Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in Stroke Unit

Author:

Reale Giuseppe1,Iacovelli Chiara2ORCID,Rabuffetti Marco3ORCID,Manganotti Paolo4,Marinelli Lucio56ORCID,Sacco Simona7,Furlanis Giovanni4,Ajčević Miloš4ORCID,Zauli Aurelia8,Moci Marco8ORCID,Giovannini Silvia1ORCID,Crosetti Simona5,Grazzini Matteo6ORCID,Castiglia Stefano Filippo910ORCID,Podestà Matteo11,Calabresi Paolo811,Ferrarin Maurizio3ORCID,Caliandro Pietro11

Affiliation:

1. UOC Neuroriabilitazione ad Alta Intensità, Dipartimento Neuroscienze, Organi di Senso, Torace, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy

2. Department of Emergency, Anaesthesiology and Intensive Care Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy

3. IRCCS Fondazione Don Carlo Gnocchi, 20148 Milan, Italy

4. Clinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Trieste University Hospital, University of Trieste, 34149 Trieste, Italy

5. IRCCS Ospedale Policlinico San Martino, Department of Neuroscience, Division of Clinical Neurophysiology, 16132 Genova, Italy

6. Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16132 Genova, Italy

7. Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, 67100 L’Aquila, Italy

8. Department of Neuroscience, Catholic University of the Sacred Hearth, 00168 Rome, Italy

9. Department of Medical and Surgical Sciences and Biotechnologies, “Sapienza” University of Rome-Polo Pontino, 04100 Latina, Italy

10. Department of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy

11. UOC Neurologia, Dipartimento Neuroscienze, Organi di Senso, Torace, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy

Abstract

Actigraphy is a tool used to describe limb motor activity. Some actigraphic parameters, namely Motor Activity (MA) and Asymmetry Index (AR), correlate with stroke severity. However, a long-lasting actigraphic monitoring was never performed previously. We hypothesized that MA and AR can describe different clinical conditions during the evolution of the acute phase of stroke. We conducted a multicenter study and enrolled 69 stroke patients. NIHSS was assessed every hour and upper limbs’ motor activity was continuously recorded. We calculated MA and AR in the first hour after admission, after a significant clinical change (NIHSS ± 4) or at discharge. In a control group of 17 subjects, we calculated MA and AR normative values. We defined the best model to predict clinical status with multiple linear regression and identified actigraphic cut-off values to discriminate minor from major stroke (NIHSS ≥ 5) and NIHSS 5–9 from NIHSS ≥ 10. The AR cut-off value to discriminate between minor and major stroke (namely NIHSS ≥ 5) is 27% (sensitivity = 83%, specificity = 76% (AUC 0.86 p < 0.001), PPV = 89%, NPV = 42%). However, the combination of AR and MA of the non-paretic arm is the best model to predict NIHSS score (R2: 0.482, F: 54.13), discriminating minor from major stroke (sensitivity = 89%, specificity = 82%, PPV = 92%, NPV = 75%). The AR cut-off value of 53% identifies very severe stroke patients (NIHSS ≥ 10) (sensitivity = 82%, specificity = 74% (AUC 0.86 p < 0.001), PPV = 73%, NPV = 82%). Actigraphic parameters can reliably describe the overall severity of stroke patients with motor symptoms, supporting the addition of a wearable actigraphic system to the multi-parametric monitoring in stroke units.

Funder

Ministry of Health

Publisher

MDPI AG

Subject

General Medicine

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