Using Presurgical Biopsychosocial Features to Develop an Advanced Clinical Decision-Making Support Tool for Predicting Recovery Trajectories in Patients Undergoing Total Knee Arthroplasty: Protocol for a Prospective Observational Study.

BACKGROUND: Following total knee arthroplasty (TKA), 10% to 20% of patients report dissatisfaction with procedural outcomes. There is growing recognition that postsurgical satisfaction is shaped not only by the quality of surgery but also by psychological and social factors. Surprisingly, information on the psychological and social determinants of surgical outcomes is rarely collected before surgery. A comprehensive collection of biopsychosocial information could assist clinicians in making recommendations in relation to rehabilitation, particularly if there is robust evidence to support the ability of presurgical constructs to predict postsurgical outcomes. Clinical decision support tools can help identify factors influencing patient outcomes and support the provision of interventions or services that can be tailored to meet individuals' needs. However, despite their potential clinical benefit, the application of such tools remains limited. OBJECTIVE: This study aims to develop a clinical decision tool that will assist with patient stratification and more precisely targeted clinical decision-making regarding prehabilitation and rehabilitation for TKA, based on the identified individual biopsychosocial needs. METHODS: In this prospective observational study, all participants provided written or electronic consent before study commencement. Patient-completed questionnaires captured information related to a broad range of biopsychosocial parameters during the month preceding TKA. These included demographic factors (sex, age, and rurality), psychological factors (mood status, pain catastrophizing, resilience, and committed action), quality of life, social support, lifestyle factors, and knee symptoms. Physical measures assessing mobility, balance, and functional lower body strength were performed via video calls with patients in their home. Information related to preexisting health issues and concomitant medications was derived from hospital medical records. Patient recovery outcomes were assessed 3 months after the surgical procedure and included quality of life, patient-reported knee symptoms, satisfaction with the surgical procedure, and mood status. Machine learning data analysis techniques will be applied to determine which presurgery parameters have the strongest power for predicting patient recovery following total knee replacement. On the basis of these analyses, a predictive model will be developed. Predictive models will undergo internal validation, and Bayesian analysis will be applied to provide additional metrics regarding prediction accuracy. RESULTS: Patient recruitment and data collection commenced in November 2019 and was completed in June 2022. A total of 1050 patients who underwent TKA were enrolled in this study. CONCLUSIONS: Our findings will facilitate the development of the first comprehensive biopsychosocial prediction tool, which has the potential to objectively predict a patient's individual recovery outcomes following TKA once selected by an orthopedic surgeon to undergo TKA. If successful, the tool could also inform the evolution rehabilitation services, such that factors in addition to physical performance can be addressed and have the potential to further enhance patient recovery and satisfaction. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48801.

Neurometabolic changes in multiple sclerosis: Fingolimod versus beta interferon or glatiramer acetate therapy.

BACKGROUND AND PURPOSE: Fingolimod has been shown to be more effective in reducing relapse rate and disability than injectable therapies in clinical trials. An increase in N-acetylaspartate (NAA) as measured by MR spectroscopy is correlated with maintaining axonal metabolic functions. This study compared the neurometabolic and volumetric changes in relapsing-remitting multiple sclerosis (RRMS) patients on fingolimod or injectable therapies with healthy controls (HCs). METHODS: Ninety-eight RRMS (52 on fingolimod, 46 on injectable therapies (27 on glatiramer acetate and 19 on interferon) were age and sex-matched to 51 HCs. RRMS patients underwent cognitive, fatigue, and mental health assessments, as well as an Expanded disability status scale (EDSS). MRI/S was acquired from the hippocampus, posterior cingulate gyrus (PCG), and prefrontal cortex (PFC). Volumetric and neurometabolic measures were compared across cohorts using a univariate general linear model and correlated with clinical severity and neuropsychological scores. RESULTS: Clinical parameters, MR-volumetric, and neurometabolic profiles showed no differences between treatment groups (p > .05). Compared to HCs, both RRMS cohorts showed volume changes in white matter (-13%), gray matter (-16%), and cerebral spinal fluid (CSF) (+17-23%), as well as reduced NAA (-17%, p = .001, hippocampus), (-7%, p = .001, PCG), and (-9%, p = .001, PFC). MRI/S metrics in three regions were moderately correlated with cognition and fatigue functions. CONCLUSION: While both treatment arms showed overall similar volumetric and neurometabolic profiles, longitudinal studies are warranted to clarify neurometabolic changes and associations with treatment efficacy.

