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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...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9918210/ https://www.ncbi.nlm.nih.gov/pubmed/36769826 http://dx.doi.org/10.3390/jcm12031178 |
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author | Reale, Giuseppe Iacovelli, Chiara Rabuffetti, Marco Manganotti, Paolo Marinelli, Lucio Sacco, Simona Furlanis, Giovanni Ajčević, Miloš Zauli, Aurelia Moci, Marco Giovannini, Silvia Crosetti, Simona Grazzini, Matteo Castiglia, Stefano Filippo Podestà, Matteo Calabresi, Paolo Ferrarin, Maurizio Caliandro, Pietro |
author_facet | Reale, Giuseppe Iacovelli, Chiara Rabuffetti, Marco Manganotti, Paolo Marinelli, Lucio Sacco, Simona Furlanis, Giovanni Ajčević, Miloš Zauli, Aurelia Moci, Marco Giovannini, Silvia Crosetti, Simona Grazzini, Matteo Castiglia, Stefano Filippo Podestà, Matteo Calabresi, Paolo Ferrarin, Maurizio Caliandro, Pietro |
author_sort | Reale, Giuseppe |
collection | PubMed |
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 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 (R(2): 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. |
format | Online Article Text |
id | pubmed-9918210 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99182102023-02-11 Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in Stroke Unit Reale, Giuseppe Iacovelli, Chiara Rabuffetti, Marco Manganotti, Paolo Marinelli, Lucio Sacco, Simona Furlanis, Giovanni Ajčević, Miloš Zauli, Aurelia Moci, Marco Giovannini, Silvia Crosetti, Simona Grazzini, Matteo Castiglia, Stefano Filippo Podestà, Matteo Calabresi, Paolo Ferrarin, Maurizio Caliandro, Pietro J Clin Med Article 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 (R(2): 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. MDPI 2023-02-02 /pmc/articles/PMC9918210/ /pubmed/36769826 http://dx.doi.org/10.3390/jcm12031178 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Reale, Giuseppe Iacovelli, Chiara Rabuffetti, Marco Manganotti, Paolo Marinelli, Lucio Sacco, Simona Furlanis, Giovanni Ajčević, Miloš Zauli, Aurelia Moci, Marco Giovannini, Silvia Crosetti, Simona Grazzini, Matteo Castiglia, Stefano Filippo Podestà, Matteo Calabresi, Paolo Ferrarin, Maurizio Caliandro, Pietro Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in 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 | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9918210/ https://www.ncbi.nlm.nih.gov/pubmed/36769826 http://dx.doi.org/10.3390/jcm12031178 |
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