A Comparison of Approaches for Segmenting the Reaching and Targeting Motion Primitives in Functional Upper Extremity Reaching Tasks.

There is growing interest in the kinematic analysis of human functional upper extremity movement (FUEM) for applications such as health monitoring and rehabilitation. Deconstructing functional movements into activities, actions, and primitives is a necessary procedure for many of these kinematic analyses. Advances in machine learning have led to progress in human activity and action recognition. However, their utility for analyzing the FUEM primitives of reaching and targeting during reach-to-grasp and reach-to-point tasks remains limited. Domain experts use a variety of methods for segmenting the reaching and targeting motion primitives, such as kinematic thresholds, with no consensus on what methods are best to use. Additionally, current studies are small enough that segmentation results can be manually inspected for correctness. As interest in FUEM kinematic analysis expands, such as in the clinic, the amount of data needing segmentation will likely exceed the capacity of existing segmentation workflows used in research laboratories, requiring new methods and workflows for making segmentation less cumbersome. This paper investigates five reaching and targeting motion primitive segmentation methods in two different domains (haptics simulation and real world) and how to evaluate these methods. This work finds that most of the segmentation methods evaluated perform reasonably well given current limitations in our ability to evaluate segmentation results. Furthermore, we propose a method to automatically identify potentially incorrect segmentation results for further review by the human evaluator. Clinical impact: This work supports efforts to automate aspects of processing upper extremity kinematic data used to evaluate reaching and grasping, which will be necessary for more widespread usage in clinical settings.

Towards understanding policy design through text-as-data approaches: The policy design annotations (POLIANNA) dataset.

Despite the importance of ambitious policy action for addressing climate change, large and systematic assessments of public policies and their design are lacking as analysing text manually is labour-intensive and costly. POLIANNA is a dataset of policy texts from the European Union (EU) that are annotated based on theoretical concepts of policy design, which can be used to develop supervised machine learning approaches for scaling policy analysis. The dataset consists of 20,577 annotated spans, drawn from 18 EU climate change mitigation and renewable energy policies. We developed a novel coding scheme translating existing taxonomies of policy design elements to a method for annotating text spans that consist of one or several words. Here, we provide the coding scheme, a description of the annotated corpus, and an analysis of inter-annotator agreement, and discuss potential applications. As understanding policy texts is still difficult for current text-processing algorithms, we envision this database to be used for building tools that help with manual coding of policy texts by automatically proposing paragraphs containing relevant information.

SMRT-AgRenSeq-d in potato (Solanum tuberosum) as a method to identify candidates for the nematode resistance Gpa5.

Potato is the third most important food crop in the world. Diverse pathogens threaten sustainable crop production but can be controlled, in many cases, through the deployment of disease resistance genes belonging to the family of nucleotide-binding, leucine-rich-repeat (NLR) genes. To identify effective disease resistance genes in established varieties, we have successfully established SMRT-AgRenSeq in tetraploid potatoes and have further enhanced the methodology by including dRenSeq in an approach that we term SMR-AgRenSeq-d. The inclusion of dRenSeq enables the filtering of candidates after the association analysis by establishing a presence/absence matrix across resistant and susceptible varieties that is translated into an F1 score. Using a SMRT-RenSeq-based sequence representation of the NLRome from the cultivar Innovator, SMRT-AgRenSeq-d analyses reliably identified the late blight resistance benchmark genes Rpi-R1, Rpi-R2-like, Rpi-R3a, and Rpi-R3b in a panel of 117 varieties with variable phenotype penetrations. All benchmark genes were identified with an F1 score of 1, which indicates absolute linkage in the panel. This method also identified nine strong candidates for Gpa5 that controls the potato cyst nematode (PCN) species Globodera pallida (pathotypes Pa2/3). Assuming that NLRs are involved in controlling many types of resistances, SMRT-AgRenSeq-d can readily be applied to diverse crops and pathogen systems.

Severe, Persistent, Disruptive Fatigue Post-SARS-CoV-2 Disproportionately Affects Young Women.