Do people with multiple sclerosis receive appropriate support from the National Disability Insurance Scheme matching their level of disability? A description of disease 'burden and societal cost in people with multiple sclerosis in Australia' (BAC-MS).

Objective This study is the first to assess if the National Disability Insurance Scheme (NDIS) package allocated to people with multiple sclerosis (pwMS) is correlated with the disability level measured by standardised neurological assessment. Methods We aimed to recruit 10 pwMS per expanded disability status score (EDSS) step, including EDSS 0 (no disability) up to 9 (bedridden), and requested information about their NDIS application. Value of their packages was compared with mobility, cognition and psychological impact. Results Out of 186 pwMS, only 49% of all patients had an NDIS package approved. The mean values of the annual allowance were AU$30 318 for patients with mild disability, AU$38 361 for moderate disability and AU$115 113 for severe disability. There was a striking variability in packages approved, but restricted mobility seems to be the driving factor. Rejection rates were <20% in patients with mild and moderate disability and none in those with severe disability. The package value correlated with EDSS steps, cognitive impairment and physical impact, but not psychological impact. Conclusions This is the first study to assess if NDIS packages correlate with internationally accepted disability scales. The NDIS support was correlated with disability measured by EDSS steps and cognition, but not psychological impact of the disease. What is known about the topic? There are over 25 000 Australians living with multiple sclerosis, which is one of the most common neurological diseases leading to disability in early age. The National Disability Insurance Scheme has been introduced since 2013 to particularly assist young disabled Australians to participate in the community. Whether the approved package correlates with internationally accepted disability scores has not yet been assessed. What does this paper add? This study is the first to correlate disability, as assessed by the Expanded Disability Severity Scale (EDSS), with the approved package value. What are the implications for practitioners? Multiple sclerosis is a very variable disease affecting quality of life not only due to impairment of mobility, but also cognition and mental health. Although the NDIS package value was correlated with an EDSS and cognition, the psychological impact of the disease is often neglected.

Biochemical Correlations with Fatigue in Multiple Sclerosis Detected by MR 2D Localized Correlated Spectroscopy.

BACKGROUND AND PURPOSE: Fatigue is the common symptom in patients with multiple sclerosis (MS), yet its pathophysiological mechanism is poorly understood. We investigated the metabolic changes in fatigue in a group of relapsing-remitting MS (RRMS) patients using MR two-dimensional localized correlated spectroscopy (2D L-COSY). METHODS: Sixteen RRMS and 16 healthy controls were included in the study. Fatigue impact was assessed with the Modified Fatigue Impact Scale (MFIS). MR 2D L-COSY data were collected from the posterior cingulate cortex. Nonparametric statistical analysis was used to calculate the changes in creatine scaled metabolic ratios and their correlations with fatigue scores. RESULTS: Compared to healthy controls, the RRMS group showed significantly higher fatigue and lower metabolic ratios for tyrosine, glutathione, homocarnosine (GSH+Hca), fucose-3, glutamine+glutamate (Glx), glycerophosphocholine (GPC), total choline, and N-acetylaspartate (NAA-2), while increased levels for isoleucine and glucose (P ≤ .05). Only GPC showed positive correlation with all fatigue domains (r = .537, P ≤ .05). On the other hand, Glx-upper, NAA-2, GSH+Hca, and fucose-3 showed negative correlations with all fatigue domains (r = -.345 to -.580, P ≤ .05). While tyrosine showed positive correlation with MFIS (r = .499, P ≤ .05), cognitive fatigue was negatively correlated with total GSH (r = -.530, P ≤ .05). No correlations were found between lesion load or brain volumes with fatigue score. CONCLUSIONS: Our results suggest that fatigue in MS is strongly correlated with an imbalance in neurometabolites but not structural brain measurements.

