One- and 2-Year Mortality Prediction for Patients Starting Chronic Dialysis

Mortality Risk Prediction Models for People With Kidney Failure: A Systematic Review

Importance

People with kidney failure have a high risk of death and poor quality of life. Mortality risk prediction models may help them decide which form of treatment they prefer.

Objective

To systematically review the quality of existing mortality prediction models for people with kidney failure and assess whether they can be applied in clinical practice.

Evidence Review

MEDLINE, Embase, and the Cochrane Library were searched for studies published between January 1, 2004, and September 30, 2024. Studies were included if they created or evaluated mortality prediction models for people who developed kidney failure, whether treated or not treated with kidney replacement with hemodialysis or peritoneal dialysis. Studies including exclusively kidney transplant recipients were excluded. Two reviewers independently extracted data and graded each study at low, high, or unclear risk of bias and applicability using recommended checklists and tools. Reviewers used the Prediction Model Risk of Bias Assessment Tool and followed prespecified questions about study design, prediction framework, modeling algorithm, performance evaluation, and model deployment. Analyses were completed between January and October 2024.

Findings

A total of 7184 unique abstracts were screened for eligibility. Of these, 77 were selected for full-text review, and 50 studies that created all-cause mortality prediction models were included, with 2 963 157 total participants, who had a median (range) age of 64 (52-81) years. Studies had a median (range) proportion of women of 42% (2%-54%). Included studies were at high risk of bias due to inadequate selection of study population (27 studies [54%]), shortcomings in methods of measurement of predictors (15 [30%]) and outcome (12 [24%]), and flaws in the analysis strategy (50 [100%]). Concerns for applicability were also high, as study participants (31 [62%]), predictors (17 [34%]), and outcome (5 [10%]) did not fit the intended target clinical setting. One study (2%) reported decision curve analysis, and 15 (30%) included a tool to enhance model usability.

Conclusions and Relevance

According to this systematic review of 50 studies, published mortality prediction models were at high risk of bias and had applicability concerns for clinical practice. New mortality prediction models are needed to inform treatment decisions in people with kidney failure.

The Lack of a Standardized Definition of Chronic Dialysis Treatment in German Statutory Health Insurance Claims Data—Effects on Estimated Incidence and Mortality

BACKGROUND

Chronic kidney failure (CKF) is often treated with dialysis, which is invasive and costly and carries major medical risks. The existing studies of patients with CKF requiring dialysis that are based on claims data from German statutory health insurance (SHI) carriers employ varying definitions of this entity, with unclear consequences for the resulting statistical estimates.

METHODS

We carried out a cohort study on four random samples, each consisting of 62 200 persons aged 70 or above, from among the insurees of the SHI AOK Nordost, with one sample for each of the years 2012, 2014, 2016, and 2018. The prevalence, incidence, mortality, and direct health care costs of CKF requiring dialysis were estimated and compared on the basis of four different definitions from literature and a new definition developed by the authors in reference to billing data.

RESULTS

The different definitions led to variation in 12-month prevalences (range: 0.33-0.61%) and 6-month incidences (0.058-0.100%). The percentage of patients with prior acute kidney injury (AKI) ranged from 27.6% to 61.8%. Among incident patients, three-month survival ranged from 70.2% to 88.1%, and six-month survival from 60.5% to 81.3%. In CKF patients without prior AKI, the survival curves differed less across definitions (80.2-91.8% at three months, 70.7-84.4% at six months). The monthly health care costs ranged from €6010 to €9606, with marked variability across definitions in the costs of inpatient and outpatient care.

CONCLUSION

The lack of a standardized definition of CKF requiring dialysis in German SHI claims data leads to variability in the estimated case numbers, mortality, and health care costs. These differences are most probably in part due to the variable inclusion of inpatients who received short-term dialysis after AKI.