Introduction: Post-acute SARS-CoV-2 (PASC) symptoms are often persistent, disruptive, and difficult to treat effectively. Fatigue is often among the most frequently reported symptoms and may indicate a more challenging road to recovery. Purpose: To describe the natural history, symptomology, and risk profile of long-term post-acute SARS-CoV-2. Patients and Methods: Participants treated for SARS-CoV-2 within a large, community health system in the US were enrolled prospectively in a longitudinal, observational PASC study examining participants at enrollment and 6 months. Medical history, symptom reporting, validated measures of cognition, and patient-reported outcomes (PROs), were performed for all participants and repeated during study follow-up visits. Results: A total of 323 participants completed baseline evaluations. Sixty one participants indicated clinically significant fatigue (23.1% at baseline); a representative sample of 141 enrollees also completed a baseline Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) in-depth fatigue reporting questionnaire, 37 had severe fatigue. The severely fatigued (FACIT-F ≤29.7) were significantly younger, female, had more anxiety and depression, had a higher resting heart rate, reported more sick days, and were less physically active post-COVID. They were more likely to have a diagnosis of chronic kidney disease (13.5% vs 2.9%) but less likely to have a history of cancer (8.1% vs 23.1). Participants who were severely fatigued reported health, diet, weight, and sleep were worse than those not severely fatigued post-COVID (p = 0.02 to 0.0002). Fatigue was significantly correlated with impairment of all PROs administered after COVID-19 infection. Conclusion: Fatigue is a common symptom post-COVID-19 infection and is associated with lower reported well-being and function. Those with severe fatigue tended to be younger and female and have a past medical history of anxiety, depression, kidney disease, and more sedentary lifestyles.

Toll-like receptor 4 and CD11b expressed on microglia coordinate eradication of Candida albicans cerebral mycosis.

The fungal pathogen Candida albicans is linked to chronic brain diseases such as Alzheimer's disease (AD), but the molecular basis of brain anti-Candida immunity remains unknown. We show that C. albicans enters the mouse brain from the blood and induces two neuroimmune sensing mechanisms involving secreted aspartic proteinases (Saps) and candidalysin. Saps disrupt tight junction proteins of the blood-brain barrier (BBB) to permit fungal brain invasion. Saps also hydrolyze amyloid precursor protein (APP) into amyloid ß (Aß)-like peptides that bind to Toll-like receptor 4 (TLR4) and promote fungal killing in vitro while candidalysin engages the integrin CD11b (Mac-1) on microglia. Recognition of Aß-like peptides and candidalysin promotes fungal clearance from the brain, and disruption of candidalysin recognition through CD11b markedly prolongs C. albicans cerebral mycosis. Thus, C. albicans is cleared from the brain through innate immune mechanisms involving Saps, Aß, candidalysin, and CD11b.

A model for personalized diagnostics for non-specific low back pain: the role of the myofascial unit.

Low back pain (LBP) is the leading cause of disability worldwide. Most LBP is non-specific or idiopathic, which is defined as symptoms of unknown origin without a clear specific cause or pathology. Current guidelines for clinical evaluation are based on ruling out underlying serious medical conditions, but not on addressing underlying potential contributors to pain. Although efforts have been made to identify subgroups within this population based on response to treatment, a comprehensive framework to guide assessment is still lacking. In this paper, we propose a model for a personalized mechanism-based assessment based on the available evidence that seeks to identify the underlying pathologies that may initiate and perpetuate central sensitization associated with chronic non-specific low back pain (nsLBP). We propose that central sensitization can have downstream effects on the "myofascial unit", defined as an integrated anatomical and functional structure that includes muscle fibers, fascia (including endomysium, perimysium and epimysium) and its associated innervations (free nerve endings, muscle spindles), lymphatics, and blood vessels. The tissue-level abnormalities can be perpetuated through a vicious cycle of neurogenic inflammation, impaired fascial gliding, and interstitial inflammatory stasis that manifest as the clinical findings for nsLBP. We postulate that our proposed model offers biological plausibility for the complex spectrum of clinical findings, including tissue-level abnormalities, biomechanical dysfunction and postural asymmetry, ecological and psychosocial factors, associated with nsLBP. The model suggests a multi-domain evaluation that is personalized, feasible and helps rule out specific causes for back pain guiding clinically relevant management. It may also provide a roadmap for future research to elucidate mechanisms underlying this ubiquitous and complex problem.

