Fatigue is often described by patients as a lack of energy, mental or physical tiredness, diminished endurance, and prolonged recovery after physical activity. Etiologic mechanisms underlying fatigue are not well understood; however, fatigue is a hallmark symptom of mitochondrial disease, making mitochondrial dysfunction a putative biological mechanism for fatigue. Therefore, this review examined studies that investigated the association of markers of mitochondrial dysfunction with fatigue and proposes possible research directions to enhance understanding of the role of mitochondrial dysfunction in fatigue. A thorough search using PubMed, Scopus, Web of Science, and Embase databases returned 1,220 articles. After application of inclusion and exclusion criteria, a total of 25 articles meeting eligibility criteria were selected for full review. Dysfunctions in the mitochondrial structure, mitochondrial function (mitochondrial enzymes and oxidative/nitrosative stress), mitochondrial energy metabolism (ATP production and fatty acid metabolism), immune response, and genetics were investigated as potential contributors to fatigue. Carnitine was the most investigated mitochondrial function marker. Dysfunctional levels were reported in all the studies investigating carnitine; however, the specific type of carnitine that was dysfunctional varied. Genetic profiles were the second most studied mitochondrial parameter. Six common pathways were proposed: metabolism, energy production, protein transport, mitochondrial morphology, central nervous system dysfunction and post-viral infection. Coenzyme Q10 was the most commonly investigated mitochondrial enzyme. Low levels of Coenzyme Q10 were consistently associated with fatigue. Potential targets for further investigation were identified as well as gaps in the current literature.

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Objective The study’s purpose was to develop symptoms cluster model that can describe factors of FMS associated with fatigue severity as reported by the sample. The study will also explore FMS clinical symptom sub-clusters based on varying symptom intensities. Methods FMS individuals (n = 120; 82% between 31–60 years of age, 90% women, 59% Caucasian) diagnosed with the 1990 or 2010 American College of Rheumatology diagnostic criteria were enrolled. Participants completed multiple validated self-report questionnaires to measure fatigue, pain, depression, anxiety, pain catastrophizing, daytime sleepiness, cognitive function, and FMS-related polysymptomatic distress. Cluster analysis using SPSS 19.0 and Structural Equation Modeling using AMOS 17.0 were used. Results Final Structural Equation Modeling symptoms cluster model showed good fit and revealed that FMS fatigue was associated with widespread pain, symptoms severity, pain intensity, pain interference, cognitive dysfunction, catastrophizing, anxiety, and depression (χ2 = 121.72, df = 98, p > 0.05, χ2/df = 1.242, CFI = 0.982, RMSEA = 0.045). Two distinct clinical symptom sub-clusters emerged; sub-cluster 1 (78% of total subjects) defined by widespread pain, unrefreshed waking, and somatic symptoms and sub-cluster 2 (22% of total subjects) defined by fatigue and cognitive dysfunction with pain being a less severe and less widespread complaint. Conclusion Overall, sub-cluster 1 had more intense symptoms than sub-cluster 2. FMS symptoms may be categorized into two clinical sub-clusters. These findings have implications for an illness whose diagnosis and management are symptom-dependent. A longitudinal study capturing the variability in symptom experience of FMS subjects is warranted.

Red blood cells, hemoglobin, and hematocrit levels were highly intercorrelated and, therefore, were grouped as one composite variable termed heme. Heme levels at baseline and androgen-deprivation therapy (ADT) were significantly correlated with worsening of fatigue symptoms from baseline to midpoint and endpoint. ADT alone did not have a significant correlation with fatigue, but it indirectly affected fatigue levels by influencing heme markers as treatment progressed. These findings provide evidence that hematologic markers and the use of ADT assist in predicting radiation therapy-related fatigue and guide symptom management.