Data-driven, two-stage machine learning algorithm-based prediction scheme for assessing 1-year and 3-year mortality risk in chronic hemodialysis patients

Life expectancy is likely to be substantially reduced in patients undergoing chronic hemodialysis (CHD). However, machine learning (ML) may predict the risk factors of mortality in patients with CHD by analyzing the serum laboratory data from regular dialysis routine. This study aimed to establish the mortality prediction model of CHD patients by adopting two-stage ML algorithm-based prediction scheme, combined with importance of risk factors identified by different ML methods. This is a retrospective, observational cohort study. We included 800 patients undergoing CHD between December 2006 and December 2012 in Shin-Kong Wu Ho-Su Memorial Hospital. This study analyzed laboratory data including 44 indicators. We used five ML methods, namely, logistic regression (LGR), decision tree (DT), random forest (RF), gradient boosting (GB), and eXtreme gradient boosting (XGB), to develop a two-stage ML algorithm-based prediction scheme and evaluate the important factors that predict CHD mortality. LGR served as a bench method. Regarding the validation and testing datasets from 1- and 3-year mortality prediction model, the RF had better accuracy and area-under-curve results among the five different ML methods. The stepwise RF model, which incorporates the most important factors of CHD mortality risk based on the average rank from DT, RF, GB, and XGB, exhibited superior predictive performance compared to LGR in predicting mortality among CHD patients over both 1-year and 3-year periods. We had developed a two-stage ML algorithm-based prediction scheme by implementing the stepwise RF that demonstrated satisfactory performance in predicting mortality in patients with CHD over 1- and 3-year periods. The findings of this study can offer valuable information to nephrologists, enhancing patient-centered decision-making and increasing awareness about risky laboratory data, particularly for patients with a high short-term mortality risk.

Patient-focused outcomes after initiation of dialysis for ESRD: mortality, hospitalization and functional impairment

BACKGROUND

Outcome data regarding clinically relevant endpoints after starting dialysis for end-stage renal disease (ESRD) are sparse, and early events after starting dialysis are particularly underestimated. The aim of this study was to describe patient-focused outcomes in ESRD patients starting from first dialysis.

METHODS

The data basis for this retrospective observational study were anonymized healthcare data from Germany's largest statutory health insurer. We identified ESRD patients who initiated dialysis in 2017. Deaths, hospitalizations and occurrence of functional impairment within 4 years after starting dialysis were recorded starting from first treatment. Hazard ratios in dialysis patients compared with an age- and sex-matched reference population without dialysis were generated, stratified by age.

RESULTS

The dialysis cohort included 10 328 ESRD patients who started dialysis in 2017. First dialysis was performed in-hospital for 7324 patients (70.9%), and 865 of these died during the same hospitalization. One-year mortality for ESRD patients initiating dialysis was 33.8%. Functional impairment occurred in 27.1% of patients, while 82.8% of patients required hospitalization within 1 year. Hazard ratios of dialysis patients compared with the reference population for mortality, functional impairment and hospitalization at 1-year were 8.6, 4.3 and 6.2. Dialysis patients <50 years were disproportionately affected, with >40-fold increased risk of adverse events compared with their peers.

CONCLUSIONS

The emergence of morbidity and mortality after starting dialysis for ESRD is significant, especially in younger patients. Patients have a right to be informed about the prognosis associated with their condition.

Predicting outcomes in chronic kidney disease: needs and preferences of patients and nephrologists

INTRODUCTION

Guidelines on chronic kidney disease (CKD) recommend that nephrologists use clinical prediction models (CPMs). However, the actual use of CPMs seems limited in clinical practice. We conducted a national survey study to evaluate: 1) to what extent CPMs are used in Dutch CKD practice, 2) patients' and nephrologists' needs and preferences regarding predictions in CKD, and 3) determinants that may affect the adoption of CPMs in clinical practice.

METHODS

We conducted semi-structured interviews with CKD patients to inform the development of two online surveys; one for CKD patients and one for nephrologists. Survey participants were recruited through the Dutch Kidney Patient Association and the Dutch Federation of Nephrology.

