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 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

Actigraphic Measurement of the Upper Limbs for the Prediction of Ischemic Stroke Prognosis: An Observational Study

Background: It is often challenging to formulate a reliable prognosis for patients with acute ischemic stroke. The most accepted prognostic factors may not be sufficient to predict the recovery process. In this view, describing the evolution of motor deficits over time via sensors might be useful for strengthening the prognostic model. Our aim was to assess whether an actigraphic-based parameter (Asymmetry Rate Index for the 24 h period (AR2_24 h)) obtained in the acute stroke phase could be a predictor of a 90 d prognosis. Methods: In this observational study, we recorded and analyzed the 24 h upper limb movement asymmetry of 20 consecutive patients with acute ischemic stroke during their stay in a stroke unit. We recorded the motor activity of both arms using two programmable actigraphic systems positioned on patients’ wrists. We clinically evaluated the stroke patients by NIHSS in the acute phase and then assessed them across 90 days using the modified Rankin Scale (mRS). Results: We found that the AR2_24 h parameter positively correlates with the 90 d mRS (r = 0.69, p < 0.001). Moreover, we found that an AR2_24 h > 32% predicts a poorer outcome (90 d mRS > 2), with sensitivity = 100% and specificity = 89%. Conclusions: Sensor-based parameters might provide useful information for predicting ischemic stroke prognosis in the acute phase

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 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

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 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

Risk factors for intracerebral hemorrhage in patients with atrial fibrillation on NOACs for stroke prevention

Background and Purpose: Clinical trials on stroke prevention in patients with atrial fibrillation have consistently shown clinical benefit from either warfarin or non–vitamin K antagonist oral anticoagulants (NOACs). NOAC-treated patients have consistently reported to be at lower risk for intracerebral hemorrhage (ICH) than warfarin-treated patients. The aims of this prospective, multicenter, multinational, unmatched, case-control study were (1) to investigate for risk factors that could predict ICH occurring in patients with atrial fibrillation during NOAC treatment and (2) to evaluate the role of CHA2DS2-VASc and HAS-BLED scores in the same setting. Methods: Cases were consecutive patients with atrial fibrillation who had ICH during NOAC treatment. Controls were consecutive patients with atrial fibrillation who did not have ICH during NOAC treatment. As within the CHA2DS2-VASc and HAS-BLED scores there are some risk factors in common, several multivariable logistic regression models were performed to identify independent prespecified predictors for ICH events. Results: Four hundred nineteen cases (mean age, 78.8±8.1 years) and 1526 controls (mean age, 76.0±10.3 years) were included in the study. From the different models performed, independent predictors of ICH were increasing age, concomitant use of antiplatelet agents, active malignancy, high risk of fall, hyperlipidemia, low clearance of creatinine, peripheral artery disease, and white matter changes. Low doses of NOACs (given according to label or not) and congestive heart failure were inversely associated with the risk of ICH. HAS-BLED and CHA2DS2-VASc scores performed poorly in predicting ICH with areas under the curves of 0.496 (95% CI, 0.468-0.525) and 0.530 (95% CI, 0.500-0.560), respectively. Conclusions: Several risk factors were associated to ICH in patients treated with NOACs for stroke prevention but not HAS-BLED and CHA2DS2-VASc scores

Recurrent ischemic stroke and bleeding in patients with atrial fibrillation who suffered an acute stroke while on treatment with nonvitamin K antagonist oral anticoagulants: the RENO-EXTEND study

