Neurodegeneration and its potential markers in the diagnosing of secondary progressive multiple sclerosis. A review

Approximately 70% of relapsing-remitting multiple sclerosis (RRMS) patients will develop secondary progressive multiple sclerosis (SPMS) within 10-15 years. This progression is characterized by a gradual decline in neurological functionality and increasing limitations of daily activities. Growing evidence suggests that both inflammation and neurodegeneration are associated with various pathological processes throughout the development of MS; therefore, to delay disease progression, it is critical to initiate disease-modifying therapy as soon as it is diagnosed. Currently, a diagnosis of SPMS requires a retrospective assessment of physical disability exacerbation, usually over the previous 6-12 months, which results in a delay of up to 3 years. Hence, there is a need to identify reliable and objective biomarkers for predicting and defining SPMS conversion. This review presents current knowledge of such biomarkers in the context of neurodegeneration associated with MS, and SPMS conversion.

Cladribine tablets for highly active relapsing-remitting multiple sclerosis in Poland: a real-world, multi-centre, retrospective, cohort study during the COVID-19 pandemic

INTRODUCTION

Treatment with cladribine tablets is indicated in highly active relapsing-remitting multiple sclerosis (RRMS). Cladribine tablets proved safe and effective in the pivotal CLARITY trial, but that trial included primarily treatment-naïve patients. In clinical practice however, cladribine tablets are often given to patients who have failed other treatments. Therefore, this study investigated the real-world safety and efficacy of cladribine tablets.

MATERIAL AND METHODS

We gathered data from nine MS clinical centres across Poland for patients with RRMS who started treatment with cladribine tablets from December 2019 to June 2022.

RESULTS

We enrolled 140 patients, with follow-up data available for 136 in year 1 and for 66 in year 2. At baseline, the mean age was 35.6 years, mean disease duration was 7.3 years, median EDSS score was 2.5, and 94% of patients were treatment- -experienced. Thirty-nine patients (27.9%) had undergone COVID-19, and 94 (67.1%) were vaccinated against COVID-19. The annualised relapse rate (ARR) decreased from 1.49 at baseline to 0.33 in year 1 (p < 0.001) and to 0.25 in year 2 (p < 0.001). The percentage of relapse-free patients increased from 11.5% at baseline to 70.2% in year 1 and 82.1% in year 2. The percentage of patients with active lesions decreased from 91.4% at baseline to 36.2% in year 1 and 18.2% in year 2. EDSS score remained stable or improved in 83.7% of patients in year 1 and 89.6% in year 2. No evidence of disease activity (NEDA-3) was achieved in 42.7% of patients in year 1 and 66.7% in year 2. Only one patient (0.72%) had grade 4 lymphopenia and 21 (15.1%) had grade 3 lymphopenia. Varicella zoster virus infections occurred in three patients. Eight patients discontinued treatment with cladribine: five due to inefficacy, one due to lymphopenia, and two due to a personal decision.

CONCLUSIONS

Cladribine tablets proved safe and effective in a real-world cohort of treatment-experienced patients. However, the efficacy measures improved to a lesser extent in our cohort than in the pivotal clinical trial, which is probably due to a higher proportion of treatment-experienced patients in our cohort.

Can HRV Predict Prolonged Hospitalization and Favorable or Unfavorable Short-Term Outcome in Patients with Acute Ischemic Stroke?

The aim of this study was to assess whether the heart rate variability (HRV) could predict a favorable or unfavorable stroke outcome. The endpoint was based on the National Institutes of Health Stroke Scale (NIHSS). The patient's health condition was assessed upon discharge from the hospital. An unfavorable stroke outcome was defined as death or NIHSS ≥ 9, while NIHSS < 9 meant a favorable stroke outcome. The studied group consisted of 59 patients with acute ischemic stroke AIS (mean age of 65.6 ± 13.2; 58% were females). An original and innovative non-linear measure was used to analyze HRV. It was based on symbolic dynamics consisting of comparing the "length of the longest words" in the night recording of HRV. "The length of the longest word" meant the longest sequence of identical adjacent symbols possible for a patient. An unfavorable stroke outcome occurred in 22 patients, whereas the majority of patients (37) had a favorable stroke outcome. The average hospitalization time of patients with clinical progression was 29 ± 14 days, and with favorable outcomes was 10 ± 3 days. Patients with long words (more than 150 adjacent RR intervals having the same symbol) were hospitalized no longer than 14 days and they had no clinical progression. The patients with a favorable stroke outcome were characterized by longer words. Our pilot study may be the beginning of work on the development of a non-linear, symbolic method as a predictor of prolonged hospitalization and increased risk of clinical progression in patients with AIS.