RESULTS

A total of 126 patients and 50 nephrologists responded to the surveys. Most patients (89%) reported they had discussed predictions with their nephrologists. They most frequently discussed predictions regarded CKD progression: when they were expected to need kidney replacement therapy (KRT) (n = 81), and how rapidly their kidney function was expected to decline (n = 68). Half of the nephrologists (52%) reported to use CPMs in clinical practice, in particular CPMs predicting the risk of cardiovascular disease. Almost all nephrologists (98%) reported discussing expected CKD trajectories with their patients; even those that did not use CPMs (42%). The majority of patients (61%) and nephrologists (84%) chose a CPM predicting when patients would need KRT in the future as the most important prediction. However, a small portion of patients indicated they did not want to be informed on predictions regarding CKD progression at all (10-15%). Nephrologists not using CPMs (42%) reported they did not know CPMs they could use or felt that they had insufficient knowledge regarding CPMs. According to the nephrologists, the most important determinants for the adoption of CPMs in clinical practice were: 1) understandability for patients, 2) integration as standard of care, 3) the clinical relevance.

CONCLUSION

Even though the majority of patients in Dutch CKD practice reported discussing predictions with their nephrologists, CPMs are infrequently used for this purpose. Both patients and nephrologists considered a CPM predicting CKD progression most important to discuss. Increasing awareness about existing CPMs that predict CKD progression may result in increased adoption in clinical practice. When using CPMs regarding CKD progression, nephrologists should ask whether patients want to hear predictions beforehand, since individual patients' preferences vary.

Predicting mortality after start of long-term dialysis-International validation of one- and two-year prediction models

BACKGROUND

Mortality prediction is critical on long-term kidney replacement therapy (KRT), both for individual treatment decisions and resource planning. Many mortality prediction models already exist, but as a major shortcoming most of them have only been validated internally. This leaves reliability and usefulness of these models in other KRT populations, especially foreign, unknown. Previously two models were constructed for one- and two-year mortality prediction of Finnish patients starting long-term dialysis. These models are here internationally validated in KRT populations of the Dutch NECOSAD Study and the UK Renal Registry (UKRR).

METHODS

We validated the models externally on 2051 NECOSAD patients and on two UKRR patient cohorts (5328 and 45493 patients). We performed multiple imputation for missing data, used c-statistic (AUC) to assess discrimination, and evaluated calibration by plotting average estimated probability of death against observed risk of death.

RESULTS

Both prediction models performed well in the NECOSAD population (AUC 0.79 for the one-year model and 0.78 for the two-year model). In the UKRR populations, performance was slightly weaker (AUCs: 0.73 and 0.74). These are to be compared to the earlier external validation in a Finnish cohort (AUCs: 0.77 and 0.74). In all tested populations, our models performed better for PD than HD patients. Level of death risk (i.e., calibration) was well estimated by the one-year model in all cohorts but was somewhat overestimated by the two-year model.

CONCLUSIONS

Our prediction models showed good performance not only in the Finnish but in foreign KRT populations as well. Compared to the other existing models, the current models have equal or better performance and fewer variables, thus increasing models' usability. The models are easily accessible on the web. These results encourage implementing the models into clinical decision-making widely among European KRT populations.

A dynamic nomogram for predicting survival among diabetic patients on maintenance hemodialysis

INTRODUCTION

Among maintenance hemodialysis (MHD) patients, ones with diabetes mellitus (DM) are known to have the worst outcome.

METHODS

A total of 263 MHD patients were included, a dynamic nomogram was established based on multivariable Cox regression analysis.

RESULTS

The median overall survival (OS) time was 46 months. The 1-, 3-, and 5-year OS rates were 90.9%, 70.5% and 53.9%, respectively. The multivariable Cox regression analysis indicated that DM duration, cardiovascular complication, baseline values before starting MHD for estimated glomerular filtration rate and serum phosphate were independent risk factors. The C-index of the dynamic nomogram was 0.745 and the calibration curves showed optimal agreement between the model prediction and actual observation for predicting survival probabilities.

CONCLUSIONS

Our study was the first to establish dynamic nomogram among diabetic MHD patients, the fast and convenient online tool can be used for individual risk estimation at the point of prognosis prediction.

