Feasibility of a Multiple-Choice Mini Mental State Examination for Chronically Critically Ill Patients

Miguélez, M.; Merlani, Paolo; Gigon, Fabienne; Verdon, Mélanie; Annoni, Jean‐Marie; Ricou, Bara

doi:10.1097/ccm.0000000000000342

Cited by 6 publications

(2 citation statements)

References 33 publications

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“…Therefore, neurocognitive assessment should be an integral part of care: as soon as patients are conscious (Glasgow coma scale above 12), they are assessed weekly with a modified Mini Mental State Examination (MMSE). This tool has been developed by our team to be applicable to intubated patients, with the collaboration of a neuropsychiatrist, and has been validated [25]. The MMSE is used to anticipate, detect and monitor potential neurocognitive disorders.…”

Section: Cognitive Disorders and Psychological Traumamentioning

confidence: 99%

The chronic critical illness: a new disease in intensive care

Desarmenien¹,

Blanchard-Courtois²,

Ricou³

2016

Swiss Med Wkly

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Advances in intensive care medicine have created a new disease called the chronic critical illness. While a significant proportion of severely ill patients who twenty years ago would have died survive the acute phase, they remain heavily dependent on intensive care for a prolonged period of time. These patients, who can be called "Patient Long Séjour" in French (PLS) or Prolonged Length of Stay patients in English, develop specific health issues that are still poorly recognised. They require special care, which differs from treatments that are given during the acute phase of their illness. A multidisciplinary team dedicated to ensuring their management and follow-up acquired a wide range of knowledge and expertise about these PLSs. Many new monitoring tools and diverse human approaches were implemented to ensure that care was targeted to these patients' needs. This multimodal care management aims to optimise the patients' and their families' quality of life during and following intensive care, whilst maintaining the motivation of the healthcare team of the unit. The purpose of this article is to present new management techniques to hospital and ambulatory caregivers, physicians and nurses, who may be taking care of such patients.

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Section: Cognitive Disorders and Psychological Traumamentioning

confidence: 99%

The chronic critical illness: a new disease in intensive care

Desarmenien¹,

Blanchard-Courtois²,

Ricou³

2016

Swiss Med Wkly

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“…The Research Triangle Institute (RTI) International presented a report and de ned CCI based on the requirements of the Centers for Medical Care & Medical Services (CMS)[7].Whether it is patients, family members, or medical staff, several problems remain to be solved in the communication and treatment decision-making of CCI patients [8,9]. Many patients live in pain and despair [10][11][12], are unable to participate in their own treatment decisions due to disease restrictions [13,14], and, thereby, are forced to accept their families' decisions. However, family decision-makers often have unrealistic expectations of outcomes [15].…”

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confidence: 99%

Development and clinical empirical validation of the chronic critical illness prognosis prediction model

Zhao

Wáng

et al. 2024

THC

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BACKGROUND: The evolution of critical care medicine and nursing has aided and enabled the rescue of a large number of patients from numerous life-threatening diseases. However, in many cases, patient health may not be quickly restored, and the long-term prognosis may not be optimistic. OBJECTIVES: In this study, we aimed to develop and validate a prediction model for accurate, precise, and objective identification of the severity of chronic critical illness (CCI) in patients. METHODS: We used a retrospective case-control and prospective cohort study with no interventions. Patients diagnosed with CCI admitted to the ICU of a large metropolitan public hospital were selected. In the case-control study, 344 patients (case: 172; control:172) were enrolled to develop the prognosis prediction model of chronic critical illness (PPCCI Model); 88 patients (case:44; control: 44) in a prospective cohort study, served as the validation cohort. The discrimination of the model was measured using the area under the curve (AUC) of the receiver operating characteristic curve (ROC). RESULTS: Age, prolonged mechanical ventilation (PMV), sepsis or other severe infections, Glasgow Coma Scale (GCS), mean artery pressure (MAP), heart rate (HR), respiratory rate (RR), oxygenation index (OI), and active bleeding were the nine predictors included in the model. In both cohorts, the PPCCI model outperformed the Acute Physiology And Chronic Health Evaluation II (APACHE II), Modified Early Warning Score (MEWS), and Sequential Organ Failure Assessment (SOFA) in identifying deceased patients with CCI (development cohort: AUC, 0.934; 95%CI, 0.908–0.960; validation cohort: AUC, 0.965; 95% CI, 0.931–0.999). CONCLUSION: The PPCCI model can provide ICU medical staff with a standardized measurement tool for assessing the condition of patients with CCI, enabling them to allocate ward monitoring resources rationally and communicate with family members.

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