Long-term outcomes among Medicare patients readmitted in the first year of hemodialysis: a retrospective cohort study

Dialysis Outcomes Across Countries and Regions: A Global Perspective From the International Society of Nephrology Global Kidney Health Atlas Study

Introduction

Kidney failure treated with hemodialysis (HD), or peritoneal dialysis (PD) is a major global health problem that is associated with increased risks of death and hospitalization. This study aimed to compare the incidence and causes of death and hospitalization during the first year of HD or PD among countries.

Methods

The third iteration of the International Society of Nephrology Global Kidney Health Atlas (ISN-GKHA) was conducted between June and September 2022. For this analysis, data were obtained from the cross-sectional survey of key stakeholders from ISN-affiliated countries.

Results

A total of 167 countries participated in the survey (response rate 87.4%). In 48% and 58% of countries, 1% to 10% of people treated with HD and PD died within the first year, respectively, with cardiovascular disease being the main cause. Access-related infections or treatment withdrawal owing to cost were important causes of death in low-income countries (LICs). In most countries, <30% and <20% of patients with HD and PD, respectively, required hospitalization during the first year. A greater proportion of patients with HD and PD in LICs were hospitalized in the first year than those in high-income countries (HICs). Access-related infection and cardiovascular disease were the commonest causes of hospitalization among patients with HD, whereas PD-related infection was the commonest cause in patients with PD.

Conclusion

There is significant heterogeneity in the incidence and causes of death and hospitalization in patients with kidney failure treated with dialysis. These findings highlight opportunities to improve care, especially in LICs where infectious and social factors are strong contributors to adverse outcomes.

Understanding Hospital Readmissions: Insights, Patterns, and Interventions for Improvement in Chronic Kidney Disease

BACKGROUND

Hospital readmissions among chronic kidney disease (CKD) patients pose substantial challenges in healthcare, impacting both patients and healthcare systems. Understanding the patterns and determinants of CKD-related readmissions is crucial for devising effective interventions.

OBJECTIVE

This research aimed to investigate the factors contributing to hospital readmissions among CKD patients, identify the primary reasons for readmissions, and explore potential interventions to mitigate readmission risks.

METHODS

A retrospective analysis was conducted among a cohort of 300 CKD patients over an 18-month period at a tertiary care unit specializing in nephrology services. Data on demographics, CKD stages, comorbidities, reasons for readmissions, and lengths of hospital stays were analyzed. Logistic regression models were employed to identify predictors of readmissions.

RESULTS

Advancing CKD stages were associated with increased readmission rates, with higher rates observed in older patients. Cardiovascular complications and acute kidney injury were prominent reasons for readmissions. Age, comorbid conditions, and previous hospitalizations emerged as significant predictors of readmissions. Lengths of hospital stays during readmissions were also correlated with CKD stages.

CONCLUSION

The research underscores the complex interplay of demographic and clinical factors contributing to hospital readmissions among CKD patients. Tailored interventions addressing disease severity, comorbidities, and patient-specific characteristics are pivotal in reducing readmission risks and enhancing care outcomes for this population.

Analyzing Monthly Blood Test Data to Forecast 30-Day Hospital Readmissions among Maintenance Hemodialysis Patients

Background: The increase in the global population of hemodialysis patients is linked to aging demographics and the prevalence of conditions such as arterial hypertension and diabetes mellitus. While previous research in hemodialysis has mainly focused on mortality predictions, there is a gap in studies targeting short-term hospitalization predictions using detailed, monthly blood test data. Methods: This study employs advanced data preprocessing and machine learning techniques to predict hospitalizations within a 30-day period among hemodialysis patients. Initial steps include employing K-Nearest Neighbor (KNN) imputation to address missing data and using the Synthesized Minority Oversampling Technique (SMOTE) to ensure data balance. The study then applies a Support Vector Machine (SVM) algorithm for the predictive analysis, with an additional enhancement through ensemble learning techniques, in order to improve prediction accuracy. Results: The application of SVM in predicting hospitalizations within a 30-day period among hemodialysis patients resulted in an impressive accuracy rate of 93%. This accuracy rate further improved to 96% upon incorporating ensemble learning methods, demonstrating the efficacy of the chosen machine learning approach in this context. Conclusions: This study highlights the potential of utilizing machine learning to predict hospital readmissions within a 30-day period among hemodialysis patients based on monthly blood test data. It represents a significant leap towards precision medicine and personalized healthcare for this patient group, suggesting a paradigm shift in patient care through the proactive identification of hospitalization risks.

Is central venous catheter in haemodialysis still the main factor of mortality after hospitalization?

BACKGROUND

Haemodialysis is the most frequently prescribed Renal Replacement Therapy modality worldwide. However, patients undergoing this therapy have an unpredictable evolution related to vascular access.

OBJECTIVE

To determine the factors associated with the mortality and hospitalization rate in haemodialysis patients at a third-level care Centre in the Dominican Republic.

