Predictors of Hyperkalemia among Patients on Maintenance Hemodialysis Transported to the Emergency Department by Ambulance

Ambulance Service Utilization by Kidney Transplant Recipients

Background

Compared with the general population, kidney transplant recipients (KTRs) frequently visit the emergency department (ED), but much less is known about the characteristics of ED presentations requiring ambulance transport and the impact on subsequent outcomes for KTRs.

Objectives

To identify predictors of ambulance transport to the ED (ambulance-ED) and outcomes (graft failure and mortality) for those who experienced an ambulance-ED event in a cohort of KTRs.

Design

Retrospective cohort study of incident, adult KTRs receiving a transplant from 2008 to 2020.

Setting

Nova Scotia, Canada.

Patients

Adult (≥18 years), Nova Scotian KTRs affiliated with the Atlantic Canada Multi-Organ Transplant Program.

Measurements

Ambulance-ED events were captured for all transplant recipients (following the day of discharge from their initial transplant admission) using electronic records (provided by Emergency Health Services, the sole provider of emergency medical services for Nova Scotia). Ambulance-ED was defined as ambulance transport to the ED following a 911 call; interfacility transfers were excluded. Predictors of ambulance-ED included recipient, donor, immunological, and perioperative characteristics (pertaining to the initial admission for kidney transplantation). Outcomes included graft failure and mortality.

Methods

Predictors of ambulance-ED were analyzed using a multivariable negative binomial regression model and reported using incidence rate ratios (IRRs) and 95% confidence intervals (CIs). The risk of death/graft failure for those with an ambulance-ED within 30 days of hospital discharge following transplantation was analyzed using an adjusted Cox survival analysis and reported using hazard ratios (HRs) and 95% CIs.

Results

A total of 418 patients received a transplant during the study period. A total of 179 (42.8%) experienced one or more ambulance-ED events. Female sex (IRR = 1.60; 95% CI = 1.12-2.29), kidney failure secondary to diabetes (IRR = 2.52; 95% CI = 1.19-5.31), and donor age ≥45 (IRR = 1.50; 95% CI = 1.04-2.15) were all associated with ambulance-ED. There was no significant increase in the risk of death/graft failure for those that experienced ambulance-ED within 30 days of hospital discharge following transplantation (HR = 1.31; 95% CI = 0.44-3.94).

Limitations

A limitation of this study was that ambulance-ED is not a perfect surrogate marker of acute care needs in a population. Important determinants of health such as living situation and socioeconomic status were not available in this data set.

Conclusions

This study highlights the burden of ambulance use for KTRs and provides insight into the need for more optimal follow-up in certain patient subgroups who are at particularly high risk.

Appropriately Matching Transport Care Units to Patients in Interhospital Transport Care: Implementation Study

BACKGROUND

In interfacility transport care, a critical challenge exists in accurately matching ambulance response levels to patients' needs, often hindered by limited access to essential patient data at the time of transport requests. Existing systems cannot integrate patient data from sending hospitals' electronic health records (EHRs) into the transfer request process, primarily due to privacy concerns, interoperability challenges, and the sensitive nature of EHR data. We introduce a distributed digital health platform, Interfacility Transport Care (ITC)-InfoChain, designed to solve this problem without compromising EHR security or data privacy.

OBJECTIVE

This study aimed to detail the implementation of ITC-InfoChain, a secure, blockchain-based platform designed to enhance real-time data sharing without compromising data privacy or EHR security.

METHODS

The ITC-InfoChain platform prototype was implemented on Amazon Web Services cloud infrastructure, using Hyperledger Fabric as a permissioned blockchain. Key elements included participant registration, identity management, and patient data collection isolated from the sending hospital's EHR system. The client program submits encrypted patient data to a distributed ledger, accessible to the receiving facility's critical care unit at the time of transport request and emergency medical services (EMS) teams during transport through the PatienTrack web app. Performance was evaluated through key performance indicators such as data transaction times and scalability across transaction loads.

RESULTS

The ITC-InfoChain demonstrated strong performance and scalability. Data transaction times averaged 3.1 seconds for smaller volumes (1-20 transactions) and 6.4 seconds for 100 transactions. Optimized configurations improved processing times to 1.8-1.9 seconds for 400 transactions. These results confirm the platform's capacity to handle high transaction volumes, supporting timely, real-time data access for decision-making during transport requests and patient transfers.

CONCLUSIONS

The ITC-InfoChain platform addresses the challenge of matching appropriate transport units to patient needs by ensuring data privacy, integrity, and real-time data sharing, enhancing the coordination of patient care. The platform's success suggests potential for regional pilots and broader adoption in secure health care systems. Stakeholder resistance due to blockchain unfamiliarity and data privacy concerns remains. Funding has been sought to support a pilot program to address these challenges through targeted education and engagement.

A Nomogram to Identify Hyperkalemia Risk in Patients with Advanced CKD

Background

Hyperkalemia is a common and life-threatening complication of CKD. We aimed to develop and validate a nomogram that could identify the risk of hyperkalemia (≥5.5 mmol/L) in patients with CKD.

Methods

A retrospective cohort study was performed in adult patients with predialysis advanced CKD (stages ≥3) in 2020-2021 for the outcome of hyperkalemia within 6 months. The training set was used to identify risk factors of hyperkalemia. Then a nomogram was developed by multivariable logistic regression analysis. C-statistics, calibration curves, and decision curve analysis (DCA) were used, and the model was validated in the internal and two external validation sets.

Results

In total, 847 patients with advanced CKD were included. In 6 months, 28% of patients had hyperkalemia (234 out of 847). Independent risk factors were: age ≥75 years, higher CKD stages, previous event of serum potassium ≥5.0 mmol/L within 3 months, and comorbidities with heart failure, diabetes, or metabolic acidosis. Then the nomogram on the basis of the risk factors adding the use of renin-angiotensin-aldosterone system inhibitors was constructed. The C-statistic of the model was 0.76 (95% CI, 0.70 to 0.78), and was stable in both the internal validation set (0.73; 95% CI, 0.63 to 0.82) and external validation sets (0.88; 95% CI, 0.84 to 0.95 and 0.82; 95% CI, 0.72 to 0.92). Calibration curves and DCA analysis both found good performances of the nomogram.

Conclusion

A feasible nomogram and online calculator were developed and validated to evaluate the risk of hyperkalemia within 6 months in patients with advanced CKD. Patients with CKD and a high risk of hyperkalemia may benefit from intensive monitoring and early triage.