Spiral MRSI and tissue segmentation of normal-appearing white matter and white matter lesions in relapsing remitting multiple sclerosis patients☆.

PURPOSE: To evaluate the performance of novel spiral MRSI and tissue segmentation pipeline of the brain, to investigate neurometabolic changes in normal-appearing white matter (NAWM) and white matter lesions (WML) of stable relapsing remitting multiple sclerosis (RRMS) compared to healthy controls (HCs). METHODS: Spiral 3D MRSI using LASER-GOIA-W [16,4] was undertaken on 16 RRMS patients and 9 HCs, to acquire MRSI data from a large volume of interest (VOI) 320 cm3 and analyzed using LCModel. MRSI data and voxel tissue segmentation were compared between the two cohorts using t-tests. Support vector machine (SVM) was used to classify tissue types and assessed by accuracy, sensitivity and specificity. RESULTS: Compared to HCs, RRMS demonstrated a statistically significant reduction in all mean brain tissues and increase in CSF volume. Within VOI, WM decreased (-10%) and CSF increased (41%) in RRMS compared to HCs (p < 0.001). MRSI revealed that total creatine (tCr) ratios of N-acetylaspartate and glutamate+glutamine in WML were significantly lower than NAWM-MS (-9%, -8%) and HCs (-14%, -10%), respectively. Myo-inositol/tCr in WML was significantly higher than NAWM-MS (14%) and HCs (10%). SVM of MRSI yielded accuracy, sensitivity and specificity of 86%, 95%, and 70%, respectively for HCs vs WML, which were higher than HC vs NAWM and WML vs NAWM models. CONCLUSION: This study demonstrates the benefit of MRSI in evaluating MS neurometabolic changes in NAWM. SVM of MRSI data in the MS brain may be suited for clinical monitoring and progression of MS patients. Longitudinal MRSI studies are warranted.

Improving Patient Outcomes Following Total Knee Arthroplasty: Identifying Rehabilitation Pathways Based on Modifiable Psychological Risk and Resilience Factors.

Total knee arthroplasty (TKA) is a commonly implemented elective surgical treatment for end-stage osteoarthritis of the knee, demonstrating high success rates when assessed by objective medical outcomes. However, a considerable proportion of TKA patients report significant dissatisfaction postoperatively, related to enduring pain, functional limitations, and diminished quality of life. In this conceptual analysis, we highlight the importance of assessing patient-centered outcomes routinely in clinical practice, as these measures provide important information regarding whether surgery and postoperative rehabilitation interventions have effectively remediated patients' real-world "quality of life" experiences. We propose a novel precision medicine approach to improving patient-centered TKA outcomes through the development of a multivariate machine-learning model. The primary aim of this model is to predict individual postoperative recovery trajectories. Uniquely, this model will be developed using an interdisciplinary methodology involving non-linear analysis of the unique contributions of a range of preoperative risk and resilience factors to patient-centered TKA outcomes. Of particular importance to the model's predictive power is the inclusion of a comprehensive assessment of modifiable psychological risk and resilience factors that have demonstrated relationships with TKA and other conditions in some studies. Despite the potential for patient psychological factors to limit recovery, they are typically not routinely assessed preoperatively in this patient group, and thus can be overlooked in rehabilitative referral and intervention decision-making. This represents a research-to-practice gap that may contribute to adverse patient-centered outcomes. Incorporating psychological risk and resilience factors into a multivariate prediction model could improve the detection of patients at risk of sub-optimal outcomes following TKA. This could provide surgeons and rehabilitation providers with a simplified tool to inform postoperative referral and intervention decision-making related to a range of interdisciplinary domains outside their usual purview. The proposed approach could facilitate the development and provision of more targeted rehabilitative interventions on the basis of identified individual needs. The roles of several modifiable psychological risk and resilience factors in recovery are summarized, and intervention options are briefly presented. While focusing on rehabilitation following TKA, we advocate for the broader utilization of multivariate prediction models to inform individually tailored interventions targeting a range of health conditions.

