Non-fatigue Groups Research Articles

Abstract TMP29: Plasma Proteomics Demonstrates Immune Dysregulation in Chronic Post-Stroke Fatigue

Introduction: Post-stroke fatigue is a common and impactful complaint of stroke survivors. As with fatigue from other causes, our understanding of the biological underpinnings of post-stroke fatigue is poor. Here we used plasma proteomics to better understand post-stroke fatigue. Methods: We report here on 97 participants 5 months to 10 years after ischemic stroke. Functional Assessment of Chronic Illness-Fatigue (FACIT) scale was used to assess fatigue. Disability and self-reported mood was measured using the modified Rankin Scale (mRS) and the Stroke Impact Scale’s mood subset (SIS3), respectively. We dichotomized participants into non-fatigued (FACIT >41) and fatigued (FACIT ≤41) groups and employed a binary logistic regression to examine associations with clinical variables. Aptamer-based proteomics (Somalogic) was used to quantify 7288 plasma proteins, after which we performed pathway analyses. Results: Fatigue was present in 49.4% of our cohort. 39.2% was female and the mean age was 64.2±12.8. When adjusted for age and sex, a prior diagnosis of hypertension (OR=2.7, 95% CI 1.09-6.75, p=0.032) or any psychiatric disorder (OR=8.8, 95% CI 2.54-31, p<0.001) was associated with fatigue. Adjustment for time since stroke did not affect these associations. Higher mRS (rho=-0.49) and worse SIS3 (rho=0.59) were associated with more fatigue. 215 proteins had an absolute correlation coefficient greater than 0.3 and differed between fatigued and non-fatigued patients (p<0.001). Pathway analysis revealed dysregulation of both innate and adaptive immune responses and cytoskeletal regulation. The JAK/STAT pathway was highly dysregulated. In fatigued patients, plasma levels of several components were significantly elevated (log2Fc); CCL5 (0.81), JAK2 (0.73), and STAT3(0.53). The largest downregulation was in fetuin (AHSG, log2Fc -5.5), which contributes to the most down regulated pathway, regulation of ossification, and is an immunosuppressant. Conclusion: Immune dysregulation after stroke may be associated with fatigue, particularly upregulation of the JAK/STAT pathway and downregulation of fetuin. More studies are needed to replicate these findings and to probe mechanisms.

Immunological profiling in long COVID: overall low grade inflammation and T-lymphocyte senescence and increased monocyte activation correlating with increasing fatigue severity.

Many patients with SARS-CoV-2 infection develop long COVID with fatigue as one of the most disabling symptoms. We performed clinical and immune profiling of fatigued and non-fatigued long COVID patients and age- and sex-matched healthy controls (HCs). Long COVID symptoms were assessed using patient-reported outcome measures, including the fatigue assessment scale (FAS, scores ≥22 denote fatigue), and followed up to one year after hospital discharge. We assessed inflammation-related genes in circulating monocytes, serum levels of inflammation-regulating cytokines, and leukocyte and lymphocyte subsets, including major monocyte subsets and senescent T-lymphocytes, at 3-6 months post-discharge. We included 37 fatigued and 36 non-fatigued long COVID patients and 42 HCs. Fatigued long COVID patients represented a more severe clinical profile than non-fatigued patients, with many concurrent symptoms (median 9 [IQR 5.0-10.0] vs 3 [1.0-5.0] symptoms, p<0.001), and signs of cognitive failure (41%) and depression (>24%). Immune abnormalities that were found in the entire group of long COVID patients were low grade inflammation (increased inflammatory gene expression in monocytes, increased serum pro-inflammatory cytokines) and signs of T-lymphocyte senescence (increased exhausted CD8+ TEMRA-lymphocytes). Immune profiles did not significantly differ between fatigued and non-fatigued long COVID groups. However, the severity of fatigue (total FAS score) significantly correlated with increases of intermediate and non-classical monocytes, upregulated gene levels of CCL2, CCL7, and SERPINB2 in monocytes, increases in serum Galectin-9, and higher CD8+ T-lymphocyte counts. Long COVID with fatigue is associated with many concurrent and persistent symptoms lasting up to one year after hospitalization. Increased fatigue severity associated with stronger signs of monocyte activation in long COVID patients and potentially point in the direction of monocyte-endothelial interaction. These abnormalities were present against a background of immune abnormalities common to the entire group of long COVID patients.

