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RESULTSThere were 16,796 incident PD patients analyzed. Age, BMI, gender, PD modality, Kt/V and CrCl as well as serum phosphate varied significantly across the different cohorts, but >70% had residual renal function. For most cohorts, both CrCltotal and urea Kt/V associated negatively with serum phosphorus levels, and log-likelihood ratio tests demonstrate that models including CrCltotal have more predictive information than those including only urea Kt/V for the largest cohorts. Models including CrCltotal increase information predicting longitudinal serum phosphate levels irrespective of baseline urea Kt/V, age, use of phosphorus binder, and gender.CONCLUSIONSCrCl was not more accurate in predicting serum phosphate than urea Kt/V, but its inclusion in multivariable models predicting serum phosphate added accuracy. In conclusion, both creatinine clearance and Kt/V are associated with phosphate levels, and using both biomarkers, instead of just one, may better assist in the optimization of serum phosphate levels.BACKGROUNDHyperphosphatemia is associated with poor outcome and is still very common in peritoneal dialysis (PD) patients. Since peritoneal phosphate clearance is closer to peritoneal creatinine clearance than urea clearance, we hypothesized that weekly creatinine clearance (CrCl) could be a better marker of serum phosphate in PD.METHODSIn a retrospective observational study, data from adult PD patients were collected across five institutions in North and South America: LATAM, RRI, Mount Sinai Hospital, Hospital Civil de Guadalajara, and the BRAZPD cohort. All centers analyzed routinely available laboratory data, with exclusions for missing data on serum phosphate, CrCl, or urea Kt/V. A unified statistical protocol was employed across centers. Linear mixed-effect models examined associations between longitudinal serum phosphate levels, CrCl, and Kt/V. Adjustments were made for age, gender, and baseline phosphate binder usage. Mixed-effects meta-analysis determined the pooled effect size of CrCl and Kt/V on serum phosphate trajectories, adjusted for confounders.

RESULTSThe intervention group showed an improved median percentage of hemoglobin measurements within target at 47% (interquartile range, 39–58), with a 10% point median difference between the two groups (95% confidence interval, 3 to 16; P = 0.008). The odds ratio of being within the hemoglobin target in the standard-of-care group compared with the group receiving the personalized ESA recommendations was 0.68 (95% confidence interval, 0.51 to 0.92). The variability of hemoglobin levels decreased in the intervention group, with the percentage of patients experiencing fluctuating hemoglobin levels being 45% versus 82% in the standard-of-care group. ESA usage was reduced by approximately 25% in the intervention group.KEY POINTSWe conducted a randomized controlled pilot trial in patients on hemodialysis using a physiology-based individualized anemia therapy assistance software. Patients in the group receiving erythropoiesis-stimulating agent dose recommendations from the novel software showed improvement in hemoglobin stability and erythropoiesis-stimulating agent utilization.CONCLUSIONSOur results demonstrated an improved hemoglobin target attainment and variability by using personalized ESA recommendations using the physiology-based anemia therapy assistance software.CLINICAL TRIAL REGISTRATION NUMBER:NCT04360902.BACKGROUNDAnemia is common among patients on hemodialysis. Maintaining stable hemoglobin levels within predefined target levels can be challenging, particularly in patients with frequent hemoglobin fluctuations both above and below the desired targets. We conducted a multicenter, randomized controlled trial comparing our anemia therapy assistance software against a standard population-based anemia treatment protocol. We hypothesized that personalized dosing of erythropoiesis-stimulating agents (ESAs) improves hemoglobin target attainment.METHODSNinety-six patients undergoing hemodialysis and receiving methoxy polyethylene glycol-epoetin beta were randomized 1:1 to the intervention group (personalized ESA dose recommendations computed by the software) or the standard-of-care group for 26 weeks. The therapy assistance software combined a physiology-based mathematical model and a model predictive controller designed to stabilize hemoglobin levels within a tight target range (10–11 g/dl). The primary outcome measure was the percentage of hemoglobin measurements within the target. Secondary outcome measures included measures of hemoglobin variability and ESA utilization.

