This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Infection is a major cause of death during the first month of life, contributing to 13-15% of all neonatal deaths. Mortality for neonatal sepsis may be as high as 50% for infants who are not treated. The early signs of sepsis in the newborn are nonspecific; therefore, many infants will undergo diagnostic studies and the initiation of treatment before the diagnosis has been determined. Better diagnostic tools that can provide timely and accurate diagnosis of neonatal sepsis will be of tremendous value. Prominent low-frequency heart rate oscillations, which could be related to the instability of neuroautonomic control, have been often observed prior to the diagnosis of sepsis. We have also observed that decreased heart rate and blood pressure variability, indicative of a loss of interconnections ('uncoupling'), between the neuroautonomic and cardiovascular systems correlate with increased severity of illness and less favorable outcome in critically ill infants with sepsis. We are developing heart rate variability indices that allow for early detection and prediction of clinical deterioration and monitoring the response to therapeutic intervention in the treatment of sepsis.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR013622-07
Application #
7366515
Study Section
Special Emphasis Panel (ZRG1-SBIB-H (40))
Project Start
2006-03-01
Project End
2007-02-28
Budget Start
2006-03-01
Budget End
2007-02-28
Support Year
7
Fiscal Year
2006
Total Cost
$8,085
Indirect Cost
Name
Beth Israel Deaconess Medical Center
Department
Type
DUNS #
071723621
City
Boston
State
MA
Country
United States
Zip Code
02215
Clifford, Gari D; Silva, Ikaro; Moody, Benjamin et al. (2016) False alarm reduction in critical care. Physiol Meas 37:E5-E23
Burykin, Anton; Mariani, Sara; Henriques, Teresa et al. (2015) Remembrance of time series past: simple chromatic method for visualizing trends in biomedical signals. Physiol Meas 36:N95-102
Thomas, Robert Joseph; Mietus, Joseph E; Peng, Chung-Kang et al. (2014) Relationship between delta power and the electrocardiogram-derived cardiopulmonary spectrogram: possible implications for assessing the effectiveness of sleep. Sleep Med 15:125-31
Giladi, Nir; Horak, Fay B; Hausdorff, Jeffrey M (2013) Classification of gait disturbances: distinguishing between continuous and episodic changes. Mov Disord 28:1469-73
Maidan, Inbal; Plotnik, Meir; Mirelman, Anat et al. (2010) Heart rate changes during freezing of gait in patients with Parkinson's disease. Mov Disord 25:2346-54
Ivanov, Plamen Ch; Ma, Qianli D Y; Bartsch, Ronny P et al. (2009) Levels of complexity in scale-invariant neural signals. Phys Rev E Stat Nonlin Soft Matter Phys 79:041920
Herman, Talia; Inbar-Borovsky, Noit; Brozgol, Marina et al. (2009) The Dynamic Gait Index in healthy older adults: the role of stair climbing, fear of falling and gender. Gait Posture 29:237-41
Plotnik, M; Giladi, N; Hausdorff, J M (2009) Bilateral coordination of gait and Parkinson's disease: the effects of dual tasking. J Neurol Neurosurg Psychiatry 80:347-50
Hausdorff, Jeffrey M (2009) Gait dynamics in Parkinson's disease: common and distinct behavior among stride length, gait variability, and fractal-like scaling. Chaos 19:026113
Celi, Leo Anthony; Hinske, L Christian; Alterovitz, Gil et al. (2008) An artificial intelligence tool to predict fluid requirement in the intensive care unit: a proof-of-concept study. Crit Care 12:R151

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