Literature DB >> 1484273

Neonatal physiological trend monitoring by computer.

S Cunningham1, S Deere, R A Elton, N McIntosh.   

Abstract

A premature baby born up to four months early is a fragile patient dependent on intensive care. The body systems are physiologically immature and so tolerate stress badly. The tendency of these infants to rapidly deteriorate, has led us to use a cotside computer monitoring system which displays physiological trends. Information from standard neonatal monitors is accessed by individual cotside PC's linked to a central network server and Doctors terminal. Trend graphs can be easily manipulated, displaying from 7 minutes to 3 days of physiological information on a single screen. Pathology may be observed in real time as it occurs. The system has 3 main areas of use, (a) as a real time clinical aid to patient management, e.g. apnoea of the newborn; (b) as a research tool, demonstrating the effects of procedures on physiology; (c) for educating members of staff about how physiological events develop. Data is saved for the whole of each neonates intensive care stay. Assessment of staff and parent attitudes by questionnaire have been favourable.

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Mesh:

Year:  1992        PMID: 1484273     DOI: 10.1007/bf01133617

Source DB:  PubMed          Journal:  Int J Clin Monit Comput        ISSN: 0167-9945


  4 in total

1.  Assessment of pulmonary function in resolving chronic lung disease of prematurity.

Authors:  R Iles; A T Edmunds
Journal:  Arch Dis Child Fetal Neonatal Ed       Date:  1997-03       Impact factor: 5.747

2.  Computerisation and decision making in neonatal intensive care: a cognitive engineering investigation.

Authors:  E Alberdi; K Gilhooly; J Hunter; R Logie; A Lyon; N McIntosh; J Reiss
Journal:  J Clin Monit Comput       Date:  2000       Impact factor: 2.502

3.  Cyclical variation of blood pressure and heart rate in neonates.

Authors:  S Cunningham; S Deere; N McIntosh
Journal:  Arch Dis Child       Date:  1993-07       Impact factor: 3.791

4.  Association of Data Integration Technologies With Intensive Care Clinician Performance: A Systematic Review and Meta-analysis.

Authors:  Ying Ling Lin; Patricia Trbovich; Lauren Kolodzey; Cheri Nickel; Anne-Marie Guerguerian
Journal:  JAMA Netw Open       Date:  2019-05-03
  4 in total

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