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Predicting Episodes of Hypovigilance in Intensive Care Units Using Routine Physiological Parameters and Artificial Intelligence: Derivation Study

Predicting Episodes of Hypovigilance in Intensive Care Units Using Routine Physiological Parameters and Artificial Intelligence: Derivation Study

As defined by van Schie et al [12], “vigilance is the ability to remain aware of relevant and unpredictable changes in an individual’s surrounding environment, regardless of whether such changes actually occur.” Van Schie also described delirium as two-dimensional. First, the level of alertness required to be vigilant, and second, the extent to which vigilance may increase or decrease over time [12].

Raphaëlle Giguère, Victor Niaussat, Monia Noël-Hunter, William Witteman, Tanya S Paul, Alexandre Marois, Philippe Després, Simon Duchesne, Patrick M Archambault

JMIR AI 2025;4:e60885

Improving Prediction of Falls and Cognitive Impairment in Parkinson Disease: Protocol for a Decentralized Observational Study

Improving Prediction of Falls and Cognitive Impairment in Parkinson Disease: Protocol for a Decentralized Observational Study

Fox Insight is an online, observational research study sponsored by the Michael J Fox Foundation for Parkinson’s Research [47]. Every 3 months, participants complete a set of questionnaires, including the Patient Global Impression–Change, PD Patient Report of Problems [36], PD questionnaire-8 [48], and the Non-Motor Symptoms Questionnaire [49]. The Penn Parkinson’s Daily Activities Questionnaire [50], EQ-5 D [51], and MDS-UPDRS part II are completed on a biannual basis.

Audrey Hoyt, Casey Dorney, Peggy Auinger, Kathryn Murphy, Michelle Porto, Katrina Schmier, Renee Wilson, James C Beck, Stephanie Benvengo, Kevin Biglan, E Ray Dorsey, Alberto J Espay, Eric A Macklin, Mariana HG Monje, Dan Novak, David Oakes, Larsson Omberg, Michael A Schwarzschild, Solveig K Sieberts, Tanya Simuni, Caroline M Tanner, Daniel Weintraub, Ruth B Schneider

JMIR Res Protoc 2025;14:e71955