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Updated: Jul 10, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
[Delirium: screening, assessment and diagnosis]
Wolfgang Hasemann1, Reto W Kressig, Doris Ermini-Fünfschilling
1Abteilung Klinische Pflegewissenschaft, Universitätsspital Basel, Schweiz. whasemann@uhbs.ch
Abstract:
Delirium is an acute decline in attention and cognition. To make a diagnosis, there are two classification systems: the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) and the International Classification of Diseases (ICD-10). While the core criteria are similar in both systems, ICD-10 requires three additional criteria to make a diagnosis: disturbed psychomotor behaviour and sleep-wake-cycle and emotional disturbances. Thus, making a diagnosis according to ICD-10 criteria is more stringent. Depending on the population, up to 60 percent of patients with delirium, diagnosed by DSM-IV criteria, are missed by ICD- 10. In clinical practice, several screening and assessment instruments are available. Most of them are based on DSM-IV criteria. In this article, two instruments will be discussed, which have been used by nurses in the Basel Delirium Management Program in Switzerland. Screening for delirium is accomplished with the Delirium Observatie Screening Schaal (DOS) Scale developed by Schuurmans (2001). For assessment, the Confusion Assessment Method (CAM), developed by Inouye, is used. While the DOS is a classical observation instrument, the CAM requires a structured interview, similar to the Mini-Mental State Exam by Folstein. Both the DOS and CAM instruments were scientifically translated into German. This article will present the translated versions of both DOS and CAM, report their use in a Swiss population of patients at risk for delirium and provide the theoretical background of diagnosing delirium with the criteria of the DSM-IV and ICD-10.
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