BackgroundCOVID-19 disease results in disparate responses between individuals and has led to the emergence of long coronavirus disease (Long-COVID), characterised by persistent and cyclical symptomology. To understand the complexity of Long-COVID, the importance of symptom surveillance and prospective longitudinal studies is evident.MethodsA 9-month longitudinal prospective cohort study was conducted within Scotland (n=287), using a mobile app to determine the proportion of recovered individuals and those with persistent symptoms and common symptoms, and associations with gender and age.Results3.1% of participants experienced symptoms at month 9, meeting the criteria for Long-COVID, as defined by the National Institute for Health and Care Excellence terminology. The random effects model revealed a significant time (month) effect for infection recovery (p<0.001, estimate=0.07). Fatigue, cough and muscle pain were the most common symptoms at baseline, with fatigue persisting the longest, while symptoms like cough improved rapidly. Older age increased the likelihood of reporting pain (p=0.028, estimate=0.07) and cognitive impairment (p<0.001, estimate=0.93). Female gender increased the likelihood of headaches (p=0.024, estimate=0.53) and post-exertional malaise (PEM) frequency (p=0.05, estimate=137.68), and increased time x gender effect for PEM frequency (p=0.033, estimate=18.96).ConclusionsThe majority of people fully recover from acute COVID-19, although often slowly. Age and gender play a role in symptom burden and recovery rates, emphasising the need for tailored approaches to Long-COVID management. Further analysis is required to determine the characteristics of the individuals still reporting ongoing symptoms months after initial infection to identify risk factors and potential predictors for the development of Long-COVID.

BACKGROUND:There has been some effort to map the prevalence, frequency, and severity of symptoms of long COVID at local and national levels. However, what is frequently absent from such accounts is details of the impact the disease and its symptoms have had on those living with the condition. In this article, we present details of the impact on work, caring, and mental health gathered using a cross-sectional survey. METHODS:Data were collected using an online survey that was available from April 21, 2022, to August 5, 2022. Included participants had either self-diagnosed or confirmed long COVID, were living in Scotland, and were aged ≥18 years. Hospitalization during initial COVID-19 infection was an exclusion criterion. Participants were asked to report on the impact of their illness on everyday activities such as working, studying, or caring. They also completed an assessment of their current mood. RESULTS:People with long COVID were often severely impacted in their ability to work and study. Severe impact on work and study were predicted by more severe and more frequent fatigue, more severe pain, and more severe cognitive impairment. Respondents' ability to care for child dependents was also associated with more severe and more frequent fatigue, and more severe cognitive impairments. More severe pain associated with greater impact on adult care. Negative mood correlated most strongly with frequency and severity of neurological symptoms, including lack of attention, loss of smell, impaired sense of smell, loss of taste, impaired sense of taste, and loss of appetite. CONCLUSIONS:Long COVID has a significant impact on ability to work, study, and care for dependents. The severity of this impact is associated with specific symptom burden, including fatigue, pain, and cognitive impairment.

Background: People with Multiple Sclerosis (PwMS) find it more difficult to engage in physical activity (PA) than healthy controls. Accelerometers can be used to measure sedentary time and free-living physical activity, understanding the differences between PwMS and controls can help inform changes such as interventions to promote a more active lifestyle. This in turn will help prevent secondary conditions and reduce symptom progression. Objective: To conduct a systematic review and meta-analysis on accelerometer measured sedentary behavior and physical activity between PwMS and healthy controls. Methods: A systematic search of five databases (PubMed, Web of Science, Ovid, Science Direct and CINAHIL) from inception until 22nd November 2019. Inclusion criteria was (1) included a group of participants with a definite diagnosis of multiple sclerosis of any type; (2) have 3 or more days of PA monitoring using accelerometers during free living conditions; (3) include age matched healthy controls; (4) assess adults over the age of 18; (5) reported data had to have been reported in a manner suitable for quantitative pooling including: percent of time spent sedentary, minutes per day of sedentary, light, moderate, vigorous activity (moderate and vigorous totaled together), steps per day or counts per day. Results: Initial search produced 9021 papers, after applying inclusion criteria 21 eligible papers were included in the study. One paper was a longitudinal study from which only baseline data was included. One paper was a reliability and validity study, with data for PwMS versus controls in the validity section. All other papers are cross sectional, with one being a pilot study and another a random control study. One paper used two devices in unison, only one set of data is included in the statistics. Outcome data was available for 1098 participants, 579 PwMS and 519 healthy controls. Significant differences were seen in all categories tested: (1) sedentary time (min/day), standard mean difference -0.286, P = 0.044, n = 4 studies; (2) relative sedentary time (%/day), standard mean difference -0.646, P = 0.000, n = 5 studies; (3) LPA (min/day), standard mean difference 0.337, P = 0.039, n = 5 studies; (4) relative LPA (%/day), standard mean difference 0.211, P = 0.152, n = studies; (5) MVPA (min/day), standard mean difference 0.801, P = 0.000, n = 8 studies; (6) relative MVPA (%/day), mean difference 0.914, P = 0.000, n = 5 studies; (7) step count, standard mean difference 0.894, P = 0.000, n = 8 studies; (8) activity count, standard mean difference 0.693, P = 0.000, n = 13 studies. Conclusion: PwMS are more sedentary and engage in less LPA, MVPA, steps per day and accelerometer counts per day than healthy controls when measured using accelerometers during free-living conditions.

