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Post-discharge transitions of care for hospitalized patients with advanced cancer.

2017· article· en· W2892290548 on OpenAlexaboutno aff
Daniel E. Lage, Ryan David Nipp, Sara D’Arpino, Samantha M.C. Moran, Ephraim P. Hochberg, Lara Traeger, Vicki A. Jackson, Barbara J. Cashavelly, Holly S Martinson, David P. Ryan, Joseph A. Greer, Jennifer S. Temel, Areej El‐Jawahri

Bibliographic record

VenueJournal of Clinical Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineConstipationLogistic regressionAnxietyDepression (economics)CancerHospital Anxiety and Depression ScaleQuality of life (healthcare)Proportional hazards modelHospital dischargeInternal medicinePhysical therapyEmergency medicineNursingPsychiatry

Abstract

fetched live from OpenAlex

6504 Background: Patients with advanced cancer experience frequent hospitalizations and burdensome transitions of care post-discharge. We examined predictors of discharge location for patients with advanced cancer. Methods: We prospectively enrolled patients with advanced cancer with unplanned hospitalizations from 9/14 to 3/16. Upon admission, we used the Edmonton Symptom Assessment Scale and Patient Health Questionnaire-4 to assess physical and psychological symptoms, respectively. We used logistic regression models to identify predictors of discharge to location other than home, including post-acute care (PAC) [skilled nursing facility or long term acute care hospital] or hospice [any setting]. We used Cox regression models adjusted for clinical variables to assess the relationship between discharge location and survival. Results: Out of 932 patients, 726 (77.9%) were discharged home, 118 (12.7%) to PAC and 88 (9.4%) to hospice. Compared with patients discharged home, those discharged to PAC or hospice had higher symptom burden, including dyspnea, constipation, low appetite, drowsiness, fatigue, depression, and anxiety (all p < 0.05). Patients discharged to PAC or hospice vs. home were more likely to be older (OR 1.03, p < 0.0001), live alone (OR 1.95, 95% CI: 1.25-3.02, p < 0.003), have impaired mobility (OR 5.08, 95% CI: 3.46-7.45, p < 0.0001), longer length of stay (OR 1.15, 95% CI: 1.11-1.20, p < 0.0001), higher ESAS physical symptoms (OR 1.02, 95% CI: 1.003-1.032, p < 0.017), and higher PHQ-2 depression symptoms (OR 1.13, 95% CI: 1.01-1.25, p < 0.027). Patients discharged to hospice vs. PAC were more likely to receive palliative care consultation (OR 4.44, 95% CI: 2.12 to 9.29, p < 0.0001) and have shorter length of stay (OR 0.84, 95% CI: 0.77 to 0.91, p < 0.0001). Compared with patients discharged home, those discharged to PAC had lower survival (HR 1.53, 95% CI 1.22-1.93, p < 0.0001). Conclusions: Patients with advanced cancer discharged to PAC or hospice have substantial physical and psychological symptom burden and poor physical function. Patients discharged to PAC also have inferior survival compared with those discharged home. They may benefit from targeted interventions to improve their quality of life and care.

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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.048
GPT teacher head0.454
Teacher spread0.407 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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