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Intradialytic hypotension (IDH) is a significant complication in haemodialysis (HD) patients, affecting cardiovascular stability and treatment outcomes. Antihypertensive medications, while crucial for blood pressure control, can exacerbate IDH, necessitating careful drug selection and management. This review highlights the differential effects at the HD population level of drug classes such as beta and alpha-beta blockers, angiotensin-converting enzyme inhibitors (ACEIs), angiotensin II antagonists, diuretics and calcium antagonists. Beta and alpha-beta blockers are linked to a higher risk of IDH due to their impact on heart rate and myocardial contractility, which can impair cardiovascular reflexes during dialysis. ACEIs and angiotensin II antagonists may increase the risk of hypotension by reducing vascular resistance. Diuretics can worsen volume depletion, especially when combined with ultrafiltration. Conversely, calcium antagonists have been associated with a lower risk of IDH in low-power clinical studies. Target trials represent an opportunity to generate high-quality evidence in the absence of randomized controlled trial (RCT) data. To fill the knowledge gap, this review discusses a target trial emulation study by Zoccali et al. that provides insights into the comparative risks of antihypertensive drugs using observational data. This study underscores the need for individualized treatment plans and highlights the importance of further research, particularly RCTs, to validate findings and explore long-term cardiovascular outcomes. This review aims to guide clinicians in optimizing antihypertensive therapy for HD patients, balancing effective blood pressure control with minimizing IDH risk.

RESULTSHigher variability in fluid overload significantly increased mortality risk. A 1 % increase in the SD of the FO/ECW ratio was linked to a 5.3 % increase in the hazard ratio for mortality (HR: 1.053, 95 % CI: 1.045-1.062, p < 0.001). Patients in the highest quartile of fluid overload variability had a 46 % higher risk of death than those in the lowest quartile (HR: 1.46, 95 % CI: 1.28-1.67, p < 0.001). These associations remained consistent in patients who survived beyond the first and second years.CONCLUSIONSFluid overload variability significantly predicts mortality in KF patients, independent of average fluid overload levels, variability in BP pressure, and other potential confounders. Comprehensive fluid management strategies addressing both the level and variability of fluid status may improve clinical outcomes. Randomized controlled trials are necessary to confirm our hypothesis-generating findings.BACKGROUNDThe prognosis for kidney failure (KF) patients on long-term hemodialysis is poor, with fluid overload being a significant modifiable risk factor for mortality. Previous studies have focused on static measurements of fluid status, but the impact of long-term fluid fluctuations on clinical outcomes has not been thoroughly investigated.METHODSWe studied a cohort of 9,178 incident KF patients at Fresenius NephroCare dialysis centers across seven countries in Europe and the Middle East. Fluid status was assessed using bioimpedance spectroscopy, providing precise measurements of the fluid overload/extracellular water (FO/ECW) ratio. Fluid overload variability was calculated as the standard deviation (SD) of the FO/ECW ratio over the first three years. Time-dependent Cox regression models, adjusted for 47 covariates, evaluated the association between fluid overload variability and one-year mortality. We also analyzed mortality risk by quartiles of fluid overload variability.

RESULTSFour distinct fluid overload trajectories were identified. Patients in the highest trajectory group (8.5% of the cohort) had more frequent background cardiovascular complications, lower BMI and serum albumin, and their adjusted mortality risk was 2.20 times higher than the lowest trajectory. There was a dose-response relationship between trajectories and mortality. The incidence rate of death increased with the degree of fluid overload, from 8.6 deaths per 100 person-years in the lowest trajectory to 18.6 in the highest.CONCLUSIONSThis longitudinal study highlights the significant risk of chronic fluid overload in hemodialysis patients. Latent trajectory analysis provides novel information into the dynamic nature of fluid overload and its impact on mortality in the hemodialysis population.METHODS AND PATIENTSThis longitudinal study included 9332 incident hemodialysis patients from the EuCliD database, treated in Fresenius Medical Care NephroCare dialysis centers across seven countries between January 2016 and December 2019, with follow-up until May 2023. Fluid overload was assessed using bioimpedance spectroscopy, and patients were grouped based on fluid overload trajectories using group-based trajectory modeling. Cox regression models, adjusted for potential confounders, were used to investigate the relationship between trajectory groups and mortality.BACKGROUNDFluid overload remains critical in managing patients with end-stage kidney disease. However, there is limited empirical understanding of fluid overload's impact on mortality. This study analyzes fluid overload trajectories and their association with mortality in hemodialysis patients.

RESULTSCalcium channel blocker (CCB) use was associated with an IDH incidence rate of 7.4 events per person-year (95% confidence interval [CI], 6.2 to 8.6). Compared with CCB use, use of β and α–β blockers was strongly associated with a higher likelihood of IDH (odds ratio [OR] [95% CI, 2.27; 1.50 to 3.43]). The use of angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers (OR [95% CI, 1.71; 1.14 to 2.57]) and diuretics (OR [95% CI, 1.52; 1.07 to 2.16]) were also associated with a higher likelihood of IDH compared with CCB use.KEY POINTSAntihypertensive medications are often used by hemodialysis patients, and intradialytic hypotension is a common complication in these patients. The study emulates a randomized clinical trial comparing antihypertensive drug treatment for the risk of hemodialysis hypotension in 4072 incident patients. Compared with calcium antagonists, β and α–β blockers, angiotensin converting enzyme inhibitors or angiotensin II antagonists, and diuretics may increase the risk of hemodialysis hypotension.CONCLUSIONSThe study suggests that using β and α–β blockers, angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers, and diuretics may increase the risk of IDH in hemodialysis patients compared with CCB use.BACKGROUNDAntihypertensive medications are often prescribed to manage hypertension in hemodialysis patients, and intradialytic hypotension (IDH) is a common complication in these patients. We investigated the risk of IDH in incident hemodialysis patients who initiated treatment with antihypertensive drugs in monotherapy.METHODSThe study was conducted as an emulation of a randomized clinical trial in 4072 incident hemodialysis patients who started antihypertensive drug treatment between January 2016 and December 2019. The primary outcome was the occurrence of IDH during hemodialysis sessions. The generalized estimating equation analysis was adjusted by inverse probability treatment weighting.

RESULTSThe final dataset included 1,249,813 dialysis sessions, and the incidence rate of intradialytic hypotension was 10.07% (95% CI 10.02-10.13). Our models retained good discrimination (AUC around 0.8) and a suitable calibration yielding to the selection of three classification thresholds identifying four distinct risk groups. Variables providing the most significant impact on risk estimates were blood pressure dynamics and other metrics mirroring hemodynamic instability over time.CONCLUSIONSRecurrent symptomatic intradialytic hypotension could be reliably and accurately predicted using routinely collected data during dialysis treatment and standard clinical care. Clinical application of these prediction models would allow for personalized risk-based interventions for preventing and managing intradialytic hypotension.BACKGROUNDIntradialytic hypotension remains one of the most recurrent complications of dialysis sessions. Inadequate management can lead to adverse outcomes, highlighting the need to develop personalized approaches for the prevention of intradialytic hypotension. Here, we sought to develop and validate two AI-based risk models predicting the occurrence of symptomatic intradialytic hypotension at different time points.METHODSThe models were built using the XGBoost algorithm and they predict the occurrence of intradialytic hypotension in the next dialysis session and in the next month. The initial dataset, obtained from routinely collected data in the EuCliD® Database, was split to perform model derivation, training and validation. Model performance was evaluated by concordance statistic and calibration charts; the importance of features was assessed with the Shapley Additive Explanation (SHAP) methodology.