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Details

Autor(en) / Beteiligte
Titel
Comparison of IFCC-calibrated HbA(1c) from laboratory and point of care testing systems
Ist Teil von
  • Diabetes research and clinical practice, 2014-09, Vol.105 (3), p.364-372
Ort / Verlag
Ireland
Erscheinungsjahr
2014
Quelle
MEDLINE
Beschreibungen/Notizen
  • WHO, IDF and ADA recommend HbA(1c) ≥6.5% (48 mmol/mol) for diagnosis of diabetes with pre-diabetes 6.0% (42 mmol/mol) [WHO] or 5.7% (39 mmol/mol) [ADA] to 6.4% (47 mmol/mol). We have compared HbA(1c) from several methods for research relating glycaemic markers. HbA1c was measured in EDTA blood from 128 patients with diabetes on IE HPLC analysers (Bio-Rad Variant II NU, Menarini HA8160 and Tosoh G8), point of care systems, POCT, (A1cNow+ disposable cartridges and DCA 2000(®)+ analyser), affinity chromatography (Primus Ultra2) and the IFCC secondary reference method (Menarini HA8160 calibrated using IFCC SRM protocol). Median (IQ range) on IFCC SRM was 7.5% (6.8-8.4) (58(51-68) mmol/mol) HbA(1c) with minimum 5.3%(34 mmol/mol)/maximum 11.9%(107 mmol/mol). There were positive offsets between IFCC SRM and Bio-Rad Variant II NU, mean difference (1SD), +0.33%(0.17) (+3.6(1.9) mmol/mol), r(2)=0.984, p<0.001 and Tosoh G8, +0.22%(0.20) (2.4(2.2) mmol/mol), r(2)=0.976, p<0.001 with a very small negative difference -0.04%(0.11) (-0.4(1.2) mmol/mol), r(2)=0.992, p<0.001 for Menarini HA8160. POCT methods were less precise with negative offsets for DCA 2000(®)+ analyser -0.13%(0.28) (-1.4(3.1) mmol/mol), r(2)=0.955, p<0.001 and A1cNow+ cartridges -0.70%(0.67) (-7.7(7.3) mmol/mol), r(2)=0.699, p<0.001 (n=113). Positive biases for Tosoh and Bio-Rad (compared with IFCC SRM) have been eliminated by subsequent revision of calibration. Small differences observed between IFCC-calibrated and NGSP certified methods across a wide HbA(1c) range were confirmed by quality control and external quality assurance. As these offsets affect estimates of diabetes prevalence, the analyser (and calibrator) employed should be considered when evaluating diagnostic data.

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