MétaCan
Menu
← Back to cohort

Phenotyping patient-reported health profiles in octogenarians with coronary artery disease – a latent profile analysis

2022· article· en· W4306319990 on OpenAlexaboutno aff
Irene Instenes, Kyrre Breivik, H Allore, Britt Borregaard, Christi Deaton, Alf Inge Larsen, Tore Wentzel‐Larsen, Tone M. Norekvål

Bibliographic record

VenueEuropean Heart Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAnxietyAnginaMental healthCoronary artery diseaseQuality of life (healthcare)Depression (economics)Hospital Anxiety and Depression ScalePercutaneous coronary interventionPhysical therapyCanadian Cardiovascular SocietyMyocardial infarctionInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Abstract Background Percutaneous coronary intervention (PCI) has demonstrated to be an effective treatment strategy also in octogenarian patients (≥80 years). However, limited studies describe patient-reported outcomes in older adults two months after the PCI procedure. Purpose To identify latent health profiles concerning fatigue, generic and disease-specific physical and mental health, anxiety and depression, insecurity, dependency and angina frequency. Further, to investigate if these profiles were associated with sex or cohabitation status. Method A prospective cohort multicenter study including 3417 patients was conducted. The following patient-reported outcome measures were used: Level of fatigue was assessed using de novo created questions. Generic physical and mental health was assessed using RAND-12. Anxiety and depression were assessed using the Hospital Anxiety and Depression Scale. Disease-specific physical and mental health status, insecurity and dependency were assessed with Myocardial Infarction Dimensional Assessment Scale, and disease-specific physical limitation, quality of life and angina frequency was assessed with Seattle Angina Questionnaire (SAQ-7). All scales were converted to a 0–100 scale (worst to best). Latent profile analysis was used for phenotyping health profiles and multinomial logistic regression analysis for investigating the association of sex and cohabitation status across health profiles. Result A total of 318 octogenarians were included. The mean age was 83.6 years, and 69% were males. Three health profiles differing in the level of fatigue, health status, insecurity and dependency and angina frequency were identified (Figure 1). Health profile 1 (26.1%) represents “Low-level of life satisfaction, high level of insecurity and dependency and monthly frequency of angina”. Health profile 2 (38.1%) represents “Medium-level of life satisfaction, medium-level of insecurity and dependency and monthly frequency of angina”. Health profile 3 (35.8%) represents “High-level of life satisfaction, low level of insecurity and dependency and angina free”. Importantly, female sex was strongly associated with being classified into Health profile 1 compared to Health profile 3 [OR 3.6, 95% CI 1.3–7.9]. Living alone however, did not predict a likelihood of being classified into any particular health profile. Conclusion We identified three unique health profiles of octogenarians with coronary artery disease. A quarter of the participants were classified into the “Low-level of life satisfaction” profile. In addition, female sex was strongly associated with being identified into the “Low-level of life satisfaction” profile. These result suggest a need for a more tailored and patient-centered aftercare in octogenarians undergoing PCI. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): MTG Holding AS

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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.038
GPT teacher head0.307
Teacher spread0.269 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Heart Journal→Same topicCardiac Health and Mental Health→French-language works237,207→