MétaCan
Menu
Back to cohort
Record W2077907178 · doi:10.4330/wjc.v4.i8.250

Evaluation of the prevalence and severity of pain in patients with stable chronic heart failure

2012· article· en· W2077907178 on OpenAlexaboutno aff
Dioma U. Udeoji

Bibliographic record

VenueWorld Journal of Cardiology · 2012
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHeart failureQuality of life (healthcare)Outpatient clinicChronic painChest painInternal medicineEjection fractionPhysical therapy

Abstract

fetched live from OpenAlex

AIM: To evaluate the prevalence and severity of pain in patients with chronic stable heart failure (HF) in an outpatient clinic setting. METHODS: This is a cross-sectional study evaluating symptoms of generalized or specific pain in patients with chronic stable heart failure. A standardized questionnaire (Edmonton Symptom Assessment System) was administered during a routine outpatient clinic visit. The severity of pain and other symptoms were assessed on a 10 point scale with 10 being the worst and 0 representing no symptoms. RESULTS: Sixty-two patients [age 56 ± 13 years, 51 males, 11 females, mean ejection fraction (EF) 33% ± 17%] completed the assessment. Thirty-two patients (52%) reported any pain of various character and location such as chest, back, abdomen or the extremities, with a mean pain score of 2.5 ± 3.1. Patients with an EF less than 40% (n = 45, 73%) reported higher pain scores than patients with an EF greater than 40% (n = 17, 27%), scores were 3.1 ± 3.3 vs 1.2 ± 1.9, P < 0.001. Most frequent symptoms were tiredness (in 75% of patients), decreased wellbeing (84%), shortness of breath (SOB, 76%), and drowsiness (70%). The most severe symptom was tiredness with a score of 4.0 ± 2.8, followed by decreased wellbeing (3.7 ± 2.7), SOB (3.6 ± 2.8), and drowsiness (2.8 ± 2.8). CONCLUSION: Pain appears to be prevalent and significantly affects quality of life in HF patients. Adequate pain assessment and management should be an integral part of chronic heart failure management.

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)0.003
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 score0.010
Threshold uncertainty score0.126

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.014
GPT teacher head0.260
Teacher spread0.246 · 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

Citations26
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueWorld Journal of CardiologySame topicHeart Failure Treatment and ManagementFrench-language works237,207