Dialysis patients exhibit an inverse, L- or U-shaped association between blood pressure and mortality risk, in contrast to the linear association in the general population. We prospectively studied 9333 hemodialysis patients in France, aiming to analyze associations between predialysis systolic, diastolic, and pulse pressure with all-cause mortality, cardiovascular mortality, and nonfatal cardiovascular endpoints for a median follow-up of 548 days. Blood pressure components were tested against outcomes in time-varying covariate linear and fractional polynomial Cox models. Changes throughout follow-up were analyzed with a joint model including both the time-varying covariate of sequential blood pressure and its slope over time. A U-shaped association of systolic blood pressure was found with all-cause mortality and of both systolic and diastolic blood pressure with cardiovascular mortality. There was an L-shaped association of diastolic blood pressure with all-cause mortality. The lowest hazard ratio of all-cause mortality was observed for a systolic blood pressure of 165 mm Hg, and of cardiovascular mortality for systolic/diastolic pressures of 157/90 mm Hg, substantially higher than currently recommended values for the general population. The 95% lower confidence interval was approximately 135/70 mm Hg. We found no significant correlation for either systolic, diastolic, or pulse pressure with myocardial infarction or nontraumatic amputations, but there were significant positive associations between systolic and pulse pressure with stroke (per 10-mm Hg increase: hazard ratios 1.15, 95% confidence interval 1.07 and 1.23; and 1.20, 1.11 and 1.31, respectively). Thus, whereas high pre-dialysis blood pressure is associated with stroke risk, low pre-dialysis blood pressure may be both harmful and a proxy for comorbid conditions leading to premature death.
Background Information regarding coronavirus disease 2019 (COVID-19) in haemodialysis (HD) patients is limited and early studies suggest a poor outcome. We aimed to identify clinical and biological markers associated with severe forms of COVID-19 in HD patients. Methods We conducted a prospective, observational and multicentric study. Sixty-two consecutive adult HD patients with confirmed COVID-19 from four dialysis facilities in Paris, France, from 19 March to 19 May 2020 were included. Blood tests were performed before diagnosis and at Days 7 and 14 after diagnosis. Severe forms of COVID-19 were defined as requiring oxygen therapy, admission in an intensive care unit or death. Cox regression models were used to compute adjusted hazard ratios (aHRs). Kaplan–Meier curves and log-rank tests were used for survival analysis. Results Twenty-eight patients (45%) displayed severe forms of COVID-19. Compared with non-severe forms, these patients had more fever (93% versus 56%, P < 0.01), cough (71% versus 38%, P = 0.02) and dyspnoea (43% versus 6%, P < 0.01) at diagnosis. At Day 7 post-diagnosis, neutrophil counts, neutrophil:lymphocyte (N:L) ratio, C-reactive protein, ferritin, fibrinogen and lactate dehydrogenase levels were significantly higher in severe COVID-19 patients. Multivariate analysis revealed an N:L ratio >3.7 was the major marker associated with severe forms, with an aHR of 4.28 (95% confidence interval 1.52–12.0; P = 0.006). After a median follow-up time of 48 days (range 27–61), six patients with severe forms died (10%). Conclusions HD patients are at increased risk of severe forms of COVID-19. An elevated N:L ratio at Day 7 was highly associated with the severe forms. Assessing the N:L ratio could inform clinicians for early treatment decisions.
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.
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 (β = 3.175e−2, P < 0.001), CD (β = 5.243e−1, P < 0.001) and FO (β = 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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.