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Record W2887648674 · doi:10.1002/cam4.1728

Cancer patients as frequent attenders in emergency departments: A national cohort study

2018· article· en· W2887648674 on OpenAlexaff
Ting Hway Wong, Zheng Yi Lau, Whee Sze Ong, Kelvin Bryan Tan, Yu Jie Wong, Mohamad Farid, Melissa Ching Ching Teo, Alethea Chung Pheng Yee, Hai V. Nguyen, Marcus Eng Hock Ong, N. Gopalakrishna Iyer

Bibliographic record

VenueCancer Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMedicineHazard ratioProportional hazards modelRetrospective cohort studyEmergency departmentInternal medicineCohortCancerCharlson comorbidity indexCohort studyConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: Cancer patients contribute significantly to emergency department (ED) utilization. The objective of this study was to identify factors associated with patients becoming ED frequent attenders (FA) after a cancer-related hospitalization. METHODS: A retrospective cohort study was conducted using national administrative, billing, and death records of Singapore residents discharged alive from Singapore public hospitals from January 2012 to December 2015, with a primary discharge diagnosis of cancer. Patients with four or more ED visits within any 12-month period after discharge from their index hospitalization were classified as FA. Time to FA distribution was estimated using the Kaplan-Meier method, and factors associated with risk of FA were identified using multivariate Cox regression analyses. RESULTS: Records for 47 235 patients were analyzed, of whom 2980 patients were FA within the study period. Age (<17 years, hazard ratio [HR] 2.92, 95% CI 2.28-3.74; 75-84 years, HR 1.29, 95% CI 1.16-1.45; and ≥85 years, HR 1.71, 95% CI 1.45-2.02, relative to age 55-64), male gender (HR 1.26, 95% CI 1.16-1.37), Charlson comorbidity index (HR 1.21, 95% CI 1.19-1.23), and socioeconomic factors (Medifund use, HR 1.40, 95% CI 1.23-1.59; housing subsidy type, HR 2.12, 95% CI 1.77-2.54) were associated with increased risk of FA. Primary malignancies associated with FA included brain and spine (HR 2.51, 95% CI 1.67-3.75), head and neck cancers (tongue, HR 2.05, 95% CI 1.27-3.31; hypopharynx, HR 2.72, 95% CI 1.56-4.74), lung (trachea and lung, HR 1.57, 95% CI 1.13-2.18; pleural, HR 3.69, 95% CI 2.12-6.34), upper gastrointestinal (stomach, HR 1.93, 95% CI 1.26-2.74; esophagus, HR 4.13, 95% CI 2.78-6.13), hepato-pancreato-biliary (liver, HR 1.42, 95% CI 1.01-2.00, pancreas, HR 2.48, 95% CI 1.72-3.59), and certain hematological malignancies (diffuse non-Hodgkin's lymphoma, HR1.59, 95% CI 1.08-2.33, lymphoid leukemia, HR 1.86, 95% CI 1.21-2.86). Brain (HR 1.69, 95% CI 1.27-2.26), lung (HR 1.31, 95% CI 1.01-1.71), liver (HR 1.46, 95% CI 1.14-1.89), and bone (HR 1.35, 95% CI 1.04-1.76) metastases were also associated with FA. CONCLUSION: There are cancer-specific factors contributing to ED frequent attendance. Additional resources should be allocated to support high-risk groups and prevent unnecessary ED use.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.000

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 head0.032
GPT teacher head0.387
Teacher spread0.355 · 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.

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
Published2018
Admission routes1
Has abstractyes

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