Jayita De1, Anne P F Wand2. 1. Department of Aged Care, St George Hospital, Kogarah, New South Wales, Australia. Jayita.De@sesiahs.health.nsw.gov.au. 2. Older Adults Mental Health Service, St George Hospital, Kogarah, New South Wales, Australia. Faculty of Medicine, University of New South Wales, Australia.
Abstract
BACKGROUND: Delirium occurs commonly in hospitalized older patients but is poorly recognized. Although there are a plethora of validated delirium screening tools, it is unclear which tool best suits particular populations. PURPOSE: To evaluate validation studies of delirium screening tools in non-critically ill hospital inpatients and provide guidance on the choice of screening tool. METHODS: The MEDLINE, CINAHL, and PsychInfo databases were searched for studies comparing delirium bedside screening tools with either the Diagnostic and Statistical Manual or International Classification of Diseases defined diagnosis of delirium in hospital inpatients. Information was also drawn from conference proceedings and discussion with delirium researchers. RESULTS: Thirty-one studies describing 21 delirium screening tools were included in the systematic review. The majority of studies were conducted across a broad range of inpatient settings internationally in elderly inpatients, including patients with dementia but most excluded nonnative language speakers. IMPLICATIONS: The Confusion Assessment Method was the most widely used instrument to identify delirium, however, specific training is required to ensure optimum performance. The Delirium Rating Scale and its revised version performed best in the psychogeriatric population but requires an operator with psychiatric training. The Nurses' Delirium Screening Checklist appears best suited to the surgical and recovery room setting. The Single Question in Delirium shows promise in oncology patients. The Memorial Delirium Assessment Scale, while demonstrating good measures of validity in the surgical and palliative care setting, may be better used a measure of delirium severity. The 4As Test performed well when delirium was superimposed on dementia, but it requires further study.
BACKGROUND:Delirium occurs commonly in hospitalized older patients but is poorly recognized. Although there are a plethora of validated delirium screening tools, it is unclear which tool best suits particular populations. PURPOSE: To evaluate validation studies of delirium screening tools in non-critically ill hospital inpatients and provide guidance on the choice of screening tool. METHODS: The MEDLINE, CINAHL, and PsychInfo databases were searched for studies comparing delirium bedside screening tools with either the Diagnostic and Statistical Manual or International Classification of Diseases defined diagnosis of delirium in hospital inpatients. Information was also drawn from conference proceedings and discussion with delirium researchers. RESULTS: Thirty-one studies describing 21 delirium screening tools were included in the systematic review. The majority of studies were conducted across a broad range of inpatient settings internationally in elderly inpatients, including patients with dementia but most excluded nonnative language speakers. IMPLICATIONS: The Confusion Assessment Method was the most widely used instrument to identify delirium, however, specific training is required to ensure optimum performance. The Delirium Rating Scale and its revised version performed best in the psychogeriatric population but requires an operator with psychiatric training. The Nurses' Delirium Screening Checklist appears best suited to the surgical and recovery room setting. The Single Question in Delirium shows promise in oncology patients. The Memorial Delirium Assessment Scale, while demonstrating good measures of validity in the surgical and palliative care setting, may be better used a measure of delirium severity. The 4As Test performed well when delirium was superimposed on dementia, but it requires further study.
Authors: C G Clemmesen; L M Pedersen; S Hougaard; M L Andersson; V Rosenkvist; H B Nielsen; H Palm; N B Foss Journal: J Clin Monit Comput Date: 2018-02-05 Impact factor: 2.502
Authors: Richard N Jones; Sevdenur Cizginer; Laura Pavlech; Asha Albuquerque; Lori A Daiello; Kumar Dharmarajan; Lauren J Gleason; Benjamin Helfand; Lauren Massimo; Esther Oh; Olivia I Okereke; Patricia Tabloski; Laura A Rabin; Jirong Yue; Edward R Marcantonio; Tamara G Fong; Tammy T Hshieh; Eran D Metzger; Kristen Erickson; Eva M Schmitt; Sharon K Inouye Journal: JAMA Intern Med Date: 2019-02-01 Impact factor: 21.873
Authors: Zoë Tieges; Alasdair M J Maclullich; Atul Anand; Claire Brookes; Marica Cassarino; Margaret O'connor; Damien Ryan; Thomas Saller; Rakesh C Arora; Yue Chang; Kathryn Agarwal; George Taffet; Terence Quinn; Susan D Shenkin; Rose Galvin Journal: Age Ageing Date: 2020-11-11 Impact factor: 10.668
Authors: Erika Steensma; Wenxiao Zhou; Long Ngo; Jacqueline Gallagher; Sharon Inouye; Douglas Leslie; Marie Boltz; Ann Kolanowski; Lorraine Mion; Edward R Marcantonio; Donna Fick Journal: J Am Med Dir Assoc Date: 2019-07-03 Impact factor: 4.669