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Thresholds for significant decrease in hemodialysis access blood flow
Sunanda J Ram1, Raja Nassar, Rashid Sharaf
1Division of Nephrology and Hypertension, Department of Medicine, Louisiana State University Health Sciences Center, Shreveport, Louisiana, USA.
Abstract:
During hemodialysis access surveillance, referral for evaluation and correction of stenosis is based upon determination that a significant decrease in blood flow (Q) has occurred. However, criteria for determining when a decrease is statistically significant have not yet been established. In this study we established such criteria by analyzing Q variation with the glucose pump test (GPT). We took nine Q measurements in each of 25 patients (18 grafts, 7 fistulas) during three dialysis sessions within a 2-week period (predialysis and during hours 1 and 3). We determined thresholds that define a significant percentage decrease in Q (deltaQ) for various p values. In order to confirm the general applicability of these thresholds, we computed the average within-patient Q variation during the three sessions (computed as a coefficient of variation and referred to as short-term variation). We then determined the relative influences of biological (true) variation and analytical error on short-term variation. We found that deltaQ must be > 33% to be significant at p < 0.05, whereas the threshold is > 17% for p < 0.20. Measuring Q at uniform versus different times during the sessions did not significantly reduce these thresholds. We also found that biological variation was nearly as large as short-term Q variation, whereas analytical error contributed minimally to short-term variation. In conclusion, this study defines thresholds for a significant deltaQ that have wide application in determining access referral for evaluation and correction of stenosis. Selection of a particular threshold should consider the relative importance of avoiding thrombosis versus avoiding unnecessary procedures. If avoiding unnecessary procedures is a priority, then we recommend a threshold of > 33%. These thresholds apply to other methods of measuring Q, provided analytical error is significantly less than biological variation.
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