Factors Associated with Work Fatigue among Nurses in South Tangerang City Public Hospital

Work fatigue is a pervasive issue that affects nursing care quality and patient safety in healthcare settings. This study examined the prevalence of work fatigue among nurses and its association with various factors, including age, body mass index (BMI), work tenure, and work shift. This study employed a cross-sectional quantitative approach and was conducted at the South Tangerang City Public Hospital from February to March 2023. A total of 85 nurses participated in this study. The Industrial Fatigue Research Committee (IFRC) instrument was used to measure work fatigue, encompassing general, mental, and physical domains. Workload-related symptoms were assessed using Likert scale-based responses, classifying the respondents into fatigue and non-fatigue groups. The results indicated that 55.3% of the nurses reported experiencing work fatigue. Significant associations were observed between work fatigue and several other factors. Older nurses demonstrated a lower prevalence of work fatigue (PR:0.579; 95% CI: 0.415–0.808), suggesting that age is a protective factor against fatigue. Conversely, nurses with non-normal BMI exhibited a higher prevalence of work fatigue (PR: 1.587; 95% CI: 1.100–2.291). A longer work tenure was associated with increased work fatigue (PR: 1.851, 95% CI: 1.298–2.639), possibly due to cumulative stress and physical demands. Furthermore, night-shift nurses experienced higher work fatigue (PR: 1.882, 95% CI: 1.302–2.721) than day-shift nurses, indicating the disruptive impact of irregular sleep patterns. These findings emphasize the need for healthcare organizations to address work fatigue among nurses. Strategies may include workload management, providing resources for emotional support, and promoting a healthy work environment. Addressing the specific vulnerabilities of younger nurses, individuals with non-normal BMI, and working night shifts is vital for mitigating work fatigue

The Impact of Lower Extremity Fatigue on Lower Quadrant Dysfunction and Health Profile in Hairdressers.

Fatigue is also an important occupational condition for hairdressers.The purpose of this study was to determine the lower extremity fatigue and related factors in hairdressers.Lower Extremity Fatigue was assessed with 2 questions containing a 5-point Likert scale. Numerical fatigue rating scale was used to assess general fatigue level, visual analogue scale was used to assess occupational satisfaction, Nottingham Health Profile (NHP) was used to assess health profile, and Cornell Musculoskeletal Discomfort Questionnaire (CMDQ) was used to assess lower quadrant pain profile.In the assessment of lower extremity pain, statistically significant difference was found between Fatigue and Non-fatigue groups in waist (p:0.018), right knee (p:0.020), left knee (p:0.019) and right lower leg (p:0.023) parameters. In the lower extremity Weighted Scores, there were significant differences between the fatigue and non-fatigue groups in waist (p:0.0001), right upper leg (p:0.018), left upper leg (p:0.009), right knee (p:0.0001) left knee (p:0.0001), right lower leg (p:0.001) and left lower leg (p:0.002). The difference in the Energy, Pain and Physical Mobility sub-dimensions of the Nottingham Health Profile of the hairdressers in 'Fatigue Group' was at a significant level.In conclusion, the rate of lower extremity fatigue found in hairdressers in the present study was quite high and lower extremity fatigue was associated with lower extremity pain and health profile.

Is fatigue related to the severity of liver inflammation in patients with chronic liver disease? A cross-sectional study

ObjectivesFatigue is common in patients with chronic liver disease; however, its pathogenesis is unclear. This study aimed to provide insights into the pathogenesis of chronic liver disease-related fatigue by assessing...

Orthostatic Hypotension Is a Predictor of Fatigue in Drug-Naïve Parkinson's Disease.

