Are We Adequately Assessing Delirium? An Analysis Of Liaison Psychiatry Referrals
Bibliographic record
Abstract
INTRODUCTION: Delirium is characterised by an acute, fluctuating change in cognition, attention and awareness (Wilson et al. Nature Reviews 2020; 6). This presentation can make the diagnosis of delirium extremely challenging to clinicians (Gofton., Canadian Journal of neurological sciences. 2011; 38 673-680). It is commonly reported in hospitalised patients, particularly in those over the age of sixty five (NICE. Delirium: prevention, diagnosis and management. 2010). OBJECTIVES: Our aim is to identify which investigations and cognitive assessments are completed prior to a referral to the liaison psychiatry services in patients with symptoms of delirium. METHODS: Referrals (N = 6012) to the liaison psychiatry team at Croydon University Hospital made between April and September 2022 were screened. Search parameters used to identify referrals related to a potential diagnosis of delirium were selected by the authors. The terms used were confusion; delirium; agitation; aggression; cognitive decline or impairment; disorientation; challenging behaviour. Data was collected on the completion rates of investigations for delirium as advised by the NICE clinical knowledge summaries. Further data was gathered on neuroimaging (CT or MRI), cognitive assessment tools (MOCA/MMSE) and delirium screening tools (4AT/AMTS). RESULTS: The study sample identified 114 referrals (61 males and 53 females), with 82% over 65 years at the time of referral. In 96% of referrals, U&E and CRP were performed. Sputum culture (1%), urine toxin screen (4%) and free T3/4 (8%) were the tests utilised the least. Neuroimaging was completed in 41% of referrals (see Graph 1 for a full breakdown of results). A formal cognitive assessment or delirium screening tool was completed in 32% of referrals. The AMTS and 4AT tools were documented for 65% and 24% respectively. A total of 19 referrals explicitly stated the patient was suspected to have dementia. A delirium screening tool was documented in 47% of these cases however, a formal cognitive assessment was documented in only 5% of these patients. Following psychiatric assessment 47% of referrals were confirmed as delirium. Image: CONCLUSIONS: Our data highlights the low level completion of the NICE recommended delirium screen prior to referral to liaison psychiatry. The effective implementation of a delirium screen and cognitive assessment is paramount to reduce the number of inappropriate psychiatric referrals in hospital and helps to identify reversible organic causes of delirium. This in turn will ensure timely treatment of reversible causes of delirium and reduce the length of hospital admission. DISCLOSURE OF INTEREST: None Declared
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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 | 0.007 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".