This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.The purpose of the study is to develop computational techniques for monitoring the health of patients in the NICU in order to allow early prediction of potential adverse outcomes. Predictions will be made based on data that are already being measured as a routine part of patient care: physiological measurements and standard laboratory tests.Our study makes use of electronic data that is already recorded in routine patient care, but that is discarded on a daily basis, necessitating prospective collection of data from patient monitors. We will record data from preterm infants with birth weights 401g to 1500g because this is a relatively uniform intensive care patient population who have frequent, well identified clinical problems that occur in a limited time period. Using data from this patient population allows us to retrospectively identify and correlate key clinical events that are routinely recorded at LPCH as part of the Survey of Morbidity and Mortality of Infants 401-1500g for the Cooperative Multicenter Network of Neonatal Intensive Care Units.Data collection studyType B, IPIRB Start date: 03/23/07Patients @Stanford: 150
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