Evidence for an association of serum microanalytes and myofascial pain syndrome.

BACKGROUND: Myofascial Pain Syndrome (MPS) is a common pain disorder. Diagnostic criteria include physical findings which are often unreliable or not universally accepted. A precise biosignature may improve diagnosis and treatment effectiveness. The purpose of this study was to assess whether microanalytic assays significantly correlate with characteristic clinical findings in people with MPS. METHODS: This descriptive, prospective study included 38 participants (25 women) with greater than 3 months of myofascial pain in the upper trapezius. Assessments were performed at a university laboratory. The main outcome measures were the Beighton Index, shoulder range of motion, strength asymmetries and microanalytes: DHEA, Kynurenine, VEGF, interleukins (IL-1b, IL-2, IL-4, IL-5, IL-7, IL-8, IL-13), growth factors (IGF-1, IGF2, G-CSF, GM-CSF), MCP-1, MIP-1b, BDNF, Dopamine, Noradrenaline, NPY, and Acetylcholine. Mann-Whitney test and Spearman's multivariate correlation were applied for all variables. The Spearman's analysis results were used to generate a standard correlation matrix and heat map matrix. RESULTS: Mean age of participants was 32 years (20-61). Eight (21%) had widespread pain (Widespread Pain Index ≥ 7). Thirteen (34%) had MPS for 1-3 years, 14 (37%) 3-10 years, and 11 (29%) for > 10 years. The following showed strong correlations: IL1b,2,4,5,7,8; GM-CSF and IL 2,4,5,7; between DHEA and BDNF and between BDNF and Kynurenine, NPY and acetylcholine. The heat map analysis demonstrated strong correlations between the Beighton Index and IL 5,7, GM-CSF, DHEA. Asymmetries of shoulder and cervical spine motion and strength associated with select microanalytes. CONCLUSION: Cytokine levels significantly correlate with selected clinical assessments. This indirectly suggests possible biological relevance for understanding MPS. Correlations among some cytokine clusters; and DHEA, BDNF kynurenine, NPY, and acetylcholine may act together in MPS. These findings should be further investigated for confirmation that link these microanalytes with select clinical findings in people with MPS.

Lifestyle interventions in nonalcoholic fatty liver disease.

Nonalcoholic fatty liver disease (NAFLD) is a dynamic chronic liver disease that develops in close association with metabolic irregularities. Between 2016 and 2019, the global prevalence among adults was reported as 38% and among children and adolescents it was about 10%. NAFLD can be progressive and is associated with increased mortality from cardiovascular disease, extrahepatic cancers and liver complications. Despite these numerous adverse outcomes, no pharmacological treatments currently exist to treat nonalcoholic steatohepatitis, the progressive form of NAFLD. Therefore, the main treatment is the pursuit of a healthy lifestyle for both children and adults, which includes a diet rich in fruits, nuts, seeds, whole grains, fish and chicken and avoiding overconsumption of ultra-processed food, red meat, sugar-sweetened beverages and foods cooked at high heat. Physical activity at a level where one can talk but not sing is also recommended, including leisure-time activities and structured exercise. Avoidance of smoking and alcohol is also recommended. Policy-makers, community and school leaders need to work together to make their environments healthy by developing walkable and safe spaces with food stores stocked with culturally appropriate and healthy food items at affordable prices as well as providing age-appropriate and safe play areas in both schools and neighbourhoods.

Effectiveness of Bundled Hyperpolypharmacy Deprescribing Compared With Usual Care Among Older Adults: A Randomized Clinical Trial.