METHODS

This was an observational and prospective study involving a cohort of 192 haemodialysis patients. The patient selection was non-probabilistic for convenience, and a direct source questionnaire was applied.

RESULTS

Of the 192 patients in the cohort, 103 (53.6%) were hospitalized and evaluated. The most frequent cause of hospitalization was catheter-related bloodstream infections (53.4%). Almost one-third (28.2%) of the hospitalized patients died, mostly due to infections (12.6%). Of those who died 29 patients (90%) had a Central venous catheter (CVC) with a non-tunnelled catheter (NTCVC) (65.5%); having an NTC CVC makes a patient 85.5 times more likely to be hospitalized than patients with arteriovenous fistulas.

CONCLUSION

Vascular access plays a predominant role in the hospitalization and mortality rates in haemodialysis. Patients with an arteriovenous fistula obtained significantly better outcomes than those with central venous catheters.

Outcomes of early hospital readmission after kidney transplantation: Perspectives from a Canadian transplant centre

BACKGROUND

Early hospital readmissions (EHRs) after kidney transplantation range in incidence from 18%-47% and are important and substantial healthcare quality indicators. EHR can adversely impact clinical outcomes such as graft function and patient mortality as well as healthcare costs. EHRs have been extensively studied in American healthcare systems, but these associations have not been explored within a Canadian setting. Due to significant differences in the delivery of healthcare and patient outcomes, results from American studies cannot be readily applicable to Canadian populations. A better understanding of EHR can facilitate improved discharge planning and long-term outpatient management post kidney transplant.

AIM

To explore the burden of EHR on kidney transplant recipients (KTRs) and the Canadian healthcare system in a large transplant centre.

METHODS

This single centre cohort study included 1564 KTRs recruited from January 1, 2009 to December 31, 2017, with a 1-year follow-up. We defined EHR as hospitalizations within 30 d or 90 d of transplant discharge, excluding elective procedures. Multivariable Cox and linear regression models were used to examine EHR, late hospital readmissions (defined as hospitalizations within 31-365 d for 30-d EHR and within 91-365 d for 90-d EHR), and outcomes including graft function and patient mortality.

RESULTS

In this study, 307 (22.4%) and 394 (29.6%) KTRs had 30-d and 90-d EHRs, respectively. Factors such as having previous cases of rejection, being transplanted in more recent years, having a longer duration of dialysis pretransplant, and having an expanded criteria donor were associated with EHR post-transplant. The cumulative probability of death censored graft failure, as well as total graft failure, was higher among the 90-d EHR group as compared to patients with no EHR. While multivariable models found no significant association between EHR and patient mortality, patients with EHR were at an increased risk of late hospital readmissions, poorer kidney function throughout the 1st year post-transplant, and higher hospital-based care costs within the 1st year of follow-up.

CONCLUSION

EHRs are associated with suboptimal outcomes after kidney transplant and increased financial burden on the healthcare system. The results warrant the need for effective strategies to reduce post-transplant EHR.

Factors associated with readmission in chronic kidney disease: Systematic review and meta-analysis

BACKGROUND

Risk factors associated with all-cause hospital readmission are poorly characterised in patients with chronic kidney disease.

OBJECTIVE

A systematic review and meta-analysis were conducted to identify risk factors and protectors of hospital readmission in chronic kidney disease.

DESIGN, PARTICIPANTS & MEASUREMENTS

Studies involving adult patients were identified from four databases from inception to 31/03/2020. Random-effects meta-analyses were conducted to determine factors associated with all-cause 30-day hospital readmission in general chronic kidney disease, in dialysis and in kidney transplant recipient groups.

RESULTS

Eighty relevant studies (chronic kidney disease, n = 14 studies; dialysis, n = 34 studies; and transplant, n = 32 studies) were identified. Meta-analysis revealed that in both chronic kidney disease and transplant groups, increasing age in years and days spent at the hospital during the initial stay were associated with a higher risk of 30-day readmission. Other risk factors identified included increasing body mass index (kg/m2 ) in the transplant group, and functional impairment and discharge destination in the dialysis group. Within the chronic kidney disease ​​​​group, having an outpatient follow-up appointment with a nephrologist within 14 days of discharge was protective against readmission but this was not protective if provided by a primary care provider or a cardiologist.

CONCLUSION

Risk-reduction interventions that can be implemented include a nephrologist appointment within 14 days of hospital discharge, rehabilitation programme for functional improvement in the dialysis group and meal plans in the transplant group. Future risk analysis should focus on modifiable factors to ensure that strategies can be tested and implemented in those who are more at risk.

Interventions to Reduce Hospital Readmissions in Older African Americans: A Systematic Review of Studies Including African American Patients

OBJECTIVES

This systematic review aims to summarize interventions that effectively reduced hospital readmission rates for African Americans (AAs) aged 65 and older.

