We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us

Download Mobile App




Automated Monitoring Spots Growth Disorders in Children

By HospiMedica International staff writers
Posted on 31 Mar 2015
Print article
Children's growth disorders can be detected earlier and more efficiently with the help of new electronic health record (EHR) monitoring tools, according to a new study.

Developed by Antti Saari, MD, of the University of Eastern Finland (Joensuu, Finland), the tools include up-to-date growth reference curves, evidence-based screening cut-off values for abnormal growth, and automated growth monitoring, all based on EHRs. The study defined new growth, height, and BMI reference curves for Finnish children by making use of auxological [auxanological] data from approximately 72,000 children over a period of 60 years. The revised growth reference curves helped enhance the detection of growth disorders causing growth failure.

The study was used to determine evidence-based cut-off limits for attained height, weight, and growth rate, and validated these against two target conditions: Turner syndrome and Celiac disease. The findings showed that the screening precision was excellent for Turner syndrome, and good for Celiac disease. The new monitoring methods could also help in the early detection of growth disorders by automating growth monitoring methods developed in the study, using EHRs and growth monitoring software.

Among the findings was that healthy children born between 1983 and 2008 were growing taller than children in the former Finnish growth reference, which consisted of charts for children born between 1956 and 1973. The mean adult height of Finnish boys has increased from 178.9 cm to 180.7 cm (+1.8 cm), and the mean adult height of Finnish girls from 165.6 cm to 167.5 cm (+1.9 cm). The study also suggested that if Finland was to use the multiethnic World Health Organization (WHO; Geneva, Switzerland) growth charts instead of the updated national ones, many disorders affecting growth could go undetected.

“The study showed that computer-assisted growth monitoring clearly enhanced monitoring precision in primary health care when combined with automated growth consultation services used in special health care,” concluded Dr. Saari, who presented the study as his doctoral thesis. “The automated strategy improved the detection precision by approximately six-fold and often also allowed for a considerably earlier detection of disorders affecting growth than the traditional manual method.”

Related Links:

University of Eastern Finland
World Health Organization


Gold Member
Disposable Protective Suit For Medical Use
Disposable Protective Suit For Medical Use
Gold Member
STI Test
Vivalytic Sexually Transmitted Infection (STI) Array
Silver Member
Wireless Mobile ECG Recorder
NR-1207-3/NR-1207-E
New
Endoscope Tracking Software
T-DOC Endo

Print article

Channels

Surgical Techniques

view channel
Image: NTT and Olympus have begun the world\'s first joint demonstration experiment of a cloud endoscopy system (Photo courtesy of Olympus)

Cloud Endoscopy System Enables Real-Time Image Processing on the Cloud

Endoscopes, which are flexible tubes inserted into the body's natural openings for internal examination and biopsy collection, are becoming increasingly vital in medical diagnostics. Their minimal invasiveness... Read more

Patient Care

view channel
Image: The newly-launched solution can transform operating room scheduling and boost utilization rates (Photo courtesy of Fujitsu)

Surgical Capacity Optimization Solution Helps Hospitals Boost OR Utilization

An innovative solution has the capability to transform surgical capacity utilization by targeting the root cause of surgical block time inefficiencies. Fujitsu Limited’s (Tokyo, Japan) Surgical Capacity... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The PATHFAST hs-cTnI-II high-sensitivity troponin assay has been developed for the PATHFAST Biomarker Analyzer (Photo courtesy of Polymedco)

POC Myocardial Infarction Test Delivers Results in 17 Minutes

Chest pain is the second leading cause of emergency department (ED) visits by adults in the United States, generating over 7 million visits annually. In the event of a suspected heart attack, physicians... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.