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Health-Related Quality of Life and Mortality in Heart Failure: The Global Congestive Heart Failure Study of 23 000 Patients From 40 Countries

2021· article· en· W3159134391 on OpenAlex
Isabelle Johansson, Philip Joseph, Kumar Balasubramanian, John J.V. McMurray, Lars H. Lund, Justin A. Ezekowitz, Deepak Kamath, Khalid F. AlHabib, Antoni Bayés‐Genís, Andrzej Budaj, Antonio L. Dans, Anastase Dzudié, Jefferey L. Probstfield, Keith A.A. Fox, Kamilu M. Karaye, Abel Makubi, Bianca Fukakusa, Koon Teo, Ahmet Temizhan, Thomas Wittlinger, Aldo P. Maggioni, Fernando Laņas, Patricio López‐Jaramillo, José Silva‐Cardoso, Karen Sliwa, Hisham Dokainish, Alex Grinvalds, Tara McCready, Salim Yusuf

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 · 2021
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsCanadian VIGOUR CentreHamilton Health SciencesMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsMedicineHeart failureEjection fractionHazard ratioInternal medicineQuality of life (healthcare)Proportional hazards modelHealth related quality of lifeCardiologyConfidence intervalDisease

Abstract

fetched live from OpenAlex

Background: Poor health-related quality of life (HRQL) is common in heart failure (HF), but there are few data on HRQL in HF and the association between HRQL and mortality outside Western countries. Methods: We used the Kansas City Cardiomyopathy Questionnaire–12 (KCCQ-12) to record HRQL in 23 291 patients with HF from 40 countries in 8 different world regions in the G-CHF study (Global Congestive Heart Failure). We compared standardized KCCQ-12 summary scores (adjusted for age, sex, and markers of HF severity) among regions (scores range from 0 to 100, with higher score indicating better HRQL). We used multivariable Cox regression with adjustment for 15 variables to assess the association between KCCQ-12 summary scores and the composite of all-cause death, HF hospitalization, and each component over a median follow-up of 1.6 years. Results: The mean age of participants was 65 years; 61% were men; 40% had New York Heart Association class III or IV symptoms; and 46% had left ventricular ejection fraction ≥40%. Average HRQL differed between regions (lowest in Africa [mean± SE, 39.5±0.3], highest in Western Europe [62.5±0.4]). There were 4460 (19%) deaths, 3885 (17%) HF hospitalizations, and 6949 (30%) instances of either event. Lower KCCQ-12 summary score was associated with higher risk of all outcomes; the adjusted hazard ratio (HR) for each 10-unit KCCQ-12 summary score decrement was 1.18 (95% CI, 1.17–1.20) for death. Although this association was observed in all regions, it was less marked in South Asia, South America, and Africa (weakest association in South Asia: HR, 1.08 [95% CI, 1.03–1.14]; strongest association in Eastern Europe: HR, 1.31 [95% CI, 1.21–1.42]; interaction P <0.0001). Lower HRQL predicted death in patients with New York Heart Association class I or II and III or IV symptoms (HR, 1.17 [95% CI, 1.14–1.19] and HR, 1.14 [95% CI, 1.12–1.17]; interaction P =0.13) and was a stronger predictor for the composite outcome in New York Heart Association class I or II versus class III or IV (HR 1.15 [95% CI, 1.13–1.17] versus 1.09 [95% CI, [1.07–1.11]; interaction P <0.0001). HR for death was greater in ejection fraction ≥40 versus <40% (HR, 1.23 [95% CI, 1.20–1.26] and HR, 1.15 [95% CI, 1.13–1.17]; interaction P <0.0001). Conclusion: HRQL is a strong and independent predictor of all-cause death and HF hospitalization across all geographic regions, in mildly and severe symptomatic HF, and among patients with preserved and reduced ejection fraction. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03078166.

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)0.000
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 score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.033
GPT teacher head0.316
Teacher spread0.283 · 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