Shared decision-making in advanced kidney disease: a scoping review

OBJECTIVES

To provide a comprehensive overview of interventions that support shared decision-making (SDM) for treatment modality decisions in advanced kidney disease (AKD). To provide summarised information on their content, use and reported results. To provide an overview of interventions currently under development or investigation.

DESIGN

The JBI methodology for scoping reviews was followed. This review conforms to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) checklist.

DATA SOURCES

MEDLINE, Embase, Web of Science, Cochrane Library, Emcare, PsycINFO, PROSPERO and Academic Search Premier for peer-reviewed literature. Other online databases (eg, clinicaltrials.gov, OpenGrey) for grey literature.

ELIGIBILITY FOR INCLUSION

Records in English with a study population of patients >18 years of age with an estimated glomerular filtration rate <30 mL/min/1.73 m2. Records had to be on the subject of SDM, or explicitly mention that the intervention reported on could be used to support SDM for treatment modality decisions in AKD.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently screened and selected records for data extraction. Interventions were categorised as prognostic tools (PTs), educational programmes (EPs), patient decision aids (PtDAs) or multicomponent initiatives (MIs). Interventions were subsequently categorised based on the decisions they were developed to support.

RESULTS

One hundred forty-five interventions were identified in a total of 158 included records: 52 PTs, 51 EPs, 29 PtDAs and 13 MIs. Sixteen (n=16, 11%) were novel interventions currently under investigation. Forty-six (n=46, 35.7%) were reported to have been implemented in clinical practice. Sixty-seven (n=67, 51.9%) were evaluated for their effects on outcomes in the intended users.

CONCLUSION

There is no conclusive evidence on which intervention is the most efficacious in supporting SDM for treatment modality decisions in AKD. There is a lot of variation in selected outcomes, and the body of evidence is largely based on observational research. In addition, the effects of these interventions on SDM are under-reported.

Iron Deficiency is Associated With Platelet Count Elevation in Patients With Dialysis-dependent Chronic Kidney Disease

OBJECTIVE

Iron deficiency is common in patients with end-stage renal disease (ESRD). Platelet count changes may reflect iron status, but the relationship between platelet count and iron indices is unclear in patients with ESRD.

METHODS

We conducted a retrospective study in 1,167 patients with ESRD from 2012 to 2017 in West China Hospital. Baseline data were used to analyze the relationship between the platelet count and iron indices. Patients were followed up for 3 years.

RESULTS

Patients with iron deficiency (both absolute and functional) had a higher platelet count than those without iron deficiency (174 ± 61 × 10⁹/L vs. 153 ± 58 × 10⁹/L, P < .001). Receiver operating characteristic analysis showed a weak predictive power of platelet count on absolute iron deficiency (area under curve 0.620; cutoff value > 137 × 10⁹/L, sensitivity 76%, specificity 43%) and functional iron deficiency (area under curve 0.540; cutoff value > 124 × 10⁹/L, sensitivity 77%, specificity 32%). Platelet count was negatively correlated with ferritin (Spearman's rho [ρ] -0.1547, P < .001), transferrin saturation (ρ = -0.1895, P < .001), and serum iron (ρ = -0.1466, P < .001). The abovementioned correlations remained significant in multivariate regression (β -0.7285, 95% confidence interval [CI] -1.0757 to -0.3814; β -.00347, 95% CI -0.0520 to -0.0174; β -0.0097, 95% CI -0.0159 to -0.0035, respectively). In unadjusted and adjusted Cox regression models, neither baseline platelet count nor relative thrombocytosis was associated with 3-year mortality.

CONCLUSION

There was a weak but significant platelet count elevation in patients with ESRD and with iron deficiency.

KEY WORDS

end-stage renal disease; iron deficiency; iron supplement; mortality; platelet count.

Predicting 3-month and 1-year mortality for patients initiating dialysis: a population-based cohort study

BACKGROUND

Despite the continual improvements in dialysis treatments, mortality in end-stage kidney disease (ESKD) remains high. Many mortality prediction models are available, but most of them are not precise enough to be used in the clinical practice. We aimed to develop and validate two prediction models for 3-month and 1-year patient mortality after dialysis initiation in our population.