Importance: Older patients using many prescription drugs (hyperpolypharmacy) may be at increased risk of adverse drug effects. Objective: To test the effectiveness and safety of a quality intervention intended to reduce hyperpolypharmacy. Design, Setting, and Participants: This randomized clinical trial allocated patients 76 years or older who used 10 or more prescription medications to a deprescribing intervention or to usual care (1:1 ratio) at an integrated health system with multiple preexisting deprescribing workflows. Data were collected from October 15, 2020, to July 29, 2022. Intervention: Physician-pharmacist collaborative drug therapy management, standard-of-care practice recommendations, shared decision-making, and deprescribing protocols administered by telephone over multiple cycles for a maximum of 180 days after allocation. Main Outcomes and Measures: Primary end points were change in the number of medications and in the prevalence of geriatric syndrome (falls, cognition, urinary incontinence, and pain) from 181 to 365 days after allocation compared with before randomization. Secondary outcomes were use of medical services and adverse drug withdrawal effects. Results: Of a random sample of 2860 patients selected for potential enrollment, 2470 (86.4%) remained eligible after physician authorization, with 1237 randomized to the intervention and 1233 to usual care. A total of 1062 intervention patients (85.9%) were reached and agreed to enroll. Demographic variables were balanced. The median age of the 2470 patients was 80 (range, 76-104) years, and 1273 (51.5%) were women. In terms of race and ethnicity, 185 patients (7.5%) were African American, 234 (9.5%) were Asian or Pacific Islander, 220 (8.9%) were Hispanic, 1574 (63.7%) were White (63.7%), and 257 (10.4%) were of other (including American Indian or Alaska Native, Native Hawaiian, or >1 race or ethnicity) or unknown race or ethnicity. During follow-up, both the intervention and usual care groups had slight reductions in the number of medications dispensed (mean changes, -0.4 [95% CI, -0.6 to -0.2] and -0.4 [95% CI, -0.6 to -0.3], respectively), with no difference between the groups (P = .71). There were no significant changes in the prevalence of a geriatric condition in the usual care and intervention groups at the end of follow-up and no difference between the groups (baseline prevalence: 47.7% [95% CI, 44.9%-50.5%] vs 42.9% [95% CI, 40.1%-45.7%], respectively; difference-in-differences, 1.0 [95% CI, -3.5 to 5.6]; P = .65). No differences in use of medical services or adverse drug withdrawal effects were observed. Conclusions and Relevance: In this randomized clinical trial from an integrated care setting with various preexisting deprescribing workflows, a bundled hyperpolypharmacy deprescribing intervention was not associated with reduction in medication dispensing, prevalence of geriatric syndrome, utilization of medical services, or adverse drug withdrawal effects. Additional research is needed in less integrated settings and in more targeted populations. Trial Registration: ClinicalTrials.gov Identifier: NCT05616689.

HISS: Snakemake-based workflows for performing SMRT-RenSeq assembly, AgRenSeq and dRenSeq for the discovery of novel plant disease resistance genes.

BACKGROUND: In the ten years since the initial publication of the RenSeq protocol, the method has proved to be a powerful tool for studying disease resistance in plants and providing target genes for breeding programmes. Since the initial publication of the methodology, it has continued to be developed as new technologies have become available and the increased availability of computing power has made new bioinformatic approaches possible. Most recently, this has included the development of a k-mer based association genetics approach, the use of PacBio HiFi data, and graphical genotyping with diagnostic RenSeq. However, there is not yet a unified workflow available and researchers must instead configure approaches from various sources themselves. This makes reproducibility and version control a challenge and limits the ability to perform these analyses to those with bioinformatics expertise. RESULTS: Here we present HISS, consisting of three workflows which take a user from raw RenSeq reads to the identification of candidates for disease resistance genes. These workflows conduct the assembly of enriched HiFi reads from an accession with the resistance phenotype of interest. A panel of accessions both possessing and lacking the resistance are then used in an association genetics approach (AgRenSeq) to identify contigs positively associated with the resistance phenotype. Candidate genes are then identified on these contigs and assessed for their presence or absence in the panel with a graphical genotyping approach that uses dRenSeq. These workflows are implemented via Snakemake, a python-based workflow manager. Software dependencies are either shipped with the release or handled with conda. All code is freely available and is distributed under the GNU GPL-3.0 license. CONCLUSIONS: HISS provides a user-friendly, portable, and easily customised approach for identifying novel disease resistance genes in plants. It is easily installed with all dependencies handled internally or shipped with the release and represents a significant improvement in the ease of use of these bioinformatics analyses.

