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      Serum Potassium Levels and Its Variability in Incident Peritoneal Dialysis Patients: Associations with Mortality

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          Abnormal serum potassium is associated with an increased risk of mortality in dialysis patients. However, the impacts of serum potassium levels on short- and long-term mortality and association of potassium variability with death in peritoneal dialysis (PD) patients are uncertain.


          We examined mortality-predictability of serum potassium at baseline and its variability in PD patients treated in our center January 2006 through December 2010 with follow-up through December 2012. The hazard ratios (HRs) were used to assess the relationship between baseline potassium levels and short-term (≤1 year) as well as long-term (>1 year) survival. Variability of serum potassium was defined as the coefficient of variation of serum potassium (CVSP) during the first year of PD.


          A total of 886 incident PD patients were enrolled, with 248 patients (27.9%) presented hypokalemia (serum potassium <3.5 mEq/L). During a median follow-up of 31 months (range: 0.5–81.0 months), adjusted all-cause mortality hazard ratio (HR) and 95% confidence interval (CI) for baseline serum potassium of <3.0, 3.0 to <3.5, 3.5 to <4.0, 4.5 to <5.0, and ≥5.0 mEq/L, compared with 4.0 to <4.5 (reference), were 1.79 (1.02–3.14), 1.15 (0.72–1.86), 1.31 (0.82–2.08), 1.33 (0.71–2.48), 1.28 (0.53–3.10), respectively. The increased risk of lower potassium with mortality was evident during the first year of follow-up, but vanished thereafter. Adjusted all-cause mortality HR for CVSP increments of 7.5% to <12.0%; 12.0% to <16.7% and ≥16.7%, compared with <7.5% (reference), were 1.35 (0.67–2.71), 2.00 (1.05–3.83) and 2.18 (1.18–4.05), respectively. Similar association was found between serum potassium levels and its variability and cardiovascular mortality.


          A lower serum potassium level was associated with all-cause and cardiovascular mortality during the first year of follow-up in incident PD patients. In addition, higher variability of serum potassium levels conferred an increased risk of death in this population.

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          Most cited references 31

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          Serum and dialysate potassium concentrations and survival in hemodialysis patients.

          Controlling serum potassium is an important goal in maintenance hemodialysis patients. We examined the achievement of potassium balance through hemodialysis treatments and the associated fluctuations in serum potassium. A 3-yr (July 2001 to June 2004) cohort of 81,013 maintenance hemodialysis patients from all DaVita dialysis clinics across the United States were studied. Nine quarterly-averaged serum potassium groups ( or = 6.3 mEq/L and seven increments in-between) and four dialysate potassium concentration groups were created in each of the 12 calendar quarters. The death risk associated with predialysis potassium level and dialysate potassium concentration was examined using unadjusted, case-mix adjusted, and malnutrition-inflammation-adjusted time-dependent survival models. Serum potassium correlated with nutritional markers. Serum potassium between 4.6 and 5.3 mEq/L was associated with the greatest survival, whereas potassium or = 5.6 mEq/L was associated with increased mortality. The death risk of serum potassium > or = 5.6 mEq/L remained consistent after adjustments. Higher dialysate potassium concentration was associated with increased mortality in hyperkalemic patients with predialysis serum potassium > or = 5.0 mEq/L. A predialysis serum potassium of 4.6 to 5.3 mEq/L is associated with the greatest survival in maintenance hemodialysis patients. Hyperkalemic patients who undergo maintenance hemodialysis against lower dialysate bath may have better survival. Limitations of observational studies including confounding by indication should be considered when interpreting these results.
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            Cardiac valve calcification as an important predictor for all-cause mortality and cardiovascular mortality in long-term peritoneal dialysis patients: a prospective study.

