Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in Stroke Unit
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 diff...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Journal of Clinical Medicine |
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| Online Access: | https://www.mdpi.com/2077-0383/12/3/1178 |
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| author | Giuseppe Reale Chiara Iacovelli Marco Rabuffetti Paolo Manganotti Lucio Marinelli Simona Sacco Giovanni Furlanis Miloš Ajčević Aurelia Zauli Marco Moci Silvia Giovannini Simona Crosetti Matteo Grazzini Stefano Filippo Castiglia Matteo Podestà Paolo Calabresi Maurizio Ferrarin Pietro Caliandro |
| author_facet | Giuseppe Reale Chiara Iacovelli Marco Rabuffetti Paolo Manganotti Lucio Marinelli Simona Sacco Giovanni Furlanis Miloš Ajčević Aurelia Zauli Marco Moci Silvia Giovannini Simona Crosetti Matteo Grazzini Stefano Filippo Castiglia Matteo Podestà Paolo Calabresi Maurizio Ferrarin Pietro Caliandro |
| author_sort | Giuseppe Reale |
| collection | DOAJ |
| description | 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 <i>p</i> < 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 (R<sup>2</sup>: 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 <i>p</i> < 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. |
| first_indexed | 2024-03-11T09:38:18Z |
| format | Article |
| id | doaj.art-c3f823a56b714fd29947ae02f9b25425 |
| institution | Directory Open Access Journal |
| issn | 2077-0383 |
| language | English |
| last_indexed | 2024-03-11T09:38:18Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Clinical Medicine |
| spelling | doaj.art-c3f823a56b714fd29947ae02f9b254252023-11-16T17:12:53ZengMDPI AGJournal of Clinical Medicine2077-03832023-02-01123117810.3390/jcm12031178Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in Stroke UnitGiuseppe Reale0Chiara Iacovelli1Marco Rabuffetti2Paolo Manganotti3Lucio Marinelli4Simona Sacco5Giovanni Furlanis6Miloš Ajčević7Aurelia Zauli8Marco Moci9Silvia Giovannini10Simona Crosetti11Matteo Grazzini12Stefano Filippo Castiglia13Matteo Podestà14Paolo Calabresi15Maurizio Ferrarin16Pietro Caliandro17UOC Neuroriabilitazione ad Alta Intensità, Dipartimento Neuroscienze, Organi di Senso, Torace, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, ItalyDepartment of Emergency, Anaesthesiology and Intensive Care Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, ItalyIRCCS Fondazione Don Carlo Gnocchi, 20148 Milan, ItalyClinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Trieste University Hospital, University of Trieste, 34149 Trieste, ItalyIRCCS Ospedale Policlinico San Martino, Department of Neuroscience, Division of Clinical Neurophysiology, 16132 Genova, ItalyDepartment of Biotechnological and Applied Clinical Sciences, University of L’Aquila, 67100 L’Aquila, ItalyClinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Trieste University Hospital, University of Trieste, 34149 Trieste, ItalyClinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Trieste University Hospital, University of Trieste, 34149 Trieste, ItalyDepartment of Neuroscience, Catholic University of the Sacred Hearth, 00168 Rome, ItalyDepartment of Neuroscience, Catholic University of the Sacred Hearth, 00168 Rome, ItalyUOC Neuroriabilitazione ad Alta Intensità, Dipartimento Neuroscienze, Organi di Senso, Torace, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, ItalyIRCCS Ospedale Policlinico San Martino, Department of Neuroscience, Division of Clinical Neurophysiology, 16132 Genova, ItalyDepartment of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16132 Genova, ItalyDepartment of Medical and Surgical Sciences and Biotechnologies, “Sapienza” University of Rome-Polo Pontino, 04100 Latina, ItalyUOC Neurologia, Dipartimento Neuroscienze, Organi di Senso, Torace, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, ItalyDepartment of Neuroscience, Catholic University of the Sacred Hearth, 00168 Rome, ItalyIRCCS Fondazione Don Carlo Gnocchi, 20148 Milan, ItalyUOC Neurologia, Dipartimento Neuroscienze, Organi di Senso, Torace, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, ItalyActigraphy 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 <i>p</i> < 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 (R<sup>2</sup>: 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 <i>p</i> < 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.https://www.mdpi.com/2077-0383/12/3/1178ischemic strokeactigraphyactigraphic parametersactigraphic sensorsacute strokestroke unit |
| spellingShingle | Giuseppe Reale Chiara Iacovelli Marco Rabuffetti Paolo Manganotti Lucio Marinelli Simona Sacco Giovanni Furlanis Miloš Ajčević Aurelia Zauli Marco Moci Silvia Giovannini Simona Crosetti Matteo Grazzini Stefano Filippo Castiglia Matteo Podestà Paolo Calabresi Maurizio Ferrarin Pietro Caliandro Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in Stroke Unit Journal of Clinical Medicine ischemic stroke actigraphy actigraphic parameters actigraphic sensors acute stroke stroke unit |
| title | Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in Stroke Unit |
| title_full | Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in Stroke Unit |
| title_fullStr | Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in Stroke Unit |
| title_full_unstemmed | Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in Stroke Unit |
| title_short | Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in Stroke Unit |
| title_sort | actigraphic sensors describe stroke severity in the acute phase implementing multi parametric monitoring in stroke unit |
| topic | ischemic stroke actigraphy actigraphic parameters actigraphic sensors acute stroke stroke unit |
| url | https://www.mdpi.com/2077-0383/12/3/1178 |
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