Characteristics of improvements in balance control using vibro-tactile biofeedback of trunk sway for multiple sclerosis patients

Background and aims: Previously, we determined that training with vibrotactile feedback (VTfb) of trunk sway improves MS patients’ balance impairment. Here, we posed 5 questions: 1) How many weeks of VTfb training are required to obtain the best short-term carry over effect (CoE) with VTfb? 2) How long does the CoE last once VTfb training terminates? 3) Is the benefit similar for stance and gait? 4) Is position or velocity based VTfb more effective in reducing trunk sway? 5) Do patients’ subjective assessments of balance control improve? Methods: Balance control of 16 MS patients was measured with gyroscopes at the lower trunk. The gyroscopes drove directionally active VTfb in a head-band. Patients trained twice per week with VTfb for 4 weeks to determine when balance control with and without VTfb stopped improving. Thereafter, weekly assessments without VTfb over 4 weeks and at 6 months determined when CoEs ended. Results: A 20% improvement in balance to normal levels occurred with VTfb. Short term CoEs improved from 15 to 20% (p ≤0.001). Medium term (1–4 weeks) CoEs were constant at 19% (p ≤0.001). At 6 months improvement was not significant, 9%. Most improvement was for lateral sway. Equal improvement occurred when angle position or velocity drove VTfb. Subjectively, balance improvements peaked after 3 weeks of training (32%, p ≤0.05). Conclusions: 3–4 weeks VTfb training yields clinically relevant sway reductions and subjective improvements for MS patients during stance and gait. The CoEs lasted at least 1 month. Velocity-based VTfb was equally effective as position-based VTf

A case series on the value of tau and neurofilament protein levels to predict and detect delirium in cardiac surgery patients

BACKGROUND: Delirium following cardiac surgery is a relevant complication in the majority of elderly patients but its prediction is challenging. Cardiopulmonary bypass, essential for many interventions in cardiac surgery, is responsible for a severe inflammatory response leading to neuroinflammation and subsequent delirium. Neurofilament light protein (NfL) and tau protein (tau) are specific biomarkers to detect neuroaxonal injury as well as glial fibrillary acidic protein (GFAP), a marker of astrocytic activation. METHODS: We thought to examine the perioperative course of these markers in a case series of each three cardiac surgery patients under off-pump cardiac arterial bypass without evolving delirium (OPCAB-NDEL), patients with a procedure under cardio-pulmonary bypass (CPB) without delirium (CPB-NDEL) and delirium after a CPB procedure (CPB-DEL). Delirium was diagnosed by the Confusion Assessment Method for the ICU and chart reviews. RESULTS: We observed increased preoperative levels of tau in patients with later delirium, whereas values of NfL and GFAP did not differ. In the postoperative course, all biomarkers increased multi-fold. NfL levels sharply increased in patients with CPB reaching the highest levels in the CPB-DEL group. CONCLUSION: Tau and NfL might be of benefit to identify patients in cardiac surgery at risk for delirium and to detect patients with the postoperative emergence of delirium

Kappa free light chains is a valid tool in the diagnostics of MS: A large multicenter study

To validate kappa free light chain (KFLC) and lambda free light chain (LFLC) indices as a diagnostic biomarker in multiple sclerosis (MS).We performed a multicenter study including 745 patients from 18 centers (219 controls and 526 clinically isolated syndrome (CIS)/MS patients) with a known oligoclonal IgG band (OCB) status. KFLC and LFLC were measured in paired cerebrospinal fluid (CSF) and serum samples. Gaussian mixture modeling was used to define a cut-off for KFLC and LFLC indexes.The cut-off for the KFLC index was 6.6 (95% confidence interval (CI) = 5.2-138.1). The cut-off for the LFLC index was 6.9 (95% CI = 4.5-22.2). For CIS/MS patients, sensitivity of the KFLC index (0.88; 95% CI = 0.85-0.90) was higher than OCB (0.82; 95%CI = 0.79-0.85; p < 0.001), but specificity (0.83; 95% CI = 0.78-0.88) was lower (OCB = 0.92; 95% CI = 0.89-0.96; p < 0.001). Both sensitivity and specificity for the LFLC index were lower than OCB.Compared with OCB, the KFLC index is more sensitive but less specific for diagnosing CIS/MS. Lacking an elevated KFLC index is more powerful for excluding MS compared with OCB but the latter is more important for ruling in a diagnosis of CIS/MS

Divergent Roles of Salmonella Pathogenicity Island 2 and Metabolic Traits during Interaction of S. enterica Serovar Typhimurium with Host Cells

