Psychometric Properties of the Piper Fatigue Scale-12.

Background and Purpose: The Piper Fatigue Scale (PFS)-12 is a recently shortened version of the original PFS that has 40 items. Psychometric evidence for PFS-12 from a small sample of individuals on hemodialysis is presented. Methods: The psychometric analysis with pilot data was done using a detailed item analysis, including Bland-Altman plots, exploratory factor analysis of pre- and post-item scores, and item change scores. Additional measures were used to investigate the validity including the Patient-Reported Outcomes Measurement Information System-Fatigue Scale and the 6-minute walk test. Results: The sample consisted of 86 hemodialysis individuals. The internal consistency reliability of the PFS-12 total scale was 0.91 (pre), 0.95 (post), and subscale alphas were 0.79-0.94. Convergent, concurrent, and predictive validity of PFS-12 were supported. Construct validity of PFS-12 was confirmed predialysis and partially supported in the change score analysis. Conclusion: The brief 12-item PFS is a good alternative to the longer version of this scale to reduce the respondent burden and measure the overall fatigue; further validation in test-retest situations and subscale validity is needed.

Evaluating Subjective and Objective Fatigue Immediately Before and After Hemodialysis: A Within-Subjects' Design.

Change in fatigue within a hemodialysis (HD) session has not been established previously. A total of 55 cognitively intact adults on HD were included; individuals with mobility/hemodynamic issues were excluded. Measures included the Piper Fatigue Scale-12 (PFS-12), 6-Minute Walk Test (6MWT), demographic and clinical. Descriptive statistics, ANOVA, and stepwise regression were used. Mean age was 57 years. Mean change in PFS-12 was -4.56 ± 27.85. Mean change in walk distance was -16.26 ± 43.87 meters (p = 0.03). The change in the PFS-12 accounted for 47% quadratic trend in the change in 6MWD (p < 0.001). Both fatigue measures (PFS-12 and 6MWT) can be useful for examining changes in fatigue levels within an HD session. Our findings speak to the convergent validity of these two measures of fatigue.

Multiple Dimensions and Correlates of Fatigue in Individuals on Hemodialysis.

This study examined the severity, pattern, and correlates of fatigue among adults undergoing hemodialysis. Measures included the Piper Fatigue Scale (PFS-12), Patient-Reported Outcomes Measurement Information System (PROMIS) - Fatigue, Charlson Comorbidity Index, and Six-Minute Walk Test (6MWT). Patients were excluded if mobility or cardiovascular issues prevented conducting the 6MWT. Participants were 86 cognitively intact adults (M = 61.7 years, SD = 13.81), predominantly male (58.1%), and African American (48.8%), with 80% reporting fatigue in the week prior to hemodialysis. Significant increases were noted in sensory and cognitive fatigue from pre- to post-dialysis, while the 6MWT distance decreased significantly pre- to post-dialysis. Factors significantly associated with pre-dialysis fatigue included low hemoglobin, younger age, and living with someone else, while comorbidities and dialysis inadequacy were trending to significant associations with fatigue.

Fatigue in Patients with Chronic Kidney Disease: Evidence and Measures.

As many as 70% to 97% of individuals with chronic kidney disease (CKD) report fatigue. Fatigue is one of the common, troubling symptoms that affects one's quality of life. This narrative review summarizes the evidence and gaps about the epidemiology, causative factors, and assessment of fatigue in individuals with CKD. Most studies are focused on the hemodialysis population, with very few focused on the peritoneal dialysis and transplant populations in which fatigue is also prevalent. Understanding fatigue and its correlates can help in assessing fatigue and in implementing interventions to alleviate fatigue.

Fatigue and depression and sleep problems among hemodialysis patients in a tertiary care center.

High prevalence of sleep problems, fatigue and depression are reported in maintenance hemodialysis (MHD) patients. To assess fatigue, depression, sleep problems and their co-relates among MHD patients in a tertiary care center in India, we studied 47 patients on MHD for >3 months. Patients demographic, medical and co-morbidity profile were recorded. Pittsburgh Sleep Quality Index (poor sleeper if score >5) and Epworth Sleepiness Scale (EPSS, abnormal daytime sleepiness if score >13) were used to assess sleep abnormalities and quality. Beck Depression Inventory (BDI) was used to screen for depression. Depression was classified on BDI scores as mild-moderate (score 11-30) and severe (score >30). Fatigue Severity Scale was used to assess fatigue (score ≥36 indicates fatigue). The correlations of these parameters among themselves and with social and demographic parameters were also analyzed. The mean age of the study population was 37.1 ± 13.1 (range 19-65 years) years, with 89.3% being males. The majority (68.1%) of the MHD patients was poor sleepers, but only five (10.6%) patients had borderline or abnormal daytime sleepiness. Of the patients, 44.7% reported fatigue and (72.3%) had depression (mild to moderate in 59.7% and severe in 12.6%). Fatigue scores were found to be significantly associated with lesser frequency of dialysis (P < 0.05). There was higher daytime sleepiness in patients who were working (mean EPSS score 6.2 ± 3.7) than who were unemployed (mean EPSS score 3.9 ± 2.7). Depression was found to be higher in those who were paying for the treatment themselves (mean BDI score 20 ± 11.8) as compared with those who were getting medical expenditure reimbursed (mean BDI score 12.9 ± 8.8). Fatigue positively correlated with that of daytime sleepiness (P = 0.02), poor nighttime sleep (P = 0.02) and depression (P=0.006). In the present study, there was no correlation (P <0.05) found between daytime and night time sleep and depression. We found a high prevalence of fatigue, depression and poor sleep quality in our MHD patients. These abnormalities are closely related to each other and to the socioeconomic and demographic profiles of the population.