Post-Acute SARS-CoV-2 Symptoms are Fewer, Less Intense Over Time in People Treated with Mono-Clonal Antibodies for Acute Infection.

Introduction: Many with post-acute SARS-CoV-2 (PASC) have persistent symptoms impacting physical and cognitive function, decreased health and health-related life quality. Monoclonal antibody (mAb) treatment was available to acutely infected patients which might improve these outcomes. Purpose: To compare patient perception of PASC symptoms for those receiving bamlanivimab or casirivimab and imdevimab (mAbs) to those not receiving this treatment (non-mAbs). To compare changes between these groups in symptoms, function and quality of life over a 6-month follow-up. Patients and Methods: Consented adults >28 days post-infection with positive SARS-CoV-2 qPCR or antigen test and SARS-CoV-2 infection between March of 2020 and July of 2022 were enrolled. This prospective, repeated measure observational study reports baseline through 6-month follow-up. Extensive sociodemographic data, detailed medical history, COVID-19 symptom history, and standardized measures of well-being, depression, anxiety, stigma, cognition, symptom assessment, distress, and health status were collected. Results: 323 participants [101 mAb, 221 non-mAb, 52.7±15.5 years, 47.7% male, body mass index (BMI) 31.4±8.4] were analyzed. Fewer symptoms at baseline were reported in mAb versus non-mAb participants (1.06±1.31 vs 1.78±2.15, respectively p=0.0177) 6 months: (0.911±1.276 mAb vs.1.75±2.22 non-mAb, p=0.0427). Both groups showed significant within-group decreases in symptom number (52 to 21 mAb, 126 to 63 non-mAb) and symptom burden (p=0.0088 mAb, p<0.00001 non-mAb). mAb patients had significantly shorter infection-to-baseline interval (days) (120.4±55.3 mAb vs 194.0±89.3 non-mAb, p<0.00001); less frequent history of myocardial infarction (0.0 vs 3.9%, p=0.0464); headache (2.0% vs.11.8%, p=0.0046), rash (3.1% vs 9.9%, p=0.0377), and miscellaneous muscle complaints (2.0% vs 12.3%, p=0.0035), plus significantly better 6-month mood. (2.2% vs 13.2%, p=0.0390). Conclusion: mAb treated participants had reduced symptom burden and consistently reported fewer symptoms than non-mAb at all time points despite less time since acute illness. Both groups reported a statistically significant decrease in symptoms by 6-month visit with no statistically significant differences between them at follow-up.

Clinics in Liver Disease: Update on Nonalcoholic Steatohepatitis: Sarcopenia and Nonalcoholic Fatty Liver Disease.

Dual diagnoses of sarcopenia and nonalcoholic fatty liver disease (NAFLD) increase the risk of all cause mortality and severe liver disease, regardless of nationality. General agreement about diagnostic criteria for sarcopenia includes loss of skeletal muscle mass, weakness, and reduced physical performance. Histopathology demonstrates loss of type 2 muscle fibers, more than type 1 fibers and myosteatosis, a risk factor for severe liver disease. Low skeletal mass and NAFLD are inversely related; the mechanism is through decreased insulin signaling and insulin resistance, critical for metabolic homeostasis. Weight loss, exercise, and increased protein intake have been effective in reducing NAFLD and sarcopenia.

Computer-assisted approaches for measuring, segmenting, and analyzing functional upper extremity movement: a narrative review of the current state, limitations, and future directions.

