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Record W4318699292 · doi:10.1136/spcare-2022-004154

Non-steroidal anti-inflammatory drugs for pain in hospice/palliative care: an international pharmacovigilance study

2023· article· en· W4318699292 on OpenAlexaff
Richard McNeill, Jason W Boland, Andrew Wilcock, Aynharan Sinnarajah, David C. Currow

Bibliographic record

VenueBMJ Supportive & Palliative Care · 2023
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsLakeridge HealthQueen's University
Fundersnot available
KeywordsMedicinePharmacovigilanceNauseaPalliative careVomitingAdverse effectCommon Terminology Criteria for Adverse EventsIntensive care medicineInternal medicineNursing

Abstract

fetched live from OpenAlex

OBJECTIVES: To describe the current, real-world use of non-steroidal anti-inflammatory drugs for pain and the associated benefits and harms. METHODS: A prospective, multicentre, consecutive cohort pharmacovigilance study conducted at 14 sites across Australia, Aotearoa/New Zealand and the UK including hospital, hospice inpatient and outpatient services. Pain scores and harms were graded using the National Cancer Institute Common Terminology Criteria for Adverse Events at baseline, 2 days and 14 days. Ad-hoc safety reporting continued until day 28. RESULTS: Data were collected from 92 patients between March 2018 and October 2021. Most patients had cancer (91%) and were coprescribed opioids (90%). At 14 days, 83% of patients had benefit from non-steroidal anti-inflammatory drugs and 22% had harm. The most common harms were nausea (8%), vomiting (3%), acute kidney injury (3%) and non-gastrointestinal bleeding (3%); only 2% were severe and no patients ceased their non-steroidal anti-inflammatory drugs due to toxicity. Overall, 65% had benefit without harm and 3% had harm without benefit. CONCLUSIONS: Most patients benefited from non-steroidal anti-inflammatory drugs with only one in five patients experiencing tolerable harm. This suggests that short-term use of non-steroidal anti-inflammatory drugs in patients receiving palliative care is safer than previously thought and may be underused.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.036
GPT teacher head0.391
Teacher spread0.354 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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