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed for this review. Studies were identified by searching PubMed for clinical trials on reducing hospital readmission among older patients published between 1 January 1990 and 31 January 2020. Eligibility criteria for the included studies were mean or median age ≥ 65 years, AAs included in the study, randomized clinical trial or quasi-experimental design, presence of an intervention, and hospital readmission as an outcome.

RESULTS

There were 5270 articles identified and 11 were included in the final review based on eligibility criteria. The majority of studies were conducted in academic centers, were multi-center trials, and included over 200 patients, and 6-90% of participants were older AAs. The length of intervention ranged from 1 week to over a year, with readmission assessed between 30 days and 1 year. Four studies which reported interventions that significantly reduced readmissions included both inpatient (e.g., discharge planning prior to discharge) and outpatient care components (e.g., follow-ups after discharge), and the majority used a multifaceted approach.

CONCLUSION

Findings from the review suggest successful interventions to reduce readmissions among AAs aged 65 and older should include inpatient and outpatient care components at a minimum. This systematic review showed limited evidence of interventions successfully decreasing readmission in older AAs, suggesting a need for research in the area to reduce readmission disparities and improve overall health.

Effectiveness of a Web-Based Provider Communications Platform in Reducing Hospital Readmissions Among Patients Receiving Dialysis: A Pilot Pre-Post Study

Rationale & Objective

Suboptimal care coordination between dialysis facilities and hospitals is an important driver of 30-day hospital readmissions among patients receiving dialysis. We examined whether the introduction of web-based communications platform (“DialysisConnect”) was associated with reduced hospital readmissions.

Study Design

Pilot pre-post study.

Setting & Participants

A total of 4,994 index admissions at a single hospital (representing 2,419 patients receiving dialysis) during the study period (January 1, 2019-May 31, 2021).

Intervention

DialysisConnect was available to providers at the hospital and 4 affiliated dialysis facilities (=intervention facilities) during the pilot period (November 1, 2020-May 31, 2021).

Outcomes

The primary outcome was 30-day readmission; secondary outcomes included 30-day emergency department visits and observation stays. Interrupted time series and linear models with generalized estimating equations were used to assess pilot versus prepilot differences in outcomes; difference-in-difference analyses were performed to compare these differences between intervention versus control facilities. Sensitivity analyses included a third, prepilot/COVID-19 period (March 1, 2020-October 31, 2020).

Results

There was no statistically significant difference in the monthly trends in the 30-day readmissions pilot versus prepilot periods (−0.60 vs -0.13, P = 0.85) for intervention facility admissions; the difference-in-difference estimate was also not statistically significant (0.54 percentage points, P = 0.83). Similar analyses including the prepilot/COVID-19 period showed that, despite a substantial drop in admissions at the start of the pandemic, there were no statistically significant differences across the 3 periods. The age-, sex-, race-, and comorbid condition-adjusted, absolute pilot versus prepilot difference in readmissions rate was 1.8% (−3.7% to 7.3%); similar results were found for other outcomes.

Limitations

Potential loss to follow-up and pandemic effects.

Conclusions

In this pilot, the introduction of DialysisConnect was not associated with reduced hospital readmissions. Tailored care coordination solutions should be further explored in future, multisite studies to improve the communications gap between dialysis facilities and hospitals.

Risk factors and outcomes of cardiovascular disease readmission within the first year after dialysis in peritoneal dialysis patients

Background

In the first year of dialysis, patients are vulnerable to cardiovascular disease (CVD) hospitalization, but knowledge regarding the risk factors and long-term outcomes of cardiovascular readmission within the first year after dialysis in incident continuous ambulatory peritoneal dialysis (CAPD) patients is limited.

Methods

This retrospective cohort study was conducted in incident CAPD patients. The demographic characteristics, laboratory parameters, and CVD readmission were collected and analyzed. The primary outcome was all-cause mortality, and the secondary outcomes included CVD mortality, infection-related mortality and technique failure. A logistic regression was used to identify the risk factors associated with CVD readmission within the first year after dialysis. Cox proportional hazards models were used to evaluate the association between CVD readmission and the outcomes.

Results

In total, 1589 peritoneal dialysis (PD) patients were included in this study, of whom 120 (7.6%) patients had at least one episode of CVD readmission within the first year after dialysis initiation. Advanced age, CVD history, and a lower level of serum albumin were independently associated with CVD readmission. CVD readmission within the first year after dialysis was significantly associated with all-cause (HR 2.66, 95%CI 1.91–3.70, p < 0.001) and CVD (HR 3.42, 95%CI 2.20–5.31, p < 0.001) mortality, but not infection-related mortality or technique failure, after adjusting for confounders.

Conclusions

Our findings suggest that an advanced age, a history of CVD, and a lower level of serum albumin were independently associated with CVD readmission. Moreover, CVD readmission was associated with all-cause and cardiovascular mortality in incident CAPD patients.