The molecular mechanisms of virulence of the gastrointestinal pathogen Salmonella enterica are commonly studied using cell culture models of infection. In this work, we performed a direct comparison of the interaction of S. enterica serovar Typhimurium (S. Typhimurium) with the non-polarized epithelial cell line HeLa, the polarized cell lines CaCo2, T84 and MDCK, and macrophage-like RAW264.7 cells. The ability of S. Typhimurium wild-type and previously characterized auxotrophic mutant strains to enter host cells, survive and proliferate within mammalian cells and deploy the Salmonella Pathogenicity Island 2-encoded type III secretion system (SPI2-T3SS) was quantified. We found that the entry of S. Typhimurium into polarized cells was much more efficient than entry into non-polarized cells or phagocytic uptake. While SPI2-T3SS dependent intracellular proliferation was observed in HeLa and RAW cells, the intracellular replication in polarized cells was highly restricted and not affected by defective SPI2-T3SS. The contribution of aromatic amino acid metabolism and purine biosynthesis to intracellular proliferation was distinct in the various cell lines investigated. These observations indicate that the virulence phenotypes of S. Typhimurium are significantly affected by the cell culture model applied

Factors associated with time from first-symptoms to diagnosis and treatment initiation of Multiple Sclerosis in Switzerland.

Recent studies emphasise the importance of timely diagnosis and early initiation of disease-modifying treatment in the long-term prognosis of multiple sclerosis. The objective of this study was to investigate factors associated with extended time to diagnosis and time to disease-modifying treatment initiation in the Swiss Multiple Sclerosis Registry. We used retrospective data (diagnoses 1996-2017) of the survey-based Swiss Multiple Sclerosis Registry and fitted logistic regression models (extended time to diagnosis ≥2 years from first symptoms, extended time to disease-modifying treatment initiation ≥1 year from diagnosis) with demographic and a priori defined variables. Our study, based on 996 persons with multiple sclerosis, suggests that 40% had an extended time to diagnosis, and extended time to disease-modifying treatment initiation was seen in 23%. Factors associated with extended time to diagnosis were primary progressive multiple sclerosis (odds ratio (OR) 5.09 (3.12-8.49)), diagnosis setting outside of hospital (neurologist (private practice) OR 1.54 (1.16-2.05)) and more uncommon first symptoms (per additional symptom OR 1.17 (1.06-1.30)). Older age at onset (per additional 5 years OR 0.84 (0.78-0.90)) and gait problems (OR 0.65 (0.47-0.89)) or paresthesia (OR 0.72 (0.54-0.95)) as first symptoms were associated with shorter time to diagnosis. Extended time to disease-modifying treatment initiation was associated with older age at diagnosis (per additional 5 years OR 1.18 (1.09-1.29)). In more recent years, time to diagnosis and time to disease-modifying treatment initiation tended to be shorter. Even in recent periods, substantial and partially systematic variation regarding time to diagnosis and time to disease-modifying treatment initiation remains. With the emerging paradigm of early treatment, the residual variation should be monitored carefully

Kappa free light chains is a valid tool in the diagnostics of MS: A large multicenter study

Objective: To validate kappa free light chain (KFLC) and lambda free light chain (LFLC) indices as a diagnostic biomarker in multiple sclerosis (MS). Methods: We performed a multicenter study including 745 patients from 18 centers (219 controls and 526 clinically isolated syndrome (CIS)/MS patients) with a known oligoclonal IgG band (OCB) status. KFLC and LFLC were measured in paired cerebrospinal fluid (CSF) and serum samples. Gaussian mix- ture modeling was used to define a cut-off for KFLC and LFLC indexes. Results: The cut-off for the KFLC index was 6.6 (95% confidence interval (CI) = 5.2-138.1). The cut-off for the LFLC index was 6.9 (95% CI=4.5-22.2). For CIS/MS patients, sensitivity of the KFLC index (0.88; 95% CI = 0.85-0.90) was higher than OCB (0.82; 95%CI = 0.79-0.85; p < 0.001), but specificity (0.83; 95% CI = 0.78-0.88) was lower (OCB = 0.92; 95% CI = 0.89-0.96; p < 0.001). Both sensitivity and specificity for the LFLC index were lower than OCB. Conclusion: Compared with OCB, the KFLC index is more sensitive but less specific for diagnosing CIS/MS. Lacking an elevated KFLC index is more powerful for excluding MS compared with OCB but the latter is more important for ruling in a diagnosis of CIS/MS

Biomarker Report from the Phase II Lamotrigine Trial in Secondary Progressive MS - Neurofilament as a Surrogate of Disease Progression

This work was supported by National MS Society (USA) under the Promise 2010 initiative and the MS Society of Great Britain and Northern Ireland as part of exploratory analysis for the UK MS Clinical Trial Network. VL is supported by Italian Minister of Health grant for young researcher 2008

Consortium for the Study of Pregnancy Treatments (Co-OPT): An international birth cohort to study the effects of antenatal corticosteroids

