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Record W2045193090 · doi:10.1186/1472-684x-11-3

Autonomic dysfunction in patients with advanced cancer; prevalence, clinical correlates and challenges in assessment

2012· article· en· W2045193090 on OpenAlexaff
Carol Stone, Rose Anne Kenny, Bríd Nolan, Peter G. Lawlor

Bibliographic record

VenueBMC Palliative Care · 2012
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsBruyèreUniversity of Ottawa
FundersIrish Cancer SocietyHealth Research BoardIrish Hospice FoundationAtlantic Philanthropies
KeywordsMedicineLogistic regressionInternal medicineNauseaCancerProspective cohort studyUnivariate analysisPerformance statusProportional hazards modelMultivariate analysisPhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: The results of a small number of studies of autonomic function in patients with advanced cancer suggest that autonomic dysfunction (AD) is common. In other disease-specific groups this is associated with decreased survival, falls and symptoms such as postural hypotension, nausea, early satiety and fatigue. The contribution of AD to symptoms in advanced cancer is unknown. METHODS: We conducted a prospective cohort study designed to identify the risk factors for falls in patients with advanced cancer. Ambulant adult patients admitted consecutively to palliative care services were invited to participate. Participants underwent an assessment at baseline which included standard clinical tests of autonomic function, assessment of symptom severity, muscle strength, anthropometric measurements, walking speed, medication use, comorbidities and demographics. Information regarding survival was recorded ten months following cessation of recruitment. The clinical correlates of AD, defined as definite or severe dysfunction using Ewing's classification, were examined by univariate and multivariate logistic regression analysis. Survival analysis was conducted using Kaplan-Meier plots and the log rank test. RESULTS: Of 185 patients recruited, 45% were unable to complete all of the clinical tests of autonomic function. Non-completion was associated with scoring high on clinical indicators of frailty. It was possible to accurately classify 138/185 (74.6%) of participants as having either definite or severe versus normal, early or atypical AD: 110 (80%) had definite/severe AD. In logistic regression analysis, age (OR = 1.07 [95% CI; 1.03-1.1] P = 0.001) and increased severity of fatigue (OR = 1.26 [95% CI; 1.05-1.5] p = 0.016) were associated with having definite/severe AD. In analysis adjusted for age, median survival of participants with definite/severe AD was shorter than in those with normal/early/atypical classification (χ2 = 4.3, p = 0.038). CONCLUSIONS: Autonomic dysfunction is highly prevalent in patients with advanced cancer and is associated with increased severity of fatigue and reduced survival. Due to frailty, up to 45% of participants were unable to complete standard clinical tests of autonomic function. In order to further investigate the impact of AD and the therapeutic potential of treatment of AD in patients with advanced cancer, the validity of alternative novel methods of assessing autonomic function must be appraised.

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 score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.068
GPT teacher head0.359
Teacher spread0.291 · 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

Citations50
Published2012
Admission routes1
Has abstractyes

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