Fatigue and orthostatic hypotension (OH) are common and disabling nonmotor symptoms (NMSs) of Parkinson's disease (PD), but none of the studies have reported on the longitudinal association between fatigue and OH. Drug-naïve PD patients were recruited from a hospital-based cohort and evaluated with the Parkinson Fatigue Scale (PFS), head-up tilt test, Unified PD Rating Scale, Hoehn and Yahr stage, Montreal Cognitive Assessment, Scale for Outcomes in PD-Autonomic (SCOPA-AUT), Beck Depression Inventory (BDI), Beck Anxiety Inventory, PD Sleep Scale, and medications at the baseline and follow-up visits. A total of 80 patients were included, and the mean ages were 66.6 and 63.8 years in the fatigue and nonfatigue groups, respectively. The prevalence of fatigue was 17.5% (14/80) at the baseline and follow-up (mean follow-up: 23.3 ± 9.9 months). The prevalence of OH in the fatigue group was 57.1%, and it was significantly higher than that of the nonfatigue group. Six of the 14 patients (42.9%) in the fatigue group had persistent fatigue at the follow-up, and eight of them (57.1%) converted to the nonfatigue group. Logistic regression analysis demonstrated that the changes of BDI and the presence of OH at the baseline were the predictors for fatigue in drug-naïve PD. Fatigue is a common NMS in PD but can vary depending on the disease course. OH and depression are the most relevant predictors for the development of fatigue in drug-naïve PD. The present study suggests that the management of autonomic symptoms and depression might be helpful for managing fatigue in PD.

Association of baseline self-reported fatigue with overall survival after stereotactic body radiation therapy for localized prostate cancer.

Stereotactic Body Radiation Therapy (SBRT) has emerged as a definitive therapy for localized prostate cancer (PCa). However, more data is needed to predict patient prognosis to help guide which patients will benefit most from treatment. The FACIT-Fatigue (FACIT-F) is a well validated, widely used survey for assessing fatigue. However, the role of fatigue in predicting PCa survival has yet to be studied. Herein, we investigate the role of FACIT-F as a baseline predictor for overall survival (OS) in patients undergoing SBRT for localized PCa. A retrospective review was conducted of 1358 patients who received SBRT monotherapy between January 2008 to April 2021 at an academic, tertiary referral center. FACIT-F scores (range 0 to 52) were summed for patients who answered all 13-items on the survey. FACIT-F total scores of ≥35 represented severe fatigue. Patients receiving androgen deprivation therapy were excluded. Differences in fatigue groups were evaluated using chi-squared tests. OS rates were determined using the Kaplan-Meier method and predictors of OS were evaluated using Cox proportional hazard method. Baseline full FACIT-F scores and survival data was available for 891 patients. 5-year OS was 87.6% and 95.2%, respectively, for the severely fatigued and non-fatigued groups. Chi-squared analysis of fatigue groups showed no significant difference in the following categories: D'Amico risk group, age, ethnicity, grade group, T-stage, or PSA density. Severe fatigue was associated with a significant decrease in OS (hazard ratio 2.76; 95%CI 1.55 - 4.89). The Cox proportional hazard model revealed that age and FACIT-F were both statistically significant (p <0.05). Baseline FACIT-F scores are significantly associated with OS. Higher FACIT-F scores, representing less fatigued patients, are associated with an overall survival benefit. These results indicate that the FACIT-F survey could serve as an additional metric for clinicians in determining prognostic factors for patients undergoing SBRT.

The Fatigue-Related Symptoms Post-Acute SARS-CoV-2: A Preliminary Comparative Study.

A sizeable sub-group of individuals continue to experience persistent debilitating symptoms post-acute SARS-CoV-2. Although these can vary from person to person, fatigue appears to be the most common symptom. Post-viral fatigue has been documented in conditions such as influenza, infectious mononucleosis and more recently chronic fatigue syndrome (CFS). The current study uses measures that successfully describe the fatigue-related symptoms associated with CFS to investigate the fatigue experienced post-acute SARS-CoV-2. Twenty-six volunteers were recruited from Long COVID support groups active on social media. Data were collected anonymously using an online survey platform. These data were compared to pre-pandemic data from non-fatigued and CFS groups. The post-acute SARS-CoV-2 volunteers reported significantly higher levels of fatigue and cognitive difficulties than the non-fatigued controls. They also report more individual symptoms (such as lack of concentration) and problems with sleep quality. There was a similarity between the post-acute SARS-CoV-2 volunteers and the CFS group in terms of levels of depression, perceived stress, emotional distress and cognitive difficulties. Although this was a small-scale study, it demonstrates the range of symptoms experienced post-acute SARS-CoV-2. In addition, the similarities between this group and CFS suggests the need for further research into the mechanisms at play here, the need to identify those at risk of long-term symptoms and the development of possible interventions.

