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Abstract 16403: Trajectories of Depression and Anxiety Symptoms are Predictive of Physical Health-related Quality of Life, Mortality, and Hospital Admission at 1-Year Among Patients With Heart Failure

2015· article· en· W2767724221 on OpenAlexaff
Lynn Roser, Abdullah S. Alhurani, Terry A. Lennie, Christopher S. Lee, Martha Biddle, Susan K. Frazier, Stephen Fleming, Debra K. Moser

Bibliographic record

VenueCirculation · 2015
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsFleming College
Fundersnot available
KeywordsMedicineAnxietyDepression (economics)Quality of life (healthcare)Heart failurePhysical therapyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Background: Little is known about the symptom trajectories of depression and anxiety in heart failure (HF) patients and how these symptoms influence health outcomes over time. Objective: The goal of this study was to describe unique trajectories of depression and anxiety symptoms in HF patients over 12 months and determine whether changes in these symptoms predict subsequent physical health-related quality of life (P-HRQOL) and event-free survival. Method: The study sample consisted of 597 patients with HF enrolled as part of a larger longitudinal study at 8 sites from across the United States. The Patient Health Questionnaire-9, the Brief Symptom Inventory Anxiety subscale, and the Minnesota Living with Heart Failure Questionnaire Physical Subscale were used to assess depression, anxiety, and P-HRQOL, respectively. Latent growth mixture modeling was used to identify distinct trajectories of change in depression and anxiety. Results: Three trajectories of depression and three trajectories of anxiety were identified (entropy = 0.919). Trajectory changes in depressive symptoms were labeled as getting better (81.1%), bad and getting slightly worse (13.9%), and bad and getting much worse (5.0%). Trajectory changes in anxiety were labeled as getting better (66.7%), stable with slight improvement (22.1%), and getting much worse (11.2%). The trajectories of depression labeled as bad and getting slightly worse and bad and getting much worse were predictive of a poorer P-HRQOL at one-year than the trajectory which showed improvement (β 11.6, p<0.001 and β 15.6, p<0.001, respectively). Changes in depressive symptoms labeled as bad and getting slightly worse was also a significant predictor of event-free survival (HR = 2.17, p<0.001). The two anxiety trajectories which showed stable, slight improvement and much worse anxiety symptoms over 12-months were significant predictors of worse P-HRQOL (β 12.0, p<0.001 and β 18.7, p<0.001, respectively). The trajectory of anxiety symptoms labeled getting much worse was a significant predictor of event-free survival (HR = 2.18, p<0.001). Conclusion: We identified three distinct trajectories for both depression and anxiety symptoms, some of which were predictive of P-HRQOL and event-free survival at one year.

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)0.004
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.021
GPT teacher head0.308
Teacher spread0.287 · 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
Published2015
Admission routes1
Has abstractyes

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