{'fraction_non_alphanumeric': 0.023430513324986586, 'fraction_numerical': 0.006260060812019317, 'mean_word_length': 5.185840707964601, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Predicting delirium: time to use delirium risk scores in routine practice?

Delirium has been recognised for millennia. Hippocrates writing in the 4th century BC and Celsus in the 2nd century AD provide descriptions that would not be too inconsistent with current DSM-V criteria [1]. That delirium is common and has serious adverse outcomes, particularly for older people, has also been known for some time. There is a large body of evidence now from medical, surgical, intensive care, palliative care and long-term care settings describing its high prevalence and costs in terms of distress, morbidity and mortality and use of healthcare resources [2]. With an ageing demographic and related increase in the number of people living with dementia (the prevalence of Alzheimer’s Disease is set to double by 2050) [3], the already considerable burden of delirium is set to rise steeply in future. Despite this, we know surprisingly little about delirium pathogenesis or management. Delirium raises complex research and clinical challenges. Evidence for effective treatments is limited [4]. Encouragingly, there is growing evidence that delirium can be prevented. Multi-component interventions have been repeatedly shown to reduce delirium incidence by around one-third [5]. Given the high costs of delirium, it is important that healthcare services put in place measures to identify those at risk and deliver evidence-based delirium prevention. However, the implementation of multi-component interventions in clinical practice has been slow. One of the reasons cited is the lack of consensus on predictive tools to identify those at risk [6]. In 2011, the American Delirium Society set out ‘A Strategic Plan to Bring an Ancient Disease into the 21st Century’ which included a call for ‘every patient to be screened for delirium risk at every transition of care, employing a validated prediction rule’ [7]. This is clearly still very far from being realised. Although the literature describes the development of a number of delirium risk tools, few have been independently validated, and to-date, there are no reports of such tools being used in clinical practice [6]. In this issue, Pendlebury et al. report findings from a study to validate and compare performance of four published delirium risk scores in a prospective cohort of 308 older acute medicine patients. They identified four risk scores that were derived from acute medicine patients and could be adapted and simplified to use data obtained as part of the medical team’s routine clinical assessment. Simplicity and use of routinely available data are clearly attractive, increasing the potential usability of such tools in clinical practice. Each risk score included three to four different (although overlapping) factors, with unsurprisingly, cognitive impairment and age being the most common. All four delirium risk scores reliably risk-stratified patients for incident and any delirium. In addition to the prospective design, a strength of the study was that an experienced physician saw patients at least every other day with delirium diagnosis made according to DSM-IV criteria. The validation cohort included only patients 65 years or older. While this increased the rates of delirium in the study cohort, it limits the applicability of findings to general medical inpatient settings, which typically include patients aged 17 or 18 and older. A limitation, acknowledged by the authors, is that around one-third of cognitive tests were missed with no reason recorded for 79. This is an important qualification for the results, as cognitive impairment featured in three of the four risk scores, although the authors report that analyses including imputed missing data showed no major differences. Delirium risk can be stratified in acute medicine in patients with simple risk scores using routinely available information. However, the various risk models are heterogeneous, with as yet no consensus on which to use. Given the significance of cognitive impairment as a delirium risk factor, more work is also needed to establish routine cognitive testing in clinical practice. Testing cognition in unwell patients is known to be challenging; but given its major role in quantifying delirium risk and in delirium detection, it is important that cognitive testing is conducted routinely both at admission and as part of ongoing monitoring of progress. Such testing is already recommended in NICE delirium guidelines [8] and needs to become a vital sign, embedded into routine care [4]. What are the implications for clinical practice? The authors suggest using delirium risk stratification tools to target multicomponent interventions. This would, of course, make wider implementation of delirium prevention interventions more feasible where resources are limited. However, as yet, the effectiveness of these interventions for subgroups of patients (including those with dementia who are at higher risk of delirium) is unknown [5, 9]. Large-scale improvements in delirium care are urgently needed, and we clearly need to put in place what we already know. However, routine deployment of delirium risk scores in clinical practice cannot be recommended. Further work is urgently needed to develop consensus on the most appropriate risk stratification tool, identify feasible cognitive tests and understand how to embed them into routine practice. Research to identify which components of delirium prevention interventions are effective, and for whom, is also required. A delirium risk score has undoubted utility in such research.