BACKGROUND:Multiple Sclerosis (MS) is a chronic disorder which irreversibly damages axons within brain matter. Blood lactate concentration could be a biomarker of MS onset and progression, but no systematic review has yet sought to confirm or dispute the elevation and biomarker potential of blood lactate in people with MS (PwMS) or to consolidate understanding of lactate production during exercise in PwMS. OBJECTIVE:To perform a systematic review and meta-analysis on blood lactate in PwMS during rest and exertion compared to Healthy Controls (HC) and following chronic exercise intervention. METHODS:A systematic search of six electronic databases (PubMed, CINAHL, Science Direct, Cochrane Library, SPORTDiscus and PEDro) was performed on 10th April 2020. Mean, standard deviation and sample size for lactate measures at rest and during exercise were pooled to determine overall effect size using a random effects model.  The 20-point Appraisal tool for Cross-Sectional Studies was utilised to assess study quality and inherent risk of bias. To qualify for inclusion, studies had to include human adults (>18 years) with a confirmed clinical diagnosis of MS, be published in English, have undergone peer review, report absolute blood lactate values for data extraction, and if involving testing during/after exercise, to do so during bilateral exercise methods. RESULTS:18 studies were qualitatively analysed and 15 studies quantitatively analysed. Outcome data was available for 1986 participants (nMS = 1129). A total of 7 papers tested blood lactate during rest (LactateREST), 7 papers tested during sub-maximal intensity exercise (LactateSUB-MAX), and 8 papers tested during maximal intensity exercise (LactateMAX). Meta analyses showed elevated LactateREST and reduced LactateMAX in PwMS compared to HC, higher LactateMAX in lower EDSS-scoring PwMS compared to higher EDSS-scoring PwMS, and that LactateSUB-MAX decreases and LactateMAX increases in PwMS following a chronic exercise intervention. Qualitative analysis reported LactateREST to be reduced in PwMS following a chronic exercise intervention. CONCLUSIONS:LactateREST is elevated in PwMS compared to HC. LactateMAX is lower in PwMS compared to HC and lower still in higher compared to lower EDSS-scoring groups of PwMS. Chronic exercise interventions have the potential to reduce LacatateSUB-MAX for a given power output and increase LactateMAX in PwMS compared to baseline values. LactateREST may be reduced in PwMS following a chronic exercise intervention but more research is required for confirmation. The results of this review were limited by small sample sizes and number of studies available for each testing condition, limited data available for potentially confounding/correlating factors (eg. VO2 and power output) as well as heterogeneity of methodology adopted across studies, often due to lactate testing being a secondary outcome measure. PLS: Lactate levels in the blood are different during rest and at intense exercise levels in people with Multiple Sclerosis (MS) compared to healthy counterparts, with people with MS showing a smaller jump in lactate during intense exercise from a higher resting level. After exercising for at least 3 months, blood lactate levels during exercise may become more similar to the levels seen in people without Multiple Sclerosis, but more research is required to give a clearer picture of this. We can hopefully use blood lactate in future to measure the progression of MS in an individual as well as the effectiveness of their exercise programme.