MétaCan
Menu
Back to cohort
Record W3107115410 · doi:10.1093/ehjci/ehaa946.3139

Characteristics and health status of patients with and without confirmed HFpEF

2020· article· en· W3107115410 on OpenAlexaboutno aff
Christi Deaton, Faye Forsyth, Jonathan Mant, Duncan Edwards, Richard Hobbs, Clare Taylor, Amir Aziz, Rebekah Schiff, Jessica Odone, Justin Zaman

Bibliographic record

VenueEuropean Heart Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHeart failure with preserved ejection fractionAtrial fibrillationHeart failureInternal medicineCohortCardiologyComorbidityQuality of life (healthcare)Physical therapyOverweightMontreal Cognitive AssessmentBody mass indexEjection fractionDiseaseDementia

Abstract

fetched live from OpenAlex

Abstract Aims Patients with heart failure with preserved ejection fraction (HFpEF) are usually older and multi-morbid and diagnosis can be challenging. The aims of this cohort study were to confirm diagnosis of HFpEF in patients with possible HFpEF recruited from primary care, to compare characteristics and health status between those with and without HFpEF, and to determine factors associated with health status in patients with HFpEF. Methods Patients with presumed HFpEF were recruited from primary care practices and underwent clinical assessment and diagnostic evaluation as part of a longitudinal cohort study. Health status was measured by Montreal Cognitive Assessment (MOCA), 6-minute walk test, symptoms, and the Kansas City Cardiomyopathy Questionnaire (KCCQ), and quality of life (QoL) by EQ-5D-5L visual analogue scale (VAS). Results 151 patients (mean age 78.5±8.6 years, 40% women, mean EF 56% + 9.4) were recruited and 93 (61.6%) were confirmed HFpEF (those without HFpEF had other HF and cardiac diagnoses). Patients with and without HFpEF did not differ by age, MOCA, blood pressure, heart rate, NYHA class, proportion with atrial fibrillation, Charlson Comorbidity Index, or NT-ProBNP levels. Patients with HFpEF were more likely to be women, overweight or obese, frail, and to be more functionally impaired by 6 minute walk distance and gait speed than those without. Although not statistically significant, patients with HFpEF had clinically significant differences (>5 points) on the physical limitations, symptom burden and clinical summary subscales of the KCCQ, but did not differ by other subscales or by EQ-5D-5L VAS (70±17 vs 73±19, p=0.385). More patients with HFpEF reported daytime dyspnoea (63% vs 46%, p=0.035) and fatigue (81% vs 61%, p=0.008), but not other symptoms compared to those without HFpEF. For both groups BMI was moderately negatively correlated with KCCQ subscale scores, and 6 minute walk distance was positively correlated with KCCQ subscales. Conclusions Nearly 40% were not confirmed as HFpEF indicating the challenges of diagnosis. Patients with confirmed HFpEF differed by sex, overweight/obesity, frailty, functional impairment, and symptoms but not by age or comorbidities from those without HFpEF. These differences were reflected in some subscale scores of the KCCQ, but not how patients reported their quality of life on the KCCQ QoL subscale and EQ-5D-5L VAS. Older patients with HFpEF reported relatively high QoL despite poor health status by functional impairment, frailty and symptoms. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): National Institute of Health Research School of Primary Care Research

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)0.000
metaresearch head score (Gemma)0.002
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.279
Teacher spread0.240 · 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Heart JournalSame topicCardiovascular Function and Risk FactorsFrench-language works237,207