Background: Cardiac resynchronization therapy (CRT) is a promising approach to improve cardiac function in children in heart failure with cardiomyopathy. Cardiac timing measures in pediatrics are typically based on age and heart rate. However, pediatric CRT studies to date have used adult based timing cutoff values. We investigated the applicability of using these adult standards in pediatric patients with normal hearts.
Methods: We studied 88 outpatients referred for cardiac evaluation who had a normal cardiac evaluation. Subjects had 12 lead EKG and normal echocardiogram. Patients with known heart disease or abnormal rhythms were excluded. 2D echo and Doppler including color tissue Doppler imaging (TDI, Vivid 7 GE Ultrasound, Norway) were obtained. TDI was performed on three standard apical views (four chamber, two chamber, and long axis). Longitudinal dyssynchrony was determined from (1) Yu index--standard deviation of differences in timing of peak TDI velocity of all 12 basal and mid LV wall segments, adult cutoff >32 ms and (2) opposing wall difference (OWD) in timing of peak TDI velocity of 12 LV wall segments, adult cutoff >65 ms. Radial dyssynchrony was determined from differences in timing of peak radial strain between anterior-septal and posterior LV segments from speckle tracking of 2D LV views, adult cutoff >130 ms.
Results: Median age was 11.5 years; median heart rate was 74.5. Longitudinal dyssynchrony was present in 40% of normals based on Yu index, and in 43% based on OWD. No child had Radial dyssynchrony.
Conclusions: This pilot study of children with normal hearts suggests that current adult CRT dyssynchrony cutoff values are inappropriate in the pediatric population.
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http://dx.doi.org/10.1111/j.1540-8175.2010.01348.x | DOI Listing |
PLoS One
January 2025
Department of Pharmacology and Therapeutics, College of Medicine and Health Sciences, The United Arab Emirates University, Al Ain, United Arab Emirates.
Alzheimers Dement
December 2024
Department of Bioengineering, University of California, Los Angeles, CA, USA, Los Angeles, CA, USA.
Background: Alzheimer's disease (AD) is characterized by cognitive decline and increased seizure susceptibility due to brain damage and neural disruptions. This study examines the relationship between cognitive deterioration and seizure pathology in hAPP-J20 transgenic Alzheimer's mice, a model known for amyloid plaque deposition and heightened seizure activity.
Method: We observed hAPP-J20 mice aged 8 to 28 weeks using long-term wireless telemetry to assess hippocampal local field potential, sampled at 2 kHz.
Ecol Lett
December 2024
Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, California, USA.
Climate change is shifting the timing of organismal life-history events. Although consequential food-web mismatches can emerge if predators and prey shift at different rates, research on phenological shifts has traditionally focused on single trophic levels. Here, we analysed >2000 long-term, monthly time series of phytoplankton, zooplankton, and fish abundance or biomass for the San Francisco, Chesapeake, and Massachusetts bays.
View Article and Find Full Text PDFSleep Adv
December 2024
Department of Allergy, Division of Pediatric Allergy and Immunology, Ann & Robert H. Lurie Children's Hospital, Chicago, IL, USA.
Study Objectives: The complete blood count (CBC) is one of the most commonly ordered blood tests with a large range of reference values that does not consider time of day for interpretation. Our objective was to systematically review this topic to report on peak and trough timing of CBC values.
Methods: A systematic search was performed for studies evaluating any component of the CBC with at least three collections over 24 hours.
BMC Neurol
December 2024
Department of Environmental Health, Harvard T H Chan School of Public Health, Boston, MA, 02115, USA.
Parkinson's disease (PD) is a neurodegenerative disease affecting millions of people around the world. Conventional PD detection algorithms are generally based on first and second-generation artificial neural network (ANN) models which consume high energy and have complex architecture. Considering these limitations, a time-varying synaptic efficacy function based leaky-integrate and fire neuron model, called SEFRON is used for the detection of PD.
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