The analysis of functional upper extremity (UE) movement kinematics has implications across domains such as rehabilitation and evaluating job-related skills. Using movement kinematics to quantify movement quality and skill is a promising area of research but is currently not being used widely due to issues associated with cost and the need for further methodological validation. Recent developments by computationally-oriented research communities have resulted in potentially useful methods for evaluating UE function that may make kinematic analyses easier to perform, generally more accessible, and provide more objective information about movement quality, the importance of which has been highlighted during the COVID-19 pandemic. This narrative review provides an interdisciplinary perspective on the current state of computer-assisted methods for analyzing UE kinematics with a specific focus on how to make kinematic analyses more accessible to domain experts. We find that a variety of methods exist to more easily measure and segment functional UE movement, with a subset of those methods being validated for specific applications. Future directions include developing more robust methods for measurement and segmentation, validating these methods in conjunction with proposed kinematic outcome measures, and studying how to integrate kinematic analyses into domain expert workflows in a way that improves outcomes.

Association of physical activity and fine motor performance in individuals with type 2 diabetes mellitus and/or non-alcoholic fatty liver disease.

BACKGROUND: Fine motor performance may serve as an early warning sign for reduced cognitive function. Physical activity can help preserve cognitive function; however, the relationship between fine motor performance and physical activity is not well understood. Therefore, this study examined the relationship between fine motor performance and physical activity in individuals at risk for developing cognitive impairment (those with diabetes and/or non-alcoholic fatty liver disease (NAFLD)). PATIENTS AND METHODS: Individuals aged 25-69 with and without diabetes and NAFLD were enrolled. For this cross-sectional study, all participants completed the Human Activity Profile and fine motor performance tasks (Grooved Pegboard Test and Trail Making Test). RESULTS: There were 93 participants in the study (NAFLD only (n = 29); diabetes + NAFLD (n = 34), controls (n = 30)). Individuals with both diabetes and NAFLD were less physically active and performed slower on the fine motor performance task. A statistically significant correlation was found between physical activity and motor speed among those with NAFLD only (r = 0.436, p<.05), which remained statistically significant after controlling for body mass index (r = 0.385; p<.05). CONCLUSIONS: This study suggests that those with diabetes + NAFLD have lower levels of physical activity and slower fine motor performance. The relationship between physical activity and fine motor performance was only statistically significant in the group of individuals with NAFLD only. Future research needs to explore the mechanisms that impact fine motor performance and physical activity in individuals at risk for mild cognitive impairment. Individuals with diabetes and/or NAFLD should be identified, advised and encouraged to engage in physical activity.Key MessagesThose with NAFLD and T2DM have lower levels of physical activity and slower fine motor performance compared to controls and those with NAFLD only.Future research needs to explore the mechanisms that impact fine motor performance and physical activity in those with T2DM with or without NAFLD.Individuals with impaired fine motor performance should be identified and encouraged to engage in physical activity.

EUBUCCO v0.1: European building stock characteristics in a common and open database for 200+ million individual buildings.

Building stock management is becoming a global societal and political issue, inter alia because of growing sustainability concerns. Comprehensive and openly accessible building stock data can enable impactful research exploring the most effective policy options. In Europe, efforts from citizen and governments generated numerous relevant datasets but these are fragmented and heterogeneous, thus hindering their usability. Here, we present EUBUCCO v0.1, a database of individual building footprints for ~202 million buildings across the 27 European Union countries and Switzerland. Three main attributes - building height, construction year and type - are included for respectively 73%, 24% and 46% of the buildings. We identify, collect and harmonize 50 open government datasets and OpenStreetMap, and perform extensive validation analyses to assess the quality, consistency and completeness of the data in every country. EUBUCCO v0.1 provides the basis for high-resolution urban sustainability studies across scales - continental, comparative or local studies - using a centralized source and is relevant for a variety of use cases, e.g., for energy system analysis or natural hazard risk assessments.