METHODS

Using population-based data of insurance claims in Taiwan, we included more than 210,000 patients who initiated dialysis between January 1, 2006, and June 30, 2015. We developed two prognostic models, which included 9 and 11 variables, respectively (including age, sex, myocardial infarction, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, peptic ulcer disease, malignancy, moderate to severe liver disease, and first dialysis in intensive care unit).

RESULTS

The models showed adequate discrimination (C-statistics were 0.80 and 0.82 for 3-month and 1-year mortality, respectively) and good calibration. In both our models, the first dialysis in the intensive care unit and moderate-to-severe liver disease were the strongest risk factors for mortality.

CONCLUSION

The prediction models developed in our population had good predictive ability for short-term mortality in patients initiating dialysis in Taiwan and could help in decision-making regarding dialysis initiation, at least in our setting, supporting a patient-centered approach to care.

Is White Blood Cell Count Associated With Mortality in Peritoneal Dialysis Patients?: A Retrospective Single-Center Analysis

Objective

White blood cell (WBC) count was used as a predictor in researches since it is a prognostic indicator and a substantial predictor of the development of cardiovascular disease (CVD). There have been very few reports looking at the association between WBC count and overall mortality in peritoneal dialysis (PD) patients. We intended to explore if the baseline total leukocyte count is linked to all-cause mortality, considering the association for linearity in PD patients.

Material and methods

The study comprised 204 incident PD patients who began treatment at the Nephrology Department of Health Sciences University, Kayseri Medical Faculty, Kayseri City Hospital between January 2009 and December 2017. The research period ended in January 2018. The link between baseline WBC count and all-cause mortality was studied using Cox proportional hazards models.

Results

The average age of the patients was 46.75 (8.49) years, and 48.5% were male. Diabetes and hypertension were prevalent in 59.8% and 76% of the population, respectively. The average WBC count was 9.37 (2.70) × 10³/µL. The mortality risk increased by 23% for every one-unit increase in the crude model. The hazard of death in the fully corrected model was 1.12 [95% confidence interval (CI): 1.02-1.23, p = 0.015]. In the models with WBC count stratified by tertiles, the mortality hazard of patients in tertile 2 was 2.38 (95% CI: 1.24-4.58, p = 0.009) and of patients in tertile 3 in the fully adjusted model was 2.64 (95% CI: 1.30-5.33, p = 0.007), compared with patients in tertile 1.

Conclusion

The initial WBC count may have a long-term impact on patient survival. Individuals with higher basal values or even an elevation in follow-up should therefore be strictly controlled, and all preventative measures should be made to lower the risk level.

Nierenersatzverfahren bei Hochbetagten

Hochbetagte haben an der Hämodialyse eine 1‑Jahres-Mortalität, die im Zusammenhang mit Komorbiditäten und einem Katheter als Dialysezugang 30 % übersteigt. Metaanalysen zeigen aber, dass frühzeitige Vorbereitung und individuelle Verfahrensauswahl die Morbidität und Mortalität auch im hohen Lebensalter entscheidend bessern. Mit zunehmendem Alter und Gebrechlichkeit verschieben sich dabei die Behandlungsziele weg von der Verlängerung der Lebensdauer auf die Verbesserung der Lebensqualität. Damit kann die Präferenz von Heimdialyseverfahren, auch als assistierte Peritonealdialyse, ebenso Bedeutung erringen wie die fachnephrologische Behandlung ohne Nierenersatzverfahren mit palliativem Therapieziel. Im höheren Lebensalter bestimmen zunehmend Komorbiditäten, kognitive Einschränkungen, Gebrechlichkeit und die Gesamtprognose das sinnvolle Vorgehen. Bereits bei der Anlage von Gefäßzugängen ergeben sich hinsichtlich Anastomosenort und Anlagezeitpunkt bei Hochbetagten andere Entscheidungskriterien. Empfehlungen zu Dialysedauer und -frequenz folgen der Lebensqualität mit inkrementellen und am Ende des Lebens auch dekrementellen Therapieregimen. Die demographische Entwicklung stellt die Nephrologie mit einer Zunahme älterer Patienten vor besondere Herausforderungen. Frühzeitige Aufklärung über alle Nierenersatzverfahren und die Festlegung individueller Therapieziele können bei sorgfältiger Auswahl von Dialysemodalität und -intensität auch bei Hochbetagten entscheidend zur Verbesserung der Prognose und insbesondere der Lebensqualität beitragen.