언어재활사의 주관적 음성피로도와 관련된 음향적 특성*

In addition to administering a questionnaire (J-survey), which questions individuals on subjective vocal fatigue, voice samples were collected before and after speech-language pathology sessions from 50 female speech-language pathologists in their 20s and 30s in the Daejeon and Chungnam areas. We identified significant differences in Korean Vocal Fatigue Index scores between the fatigue and non-fatigue groups, with the most prominent differences in sections one and two. Regarding acoustic phonetic characteristics, both groups showed a pattern in which low-frequency band energy was relatively low, and high-frequency band energy was increased after the treatment sessions. This trend was well reflected in the low-to-high ratio of vowels, slope LTAS, energy in the third formant, and energy in the 4,000-8,000 Hz range. A difference between the groups was observed only in the vowel energy of the low-frequency band (0-4,000 Hz) before treatment, with the non-fatigue group having a higher value than the fatigue group. This characteristic could be interpreted as a result of voice abuse and higher muscle tonus caused by long-term voice work. The perturbation parameter and shimmer local was lowered in the non-fatigue group after treatment, and the noise-to-harmonics ratio (NHR) was lowered in both groups following treatment. The decrease in NHR and the fall of shimmer local could be attributed to vocal cord hypertension, but it could be concluded that the effective voice use of speech-language pathologists also contributed to this effect, especially in the non-fatigue group. In the case of the non-fatigue group, the rhamonics-to-noise ratio increased significantly after treatment, indicating that the harmonic structure was more stable after treatment.

Cognitive fatigability assessment test (cFAST): Development of a new instrument to assess cognitive fatigability and pilot study on its association to perceived fatigue in multiple sclerosis.

BackgroundFatigue is a common symptom of many diseases, including multiple sclerosis. It manifests as a cognitive or physical condition. Fatigue is poorly understood, and effective therapies are missing. Furthermore, there is a lack of methods to measure fatigue objectively. Fatigability, the measurable decline in performance during a task, has been suggested as a complementary method to quantify fatigue.ObjectiveTo develop a new and objective measurement of cognitive fatigability and investigate its association with perceived fatigue.MethodsWe introduced the cognitive fatigability assessment test (cFAST), a novel smartphone-based test to quantify cognitive fatigability. Forty-two people with multiple sclerosis (23 fatigued and 19 non-fatigued, defined by the Fatigue Scale for Motor and Cognitive Functions) took part in our validation study. Patients completed cFAST twice. We used t-tests, Monte Carlo sampling, and area under the receiver operating characteristic curves to evaluate our approach using two sets of proposed metrics.ResultsWhen classifying fatigue, our fatigability metric Δresponse time has a mean area under the receiver operating characteristic curve of 0.74 (95% CI 0.64–0.84), making it the best performing metric for this task. Furthermore, Δresponse time shows a statistically significant difference between the fatigued and non-fatigued groups (t = 2.27, P = .03). Particularly, cognitively-fatigued patients decline in performance, while non-fatigued patients do not.ConclusionsWe introduce cFAST, a new instrument to quantify cognitive fatigability. Our pilot study provides evidence that cognitive fatigability assessment test produces a quantifiable drop in cognitive performance in a short period. Furthermore, our results indicate that cFAST may have the potential to serve as a surrogate for subjective cognitive fatigue. cFAST is significantly shorter than the existing fatigability assessments and does not require specialized equipment. Thus, it could enable frequent and remote monitoring, which could substantially aid clinicians in better understanding and treating fatigue.

Gait Characteristics and Fatigue Profiles When Standing on Surfaces with Different Hardness: Gait Analysis and Machine Learning Algorithms.