Regular Exercise Is Associated With Low Fatigue Levels and Good Functional Outcomes After COVID-19: A Prospective Observational Study.

OBJECTIVE: The aim of the study is to identify the impact of postacute SARS-CoV-2 infection on patient outcomes. DESIGN: This is a prospective, repeated measure, observational study of consented adults with positive SARS-CoV-2 quantitative polymerase chain reaction or antigen test more than 28 days after infection. Only data from the initial study visit are reported, including disease history, symptoms checklist, patient questionnaires, cognitive tests, social/medical histories, vitals, grip strength, and 2-min walk distance. RESULTS: Two hundred eighteen patients were studied: 100 hospitalized (57.3 ± 15.4 yrs, 62% male, body mass index: 31.3 ± 8.0) and 118 nonhospitalized (46.2 ± 14.6 yrs, 31% male, body mass index: 29.7 ± 7.5). Post-COVID patients reported mean 1.76 symptoms; ≥15% reported fatigue, memory loss, and shortness of breath. Grip strength was 14% lower than norms ( P < 0.0001). Fatigue (Functional Assessment of Chronic Illness Therapy-Fatigue), mood (Patient Health Questionnaire), and well-being (EuroQol 5 Dimension 5 Level) scores were lower than the population norms ( P < 0.05). Hospitalized versus nonhospitalized post-COVID patients performed worse on cognitive assessments (processing speed test-Wechsler Adult Intelligence Scale-Fourth Edition Symbol Search) and reported less regular exercise (≥30 mins ≥3× per week; P < 0.05). In addition, 30% had severe fatigue (by the Functional Assessment of Chronic Illness Therapy-Fatigue); those patients reported less exercise ( P < 0.05). In multivariate models, lack of exercise was independently associated with multiple post-COVID-19 impairments. CONCLUSIONS: Low levels of exercise are an independent risk factor for post-COVID sequelae. Patients who report less exercise have low grip strength, higher levels of fatigue, memory loss, shortness of breath, depression, and poorer quality of life.

Chronic viral coinfections differentially affect the likelihood of developing long COVID.

BACKGROUNDThe presence and reactivation of chronic viral infections, such as EBV, CMV, and HIV, have been proposed as potential contributors to long COVID (LC), but studies in well-characterized postacute cohorts of individuals with COVID-19 over a longer time course consistent with current case definitions of LC are limited.METHODSIn a cohort of 280 adults with prior SARS-CoV-2 infection, we assessed the presence and types of LC symptoms and prior medical history (including COVID-19 history and HIV status) and performed serological testing for EBV and CMV using a commercial laboratory. We used covariate-adjusted binary logistic regression models to identify independent associations between variables and LC symptoms.RESULTSWe observed that LC symptoms, such as fatigue and neurocognitive dysfunction, at a median of 4 months following initial diagnosis were independently associated with serological evidence suggesting recent EBV reactivation (early antigen-diffuse IgG positivity) or high nuclear antigen (EBNA) IgG levels but not with ongoing EBV viremia. Serological evidence suggesting recent EBV reactivation (early antigen-diffuse IgG positivity) was most strongly associated with fatigue (OR = 2.12). Underlying HIV infection was also independently associated with neurocognitive LC (OR = 2.5). Interestingly, participants who had serologic evidence of prior CMV infection were less likely to develop neurocognitive LC (OR = 0.52).CONCLUSIONOverall, these findings suggest differential effects of chronic viral coinfections on the likelihood of developing LC and association with distinct syndromic patterns. Further assessment during the acute phase of COVID-19 is warranted.TRIAL REGISTRATIONLong-term Impact of Infection with Novel Coronavirus; ClinicalTrials.gov NCT04362150.FUNDINGThis work was supported by NIH/National Institute of Allergy and Infectious Diseases grants (3R01AI141003-03S1, R01AI158013, and K24AI145806); the Zuckerberg San Francisco General Hospital Department of Medicine and Division of HIV, Infectious Diseases, and Global Medicine; and the UCSF-Bay Area Center for AIDS Research (P30-AI027763).