Evolution of Physical Frailty and Patient-Reported Outcome Measures in Kidney Transplant Candidates: A Mixed-Methods Longitudinal Study Protocol

Overview

This study looks at how the physical and emotional health of people changes while they wait for a kidney transplant. Waiting for an organ can take a long time. During this period, some patients become "frail." This means they lose strength and are at a higher risk for health problems. The main goal is to follow these patients over time to better understand their needs. Researchers will use a mobile application to collect Patient-Reported Outcome Measures (PROMs) directly from patients about how they feel and their quality of life. The study will also include personal interviews to learn about the patients' experiences and any difficulties they face when using technology. The results of this study will help to: • Identify early which patients are losing strength or health. • Improve the support that nurses provide during the transplant waiting period. • Make sure that digital health tools are easy for everyone to use. In short, this work aims to help patients reach the day of their surgery in the best possible condition.

Study Design and Framework This research employs a convergent-parallel mixed-methods design to evaluate frailty dynamics and patient-reported outcomes in Kidney Transplantation (KT) candidates. The quantitative component is a longitudinal observational study, while the qualitative component is grounded in Heideggerian hermeneutic phenomenology to explore the lived experience of patients during the waiting list period. Quantitative Procedures and Data Collection Participants will be recruited during their initial KT evaluation at Hospital del Mar (Barcelona). Frailty will be assessed using the Fried Phenotype (assessing weight loss, exhaustion, physical activity, walk time, and grip strength) at baseline and subsequently every six months while the patient remains on the waiting list. To monitor Patient-Reported Outcome Measures (PROMs), the study utilizes the Patient-Reported Outcomes Measurement Information System (PROMIS)-29 v2.0 questionnaire. This instrument covers seven health domains: physical function, anxiety, depression, fatigue, sleep disturbance, ability to participate in social roles/activities, and pain interference. Data collection will be performed via a digital platform (electronic PROMs \[ePROMs\]), allowing for real-time monitoring. For patients facing technological or language barriers, an Advanced Practice Nurse (APN) will provide support to ensure data completeness and minimize selection bias. Qualitative Exploration A purposive sample of participants will undergo in-depth semi-structured interviews. These sessions will focus on the subjective meaning of frailty, the impact of the waiting period on daily life, and the experience of using digital health tools. Interviews will be audio-recorded, transcribed verbatim, and analyzed using thematic analysis to identify core existential themes. Quality Assurance and Data Management • Data Validation: A data dictionary has been developed, defining each variable, its source, and acceptable ranges to ensure consistency. • Source Data Verification: Data entered into the electronic Case Report Form (eCRF) will be cross-referenced with electronic medical records to ensure accuracy. • Standard Operating Procedures (SOPs): Specific SOPs are in place for patient recruitment, the standardized administration of physical performance tests (e.g., handgrip strength using a dynamometer), and the management of technical issues with the ePROM platform. Statistical Analysis Plan (SAP) Quantitative data will be analyzed using SPSS (Statistical Package for the Social Sciences, v.25). Descriptive statistics will summarize baseline characteristics. Longitudinal changes in frailty scores and PROMs will be analyzed using linear mixed models or Generalized Estimating Equations (GEE) to account for repeated measures. The relationship between frailty status and PROMs will be assessed using correlation coefficients and multivariate regression models adjusted for age, comorbidity, and time on dialysis. Missing Data Plan The study aims to minimize missing data through APN-led follow-up. If data are missing at random, multiple imputation techniques will be considered. For patients unable to use digital tools, paper-based alternatives or assisted entry will be provided to reduce non-response bias. Sample Size Assessment The sample size is based on the prevailing activity of the kidney transplant unit, aiming to include all eligible candidates over the recruitment period (estimated N ≈ 150-200) to ensure sufficient power for detecting longitudinal changes in frailty prevalence and its association with PROMs.