Simple SummaryThe purpose of this study was to explore if an anti-fatigue soft mat could improve the gait performance after standing for long periods and to examine if a machine-learning algorithm could evaluate fatigue state objectively. Compared with standing directly on the hard ground, using an anti-fatigue mat could reduce the negative effect of standing for a long time (4 h). The machine-learning algorithm demonstrated moderate accuracy in measuring fatigue. The accuracy of gait parameters used to consider a non-fatigued state following the use of an anti-fatigue mat was higher than that of the fatigue state. The results may indicate that it is beneficial to use anti-fatigue mats when standing for long periods, and it is feasible to use gait parameters and machine-learning algorithms to detect fatigue.Background: Longtime standing may cause fatigue and discomfort in the lower extremities, leading to an increased risk of falls and related musculoskeletal diseases. Therefore, preventive interventions and fatigue detection are crucial. This study aims to explore whether anti-fatigue mats can improve gait parameters following long periods of standing and try to use machine learning algorithms to identify the fatigue states of standing workers objectively. Methods: Eighteen healthy young subjects were recruited to stand on anti-fatigue mats and hard ground to work 4 h, including 10 min rest. The portable gait analyzer collected walking speed, stride length, gait frequency, single support time/double support time, swing work, and leg fall intensity. A Paired sample t-test was used to compare the difference of gait parameters without standing intervention and standing on two different hardness planes for 4 h. An independent sample t-test was used to analyze the difference between males and females. The K-nearest neighbor (KNN) classification algorithm was performed, the subject’s gait characteristics were divided into non-fatigued and fatigue groups. The gait parameters selection and the error rate of fatigue detection were analyzed. Results: When gender differences were not considered, the intensity of leg falling after standing on the hard ground for 4 h was significantly lower than prior to the intervention (p < 0.05). When considering the gender, the stride length and leg falling strength of female subjects standing on the ground for 4 h were significantly lower than those before the intervention (p < 0.05), and the leg falling strength after standing on the mat for 4 h was significantly lower than that recorded before the standing intervention (p < 0.05). The leg falling strength of male subjects standing on the ground for 4 h was significantly lower than before the intervention (p < 0.05). After standing on the ground for 4 h, female subjects’ walking speed and stride length were significantly lower than those of male subjects (p < 0.05). In addition, the accuracy of testing gait parameters to predict fatigue was medium (75%). After standing on the mat was divided into fatigue, the correct rate was 38.9%, and when it was divided into the non-intervention state, the correct rate was 44.4%. Conclusion: The results show that the discomfort and fatigue caused by standing for 4 h could lead to the gait parameters variation, especially in females. The use of anti-fatigue mats may improve the negative influence caused by standing for a long period. The results of the KNN classification algorithm showed that gait parameters could be identified after fatigue, and the use of an anti-fatigue mat could improve the negative effect of standing for a long time. The accuracy of the prediction results in this study was moderate. For future studies, researchers need to optimize the algorithm and include more factors to improve the prediction accuracy.

Understanding fatigue in progressive supranuclear palsy

Fatigue is a common and disabling non-motor symptom (NMS) of Parkinson’s disease (PD); however, it has been poorly understood in patients with progressive supranuclear palsy (PSP). We investigated the association between fatigue, clinical features, and other NMS in patients with probable PSP. In 72 probable PSP patients, fatigue was investigated using the Parkinson Fatigue Scale (PFS). Further, all patients were evaluated using the PSP rating scale (PSPRS), Beck Depression Inventory (BDI), Mini-Mental State Examination (MMSE), Frontal Assessment Battery (FAB), PD Sleep Scale (PDSS), NMS scale (NMSS), PD Questionnaire-39 summary index (PDQ-39 SI), and Scale for outcomes in PD-Autonomic (SCOPA-AUT). The prevalence of fatigue assessed by PFS was 38.9% (28/72) in patients with PSP. The secondary fatigue was defined as fatigued patients with depression and/or sleep disturbances. We divided the patients into primary (n = 15), secondary (n = 13), and non-fatigue groups. There were no differences in age, sex, disease duration, and PSPRS, PDSS, MMSE, and FAB scores among the three groups. The primary fatigue group had higher scores in PDQ-39 SI compared to the non-fatigue group. The secondary fatigue group showed higher scores in NMSS, PDQ-39 SI, and SCOPA-AUT compared to the non-fatigue group. PFS was positively correlated with NMSS and PDQ-39 SI and SCOPA-AUT. Fatigue is common in patients with PSP and is associated with the NMS and the quality of life in these patients. The present study provides meaningful insight into fatigue in patients with PSP.

