OBJECTIVE: Although delirium is the most common neurobehavioral complication after stroke, its motor subtypes-hypoactive, hyperactive, mixed, and none-as well as their risk factors are not well characterized. Motor subtypes influence recognition and prognosis of delirium in hospitalized patients. METHODS: The aim of this prospective study was to assess the frequency of poststroke delirium subtypes and to describe their predictive models. Consecutive patients with stroke were screened for delirium with the Confusion Assessment Method for the Intensive Care Unit. Delirium was diagnosed according to DSM-5 criteria, and subtypes were classified with the Delirium Motor Subtype Scale-4. Baseline demographic characteristics, biochemistry, stroke-related data, medications, neurological deficits, and premorbid cognitive and functional impairments were assessed. RESULTS: Out of 750 patients (mean age, 71.75 years [SD=13.13]), 203 (27.07%) had delirium: 85 (11.34%) were hypoactive, 77 (10.27%) were mixed hypoactive-hyperactive, 31 (4.13%) were hyperactive, and 10 (1.33%) had an unspecified type. Cognitive impairment at the time of hospital admission and spatial neglect, among other factors, were identified as the best predictors for all motor delirium subtypes. CONCLUSIONS: Screening for poststroke delirium is important because the hypoactive subtype bears the worst prognosis and is misdiagnosed the most compared with other subtypes. All identified factors for the predictive models of delirium subtypes are routinely assessed during hospital admission. Their occurrence in patients with stroke should alert the treating physician to the high risk for a particular delirium subtype.
OBJECTIVE: Although delirium is the most common neurobehavioral complication after stroke, its motor subtypes-hypoactive, hyperactive, mixed, and none-as well as their risk factors are not well characterized. Motor subtypes influence recognition and prognosis of delirium in hospitalized patients. METHODS: The aim of this prospective study was to assess the frequency of poststroke delirium subtypes and to describe their predictive models. Consecutive patients with stroke were screened for delirium with the Confusion Assessment Method for the Intensive Care Unit. Delirium was diagnosed according to DSM-5 criteria, and subtypes were classified with the Delirium Motor Subtype Scale-4. Baseline demographic characteristics, biochemistry, stroke-related data, medications, neurological deficits, and premorbid cognitive and functional impairments were assessed. RESULTS: Out of 750 patients (mean age, 71.75 years [SD=13.13]), 203 (27.07%) had delirium: 85 (11.34%) were hypoactive, 77 (10.27%) were mixed hypoactive-hyperactive, 31 (4.13%) were hyperactive, and 10 (1.33%) had an unspecified type. Cognitive impairment at the time of hospital admission and spatial neglect, among other factors, were identified as the best predictors for all motor delirium subtypes. CONCLUSIONS: Screening for poststroke delirium is important because the hypoactive subtype bears the worst prognosis and is misdiagnosed the most compared with other subtypes. All identified factors for the predictive models of delirium subtypes are routinely assessed during hospital admission. Their occurrence in patients with stroke should alert the treating physician to the high risk for a particular delirium subtype.
Entities:
Keywords:
Delirium; Delirium subtype; Risk Factors; Stroke and Other Cerebral Vascular Disease (Neuropsychiatric Aspects)
Authors: John Y Rhee; Mia A Colman; Maanasa Mendu; Simran J Shah; Michael D Fox; Natalia S Rost; Eyal Y Kimchi Journal: J Stroke Cerebrovasc Dis Date: 2021-12-23 Impact factor: 2.136
Authors: Hee Won Yang; Miji Lee; Jong Wook Shin; Hye Seon Jeong; Jei Kim; Jeong Lan Kim Journal: Psychiatry Investig Date: 2019-10-28 Impact factor: 2.505
Authors: Vasileios Siokas; Robert Fleischmann; Katharina Feil; Ioannis Liampas; Markus C Kowarik; Yang Bai; Maria-Ioanna Stefanou; Sven Poli; Ulf Ziemann; Efthimios Dardiotis; Annerose Mengel Journal: J Clin Med Date: 2022-10-01 Impact factor: 4.964