Use of Computed Tomography of the Head in Patients With Acute Atraumatic Altered Mental Status

Acharya, Roshan; Kafle, Smita; Shrestha, Dhan Bahadur; Sedhai, Yub Raj; Ghimire, Meera; Khanal, Kishor; Malla, Queen Baba; Nepal, Uttam; Shrestha, Ranjana; Giri, Badri

doi:10.1001/jamanetworkopen.2022.42805

Cited by 5 publications

(2 citation statements)

References 41 publications

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“…CT is the first option, although with low yield. In a meta-analysis, 100% of ICU patients with altered mental status underwent a CT scan, with positive findings in only 12% of studies [67]. MRI can add further diagnostic and prognostic information.…”

Section: Neuroimagingmentioning

confidence: 99%

Acute encephalopathy in the ICU: a practical approach

Kurtz,

van den Boogaard,

Girard

et al. 2024

Current Opinion in Critical Care

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Purpose of review Acute encephalopathy (AE) – which frequently develops in critically ill patients with and without primary brain injury – is defined as an acute process that evolves rapidly and leads to changes in baseline cognitive status, ranging from delirium to coma. The diagnosis, monitoring, and management of AE is challenging. Here, we discuss advances in definitions, diagnostic approaches, therapeutic options, and implications to outcomes of the clinical spectrum of AE in ICU patients without primary brain injury. Recent findings Understanding and definitions of delirium and coma have evolved. Delirium is a neurocognitive disorder involving impairment of attention and cognition, usually fluctuating, and developing over hours to days. Coma is a state of unresponsiveness, with absence of command following, intelligible speech, or visual pursuit, with no imaging or neurophysiological evidence of cognitive motor dissociation. The CAM-ICU(−7) and the ICDSC are validated, guideline-recommended tools for clinical delirium assessment, with identification of clinical subtypes and stratification of severity. In comatose patients, the roles of continuous EEG monitoring and neuroimaging have grown for the early detection of secondary brain injury and treatment of reversible causes. Summary Evidence-based pharmacologic treatments for delirium are limited. Dexmedetomidine is effective for mechanically ventilated patients with delirium, while haloperidol has minimal effect of delirium but may have other benefits. Specific treatments for coma in nonprimary brain injury are still lacking.

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Section: Neuroimagingmentioning

confidence: 99%

Acute encephalopathy in the ICU: a practical approach

Kurtz,

van den Boogaard,

Girard

et al. 2024

Current Opinion in Critical Care

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show abstract

“…Data on the usefulness of brain CT studies in patients with SAE is limited. In a meta-analysis conducted in adults with acute non-traumatic encephalopathy, CT abnormal findings were observed in 11% of cases [ 14 ]. In medical ICU patients, most common acute findings diagnosed from non-contrast head CT studies included infarction (5% of cases) and hemorrhage (4% of cases) [ 15 ].…”

Section: Neuroimagingmentioning

confidence: 99%

The spectrum of sepsis-associated encephalopathy: a clinical perspective

Sonneville,

Benghanem,

Jeantin

et al. 2023

Crit Care

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Sepsis-associated encephalopathy is a severe neurologic syndrome characterized by a diffuse dysfunction of the brain caused by sepsis. This review provides a concise overview of diagnostic tools and management strategies for SAE at the acute phase and in the long term. Early recognition and diagnosis of SAE are crucial for effective management. Because neurologic evaluation can be confounded by several factors in the intensive care unit setting, a multimodal approach is warranted for diagnosis and management. Diagnostic tools commonly employed include clinical evaluation, metabolic tests, electroencephalography, and neuroimaging in selected cases. The usefulness of blood biomarkers of brain injury for diagnosis remains limited. Clinical evaluation involves assessing the patient's mental status, motor responses, brainstem reflexes, and presence of abnormal movements. Electroencephalography can rule out non-convulsive seizures and help detect several patterns of various severity such as generalized slowing, epileptiform discharges, and triphasic waves. In patients with acute encephalopathy, the diagnostic value of non-contrast computed tomography is limited. In septic patients with persistent encephalopathy, seizures, and/or focal signs, magnetic resonance imaging detects brain injury in more than 50% of cases, mainly cerebrovascular complications, and white matter changes. Timely identification and treatment of the underlying infection are paramount, along with effective control of systemic factors that may contribute to secondary brain injury. Upon admission to the ICU, maintaining appropriate levels of oxygenation, blood pressure, and metabolic balance is crucial. Throughout the ICU stay, it is important to be mindful of the potential neurotoxic effects associated with specific medications like midazolam and cefepime, and to closely monitor patients for non-convulsive seizures. The potential efficacy of targeted neurocritical care during the acute phase in optimizing patient outcomes deserves to be further investigated. Sepsis-associated encephalopathy may lead to permanent neurologic sequelae. Seizures occurring in the acute phase increase the susceptibility to long-term epilepsy. Extended ICU stays and the presence of sepsis-associated encephalopathy are linked to functional disability and neuropsychological sequelae, underscoring the necessity for long-term surveillance in the comprehensive care of septic patients.

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Feature engineering of EEG applied to mental disorders: a systematic mapping study

García-Ponsoda,

García-Carrasco,

Teruel

et al. 2023

Appl Intell

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Around a third of the total population of Europe suffers from mental disorders. The use of electroencephalography (EEG) together with Machine Learning (ML) algorithms to diagnose mental disorders has recently been shown to be a prominent research area, as exposed by several reviews focused on the field. Nevertheless, previous to the application of ML algorithms, EEG data should be correctly preprocessed and prepared via Feature Engineering (FE). In fact, the choice of FE techniques can make the difference between an unusable ML model and a simple, effective model. In other words, it can be said that FE is crucial, especially when using complex, non-stationary data such as EEG. To this aim, in this paper we present a Systematic Mapping Study (SMS) focused on FE from EEG data used to identify mental disorders. Our SMS covers more than 900 papers, making it one of the most comprehensive to date, to the best of our knowledge. We gathered the mental disorder addressed, all the FE techniques used, and the Artificial Intelligence (AI) algorithm applied for classification from each paper. Our main contributions are: (i) we offer a starting point for new researchers on these topics, (ii) we extract the most used FE techniques to classify mental disorders, (iii) we show several graphical distributions of all used techniques, and (iv) we provide critical conclusions for detecting mental disorders. To provide a better overview of existing techniques, the FE process is divided into three parts: (i) signal transformation, (ii) feature extraction, and (iii) feature selection. Moreover, we classify and analyze the distribution of existing papers according to the mental disorder they treat, the FE processes used, and the ML techniques applied. As a result, we provide a valuable reference for the scientific community to identify which techniques have been proven and tested and where the gaps are located in the current state of the art. Graphical Abstract

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Use of Computed Tomography of the Head in Patients With Acute Atraumatic Altered Mental Status

Cited by 5 publications

References 41 publications

Acute encephalopathy in the ICU: a practical approach

Acute encephalopathy in the ICU: a practical approach

The spectrum of sepsis-associated encephalopathy: a clinical perspective

Feature engineering of EEG applied to mental disorders: a systematic mapping study

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