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
UOC Neuroriabilitazione ad Alta Intensità, Dipartimento Neuroscienze, Organi di Senso, Torace, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy.
Department of Emergency, Anaesthesiology and Intensive Care Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy.
J Clin Med. 2023 Feb 2;12(3):1178. doi: 10.3390/jcm12031178.
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 < 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: 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 < 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.
活动记录仪是一种用于描述肢体运动活动的工具。一些活动记录仪参数，即运动活动（MA）和不对称指数（AR），与中风严重程度相关。然而，此前从未进行过长期的活动记录仪监测。我们假设MA和AR可以描述中风急性期演变过程中的不同临床状况。我们开展了一项多中心研究，纳入了69例中风患者。每小时评估美国国立卫生研究院卒中量表（NIHSS），并持续记录上肢的运动活动。我们在入院后第一小时、出现显著临床变化（NIHSS±4）后或出院时计算MA和AR。在一个由17名受试者组成的对照组中，我们计算了MA和AR的正常值。我们用多元线性回归定义了预测临床状态的最佳模型，并确定了活动记录仪的临界值，以区分轻度与重度中风（NIHSS≥5）以及NIHSS 5 - 9与NIHSS≥10。区分轻度与重度中风（即NIHSS≥5）的AR临界值为27%（敏感性 = 83%，特异性 = 76%（AUC 0.86 < 0.001），阳性预测值 = 89%，阴性预测值 = 42%）。然而，非瘫痪侧手臂的AR和MA的组合是预测NIHSS评分的最佳模型（R：0.482，F：54.13），区分轻度与重度中风（敏感性 = 89%，特异性 = 82%，阳性预测值 = 92%，阴性预测值 = 75%）。53%的AR临界值可识别非常严重的中风患者（NIHSS≥10）（敏感性 = 82%，特异性 = 74%（AUC 0.86 < 0.001），阳性预测值 = 73%，阴性预测值 = 82%）。活动记录仪参数能够可靠地描述有运动症状的中风患者的总体严重程度，支持在卒中单元的多参数监测中增加可穿戴活动记录仪系统。