            Calcification complications are frequent among long-term dialysis patients. However, the prognostic implication of cardiac valve calcification in this population is not known. This study aimed to determine if cardiac valve calcification predicts mortality in long-term dialysis patients. Baseline echocardiography was performed in 192 patients (mean +/- SD age, 55 +/- 12 yr) on continuous ambulatory peritoneal dialysis (mean +/- SD duration of dialysis, 39 +/- 31 mo) to screen for calcification of the aortic valve, mitral valve, or both. Valvular calcification was present in 62 patients. During the mean follow-up of 17.9 mo (range, 0.6 to 33.9 mo), 46 deaths (50% of cardiovascular causes) were observed. Overall 1-yr survival was 70% and 93% for patients with and without valvular calcification (P < 0.0001, log-rank test). Cardiovascular mortality was 22% and 3% for patients with and without valvular calcification (P < 0.0001). Multivariable Cox regression analysis showed that cardiac valve calcification was predictive of an increased all-cause mortality (hazard ratio [HR], 2.50; 95% CI, 1.32 to 4.76; P = 0.005) and cardiovascular death (HR 5.39; 95% CI, 2.16 to 13.48; P = 0.0003) independent of age, male gender, dialysis duration, C-reactive protein, diabetes, and atherosclerotic vascular disease. Eighty-nine percent of patients with both valvular calcification and atherosclerotic vascular disease, 23% of patients with valvular calcification only, 21% of patients with atherosclerotic vascular disease only, and 13% of patients with neither complication died at 1-yr (P < 0.0005). The cardiovascular death rate was 85% for patients with both complications, 13% for patients with valvular calcification only, 14% for patients with atherosclerotic vascular disease only, and 5% for those with neither complication (P < 0.0005). The number of calcified valves was associated with all-cause mortality (P < 0.0005) and cardiovascular death (P < 0.0005). One-year all-cause mortality was 57% for patients with both aortic and mitral valves calcified, 40% for those with either valve calcified, and 15% for those with neither valve calcified. In conclusion, cardiac valve calcification is a powerful predictor for mortality and cardiovascular deaths in long-term dialysis patients. Valvular calcification by itself has similar prognostic importance as the presence of atherosclerotic vascular disease. Its coexistence with other atherosclerotic complications indicates more severe disease and has the worst outcome.
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              A strategy for modelling the effect of a continuous covariate in medicine and epidemiology.

               P Royston (2000)
              Low-dimensional parametric models are well understood, straightforward to communicate to other workers, have very smooth curves and may easily be checked for consistency with background scientific knowledge or understanding. They should therefore be ideal tools with which to represent smooth relationships between a continuous predictor and an outcome variable in medicine and epidemiology. Unfortunately, a seriously restricted set of such models is used routinely in practical data analysis - typically, linear, quadratic or occasionally cubic polynomials, or sometimes a power or logarithmic transformation of a covariate. Since their flexibility is limited, it is not surprising that the fit of such models is often poor. Royston and Altman's recent work on fractional polynomials has extended the range of available functions. It is clearly crucial that the chosen final model fits the data well. Achieving a good fit with minimal restriction on the functional form has been the motivation behind the major recent research effort on non-parametric curve-fitting techniques. Here I propose that one such model, a (possibly over-fitted) cubic smoothing spline, may be used to define a suitable reference curve against which the fit of a parametric model may be checked. I suggest a significance test for the purpose and examine its type I error and power in a small simulation study. Several families of parametric models, including some with sigmoid curves, are considered. Their suitability in fitting regression relationships found in several real data sets is investigated. With all the example data sets, a simple parametric model can be found which fits the data approximately as well as a cubic smoothing spline, but without the latter's tendency towards artefacts in the fitted curve. Copyright 2000 John Wiley & Sons, Ltd.

                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                27 January 2014
                : 9
                : 1
                Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health of China, Guangzhou, China
                University of Sao Paulo Medical School, Brazil
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: HPM XQY ZHZ QDX. Performed the experiments: QDX FHX LPX HYL SRC XYL. Analyzed the data: QDX FHX LF. Contributed reagents/materials/analysis tools: XQY HPM. Wrote the paper: QDX HPM.


                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Pages: 10
                This work was supported by grants from the National Key Technology Research and Development Program of the Ministry of Science and Technology of China (No. 2011BAI10B05), the National Science Fund for Distinguished Young Scholars of China (No. 30925019), 5010 Clinical Program of Sun Yat-sen University (No. 2007007) and the Guangzhou Committee of Science and Technology of China (No. 2010U1-E00831). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Research Article
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                Clinical Research Design
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                Clinical Chemistry
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                Clinical Chemistry
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                Preventive Medicine



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