718632 · doi:10.1016/s2214-109x(23)00557-0

Characteristics, management, and outcomes in women and men with congestive heart failure in 40 countries at different economic levels: an analysis from the Global Congestive Heart Failure (G-CHF) registry

2024· article· en· W4390718632 on OpenAlexaff
Marjan Walli-Attaei, Philip Joseph, Isabelle Johansson, Karen Sliwa, Eva Lonn, Aldo P. Maggioni, Lisa Mielniczuk, Heather J. Ross, Kamilu M. Karaye, Camilla Hage, Nana Pogosova, Alex Grinvalds, Tara McCready, John J.V. McMurray, Salim Yusuf

Bibliographic record

VenueThe Lancet Global Health · 2024
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsTed Rogers Centre for Heart ResearchHamilton Health SciencesUniversity Health NetworkUniversity of OttawaMcMaster UniversityPopulation Health Research Institute
FundersBayer
KeywordsHeart failureMedicineCardiologyInternal medicineIntensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND: There is a paucity of data on the clinical characteristics, management, and outcomes of women compared with men with heart failure in low-income and middle-income countries compared with high-income countries. We examined sex differences in risk factors, clinical characteristics, and treatments, and prospectively assessed the risk of heart failure hospitalisation and mortality in patients with heart failure in 40 high-income, middle-income, and low-income countries. METHODS: Participants aged 18 years or older with heart failure were enrolled from Dec 20, 2016, to Sept 9, 2020 in the prospective Global Congestive Heart Failure (G-CHF) study from 257 centres in 40 high-income, middle-income, and low-income countries. Participants were followed up until May 25, 2023. We recorded the demographic characteristics, medical history, and treatments of participants. We prospectively recorded data on heart failure hospitalisation and mortality by sex in the overall study, according to country economic status, and according to level of left ventricular ejection fraction (LVEF). FINDINGS: 23 341 participants (9119 [39·1%] women and 14 222 [60·1%] men) were recruited and followed up for a mean of 2·6 years (SD 1·4). The mean age of women in the study was 62 years (SD 17) compared with 64 years (14) in men. Fewer women than men had an LVEF of 40% or lower (51·7% women vs 66·2% men). By contrast, more women than men had an LVEF of 50% or higher (33·2% women vs 18·6% men). Hypertensive heart failure was the most common aetiology in women (25·5% women vs 16·8% men), whereas ischaemic heart failure was the most common aetiology in men (45·6% men vs 26·6% women). Signs and symptoms of congestion were more common in women than men: 42·6% of women had a New York Heart Association functional class of III or IV compared with 37·9% of men. The use of heart failure medications and cardiac tests did not differ systematically between the sexes, although implantable cardioverter defibrillator (ICD) implantation was lower among women than men (8·7% women vs 17·2% men). The adjusted risk of heart failure hospitalisation was similar in women and men (women-to-men adjusted hazard ratio [HR] 0·99 [95% CI 0·92-1·05]). This pattern was consistent within groups of countries categorised by economic status, geographical region, and by LVEF level. However, women had a lower adjusted risk of mortality (women-to-men adjusted HR 0·79 [95% CI 0·75-0·84]) despite adjustments for prognostic factors-a pattern which was consistently observed across groups of countries irrespective of economic status, geography, and LVEF levels of patients. INTERPRETATION: The underlying cause of heart failure and ejection fraction phenotype differ between women and men, as do the severity of symptoms. Heart failure treatments (except ICD use) were not consistently in favour of one sex. Paradoxically, while the rates of hospitalisations were similar among women and men, the risk of death was lower among women. These patterns were consistent regardless of the economic status of the countries. The higher mortality among men is unexplained and warrants further study. FUNDING: Bayer.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.153
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.018
GPT teacher head0.307
Teacher spread0.289 · 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 teacher head, 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
Published2024
Admission routes1
Has abstractyes

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