Risk Factors and Imaging Mechanisms of Fatigue After Mild Ischemic Stroke: An Exploratory Study From a Single Chinese Center.

Objective: To explore the biochemical risk factors and imaging mechanisms of post fatigue after mild ischemic stroke among a Chinese population.Methods: Forty consecutive patients with mild ischemic stroke within onset of 14 ± 2 days were enrolled between March and June 2018. The clinical information, scale data, biomarkers in peripheral venous blood, and imaging data during hospitalization and follow-up period were collected.Results: Patient age (range 34–78) was positively correlated with the prevalence of fatigue (p = 0.009). Both blood norepinephrine and serotonin levels during hospitalization were negatively correlated to the prevalence of post-stroke fatigue (model 1 p = 0.009 and model 2 P = 0.043, respectively). Infarct of right cerebral hemisphere is positively correlated with the occurrence of fatigue after mild ischemic stroke (p = 0.020). Compared to non-fatigue patients, amplitude of low-frequency fluctuation (ALFF) was lower in several areas of brain in stroke patients with fatigue, including the right orbital inferior frontal, right inner orbital frontal, right frontal, right triangular frontal inferior, right anterior and lateral cingulate, and right medial frontal gyruses. Analysis of the difference in functional connectivity between the fatigue and non-fatigue groups found no cluster.Conclusions: Frontal lobe-related neural pathways may play an essential role in the regulation of fatigue after mild ischemic stroke. Abnormal neural circuits may reduce the levels of neurotransmitters such as serotonin and norepinephrine and lead to post-stroke fatigue.

4313 Impaired Natural Killer Cell Function May Be Associated with Cancer-related Fatigue

OBJECTIVES/GOALS: During and after cancer treatment, cancer-related fatigue (CRF) is a debilitating symptom reported by up to 80% of cancer patients Our understanding of the pathology underlying CRF is limited. Preliminary RNA sequencing data suggest that increased levels of KIR3DL1, the natural killer cell (NK) immunoglobulin-like receptor 3DL1a, may be associated with CRF. METHODS/STUDY POPULATION: Fatigue was measured using the Functional Assessment of Chronic Illness Therapy-Fatigue (FACT-F). Functional validation of the NK cell finding was performed from whole blood obtained from fatigued and non-fatigued subjects. NK cells were isolated from freshly collected whole blood using a human NK cell isolation kit based on CD56 microbead positive selection. NK cell function was assessed using the NK cell direct cytotoxicity assay. Briefly, isolated NK cells were co-cultured in a 2:1 ratio with calcein AM-labelled K562 cells, which are NK cell-sensitive due to the very low MHCI expression. NK cell-mediated cytotoxicity was assessed with Cytation 1 Cell Imaging Multi-Mode reader. Flow cytometric protocols were used to examine NK subset differences between the fatigued and non-fatigued groups. RESULTS/ANTICIPATED RESULTS: NK cells isolated from the fatigued group exhibited decreased cytotoxicity at 12.28% compared to NK cells isolated from non-fatigued controls at a mean of 40.6% cytotoxicity. Flow cytometry analysis revealed a decrease in the CD56dim CD16bright population in the fatigued group (87.1% of CD56+CD4- cells) compared to the control (91.4% of CD56+CD4- cells). Furthermore, there was a decrease in NKG2A expression in mature NK cells (CD56dim CD16bright) isolated from the fatigued group compared to the non-fatigued group. DISCUSSION/SIGNIFICANCE OF IMPACT: Results from the pilot study suggest that there was a decrease in NK cell cytotoxicity in the fatigued group. In addition, there may be a shift in NK cell subpopulations associated with fatigue. Findings from this pilot study suggest that impaired NK cell function may be associated with CRF pathogenesis.

The Dysfunctional Autonomic Function and "Dysfunctional" Fatigue in Drug Naïve Parkinson's Disease.

