Clinical Research Directory

Examine the Epidemiology and Outcomes of Transitions From PD-to-HD in Canada

Transitions from peritoneal dialysis to hemodialysis are common during kidney replacement therapy and may be associated with adverse outcomes. However, the incidence, predictors, and outcomes of PD-to-HD transitions at a national level remain incompletely characterized. This study will use Canadian dialysis and hospitalization databases to examine the epidemiology and outcomes of PD-to-HD transitions among adults initiating dialysis in Canada. The study will evaluate transition incidence, predictors, and post-transition outcomes including mortality, transplantation, modality changes, and hospitalizations.

A Survey for Patients and Caregivers Aiming to Understand and Improve the Care of Patients at High Risk of Transfer From Peritoneal Dialysis to Hemodialysis:

Home dialysis is encouraged in Canada and peritoneal dialysis is the most common home dialysis method. However, many patients discontinue peritoneal dialysis, often transferring to hemodialysis. Despite the frequency of this transition, little is known about its impact on patients. Overall, the UPLIFT-PD program aims to fill this gap by studying the transition from peritoneal dialysis to hemodialysis. The specific goal of this mixed methods sub-study is to conduct a national survey to ask patients and caregivers about priorities and preferences when they anticipate a transfer from peritoneal dialysis to hemodialysis. This survey will be co-created by patient-partners and dialysis experts. Results from this survey will then be used in other phases of UPLIFT-PD program, detailed in other registrations, which will support people facing a transition from peritoneal dialysis to hemodialysis..

Community Health Workers in an Interdisciplinary Outpatient CKD Clinic to Optimize Social Care Navigation, Patient Engagement, and Home Dialysis Utilization

The goal of this clinical trial is to learn if this intervention (the CHOOSE Home intervention) is feasible and may lead to more home dialysis usage in a high-risk patient population. The main questions it aims to answer are: * Will there be an increase in home dialysis selection or initiation over study follow up? * Will there be a change in patient reported status of Health-Related Social Needs (HRSNs) and patient engagement at 1 year follow up? Researchers will compare the intervention group that will include interdisciplinary care (IDC) and the integration of a Community Health Worker (CHW) into the chronic kidney disease (CKD) care process to the IDC only control group. The research team will assess whether the intervention led to better social care navigation, enhanced patient engagement, and increased home dialysis use.

The Rhabdomyolysis Evaluation in the Emergency Department (REED) Score

One in three adults over 65 fall annually, with one in five remaining on the floor for greater than one hour, which is referred to as a long lie. Pressure on the National Health Service has resulted in extended stays in the Emergency Department (ED) (sometimes longer than 12 hours) and prolonged ambulance response times. This impacts the older adults who have fallen and remain on the floor. This project aims to develop a risk prediction model (RPM) for use within the ED to understand which older adults (60 years or older) who fall over and remain on the floor for longer than one hour ("long lie") and develop rhabdomyolysis (a serious condition where muscle breaks down and releases substances into the blood that can damage the kidneys) will develop poor outcomes and need admission to hospital for treatment and which patients can be safely discharged home. Aim: To develop a RPM to identify which older adults who have a fall and a long lie and attend the ED develop poor outcomes such as Acute kidney Injury (AKI) \[kidneys suddenly stop working properly\], needing kidney replacement therapy (KRT) \[a treatment that helps kidneys that aren't working properly do their job of cleaning the blood\] and mortality \[death\]. Objectives: 1. Abstract patient level data (e.g. biochemical, demographic, situational, medical history, medication history) from medical records combined with outcomes to understand which variables lead to poor outcomes such as AKI, needing KRT and mortality. 2. Analyse the data using a statistical package (Statistical Package for Social Sciences \[SPSS\]) to develop a RPM with good discriminative abilities \[how well the score can tell high-risk from low-risk patients\]. 3. Demonstrate the ability of the RPM to identify which patients need admission to hospital with treatment and which patients can be safely discharged home.