Objectives Identification of biologic pathways of symptom clusters is necessary to develop precision therapies for distressing symptoms. This review examined extant literature evaluating relationships between biomarkers and symptom clusters in cancer survivors. Data Sources PubMed, CINAHL, Web of Science and Cochrane Library were searched using terms “biological markers” or “biomarkers” and “symptom cluster” or “symptom complex” or “multiple symptoms”. Results Biomarkers related to inflammation (e.g., cytokines) were the most studied and showed the most significant relationships with clusters of symptoms. Conclusion This review suggest that clustering of symptoms related to cancer or cancer therapy is linked to immune/inflammatory pathways. Implications for Nursing Practice Understanding the etiology of symptom clusters may guide future nursing interventions for symptom management.

Background Fatigue is one of the most debilitating side effects of cancer therapy. Identifying biomarkers early during cancer therapy may help us understand the biologic underpinnings of the persistence of fatigue following therapy. Objective We aimed to identify early biomarkers of fatigue by examining correlations of levels of cytokines during external beam radiation therapy (EBRT) with persistence of fatigue one year following treatment completion in men with non-metastatic prostate cancer (NM-PC). Methods A sample of 34 men with NM-PC scheduled to receive EBRT were followed at baseline (T1), midpoint of EBRT (T2), and one year following EBRT (T3). Demographic and clinical data were obtained by chart review. The Functional Assessment of Cancer Therapy-Fatigue (FACT-F) was administered to measure fatigue levels. Plasma cytokine levels were determined at T1 and T2 using the Bio-Rad Bio-Plex Cytokine Assay Kits. Results Significant correlations were observed between levels of IL-3, IL-8, IL-9, IL-10, IL-16, IP10, IFNα2, IFNγ, and SDF1α at T2 with worsening of fatigue from T1 to T3. Conclusions Immunological changes prior to chronic fatigue development may reflect the long term response to radiation therapy-induced damage. Implications for Practice Early biomarkers for chronic fatigue related to cancer therapy will help advance our understanding of the etiology of this distressing symptom and will help nurses identify patients at risk for developing chronic fatigue after cancer treatment. This information will also aide in patient education, as well as symptom management.

This study aimed to describe frailty and fear of falling and examine the cross‐sectional association between frailty and fear of falling in community‐dwelling older adults in China. We recruited 165 older adults from five selected communities in the five districts of Changchun, Jilin Province. Participants were asked to complete a demographic questionnaire, the Short Falls Efficacy Scale‐International, and the Tilburg Frailty Indicator. We found that 60% of our participants were frail and that 81% reported a fear of falling. Using binary logistic regression, we found that the participants with fear of falling were 7.2 times more likely to be frail. These findings suggest that fear of falling should be regularly screened in clinical practice to help identify older adults with greater risks of frailty. Future longitudinal studies of larger sample size are needed to confirm the association. Moreover, frailty prevention programs that include strategies to reduce the fear of falling should be tested among community‐dwelling older adults.

Background Chronic musculoskeletal pain (CMP) is the most common self-reported chronic pain condition. Current treatment for CMP is limited. Methods This was a two-phase study. In Phase 1, three auricular point acupressure (APA)-naïve participants were recruited to explore their experiences of APA and a smartphone app was developed based on their feedback. In Phase 2, a prospective longitudinal study was used to examine the effectiveness of the smartphone app to self-manage CMP. Results Phase 1 resulted in the successful development of the APA smartphone app. In Phase 2, after four weeks of APA, participants reported reduced pain intensity (30%), pain interference (35%), and disability (40%), as well as improved physical function (47%). The mean score for the participants’ perception of treatment efficacy was 4.94 (SD = 2.08, scale of 0–7) indicating that approximately 70% of participants rated global improvements with noticeable changes. The majority (88%, n = 22) of the participants were satisfied with the treatment: 32% [8] were very satisfied and 56% [n = 14] were somewhat satisfied. The average frequency of pressing APA seeds per day was 2.93 times (SD = 2.27, range 0–10) and 1.60 minutes per time (SD = 2.64, range 0–10); the participants were able to adhere to the suggested pressing time per day, although they only pressed the ear points about 53% of the suggested time. Conclusion It is feasible for individuals to learn APA from the smartphone app and successfully self-administer APA to manage their pain. Participants found the app useful and were satisfied with the information provided through the app.