Page 86 - Exploring the Potential of Self-Monitoring Kidney Function After Transplantation - Céline van Lint

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Chapter 4
database). Selection of 20 samples occurred based on sampling across creatinine devices used for capillary creatinine testing (n=5 for 149010610225, 149024910321, 149025210321 and 149025910321) and capillary creatinine test results, with all levels represented.
Evaluation of StatSensor®’s performance for monitoring creatinine trends in kidney transplant patients To evaluate the suitability of the StatSensor® device for trend self-monitoring, tightly monitored patients with expected changes in levels of creatinine have to be selected. In theory, dialysis patients are an ideal population, considering the raise in creatinine during the days immediately following a dialysis session. However, their high levels of serum creatinine pose a problem, as earlier studies showed a significant negative bias of the StatSensor® at high creatinine concentrations [19, 20]. Another group of kidney patients in which changes in levels of creatinine can be expected, are recently transplanted patients. During the first days after kidney transplantation, the serum creatinine usually decreases rapidly due to the well-functioning kidney graft. Although only an increase of creatinine levels is relevant for the detection of kidney deterioration, it does not matter for the analysis whether creatinine levels rise or fall. Therefore, we can use this population for validating creatinine trend monitoring. For this analysis, 20 newly transplanted patients still being under hospital management were recruited for assessing the ability of StatSensor® for detecting changes in levels of creatinine over time (trend monitoring).
StatSensor® capillary creatinine measurements were performed twice per day (at 6.00 a.m. and 20.00 p.m.) on consecutive days following transplantation. According to routine clinical practice, serum was collected once a day for creatinine measurement by the central laboratory method. Both venous and capillary punctures were performed by professional nurses working at the transplantation ward.
Data analysis
For the analytical performance study, analytical coefficients of variation (CV) for StatSensor® were calculated from replicate determinations. Predefined quality requirements that we aimed at were based on desirable performance criteria derived from biological variation [22]. A split sample comparison was planned in order to study traceability of StatSensor® test results to NIST SRM 967. Equivalence of StatSensor® and central laboratory test results was evaluated using a two-instrument comparison procedure (EP Evaluator, Rhoads). Methods produce clinically exchangeable results if (Y- X) <total allowable error (TEa) for at least 95% of the results. In addition, reference change values