Comparison of BICAMS and ARCS for assessment of cognition in multiple sclerosis and predictive value of employment status.

BACKGROUND: Cognitive impairment is common in multiple sclerosis (MS) but not adequately monitored by Expanded Disability Status Scale assessment. The Audio Recorded Cognitive Screen (ARCS) and Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) are easy-to-use tools to assess cognitive function in clinical practice. OBJECTIVE: To compare the sensitivity of ARCS to BICAMS and their relative predictive value for employment status. METHODS: MS patients and healthy controls were assessed using the ARCS and the BICAMS consecutively. Receiver Operating Characteristic (ROC) curve analyses were used to compare the two tests. A step-wise, logistic regression analysis was used to identify the cognitive test(s) that best predicted employment status and quality of life. RESULTS: Total ARCS, memory and attention domain scores were moderately correlated with all BICAMS tests (r = 0.3-0.5; P ≤ 0.05). Total ARCS predicts cognitive impairment with good sensitivity and specificity relative to the BICAMS tests (AUC = 0.8; P = 0.00045). Total ARCS detects higher levels of impairment than BICAMS in MS patients (44% versus 21%). The memory domain of the ARCS and the BVMT-R were the best predictors of employment status (OR = 1.12 and 1.14, P < 0.05). CONCLUSION: BICAMS and ARCS have comparable sensitivity for cognitive impairment in MS. Memory assessment from either tests is the best predictor of employment status; however, the BICAMS is a better predictor of work productivity.

2D in-vivo L-COSY spectroscopy identifies neurometabolite alterations in treated multiple sclerosis.

BACKGROUND: We have applied in vivo two-dimensional (2D) localized correlation spectroscopy (2D L-COSY), in treated relapsing relapsing-remitting multiple sclerosis (RRMS) to identify novel biomarkers in normal-appearing brain parenchyma. METHODS: 2D L-COSY magnetic resonance spectroscopy (MRS) spectra were prospectively acquired from the posterior cingulate cortex (PCC) in 45 stable RRMS patients undergoing treatment with Fingolimod, and 40 age and sex-matched healthy control (HC) participants. Average metabolite ratios and clinical symptoms including, disability, cognition, fatigue, and mental health parameters were measured, and compared using parametric and nonparametric tests. Whole brain volume and MRS voxel morphometry were evaluated using SIENAX and the SPM LST toolbox. RESULTS: Despite the mean whole brain lesion volume being low in this RRMS group (6.8 ml) a significant reduction in PCC metabolite to tCr ratios were identified for multiple N-acetylaspartate (NAA) signatures, gamma-aminobutyric acid (GABA), glutamine and glutamate (Glx), threonine, and isoleucine/lipid. Of the clinical symptoms measured, visuospatial function, attention, and memory were correlated with NAA signatures, Glx, and isoleucine/lipid in the brain. CONCLUSIONS: 2D L-COSY has the potential to detect metabolic alterations in the normal-appearing MS brain. Despite examining only a localised region, we could detect metabolic variability associated with symptoms.

Evaluation of MS related central fatigue using MR neuroimaging methods: Scoping review.

BACKGROUND: Fatigue is a common and debilitating symptom in multiple sclerosis (MS). Over the past decade, a growing body of research has focussed on the pathophysiological mechanisms underlying central (cognitive and physical) fatigue in MS. The precise mechanisms causing fatigue in MS patients are complex and poorly understood, and may differ between patients. Advanced quantitative magnetic resonance imaging (MRI) techniques allow for objective assessment of disease pathology and have been used to characterise the pathophysiology of central fatigue in MS. OBJECTIVE: To systematically review the existing literature of MRI-based studies assessing the pathophysiological mechanisms of MS-related central fatigue. METHODS: A systematic literature search of four major databases (PubMed, Medline, Embase, Scopus and Google Scholar) was conducted to identify MRI-based studies of MS-related fatigue published in the past 20 years. Studies using the following MRI-based methods were included: structural (lesion load/atrophy), T1 relaxation time/magnetisation transfer ratio (MTR), diffusion tensor imaging (DTI), functional MRI (fMRI) and magnetic resonance spectroscopy (MRS). RESULTS: A total of 92 studies were identified as meeting the search criteria and included for review. Structurally, regional gray/white matter atrophy, cortical thinning, decreased T1 relaxation times and reduced fractional anisotropy were associated with central fatigue in MS. Functionally, hyperactivity and reduced functional connectivity in several regional areas of frontal, parietal, occipital, temporal and cerebellum were suggested as causes of central fatigue. Biochemically, a reduction in N-acetyl aspartate/creatine and increased (glutamine+glutamate)/creatine ratios were correlated with fatigue severity in MS. CONCLUSION: Several advanced quantitative MRI methods have been employed in the study of central fatigue in MS. Central fatigue in MS is associated with macro/microstructural and functional changes within specific brain regions (frontal, parietal, temporal and deep gray matter) and specific pathways/networks (cortico-cortical and cortico-subcortical). Alternations in the cortico-striatal-thalamocortical (CSTC) loop are correlated with the development of fatigue in MS patients.

