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Record W3195633341 · doi:10.1097/nnr.0000000000000549

Latent Class Analysis of Symptom Burden Among Seriously Ill Adults at the End of Life

2021· article· en· W3195633341 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNursing Research · 2021
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute of Nursing ResearchNational Institute on Aging
KeywordsLatent class modelMedicineQuality of life (healthcare)Palliative careAnxietyDepression (economics)Psychiatry

Abstract

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BACKGROUND: Serious illness is characterized by high symptom burden that negatively affects quality of life (QOL). Although palliative care research has highlighted symptom burden in seriously ill adults with cancer, symptom burden among those with noncancer serious illness and multiple chronic conditions has been understudied. Latent class analysis is a statistical method that can be used to better understand the relationship between severity of symptom burden and covariates, such as the presence of multiple chronic conditions. Although latent class analysis has been used to highlight subgroups of seriously ill adults with cancer based on symptom clusters, none have incorporated multiple chronic conditions. OBJECTIVES: The objectives of this study were to (a) describe the demographic and baseline characteristics of seriously ill adults at the end of life in a palliative care cohort, (b) identify latent subgroups of seriously ill individuals based on severity of symptom burden, and (c) examine variables associated with latent subgroup membership, such as QOL, functional status, and the presence of multiple chronic conditions. METHODS: A secondary data analysis of a palliative care clinical trial was conducted. The latent class analysis was based on the Edmonton Symptom Assessment System, which measures nine symptoms on a scale of 0-10 (e.g., pain, fatigue, nausea, depression, anxiousness, drowsiness, appetite, well-being, and shortness of breath). Clinically significant cut-points for symptom severity were used to categorize each symptom item in addition to a categorized total score. RESULTS: Three latent subgroups were identified (e.g., low, moderate, and high symptom burden). Lower overall QOL was associated with membership in the moderate and high symptom burden subgroups. Multiple chronic conditions were associated with statistically significant membership in the high symptom burden latent subgroup. Older adults between 65 and 74 years had a lower likelihood of moderate or high symptom burden subgroup membership compared to the low symptom burden class. DISCUSSION: Lower QOL was associated with high symptom burden. Multiple chronic conditions were associated with high symptom burden, which underlines the clinical complexity of serious illness. Palliative care at the end of life for seriously ill adults with high symptom burden must account for the presence of multiple chronic conditions.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.080
Threshold uncertainty score0.320

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
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 head0.142
GPT teacher head0.467
Teacher spread0.325 · 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