BACKGROUND: Acute ischaemic stroke (AIS) triggers both systemic and neurovascular inflammation, influencing poststroke recovery. In smokers with AIS, inflammation might be further upregulated, increasing ischaemia/reperfusion injury. Here, the predictive value of leucocyte and adhesion molecules levels on poststroke outcomes was investigated. MATERIALS AND METHODS: A total of 89 patients with AIS (n = 30 smokers and n = 59 nonsmokers) were recruited and evaluated 1, 7 and 90 days after the onset to assess stroke severity by the National Institute of Health Stroke Scale (NIHSS) score as well as clinical recovery at 90 days by the modified Rankin Scale (mRS). Lesion volume was assessed by noncontrast computed tomography. Haematological parameters, blood chemistry and soluble adhesion molecules were measured. RESULTS: Smokers experienced a more severe stroke and at a younger age with respect to nonsmokers, moreover, they had higher circulating levels of monocytes, neutrophils and soluble adhesion molecules. Baseline monocytes positively correlated with stroke severity and disability across all time points in the overall cohort. No correlation was shown between adhesion molecules and poststroke outcomes. A monocyte count >0·63 × 109 /L predicted worse stroke severity (defined as NIHSS ≥5) at day 90 independently of age, hypertension, thrombolysis and active smoking in the overall cohort. Similarly, a monocyte count >0·64 × 109 /L predicted poor neurological recovery at day 90 (defined as mRS > 2). CONCLUSIONS: Smoker had more severe AIS and higher leucocytes and adhesion molecule levels. In the overall cohort, monocyte count was an independent predictor of worse poststroke outcome. Although larger trials are needed, monocyte count might be a cheap prognostic parameter in AIS.

Monocyte count at onset predicts poststroke outcomes during a 90-day follow-up / Liberale, Luca; Montecucco, Fabrizio; Bonaventura, Aldo; Casetta, Ilaria; Seraceni, Silva; Trentini, Alessandro; Padroni, Marina; Dallegri, Franco; Fainardi, Enrico; Carbone, Federico. - In: EUROPEAN JOURNAL OF CLINICAL INVESTIGATION. - ISSN 0014-2972. - ELETTRONICO. - 47:(2017), pp. 702-710. [10.1111/eci.12795]

Monocyte count at onset predicts poststroke outcomes during a 90-day follow-up

Fainardi, Enrico;
2017

Abstract

BACKGROUND: Acute ischaemic stroke (AIS) triggers both systemic and neurovascular inflammation, influencing poststroke recovery. In smokers with AIS, inflammation might be further upregulated, increasing ischaemia/reperfusion injury. Here, the predictive value of leucocyte and adhesion molecules levels on poststroke outcomes was investigated. MATERIALS AND METHODS: A total of 89 patients with AIS (n = 30 smokers and n = 59 nonsmokers) were recruited and evaluated 1, 7 and 90 days after the onset to assess stroke severity by the National Institute of Health Stroke Scale (NIHSS) score as well as clinical recovery at 90 days by the modified Rankin Scale (mRS). Lesion volume was assessed by noncontrast computed tomography. Haematological parameters, blood chemistry and soluble adhesion molecules were measured. RESULTS: Smokers experienced a more severe stroke and at a younger age with respect to nonsmokers, moreover, they had higher circulating levels of monocytes, neutrophils and soluble adhesion molecules. Baseline monocytes positively correlated with stroke severity and disability across all time points in the overall cohort. No correlation was shown between adhesion molecules and poststroke outcomes. A monocyte count >0·63 × 109 /L predicted worse stroke severity (defined as NIHSS ≥5) at day 90 independently of age, hypertension, thrombolysis and active smoking in the overall cohort. Similarly, a monocyte count >0·64 × 109 /L predicted poor neurological recovery at day 90 (defined as mRS > 2). CONCLUSIONS: Smoker had more severe AIS and higher leucocytes and adhesion molecule levels. In the overall cohort, monocyte count was an independent predictor of worse poststroke outcome. Although larger trials are needed, monocyte count might be a cheap prognostic parameter in AIS.
2017
47
702
710
Liberale, Luca; Montecucco, Fabrizio; Bonaventura, Aldo; Casetta, Ilaria; Seraceni, Silva; Trentini, Alessandro; Padroni, Marina; Dallegri, Franco; Fainardi, Enrico; Carbone, Federico
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1102957
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