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Assessment of abnormal blood flow and efficacy of treatment in patients with systemic sclerosis using a newly developed microwireless laser Doppler flowmeter and arm-raising test

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Abstract:

Summary Background 

Patients with systemic sclerosis (SSc) frequently suffer from recalcitrant digital ulceration because of impaired cutaneous blood flow (CBF). A simple and accurate CBF measurement would be helpful to evaluate the disease status and efficacy of treatment in such patients. Objectives 

To examine the feasibility of a newly developed, micromachined integrated laser blood flowmeter (MILBF) for evaluation of abnormal CBF responses in patients with SSc. Methods 

CBF of finger pulp was measured in eight patients with SSc and in six healthy controls using MILBF. CBF in the steady state and the responses to the arm-raising test and cold provocation were assessed. The therapeutic efficacy of a single and an intensive prostaglandin E1 (PGE1) infusion treatment was also evaluated in some of the SSc patients. Results 

The patients with SSc showed significantly lower steady-state CBF than controls. The rate of blood flow with cold provocation and the velocity of blood flow recovery after cold provocation (VR-CP) tended to be lower in patients with SSc. Augmentation of amplitude of the digital pulse wave by arm raising (AA-AR) was observed in controls, but not in patients with SSc. We also found that VR-CP and AA-AR may be good markers for evaluating the efficacy of vasodilatory treatment. It should be noted that the examined patients did not complain of any pain and/or distress during the arm-raising test, as opposed to during cold provocation. Conclusions 

CBF assessment using MILBF and an arm-raising test is accurate, noninvasive and well tolerated and thus the combination may be a better alternative method to evaluate abnormal CBF and efficacy of treatment in patients with SSc.

Keywords: Raynaud’s phenomenon; arm-raising test; cold provocation; laser Doppler flowmeter; systemic sclerosis

Document Type: Research Article

DOI: http://dx.doi.org/10.1111/j.1365-2133.2007.08093.x

Affiliations: Department of Intelligent Machinery and Systems, Graduate School of Engineering, Graduate School of Systems Life Sciences, Microsystems and Bioengineering Lab, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan

Publication date: October 1, 2007

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