Fatigue is a common and disabling non-motor symptom in Parkinson's disease (PD). Autonomic dysfunction is suggested as the possible pathophysiology of fatigue, but it has not been investigated in drug-naïve PD patients. In the present study, the relationship between fatigue and autonomic dysfunction in drug-naïve PD patients was investigated. In the present study, 89 drug-naïve PD patients were analyzed. The Parkinson's disease fatigue scale (PFS) was used to divide the patients into fatigue (mean PFS≥3.3) and non-fatigue groups (mean PFS < 3.3). The autonomic function test (AFT), Scale for Outcomes in Parkinson's Disease-Autonomic (SCOPA-AUT), Unified Parkinson's Disease Rating Scale (UPDRS)-I, -II, -III, modified Hoehn and Yahr (H&Y) scale, Montreal Cognitive Assessment (MoCA), Parkinson's Disease Questionnaire-39 (PDQ-39), Parkinson's Disease Sleep Scale (PDSS), and Beck Depress Index (BDI) were performed in all the participants. The AFT results and clinical scales were compared using multiple logistic regression analysis. The prevalence of fatigue was 23.6% (n = 21) in drug-naïve PD patients. Total SCOPA-AUT score was higher in the fatigue group than in the non-fatigue group. The fatigue group had lower inspiratory:expiratory (I:E) ratio and Valsalva ratio. The prevalence of abnormal sympathetic skin response and orthostatic hypotension (OH) was 19% and 38.1%, respectively, in the fatigue group. Regression model analysis revealed that SCOPA-AUT and OH were the most related factor of fatigue in drug-naïve PD patients. Autonomic dysfunction in drug-naïve PD patients was investigated using a subjective scale as well as objective tests. The results indicated that fatigue is associated with autonomic dysfunction, especially OH, in drug-naïve PD patients.

Fatigue in Ankylosing Spondylitis Is Associated With Psychological Factors and Brain Gray Matter

Background: Ankylosing spondylitis (AS) is a rheumatic inflammatory disease with unknown etiology, and fatigue is one of the main systemic symptoms of AS. The aim of the current study was to explore the mechanism of AS-associated fatigue (ASF) from multiple aspects, including neuropsychological changes.Method: A total of 120 AS patients and 78 age- and sex-matched healthy individuals were recruited into the study. Fatigue was assessed by the fatigue item of the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and the Multidimensional Assessment of Fatigue (MAF) scale. Anxiety and depression were assessed by the Hospital Anxiety and Depression Scale (HADS). The cortical thickness and subcortical gray matter volume were assessed using a Philips Achieva 3.0 T TX MRI scanner.Result: Of the 120 AS patients, 103 (85.8%) reported varying degrees of fatigue. Among these fatigue cases, 33 (32.0%) were in the severe fatigue group (BASDAI-Fatigue ≥ 5), and 70 patients (68.0%) were considered to be in the mild fatigue group (BASDAI-Fatigue > 0 but <5). The BASDAI, ASDAS-CRP, HAD-A, and HAD-D scores of AS patients in the severe fatigue group were all significantly higher than those of patients in the mild fatigue and non-fatigue groups (all, P < 0.05). The structural equation model suggested that AS activity triggered the occurrence of fatigue by inducing psychological change. Finally, head MRI imaging found that the left thalamus volume in AS patients with severe fatigue was significantly larger than that in non-fatigue AS patients and healthy controls (both, P < 0.05).Conclusion: The study revealed neuropsychological factors involved in fatigue in AS.

Effect of Self-perceived Fatigue on Balance and Functional Mobility in Middle-Aged Obese Women.

The aim of this study was to examine effect of fatigue levels on functional mobility and balance in middle-aged obese females. The study included 98 healthy females aged 40-60 years with BMI ≥ 30 kg/m2. Self-perceived fatigue was evaluated with a self-administered questionnaire, the Checklist of Individual Strength in Turkish (CIS-T), on which 62.3% of the study subjects identified themselves as fatigued. The body weight and BMI values of fatigued subjects were found to be higher than those of the non-fatigue group (p<0.05). The reported exercise habits of the fatigue group were found to be significantly lower than their non-fatigued peers (p<0.05). The level of functional mobility (Timed Up and Go Test), static balance (One-Legged Stance Test with Eyes Open) and dynamic balance (Functional Reach Test and the 3-meter Timed Tandem Walk Test) were measured, and statistically significant differences were found between fatigue and non-fatigue groups on all of them (p<0.05). In addition, correlations were found between the sub-parameters of the CIS-T scale and the functional tests at.

