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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Delirium: clinical approach and prevention
Giovanni Mistraletti1, Paolo Pelosi, Elena Silvia Mantovani
1Dipartimento di Fisiopatologia medico-chirurgica e dei trapianti, Università degli Studi di Milano, A.O. San Paolo-Polo Universitario, Milan, Italy. giovanni.mistraletti@unimi.it
Best Practice & Research. Clinical Anaesthesiology
|October 9, 2012
Summary
Delirium, an acute change in mental state, is common in hospitalized patients and linked to worse outcomes. Early detection and prevention strategies, including validated tools and prediction models, are crucial for improving patient prognosis.
Area of Science:
- Geriatrics
- Critical Care Medicine
- Neuroscience
Background:
- Delirium, characterized by acute fluctuating mental status changes, consciousness, and cognitive impairment, is prevalent in hospitalized patients.
- It is associated with increased morbidity, mortality, prolonged intensive care unit (ICU) and hospital stays, and elevated healthcare costs.
- Clinical diagnosis of delirium can be challenging due to its fluctuating nature.
Purpose of the Study:
- To provide a practical approach to delirium management in hospitalized patients.
- To highlight the importance of early diagnosis and prevention strategies.
- To review methods for classification, diagnosis, and risk prediction of delirium.
Main Methods:
- Classification and diagnosis of delirium using validated tools.
- Implementation of non-pharmacological management protocols.
- Utilisation of an early prediction model to identify high-risk individuals.
Main Results:
- The review outlines a structured approach to delirium diagnosis and management.
- Non-pharmacological interventions and early prediction models are emphasized for high-risk patients.
- The potential benefit of pharmacological prophylaxis in select high-risk groups is discussed.
Conclusions:
- Early identification and management of delirium are critical for improving patient outcomes.
- Validated diagnostic tools and non-pharmacological protocols form the cornerstone of delirium care.
- Predictive models can help target interventions, including potential prophylaxis, to at-risk populations.
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