Background: In patients with atrial fibrillation who suffered an ischemic stroke while on treatment with nonvitamin K antagonist oral anticoagulants, rates and determinants of recurrent ischemic events and major bleedings remain uncertain. Methods: This prospective multicenter observational study aimed to estimate the rates of ischemic and bleeding events and their determinants in the follow-up of consecutive patients with atrial fibrillation who suffered an acute cerebrovascular ischemic event while on nonvitamin K antagonist oral anticoagulant treatment. Afterwards, we compared the estimated risks of ischemic and bleeding events between the patients in whom anticoagulant therapy was changed to those who continued the original treatment. Results: After a mean follow-up time of 15.0±10.9 months, 192 out of 1240 patients (15.5%) had 207 ischemic or bleeding events corresponding to an annual rate of 13.4%. Among the events, 111 were ischemic strokes, 15 systemic embolisms, 24 intracranial bleedings, and 57 major extracranial bleedings. Predictive factors of recurrent ischemic events (strokes and systemic embolisms) included CHA 2 DS 2 -VASc score after the index event (odds ratio [OR], 1.2 [95% CI, 1.0–1.3] for each point increase; P =0.05) and hypertension (OR, 2.3 [95% CI, 1.0–5.1]; P =0.04). Predictive factors of bleeding events (intracranial and major extracranial bleedings) included age (OR, 1.1 [95% CI, 1.0–1.2] for each year increase; P =0.002), history of major bleeding (OR, 6.9 [95% CI, 3.4–14.2]; P =0.0001) and the concomitant administration of an antiplatelet agent (OR, 2.8 [95% CI, 1.4–5.5]; P =0.003). Rates of ischemic and bleeding events were no different in patients who changed or not changed the original nonvitamin K antagonist oral anticoagulants treatment (OR, 1.2 [95% CI, 0.8–1.7]). Conclusions: Patients suffering a stroke despite being on nonvitamin K antagonist oral anticoagulant therapy are at high risk of recurrent ischemic stroke and bleeding. In these patients, further research is needed to improve secondary prevention by investigating the mechanisms of recurrent ischemic stroke and bleeding

sj-pdf-1-eso-10.1177_23969873231186863 – Supplemental material for Anticoagulation in acute ischemic stroke patients with mechanical heart valves: To bridge or not with heparin. The ESTREM study

Supplemental material, sj-pdf-1-eso-10.1177_23969873231186863 for Anticoagulation in acute ischemic stroke patients with mechanical heart valves: To bridge or not with heparin. The ESTREM study by Maurizio Paciaroni, Valeria Caso, Michele Romoli, Cecilia Becattini, Alexander Salerno, Costanza Rapillo, Fanny Simonnet, Davide Strambo, Isabella Canavero, Marialuisa Zedde, Rosario Pascarella, Sung-Il Sohn, Simona Sacco, Raffaele Ornello, Kristian Barlinn, Daniela Schoene, Jan Rahmig, Maria Giulia Mosconi, Ilaria Leone De Magistris, Andrea Alberti, Michele Venti, Giorgio Silvestrelli, Alfonso Ciccone, Marina Padroni, Michele Laudisi, Andrea Zini, Luana Gentile, Odysseas Kargiotis, Georgios Tsivgoulis, Rossana Tassi, Francesca Guideri, Maurizio Acampa, Luca Masotti, Elisa Grifoni, Alessandro Rocco, Marina Diomedi, Theodore Karapanayiotides, Stefan T Engelter, Alexandros A Polymeris, Annaelle Zietz, Fabio Bandini, Pietro Caliandro, Giuseppe Reale, Marco Moci, Aurelia Zauli, Manuel Cappellari, Andrea Emiliani, Antonio Gasparro, Valeria Terruso, Marina Mannino, Elisa Giorli, Danilo Toni, Marco Andrighetti, Anne Falcou, Lina Palaiodimou, George Ntaios, Dimitrios Sagris, Efstathia Karagkiozi, Anastasia Adamou, Panagiotis Halvatsiotis, Yuriy Flomin, Umberto Scoditti, Antonio Genovese, Nemanja Popovic, Leonardo Pantoni, Francesco Mele, Nicola Molitierno, Piergiorgio Lochner, Alessandro Pezzini, Massimo Del Sette, Davide Sassos, Sotirios Giannopoulos, Maria Kosmidou, Evangelos Ntais, Enrico Maria Lotti, Vincenzo Mastrangelo, Alberto Chiti, Andrea Naldi, Peter Vanacker, Mario Ferrante, Vera Volodina, Michelangelo Mancuso, Nicola Giannini, Marco Baldini, Kostantinos Vadikolias, Sofia Kitmeridou, Carlo Emanuele Saggese, Tiziana Tassinari, Valentina Saia and Patrik Michel in European Stroke Journal</p