A prospective study on peptide mapping of human fatigue saliva markers based on magnetic beads.

In order to explore convenient and stable fatigue markers, we studied various high-molecular-weight peptide fragments under fatigue state and non-fatigue state in the saliva using time of flight mass spectrometry. The saliva samples were collected from 10 healthy volunteers that were in the condition of fatigue and non-fatigue, respectively. Moreover, the time of flight mass spectrometry was conducted using two kinds of sample treatment methods, the magnetic beads enrichment (MB) and direct detection of stock solution. This was followed by modeling via the mass spectra of MB and supernatant (stock solution) directly collected after centrifugation. Both MB and direct sampling produced good spectrograms between 1,000 and 15,000 Da, while some peaks were lost in the enrichment. The spectrograms in the early and late period were different in each individual. Due to the limited sample size, 20 early and 20 late spectrograms were used for modeling analysis. Three different peptides were identified in the stock solution samples that can be detected in both fatigue and non-fatigue groups. The cross validity of MB model was 92.06%, while that of the stock solution model was 95.49%. The results showed that there were different peaks within the molecular weight of 2,000-15,000 Da, which provided a scientific basis for further realization of the convenient fatigue detection method based on the biosensor technique, with important theoretical and practical significance.

Assessment of muscle fatigue during isometric contraction using autonomic nervous system correlates

Muscle fatigue is a complex phenomenon that results in a reduction of the maximal voluntary force. Measuring muscle fatigue can be a challenging task that may involve the use of intramuscular electrodes (i.e., intramuscular electromyography (EMG)) or complex acquisition techniques. In this study, we propose an alternative non-invasive methodology for muscle fatigue detection relying on the analysis of two autonomic nervous system (ANS) correlates, i.e., the electrodermal activity (EDA) and heart rate variability (HRV) series. Based on standard surface EMG analysis, we divided 32 healthy subjects performing isometric biceps contraction into two groups: a fatigued group and a non-fatigued group.EDA signals were analyzed using the recently proposed cvxEDA model in order to derive phasic and tonic components and extract effective features to study ANS dynamics. Furthermore, HRV series were processed to derive several features defined in the time and frequency domains able to estimate the cardiovascular autonomic regulation. A statistical comparison between the fatigued and the non-fatigued groups was performed for each ANS feature, and two EDA features, i.e., the tonic variability and the phasic response rate, showed significant differences. Moreover, a pattern recognition procedure was applied to the combined EDA-HRV feature-set to automatically discern between fatigued and non-fatigued subjects. The proposed SVM classifier, following a recursive feature elimination stage, exhibited a maximal balanced accuracy of 83.33%. Our results demonstrate that muscle fatigue could be identified in a non-invasive fashion through effective EDA and HRV processing.

Discovery and identification of fatigue-related biomarkers in human saliva.

To identify stable and specific biomarkers/biomarker combinations for fatigue assessment and establish a discriminant model. Saliva was collected and electroencephalogram analysis was performed for 47 emergency physicians while awake and after continuoutas duty for 18-24 h. Physicians were divided into the fatigue and non-fatigue groups. Protein spectra of completely quantified saliva specimens were identified before and after long working hours using mass spectrometry. Data were analyzed through Proteome Discoverer software combined with SEQUEST to search protein databases. Proteins were characterized by collision-induced dissociation spectra. A global internal standard (GIS) was added to each group of samples and labeled by tandem mass tags m/z 131.1. All data were compared with GIS, and data between groups were further compared. Qualitative and quantitative data on proteins were exported for fatigue-related proteomic analysis, and a fatigue assessment model was established. We identified 767 salivary proteins in the fatigue group. The correct rates of the discriminant function of the non-fatigue and fatigue groups were 97.1% and 91.7%, respectively (the total correct rate was 95.7%). We identified 30 fatigue-related protein markers from saliva. We also established a fatigue assessment model for emergency physicians using salivary biomarkers.