Diurnal stability and long-term repeatability of neurometabolites using single voxel 1H magnetic resonance spectroscopy.

PURPOSE: This study was designed to evaluate the diurnal stability and long-term repeatability and reliability of one-dimensional (1D) hydrogen magnetic resonance spectroscopy (1H-MRS) in vitro and in vivo at 3 T. MATERIAL AND METHOD: A standard brain phantom was used for in vitro study. In vivo diurnal evaluation involved ten healthy subjects, while repeatability study involved six subjects. MRS was acquired from posterior cingulate gyrus (PCG), and processed with LCModel. Diurnal effects were assessed with repeated measures ANOVAs, repeatability was evaluated using coefficient of variation (CV), while reliability was assessed with standard error measurement (SEM) and intra-class correlation coefficient (ICC). RESULTS: Diurnal metabolic changes in vitro were non-significant. The intra/inter-in vitro CVs for the major metabolites; N-acetylaspartate (NAA), creatine (Cr), myo-inositol (mI), glutamate + glutamine (Glx) and total choline (tCho) were 1-3%/2-6%, respectively. Statistically significant in vivo diurnal effects were only seen for glycerophosphocholine (GPC, +10%, F = 10.6, p = 0.001) and Glx (+6%, F = 5.1, p = 0.018). The intra/inter-subject CVs for the major metabolites ranged from 2-5%/ 5-9%, respectively. The major metabolites displayed ICC ranging from 0.5-0.7 and low SEM (0.001-0.078) reflecting high reliability in detecting neurometabolites. The inter-week interval for in vivo measurements had minimal effect on metabolite ratios (F = 1.4, p = 0.09). CONCLUSION: In vitro MRS showed no diurnal effects and minimal variation in metabolite levels. Most PCG metabolites are not altered diurnally. The low in vivo variability of metabolite concentration supports the use of localised MRS on clinical 3 T scanners for reliable neurometabolic profiling of the brain.

DNA methylation changes in CD4+ T cells isolated from multiple sclerosis patients on dimethyl fumarate.

BACKGROUND: Dimethyl fumarate is an oral treatment for multiple sclerosis, whose mechanism of action is not fully understood. OBJECTIVE: To investigate the effects of dimethyl fumarate on DNA methylation in the CD4+ T cells of multiple sclerosis patients. METHODS: We performed Illumina EPIC arrays to investigate the DNA methylation profiles of CD4+ T cells derived from multiple sclerosis patients before and after dimethyl fumarate treatment. RESULTS: Treatment with dimethyl fumarate resulted in 97% of differentially methylated positions showing hypermethylation. Four genes, SNORD1A, SHTN1, MZB1 and TNF had a differentially methylated region located within the transcriptional start site. CONCLUSION: This study investigates the effect of dimethyl fumarate on DNA methylation in multiple sclerosis patients.

Reliability of neurometabolite detection with two-dimensional localized correlation spectroscopy at 3T.

