Toward Developing a Patient-Reported Outcome Measure for Fatigue in Hemodialysis

Hidden risks associated with conventional short intermittent hemodialysis: A call for action to mitigate cardiovascular risk and morbidity

The development of maintenance hemodialysis (HD) for end stage kidney disease patients is a success story that continues to save many lives. Nevertheless, intermittent renal replacement therapy is also a source of recurrent stress for patients. Conventional thrice weekly short HD is an imperfect treatment that only partially corrects uremic abnormalities, increases cardiovascular risk, and exacerbates disease burden. Altering cycles of fluid loading associated with cardiac stretching (interdialytic phase) and then fluid unloading (intradialytic phase) likely contribute to cardiac and vascular damage. This unphysiologic treatment profile combined with cyclic disturbances including osmotic and electrolytic shifts may contribute to morbidity in dialysis patients and augment the health burden of treatment. As such, HD patients are exposed to multiple stressors including cardiocirculatory, inflammatory, biologic, hypoxemic, and nutritional. This cascade of events can be termed the dialysis stress storm and sickness syndrome. Mitigating cardiovascular risk and morbidity associated with conventional intermittent HD appears to be a priority for improving patient experience and reducing disease burden. In this in-depth review, we summarize the hidden effects of intermittent HD therapy, and call for action to improve delivered HD and develop treatment schedules that are better tolerated and associated with fewer adverse effects.

Unraveling Fatigue in Hemodialysis Patients: Comparing Retrospective Reports to Real-Time Assessments With an mHealth Experienced Sampling Method

CONTEXT

Fatigue is prevalent among hemodialysis (HD) patients and associated with depressive mood. To advance our understanding of its etiology and develop appropriate treatments, reliable measurement instruments are needed. However, conventional fatigue and mood questionnaires are prone to bias because of their retrospective nature and may misrepresent or overestimate actual symptom experience (i.e., the so-called memory-experience gap). Experience sampling methodology (ESM) overcomes this limitation through repeated real-time assessments in patients' natural environment, thereby providing reliable and ecologically valid data.

OBJECTIVES

We investigated to what extent retrospective symptom reporting accurately represents real-time experiences of fatigue and mood in HD patients using an ESM mobile Health application (PsyMate™; smartHealth GmbH, Luxembourg).

METHODS

Forty HD patients used the PsyMate for one week to assess real-time fatigue and mood. In addition, they retrospectively evaluated their symptom experience completing end-of-day and end-of-week questionnaires as well as the conventional Fatigue Severity Scale and Hospital Anxiety and Depression Scale.

RESULTS

Results of real-time observations (N = 1777) showed that fatigue and mood varied between and within individuals. Retrospective end-of-week fatigue evaluation was significantly higher than the average real-time fatigue score; t(38) = 3.54, P = 0.001, and d = 0.57. Fatigue Severity Scale and Hospital Anxiety and Depression Scale correlated moderately to strong with the average ESM score for fatigue and mood: r = 0.66 and r = 0.77, respectively.

CONCLUSION

Retrospective fatigue assessment may lead to overestimation of real-time symptom experience. ESM provides detailed insight and personalized information about symptom experiences, which may be crucial for the design of more targeted and personalized interventions for fatigue and mood problems in HD patients.

Dialysis-Induced Cardiovascular and Multiorgan Morbidity

Hemodialysis has saved many lives, albeit with significant residual mortality. Although poor outcomes may reflect advanced age and comorbid conditions, hemodialysis per se may harm patients, contributing to morbidity and perhaps mortality. Systemic circulatory "stress" resulting from hemodialysis treatment schedule may act as a disease modifier, resulting in a multiorgan injury superimposed on preexistent comorbidities. New functional intradialytic imaging (i.e., echocardiography, cardiac magnetic resonance imaging [MRI]) and kinetic of specific cardiac biomarkers (i.e., Troponin I) have clearly documented this additional source of end-organ damage. In this context, several factors resulting from patient-hemodialysis interaction and/or patient management have been identified. Intradialytic hypovolemia, hypotensive episodes, hypoxemia, solutes, and electrolyte fluxes as well as cardiac arrhythmias are among the contributing factors to systemic circulatory stress that are induced by hemodialysis. Additionally, these factors contribute to patients' symptom burden, impair cognitive function, and finally have a negative impact on patients' perception and quality of life. In this review, we summarize the adverse systemic effects of current intermittent hemodialysis therapy, their pathophysiologic consequences, review the evidence for interventions that are cardioprotective, and explore new approaches that may further reduce the systemic burden of hemodialysis. These include improved biocompatible materials, smart dialysis machines that automatically may control the fluxes of solutes and electrolytes, volume and hemodynamic control, health trackers, and potentially disruptive technologies facilitating a more personalized medicine approach.

mHealth-based experience sampling method to identify fatigue in the context of daily life in haemodialysis patients

Background

Fatigue in haemodialysis (HD) patients is a prevalent but complex symptom impacted by biological, behavioural, psychological and social variables. Conventional retrospective fatigue questionnaires cannot provide detailed insights into symptom variability in daily life and related factors. The experience sampling methodology (ESM) overcomes these limitations through repeated momentary assessments in patients’ natural environments using digital questionnaires. This study aimed to gain in-depth understanding of HD patients’ diurnal fatigue patterns and related variables using a mobile Health (mHealth) ESM application and sought to better understand the nature of their interrelationships.

Methods

Forty HD patients used the mHealth ESM application for 7 days to assess momentary fatigue and potentially related variables, including daily activities, self-reported physical activity, social company, location and mood.

Results

Multilevel regression analyses of momentary observations (n = 1777) revealed that fatigue varied between and within individuals. Fatigue was significantly related to HD treatment days, type of daily activity, mood and sleep quality. Time-lagged analyses showed that HD predicted higher fatigue scores at a later time point (β = 0.22, P = 0.013). Interestingly, higher momentary fatigue also significantly predicted more depressed feelings at a later time point (β = 0.05, P = 0.019) but not the other way around.

Conclusions

ESM offers novel insights into fatigue in chronic HD patients by capturing informative symptom variability in the flow of daily life. Electronic ESM as a clinical application may help us better understand fatigue in HD patients by providing personalized information about its course and relationship with other variables in daily life, paving the way towards personalized interventions.