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Improving Prognostic Communication and Symptom Management at a Respiratory LTACH: A Pilot in Palliative Care

2025· article· en· W4410271916 on OpenAlexaboutno aff
B.C. Walsh

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePalliative careIntensive care medicineRespiratory careMEDLINEPhysical therapyNursing

Abstract

fetched live from OpenAlex

Abstract Introduction: Long Term Acute Care Hospitals (LTACHs) treat patients with prolonged, serious, and complex medical illnesses that require ongoing hospitalization. These include those requiring tracheostomy, continued mechanical ventilation, gastrostomy, or dialysis after critical illness. While these patients have opted to continue medical therapy with the aim for recovery or life prolongation, there is an unmet need for discussing prognosis, addressing potentially unrealistic expectations, or alleviating physical, psychological, spiritual, and social symptoms. About two-thirds of U.S. LTACHs lack access to a palliative care physician. One LTACH specializing in pulmonary rehabilitation and ventilator weaning initiated a pilot palliative care program to assess unmet needs. Methods: Retrospective chart review of patients admitted between 3/1/2023 and 12/31/2023 at a single LTACH. Palliative care consultation was performed by one provider board-certified in pulmonary, critical care, and palliative medicine already practicing pulmonary & critical care at the facility. Results: Of 201 unique patients (52.7% male), 62.7% had a tracheostomy, and 77% of these were ventilated. At discharge, 41.2% were weaned from a ventilator, and 50% were further decannulated. Mortality was 24.4%, with an average length of stay of 46.7 days ± 43.8 days. Palliative care was consulted for 46 patients (22.9% service penetration). 81.8% of consultations were referred by another pulmonologist. 69.2% consultations occurred on the floor and 30.8% in the ICU. Consultation requests included goals of care (87%), family support (78%), and symptom management (43%). 42 (91.3%) patients received a goals of care meeting, 38.1% resulting in code status changes. Palliative care accounted for 57.3% of all goals of care documentation, with 33.3% of the remainder documented by a single individual. Among patients who did not survive, 32.7% had no documented goals of care. The Edmonton Symptom Assessment System, showed that 32.6% had five or more mild symptom domains and 48.7% had three or more severe symptom domains. Demographics included 69.2% English-speaking, 10.0% Armenian, and 10.0% Spanish; 58.2% White, 12.9% BIPOC, 10.9% Asian; and 57.3% Christian, 7.5% Jewish; and of mixed insurance (36.8% private and public, 38.3% private only, 8.5% public only). Conclusions: Significant gaps in goals-of-care documentation, especially among non-survivors, underscore the critical role of palliative care in ensuring goal-concordant care. Increased efforts to improve symptom relief and psychosocial support are warranted for LTACH patients undergoing ventilator weaning.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.411
Teacher spread0.344 · 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 designNon-randomized trial
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
Published2025
Admission routes1
Has abstractyes

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