BACKGROUND: Two-dimensional localized correlational spectroscopy (2D L-COSY) has been applied in vivo to investigate metabolic profiles in many disorders due to its ability to detect several metabolites simultaneously. Successful application of this technique depends on the reliability of the detection and understanding of the variability result from test-retest measurements. PURPOSE: To evaluate the test-retest repeatability/reliability of 2D L-COSY in detecting brain metabolites in a phantom and healthy subjects in a 3T scanner. STUDY TYPE: Test-retest. POPULATION/PHANTOM: Six healthy subjects and magnetic resonance spectroscopy-high definition (MRS-HD) sphere or "Braino". FIELD STRENGTH/SEQUENCE: 3T/2D L-COSY MRS. ASSESSMENT: Healthy subjects underwent eight weekly experiments over a period of 3 months with an intersession delay of 1 month after the first four measurements. Twenty-nine neurometabolite resonances (8 diagonal, 14 cross, and 7 composite resonances) were studied using a 27 cm3 voxel from the posterior cingulate cortex. In vitro evaluations were performed in a similar manner as in vivo on a Braino phantom containing brain metabolites at physiological concentrations and pH. STATISTICAL TESTS: Intra- and intersubject variability were measured. Test-retest repeatability was calculated using coefficient of variation (CV), and reliability was assessed with standard error measurement (SEM) and intraclass correlation coefficient (ICC), using SPSS software. RESULTS: The intra/inter CV for in vitro and in vivo data ranged from 0.01-0.23%/0.02-0.29% and 0.03-0.23%/0.04-0.39%, respectively. The major diagonal peaks showed ICC ranging from 0.31 to 0.93, while the ICC for cross peaks were 0.09-0.87. The SEM for in vivo data ranged from 0.0016 to 0.08. The interweek interval may have a positive effect on metabolite ratios (P = 0.08; F = 1.78). DATA CONCLUSION: The low variability in metabolite concentration in this study shows a high level of reliability of 2D L-COSY in the human brain. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;48:1559-1569.

Effectiveness and cost-effectiveness of unsupervised buprenorphine-naloxone for the treatment of heroin dependence in a randomized waitlist controlled trial.

BACKGROUND: Access to opioid agonist treatment can be associated with extensive waiting periods with significant health and financial burdens. This study aimed to determine whether patients with heroin dependence dispensed buprenorphine-naloxone weekly have greater reductions in heroin use and related adverse health effects 12-weeks after commencing treatment, compared to waitlist controls and to examine the cost-effectiveness of this strategy. METHODS: An open-label waitlist RCT was conducted in an opioid treatment clinic in Newcastle, Australia. Fifty patients with DSM-IV-TR heroin dependence (and no other substance dependence) were recruited. The intervention group (n=25) received take-home self-administered sublingual buprenorphine-naloxone weekly (mean dose, 22.7±5.7mg) and weekly clinical review. Waitlist controls (n=25) received no clinical intervention. The primary outcome was heroin use (self-report, urine toxicology verified) at weeks four, eight and 12. The primary cost-effectiveness outcome was incremental cost per additional heroin-free-day. RESULTS: Outcome data were available for 80% of all randomized participants. Across the 12-weeks, treatment group heroin use was on average 19.02days less/month (95% CI -22.98, -15.06, p<0.0001). A total 12-week reduction in adjusted costs including crime of $A5,722 (95% CI 3299, 8154) in favor of treatment was observed. Excluding crime, incremental cost per heroin-free-day gained from treatment was $A18.24 (95% CI 4.50, 28.49). CONCLUSION: When compared to remaining on a waitlist, take-home self-administered buprenorphine-naloxone treatment is associated with significant reductions in heroin use for people with DSM-IV-TR heroin dependence. This cost-effective approach may be an efficient strategy to enhance treatment capacity.

Fast magnetic resonance spectroscopic imaging techniques in human brain- applications in multiple sclerosis.

