Relative Change of Protidemia Level Predicts Intradialytic Hypotension.

Background Hemodialysis patients are at risk of intradialytic hypotension (IDH), which is associated with mortality and cardiovascular and neurological events. The use of biomarkers of volemia such as relative change in protidemia and BNP (B-natriuretic peptide) levels to predict IDH remains unknown. Methods and Results We conducted a prospective observational study, which enrolled 170 chronic hemodialysis patients in a single center from September 2015 to March 2016. BNP and the relative change of protidemia level (Δprotidemia=postdialysis protidemia-predialysis protidemia) were measured monthly over 6 months. A logistic mixed regression model was used to define the best biomarkers that predict the 30-day risk of IDH. Receiver operating characteristic analysis area under the curve was used to define the cutoff values of Δprotidemia that predict IDH A logistic mixed model reveals that Δprotidemia predicts the 30-day risk of IDH but not BNP or age; odds ratio=1.12, 95% CI 1.08-1.17), odds ratio=0.81, 95% CI (0.64; 1.07) and odds ratio =0.015 95% CI (0.99; 1.03), respectively. Adding the ultrafiltration rate did not improve the model. A receiver operating characteristic curve analysis showed that Δprotidemia of 10 g/L allowed for discrimination of the patients with IDH (area under the curve= 0.67; 95% CI 0.62-0.72, P<0.05). There was an increase in area under the curve to 0.71 (95% CI 0.63-0.76) in a subgroup of hemodialysis with BNP <300 ng/L, for a cutoff value of 11 g/L, especially for the nondiabetic patients. Conclusions Relative change in protidemia level (Δprotidemia) outperforms BNP and ultrafiltration rate as a predictor for 30-day risk of IDH. These results should be confirmed by a prospective study.

Mathematical model to predict B-type natriuretic peptide levels in haemodialysis patients.

AIM: Clinical interpretation of B-type natriuretic peptide (BNP) levels in haemodialysis (HD) patients for fluid management remains elusive. METHODS: We conducted a retrospective observational monocentric study. We built a mathematical model to predict BNP levels, using multiple linear regressions. Fifteen clinical/biological characteristics associated with BNP variation were selected. A first cohort of 150 prevalent HD (from September 2015 to March 2016) was used to build several models. The best model proposed was internally validated in an independent cohort of 75 incidents HD (from March 2016 to December 2017). RESULTS: In cohort 1, mean BNP level was 630 ± 717 ng/mL. Cardiac disease (CD - stable coronary artery disease and/or atrial fibrillation) was present in 45% of patients. The final model includes age, systolic blood pressure, albumin, CD, normo-hydrated weight (NHW) and the fluid overload (FO) assessed by bio-impedancemetry. The correlation between the measured and the predicted log-BNP was 0.567 and 0.543 in cohorts 1 and 2, respectively. Age (ß = 3.175e-2 , P < 0.001), CD (ß = 5.243e-1 , P < 0.001) and FO (ß = 1.227e-1 , P < 0.001) contribute most significantly to the BNP level, respectively, but within a certain range. We observed a logistic relationship between BNP and age between 30 and 60 years, after which this relationship was lost. BNP level was inversely correlated with NHW independently of CD. Finally, our model allows us to predict the BNP level according to the FO. CONCLUSION: We developed a mathematical model capable of predicting the BNP level in HD. Our results show the complex contribution of age, CD and FO on BNP level.