BACKGROUND: Antenatal corticosteroids (ACS) are widely prescribed to improve outcomes following preterm birth. Significant knowledge gaps surround their safety, long-term effects, optimal timing and dosage. Almost half of women given ACS give birth outside the "therapeutic window" and have not delivered over 7 days later. Overtreatment with ACS is a concern, as evidence accumulates of risks of unnecessary ACS exposure. METHODS: The Consortium for the Study of Pregnancy Treatments (Co-OPT) was established to address research questions surrounding safety of medications in pregnancy. We created an international birth cohort containing information on ACS exposure and pregnancy and neonatal outcomes by combining data from four national/provincial birth registers and one hospital database, and follow-up through linked population-level data from death registers and electronic health records. RESULTS AND DISCUSSION: The Co-OPT ACS cohort contains 2.28 million pregnancies and babies, born in Finland, Iceland, Israel, Canada and Scotland, between 1990 and 2019. Births from 22 to 45 weeks' gestation were included; 92.9% were at term (≥ 37 completed weeks). 3.6% of babies were exposed to ACS (67.0% and 77.9% of singleton and multiple births before 34 weeks, respectively). Rates of ACS exposure increased across the study period. Of all ACS-exposed babies, 26.8% were born at term. Longitudinal childhood data were available for 1.64 million live births. Follow-up includes diagnoses of a range of physical and mental disorders from the Finnish Hospital Register, diagnoses of mental, behavioural, and neurodevelopmental disorders from the Icelandic Patient Registers, and preschool reviews from the Scottish Child Health Surveillance Programme. The Co-OPT ACS cohort is the largest international birth cohort to date with data on ACS exposure and maternal, perinatal and childhood outcomes. Its large scale will enable assessment of important rare outcomes such as perinatal mortality, and comprehensive evaluation of the short- and long-term safety and efficacy of ACS

Increased serum neurofilament light and thin ganglion cell-inner plexiform layer are additive risk factors for disease activity in early multiple sclerosis

OBJECTIVE: To investigate the association of combined serum neurofilament light chain (sNfL) and retinal optical coherence tomography (OCT) measurements with future disease activity in patients with early multiple sclerosis (MS). METHODS: We analyzed sNfL by single molecule array technology and performed OCT measurements in a prospective cohort of 78 patients with clinically isolated syndrome and early relapsing-remitting MS with a median (interquartile range) follow-up of 23.9 (23.3–24.7) months. Patients were grouped into those with abnormal or normal sNfL levels, defined as sNfL ≥/<80th percentile of age-corrected reference values. Likewise, patients were grouped by a median split into those with thin or thick ganglion cell and inner plexiform layer (GCIP), peripapillary retinal nerve fiber layer, and inner nuclear layer in nonoptic neuritis eyes. Outcome parameters were violation of no evidence of disease activity (NEDA-3) criteria or its components. RESULTS: Patients with abnormal baseline sNfL had a higher risk of violating NEDA-3 (hazard ratio [HR] 2.28, 95% CI 1.27–4.09, p = 0.006) and developing a new brain lesion (HR 2.47, 95% CI 1.30(–4).69, p = 0.006), but not for a new relapse (HR 2.21, 95% CI 0.97–5.03, p = 0.058). Patients with both abnormal sNfL and thin GCIP had an even higher risk for NEDA-3 violation (HR 3.61, 95% CI 1.77–7.36, p = 4.2e−4), new brain lesion (HR 3.19, 95% CI 1.51–6.76, p = 0.002), and new relapse (HR 5.38, 95% CI 1.61–17.98, p = 0.006) than patients with abnormal sNfL alone. CONCLUSIONS: In patients with early MS, the presence of both abnormal sNfL and thin GCIP is a stronger risk factor for future disease activity than the presence of each parameter alone

Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression

Background and Objectives: Research in Multiple Sclerosis (MS) has recently focused on extracting knowledge from real-world clinical data sources. This type of data is more abundant than data produced during clinical trials and potentially more informative about real-world clinical practice. However, this comes at the cost of less curated and controlled data sets. In this work we aim to predict disability progression by optimally extracting information from longitudinal patient data in the real-world setting, with a special focus on the sporadic sampling problem. Methods: We use machine learning methods suited for patient trajectories modeling, such as recurrent neural networks and tensor factorization. A subset of 6682 patients from the MSBase registry is used. Results: We can predict disability progression of patients in a two-year horizon with an ROC-AUC of 0.85, which represents a 32% decrease in the ranking pair error (1-AUC) compared to reference methods using static clinical features. Conclusions: Compared to the models available in the literature, this work uses the most complete patient history for MS disease progression prediction and represents a step forward towards AI-assisted precision medicine in MS