Effect of comorbidities on survival in patients >80 years of age at onset of renal replacement therapy: data from the ERA-EDTA Registry

BACKGROUND

The number of elderly patients on renal replacement therapy (RRT) is increasing. The survival and quality of life of these patients may be lower if they have multiple comorbidities at the onset of RRT. The aim of this study was to explore whether the effect of comorbidities on survival is similar in elderly RRT patients compared with younger ones.

METHODS

Included were 9333 patients ≥80 years of age and 48 352 patients 20-79 years of age starting RRT between 2010 and 2015 from 15 national or regional registries submitting data to the European Renal Association-European Dialysis and Transplantation Association Registry. Patients were followed until death or the end of 2016. Survival was assessed by Kaplan-Meier curves and the relative risk of death associated with comorbidities was assessed by Cox regression analysis.

RESULTS

Patients ≥80 years of age had a greater comorbidity burden than younger patients. However, relative risks of death associated with all studied comorbidities (diabetes, ischaemic heart disease, chronic heart failure, cerebrovascular disease, peripheral vascular disease and malignancy) were significantly lower in elderly patients compared with younger patients. Also, the increase in absolute mortality rates associated with an increasing number of comorbidities was smaller in elderly patients.

CONCLUSIONS

Comorbidities are common in elderly patients who enter RRT, but the risk of death associated with comorbidities is less than in younger patients. This should be taken into account when assessing the prognosis of elderly RRT patients.

Predictors of Survival in Chronic Hemodialysis Patients: A 10-Year Longitudinal Follow-Up Analysis

BACKGROUND

Risk factors of mortality in chronic hemodialysis patients have not yet been sufficiently evaluated. In particular, chronological transits and interactions of the impact of risk factors have rarely been described.

METHODS

This study is a post hoc analysis of the participants in the Olme-sartan Clinical Trial in Okinawan Patients under OKIDS (OCTOPUS) study conducted between June 2006 and June 2011. We additionally followed up on the prognosis of the participants until July 31, 2018. Standardized univariable and multivariable Cox regression analyses were used to evaluate the influences of the participants' baseline characteristics on all-cause mortality. We also evaluated chronological changes in the impacts of risk factors, interactions among predictors, and the influence of missing values using sensitivity analyses.

RESULTS

Of the 469 original trial participants, 461 participants were evaluated. The median time of follow-up was 10.2 years. A total of 211 (45.8%) participants were deceased. The leading causes of death were infection (n = 72, 34.1%) and cardiovascular disease (n = 66, 31.3%). Univariate and multivariate Cox regression analyses revealed that the impact of diabetes mellitus, history of coronary intervention, and hypoalbuminemia were significant risk factors for mortality during the whole follow-up period. During the early follow-up period (≤3 years), standardized univariate Cox regression analyses revealed that history of amputation (hazard ratio [HR] = 4.61, p < 0.001), lower dry weight, higher cardiothoracic ratio, and lower potassium levels were statistically significant risks. In those who survived for longer than 3 years, a history of stroke (HR = 1.73, p = 0.006), higher systolic blood pressure, lower serum sodium levels, and higher levels of hemoglobin, and serum phosphate were significant risks. We also observed a stable interaction between the impacts of serum phosphate and albumin on all-cause mortality.

CONCLUSION

In chronic hemodialysis patients, targets to improve the short-term prognosis and long-term prognosis are not equivalent. Hyperphosphatemia was a significant risk factor for the all-cause mortality among patients with normal serum albumin levels but not among patients with compromised albumin levels.

