Literature DB >> 18257461

Comparative performance of two point-of-care analysers for lipid testing.

Mark D S Shephard1, Beryl C Mazzachi, Anne K Shephard.   

Abstract

The aim of this study was to compare the analytical performance of the Cholestech LDX and CardioChek PA lipid point-of-care devices to a CDC-certified laboratory. Inter-assay imprecision (n=10) for blood samples from 2 patients with different lipid profiles was 3.0% for total cholesterol, 2.6% for triglyceride, 5.2% for HDL cholesterol and 6.2% for calculated LDL cholesterol on the Cholestech, and 4.4% for total cholesterol, 4.8% for triglyceride, 7.0% for HDL cholesterol and 7.4% for calculated LDL cholesterol on the Cardiochek. In a patient comparison study (n=100), correlation coefficients (r) between the POCT and laboratory methods were greater than 0,90 for all tests for the Cholestech and greater than 0.84 for all tests for the Cardiochek. The mean difference (bias) between the results obtained on the Cholestech LDX and the laboratory method was not statistically significant; however the mean difference between the CardioChek and the laboratory method was statistically significant for total, HDL and LDL cholesterol (one way analysis of variance with Scheffe post-hoc test). The Cholestech LDX met the NCEP goal for total error for all analytes except LDL cholesterol. The CardioChek PA system met the NCEP total error goal for triglyceride but not the other lipid analytes. We conclude that the Cholestech LDX device is a suitable POCT device for cardiovascular risk assessment in the primary care setting, while the CardioChek device requires more study and refinement.

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 18257461

Source DB:  PubMed          Journal:  Clin Lab        ISSN: 1433-6510            Impact factor:   1.138


  18 in total

1.  Point-of-care testing for the analysis of lipid panels: primary care diagnostic technology update.

Authors:  Annette Plüddemann; Matthew Thompson; Christopher P Price; Jane Wolstenholme; Carl Heneghan
Journal:  Br J Gen Pract       Date:  2012-03       Impact factor: 5.386

2.  Associations of leisure screen time with cardiometabolic biomarkers in college-aged adults.

Authors:  Chantal A Vella; Katrina Taylor; Megan C Nelson
Journal:  J Behav Med       Date:  2020-05-26

3.  Being macrosomic at birth is an independent predictor of overweight in children: results from the IDEFICS study.

Authors:  Sonia Sparano; Wolfgang Ahrens; Stefaan De Henauw; Staffan Marild; Denes Molnar; Luis A Moreno; Marc Suling; Michael Tornaritis; Toomas Veidebaum; Alfonso Siani; Paola Russo
Journal:  Matern Child Health J       Date:  2013-10

4.  On-Site Classification of Pansteatitis in Mozambique Tilapia (Oreochromis mossambicus) using a Portable Lipid-Based Analyzer.

Authors:  John A Bowden; Stephen E Somerville; Theresa M Cantu; Matthew P Guillette; Hannes Botha; Ashley S P Boggs; Wilmien Luus-Powell; Louis J Guillette
Journal:  Anal Methods       Date:  2016-05-16       Impact factor: 2.896

5.  Blood lipids among young children in Europe: results from the European IDEFICS study.

Authors:  S De Henauw; N Michels; K Vyncke; A Hebestreit; P Russo; T Intemann; J Peplies; A Fraterman; G Eiben; M de Lorgeril; M Tornaritis; D Molnar; T Veidebaum; W Ahrens; L A Moreno
Journal:  Int J Obes (Lond)       Date:  2014-09       Impact factor: 5.095

6.  Identification of cardiometabolic risk among collegiate football players.

Authors:  Gary B Wilkerson; J Todd Bullard; David W Bartal
Journal:  J Athl Train       Date:  2010 Jan-Feb       Impact factor: 2.860

7.  Cardiovascular disease risk factors are elevated in urban minority children enrolled in head start.

Authors:  Kathryn Brogan; Cynthia Danford; Yulyu Yeh; Kai-Lin Catherine Jen
Journal:  Child Obes       Date:  2014-05-14       Impact factor: 2.992

8.  High-sensitivity C-reactive protein is a predictive factor of adiposity in children: results of the identification and prevention of dietary- and lifestyle-induced health effects in children and infants (IDEFICS) study.

Authors:  Annunziata Nappo; Licia Iacoviello; Arno Fraterman; Esther M Gonzalez-Gil; Charis Hadjigeorgiou; Staffan Marild; Denes Molnar; Luis A Moreno; Jenny Peplies; Isabel Sioen; Toomas Veidebaum; Alfonso Siani; Paola Russo
Journal:  J Am Heart Assoc       Date:  2013-06-06       Impact factor: 5.501

9.  Obesogenic Behaviors and Depressive Symptoms' Influence on Cardiometabolic Risk Factors in American Indian Children.

Authors:  Michelle Dennison; Susan B Sisson; Lancer Stephens; Amanda S Morris; Christopher Aston; Carol Dionne; Allen Knehans; R D Dickens
Journal:  J Allied Health       Date:  2019

10.  Metabolic syndrome among students attending a historically black college: prevalence and gender differences.

Authors:  Avinash M Topè; Phyllis F Rogers
Journal:  Diabetol Metab Syndr       Date:  2013-01-12       Impact factor: 3.320

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.