Prevalence of frailty and pain in hospitalised adult patients in an acute hospital: a protocol for a point prevalence observational study
Bibliographic record
Abstract
INTRODUCTION: Frailty and pain are associated with adverse patient clinical outcomes and healthcare system costs. Frailty and pain can interact, such that symptoms of frailty can make pain assessment difficult and pain can exacerbate the progression of frailty. The prevalence of frailty and pain and their concurrence in hospital settings are not well understood, and patients with cognitive impairment are often excluded from pain prevalence studies due to difficulties assessing their pain. The aim of this study is to determine the prevalence of frailty and pain in adult inpatients, including those with cognitive impairment, in an acute care private metropolitan hospital in Western Australia. METHODS AND ANALYSIS: A prospective, observational, single-day point prevalence, cross-sectional study of frailty and pain intensity of all inpatients (excluding day surgery and critical care units) will be undertaken. Frailty will be assessed using the modified Reported Edmonton Frail Scale. Current pain intensity will be assessed using the PainChek smart-device application enabling pain assessment in people unable to report pain due to cognitive impairment. Participants will also provide a numerical rating of the intensity of current pain and the worst pain experienced in the previous 24 hours. Demographic and clinical information will be collected from patient files. The overall response rate of the survey will be reported, as well as the percentage prevalence of frailty and of pain in the sample (separately for PainChek scores and numerical ratings). Additional statistical modelling will be conducted comparing frailty scores with pain scores, adjusting for covariates including age, gender, ward type and reason for admission. ETHICS AND DISSEMINATION: Ethical approval has been granted by Ramsay Health Care Human Research Ethics Committee WA/SA (reference: 2038) and Edith Cowan University Human Research Ethics Committee (reference: 2020-02008-SAUNDERS). Findings will be widely disseminated through conference presentations, peer-reviewed publications and social media. TRIAL REGISTRATION NUMBER: ACTRN12620000904976.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.056 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".