Literature DB >> 7903588

Detection of microemboli in patients with artificial heart valves using transcranial Doppler: preliminary observations.

J J Rams1, D A Davis, D M Lolley, M P Berger, M Spencer.   

Abstract

Embolic events, particularly involving the central nervous system, represent one of the important hazards associated with the implantation of mechanical valves. The use of the transcranial Doppler to insonate the middle cerebral artery has allowed us to detect microembolic events in some of these patients. Patients with long term implantation and frequent microemboli appear to be more prone to transient ischemic attacks or stroke. Evaluation of 26 patients with mechanical valves revealed 14 with detectable microemboli, four of whom experienced central nervous system symptoms. Modifications in the medical or anticoagulant regimes have not been successful in decreasing or eliminating these microemboli. As the transcranial Doppler is a non-invasive means of quantifying these microemboli, it may become a useful tool in identifying those patients in need of a new type of antithrombotic regimen, or even a valve replacement. Transcranial Doppler could thus provide advance warning before a catastrophic cerebral embolism occurs.

Entities:  

Mesh:

Year:  1993        PMID: 7903588

Source DB:  PubMed          Journal:  J Heart Valve Dis        ISSN: 0966-8519


  4 in total

1.  Effects of myocardial contractility on microemboli production by mechanical heart valves in a bovine model.

Authors:  G Deklunder; J L Lecroart; J L Conger; D Lapeyre; I Gregoric; H Rose; D Tamez; O H Frazier
Journal:  Tex Heart Inst J       Date:  2000

2.  Microembolic signals and diffusion-weighted MR imaging abnormalities in acute ischemic stroke.

Authors:  K Kimura; K Minematsu; M Koga; R Arakawa; M Yasaka; H Yamagami; K Nagatsuka; H Naritomi; T Yamaguchi
Journal:  AJNR Am J Neuroradiol       Date:  2001 Jun-Jul       Impact factor: 3.825

3.  Microembolization from a carotid mural thrombus detected by transcranial Doppler.

Authors:  M Solaro; C Roberti; A Spalloni; G Mancini; M Beccia; M Rasura
Journal:  Ital J Neurol Sci       Date:  1996-02

4.  An Artificial Neural Network classification approach for use the ultrasound in physiotherapy.

Authors:  Hakan Işik; Sema Arslan
Journal:  J Med Syst       Date:  2010-01-06       Impact factor: 4.460

  4 in total

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