Development and validation of a novel score to predict dialysis inadequacy in continuous ambulatory peritoneal dialysis patients

Objective

Adequate dialysis is of great importance for continuous ambulatory peritoneal dialysis (CAPD) patients. This study aimed to develop and validate an easily applicable quantitative dialysis adequacy risk scoring system in CAPD patients based on laboratory parameters from a single blood draw.

Methods

A total of 634 CAPD patients from four study centers were enrolled in this study (345 and 289 patients in development and validation groups, respectively). A risk score model for inadequate dialysis was developed based on multivariate regression analysis, which was validated by the area under the receiver operator curve and calibrated by a calibration curve.

Results

Seven independent predictors for inadequate dialysis were identified in the development group (male sex, hypoalbuminemia, anemia, being overweight, hyperuricemia, estimated glomerular filtration rate <4.7 mL/min/1.73 m², and serum creatinine >800 μmol/L). A risk prediction score model was established and validated in the development and validation groups. Further analysis indicated that this model is suitable for CAPD patients with a wide range of clinical manifestations.

Conclusion

An easily applicable novel risk scoring system was established to detect inadequate dialysis in CAPD patients.

Normal white blood cell counts predict long-term mortality of hemodialysis patients

PURPOSE

It is unclear whether normal white blood cell (WBC) counts are predictive of subsequent mortality in hemodialysis patients.

METHODS

All patients aged 17 years or more, who initiated hemodialysis at a tertiary Hospital from January 2000 to August 2017 with a dialysis vintage of greater than 90 days and normal median WBC count of their first dialysis year were included in the study. They were followed until they died, transferred to other dialysis facilities, switched to peritoneal dialysis, received a renal transplant or reached the end of the study (August 31, 2018). Cox regression was used to estimate hazard ratios for mortality of tertiles of WBC counts, adjusting for baseline demographic, clinical and laboratory variables.

RESULTS

611 patients [median (interquartile range) age 65.2 (53.3-72.6) years, 62.4% male] were studied. During a median follow-up of 3.9 (1.6-7.2) years, 270 participants died. Patients in the mid- (6.25-7.73 × 10³/μL, n = 203) and top-tertile (7.73-10.50 × 10³/μL, n = 203) of normal WBC counts had significantly higher mortality than patients in the bottom-tertile (3.50-6.25 × 10³/μL, n = 205). The adjusted hazard ratio for mortality relative to the bottom-tertile was 1.54, 95% confidence interval (CI) 1.05-2.25 and 2.20, 95% CI 1.46-3.32, for the mid- and top-tertiles, respectively.

CONCLUSIONS

In hemodialysis patients, higher WBC count within the normal range is associated with increased long-term mortality. This finding is described for the first time and provides further insight into the clinical significance of a "normal" WBC count result in dialysis patients.

Development of a risk prediction model for infection-related mortality in patients undergoing peritoneal dialysis

Background

Assessment of infection-related mortality remains inadequate in patients undergoing peritoneal dialysis. This study was performed to develop a risk model for predicting the 2-year infection-related mortality risk in patients undergoing peritoneal dialysis.

Methods

The study cohort comprised 606 patients who started and continued peritoneal dialysis for 90 at least days and was drawn from the Fukuoka Peritoneal Dialysis Database Registry Study in Japan. The patients were registered from 1 January 2006 to 31 December 2016 and followed up until 31 December 2017. To generate a prediction rule, the score for each variable was weighted by the regression coefficients calculated using a Cox proportional hazard model adjusted by risk factors for infection-related mortality, including patient characteristics, comorbidities, and laboratory data.

Results

During the follow-up period (median, 2.2 years), 138 patients died; 58 of them of infectious disease. The final model for infection-related mortality comprises six factors: age, sex, serum albumin, serum creatinine, total cholesterol, and weekly renal Kt/V. The incidence of infection-related mortality increased linearly with increasing total risk score (P for trend <0.001). Furthermore, the prediction model showed adequate discrimination (c-statistic = 0.79 [0.72–0.86]) and calibration (Hosmer–Lemeshow test, P = 0.47).

Conclusion

In this study, we developed a new model using clinical measures for predicting infection-related mortality in patients undergoing peritoneal dialysis.