RESULTSIn the studied 396,358 patients, the average ultrafiltration rate in ml/h was related to postdialysis weight (W) in kg: 3W+330. Ultrafiltration rates associated with 20% or 40% higher weight-specific mortality risk were 3W+500 and 3W+630 ml/h, respectively, and were 70 ml/h higher in men than in women. Nineteen percent or 7.5% of patients exceeded ultrafiltration rates associated with a 20% or 40% higher mortality risk, respectively. Low ultrafiltration rates were associated with subsequent weight loss. Ultrafiltration rates associated with a given mortality risk were lower in high-body weight older patients and higher in patients on dialysis for more than 3 years.CONCLUSIONSUltrafiltration rates associated with various levels of higher mortality risk depend on body weight, but not in a 1:1 ratio, and are different in men versus women, in high-body weight older patients, and in high-vintage patients.BACKGROUNDWe hypothesized that the association of ultrafiltration rate with mortality in hemodialysis patients was differentially affected by weight and sex and sought to derive a sex- and weight-indexed ultrafiltration rate measure that captures the differential effects of these parameters on the association of ultrafiltration rate with mortality.METHODSData were analyzed from the US Fresenius Kidney Care (FKC) database for 1 year after patient entry into a FKC dialysis unit (baseline) and over 2 years of follow-up for patients receiving thrice-weekly in-center hemodialysis. To investigate the joint effect of baseline-year ultrafiltration rate and postdialysis weight on survival, we fit Cox proportional hazards models using bivariate tensor product spline functions and constructed contour plots of weight-specific mortality hazard ratios over the entire range of ultrafiltration rate values and postdialysis weights (W).

Our bones are constantly being renewed in a fine-tuned cycle of destruction and formation that helps keep them healthy and strong. However, this process can become imbalanced and lead to osteoporosis, where the bones are weakened and have a high risk of fracturing. This is particularly common post-menopause, with one in three women over the age of 50 experiencing a broken bone due to osteoporosis. There are several drug types available for treating osteoporosis, which work in different ways to strengthen bones. These drugs can be taken individually or combined, meaning that a huge number of drug combinations and treatment strategies are theoretically possible. However, it is not practical to test the effectiveness of all of these options in human trials. This could mean that patients are not getting the maximum potential benefit from the drugs available. Jörg et al. developed a mathematical model to predict how different osteoporosis drugs affect the process of bone renewal in the human body. The model could then simulate the effect of changing the order in which the therapies were taken, which showed that the sequence had a considerable impact on the efficacy of the treatment. This occurs because different drugs can interact with each other, leading to an improved outcome when they work in the right order. These results suggest that people with osteoporosis may benefit from altered treatment schemes without changing the type or amount of medication taken. The model could suggest new treatment combinations that reduce the risk of bone fracture, potentially even developing personalised plans for individual patients based on routine clinical measurements in response to different drugs.

RESULTSIn the studied 2542 patients, UFR not scaled to body weight was strongly associated with MHR, whereas postdialysis weight was inversely associated with MHR. MHR crossed 1.5 when unscaled UFR exceeded 1000 ml/h, and this relationship was largely independent of postdialysis weight in the range of 80 to 140 kg. A UFR warning level associated with a lower MHR of 1.3 would be 900 ml/h, whereas the UFR associated with an MHR of 1.0 was patient-size dependent. The MHR when exceeding a UFR threshold of 13 ml/h per kg was dependent on patient weight (MHR = 1.20, 1.45, and >2.0 for a 60, 80, and 100 kg patient, respectively).CONCLUSIONUFR thresholds based on unscaled UFR give more uniform risk levels for patients of different sizes than thresholds based on UFR/kg.INTRODUCTIONOne proposed threshold ultrafiltration rate (UFR) of concern in hemodialysis patients is 13 ml/h per kg. We evaluated associations among UFR, postdialysis weight, and mortality to determine whether exceeding such a threshold would result in similar levels of risk for patients of different body weights.METHODSData were analyzed in this retrospective cohort study for 1 year following dialysis initiation (baseline) and over 2 years of follow-up in incident patients receiving thrice-weekly in-center hemodialysis. Patient-level UFR was averaged over the baseline period. To investigate the joint effect of UFR and postdialysis weight on survival, we fit Cox proportional hazards models using bivariate tensor product spline functions, adjusting for sex, race, age, diabetes, and predialysis serum albumin, phosphorus, and systolic blood pressure (BP). We constructed contour plots of mortality hazard ratios (MHRs) over the entire range of UFR values and postdialysis weights.