Multi voxel magnetic resonance spectroscopic imaging (MRSI) is an important imaging tool that combines imaging and spectroscopic techniques. MRSI of the human brain has been beneficially applied to different clinical applications in neurology, particularly in neurooncology but also in multiple sclerosis, stroke and epilepsy. However, a major challenge in conventional MRSI is the longer acquisition time required for adequate signal to be collected. Fast MRSI of the brain in vivo is an alternative approach to reduce scanning time and make MRSI more clinically suitable.Fast MRSI can be categorised into spiral, echo-planar, parallel and turbo imaging techniques, each with its own strengths. After a brief introduction on the basics of non-invasive examination (1H-MRS) and localization techniques principles, different fast MRSI techniques will be discussed from their initial development to the recent innovations with particular emphasis on their capacity to record neurochemical changes in the brain in a variety of pathologies.The clinical applications of whole brain fast spectroscopic techniques, can assist in the assessment of neurochemical changes in the human brain and help in understanding the roles they play in disease. To give a good example of the utilities of these techniques in clinical context, MRSI application in multiple sclerosis was chosen. The available up to date and relevant literature is discussed and an outline of future research is presented.

Anxiety Levels Are Independently Associated With Cognitive Performance in an Australian Multiple Sclerosis Patient Cohort.

Neurological and psychological symptoms in multiple sclerosis can affect cognitive function. The objective of this study was to explore the relationship between psychological measures and cognitive performance in a patient cohort. In 322 multiple sclerosis patients, psychological symptoms were measured using the Depression Anxiety and Stress Scale, and cognitive function was evaluated using Audio Recorded Cognitive Screen. Multifactor linear regression analysis, accounting for all clinical covariates, found that anxiety was the only psychological measure to remain a significant predictor of cognitive performance (p<0.001), particularly memory function (p<0.001). Further prospective studies are required to determine whether treatment of anxiety improves cognitive impairment.

Ongoing increase in incidence and prevalence of multiple sclerosis in Newcastle, Australia: A 50-year study.

BACKGROUND: Since 1959, multiple sclerosis (MS) prevalence has been estimated for the east coast Australian city of Newcastle. Previous surveys, conducted in 1988 and 2003, have described an increase in the prevalence and incidence of MS. OBJECTIVES: In this study, we evaluated whether these trends continue and provide 50 years of MS epidemiological follow-up for this southern hemisphere city. METHODS: Expressed per 100,000 people, prevalence of MS in Newcastle was calculated for those with a confirmed diagnosis of MS on 9 August 2011 and incidence based on the number of cases with MS diagnosis made during the preceding decade. Data were age-standardised to the total Australian population. Statistical comparisons were undertaken using Poisson regression analysis. RESULTS: In 2011, the estimate of MS prevalence was 124.2, with female-to-male ratio reaching 3.1, a 53% increase in female predominance since 1996. MS incidence increased to 6.7, with a significantly higher proportion of new female cases since the previous survey. CONCLUSION: Prevalence of MS in Newcastle has risen linearly and is contributed to by a substantial increase in new cases over the preceding decade. Female predominance of MS cases continues to increase with a new diagnosis three times more likely in women.

Male Sex Is Independently Associated with Faster Disability Accumulation in Relapse-Onset MS but Not in Primary Progressive MS.

BACKGROUND: Multiple Sclerosis is more common in women than men and females have more relapses than men. In a large international cohort we have evaluated the effect of gender on disability accumulation and disease progression to determine if male MS patients have a worse clinical outcome than females. METHODS: Using the MSBase Registry, data from 15,826 MS patients from 25 countries was analysed. Changes in the severity of MS (EDSS) were compared between sexes using a repeated measures analysis in generalised linear mixed models. Kaplan-Meier analysis was used to test for sex difference in the time to reach EDSS milestones 3 and 6 and the secondary progressive MS. RESULTS: In relapse onset MS patients (n = 14,453), males progressed significantly faster in their EDSS than females (0.133 vs 0.112 per year, P<0.001,). Females had a reduced risk of secondary progressive MS (HR (95% CI) = 0.77 (0.67 to 0.90) P = 0.001). In primary progressive MS (n = 1,373), there was a significant increase in EDSS over time in males and females (P<0.001) but there was no significant sex effect on the annualized rate of EDSS change. CONCLUSION: Among registrants of MSBase, male relapse-onset patients accumulate disability faster than female patients. In contrast, the rate of disability accumulation between male and female patients with primary progressive MS is similar.