Heart rate variability as a predictor of stroke course, functional outcome, and medical complications: A systematic review

Background: Heart rate variability (HRV) is a non-invasive marker of autonomic nervous system function that is based on the analysis of length differences between subsequent RR intervals of the electrocardiogram. The aim of this systematic review was to assess the current knowledge gap in the utility of HRV parameters and their value as predictors of the acute stroke course. Methods: A systematic review was performed in accordance with the PRISMA guidelines. Relevant articles published between 1 January 2016 and 1 November 2022 available in the PubMed, Web of Science, Scopus, and Cochrane Library databases were obtained using a systematic search strategy. The following keywords were used to screen the publications: "heart rate variability" AND/OR "HRV" AND "stroke." The eligibility criteria that clearly identified and described outcomes and outlined restrictions on HRV measurement were pre-established by the authors. Articles assessing the relationship between HRV measured in the acute phase of stroke and at least one stroke outcome were considered. The observation period did not exceed 12 months. Studies that included patients with medical conditions influencing HRV with no established stroke etiology and non-human subjects were excluded from the analysis. To minimize the risk of bias, disagreements throughout the search and analysis were resolved by two independent supervisors. Results: Of the 1,305 records obtained from the systematic search based on keywords, 36 were included in the final review. These publications provided insight into the usability of linear and non-linear HRV analysis in predicting the course, complications, and mortality of stroke. Furthermore, some modern techniques, such as HRV biofeedback, for the improvement of cognition performance after a stroke are discussed. Discussion: The present study showed that HRV could be considered a promising biomarker of a stroke outcome and its complications. However, further research is needed to establish a methodology for appropriate quantification and interpretation of HRV-derived parameters.

The Hemisphere of the Brain in Which a Stroke Has Occurred Visible in the Heart Rate Variability

The aim of this study was to assess whether heart rate variability (HRV) could predict which hemisphere of the brain was affected during an acute ischemic stroke (AIS). To achieve this goal, we compared HRV between patients with a right (RH) and left hemispheric (LH) stroke. The studied group consisted of 64 patients with AIS (25 with RH and 39 with LH stroke, with a mean age of 64 ± 12 and 66 ± 13, p = 0.3, respectively) using 24 h Holter ECG records at NN intervals performed at a mean of 4.3 ± 2 days following their AIS. Standard linear methods were used to analyze HRV in the time and frequency domains, as well as nonlinear methods, including sample entropy, detrended fluctuation analysis, and asymmetry measures. Patients with an LH stroke had significantly greater values for sample entropy compared to subjects with an RH stroke (1.31 ± 0.53 vs. 0.92 ± 0.46, p = 0.003, Bonferroni-corrected p = 0.033, effect size = 0.8). The LH stroke group also had higher RMSSD (113 ± 81 vs. 76 ± 61, p = 0.06), pNN50 (33.35 ± 28.54 vs. 18.52 ± 23.75, p = 0.02), and HF_nu (48.42 ± 16.41 vs. 42.66 ± 17.88, p = 0.11) values, when compared to the RH group, which was possibly related to higher activity in the parasympathetic system in the LH group. Conversely, subjects with RH stroke had higher LF_nu (57.34 ± 17.88 vs. 51.58 ± 16.41, p-value = 0.11) and LF/HF ratios (2.24 ± 2.87 vs. 1.68 ± 2.50, p-value = 0.11), which were likely related to higher activity in the sympathetic nervous system, when compared to the LH stroke group. Our pilot study demonstrated that patients with RH stroke had lower HRV complexity than those with LH stroke, indicating that HRV could be useful in the discrimination of hemispheric involvement in AIS.

Mean Platelet Volume as a Potential Marker of Large Vessel Occlusion and Predictor of Outcome in Acute Ischemic Stroke Patients Treated with Reperfusion Therapy

(1) Background: An early diagnosis of a large vessel occlusion (LVO) is crucial in the management of the acute ischemic stroke (AIS). The laboratory predictors of LVO and a stroke outcome remain unknown. We have hypothesized that high MPV—a surrogate marker of the activated platelet—may be associated with LVO, and it may predict a worse AIS outcome. (2) Methods: This was a retrospective study of 361 patients with AIS who were treated with thrombolysis (tPA, 65.7%) and/or mechanical thrombectomy (MT, 34.3%) in a tertiary Stroke Center between 2011 and 2019. (3) Results: The mean MPV in the cohort was 9.86 ± 1.5 fL (1st–4th quartiles: <8.8, >10.80 fL). Patients in the 4th quartile compared to the 1st had a significantly (p < 0.01) more often incidence of an LVO related stroke (75% vs. 39%) and a severe stroke manifestation with a higher RACE score (5.2 ± 2.8 vs. 3.3 ± 2.4), NIHSS at baseline (mean ± SD, 14 ± 6.5 vs. 10.9 ± 5.2), and NIHSS at discharge (6.9 ± 7 vs. 3.9 ± 3.6). A multivariate analysis revealed that quartiles of MPV (OR 1.4; 95%CI 1.2–1.8) significantly predicted an LVO stroke, also after the adjustment for RACE < 5 (OR 1.4; 95%CI 1.08–1.89), but MPV quartiles did not predict a favorable stroke outcome (mRS ≤ 2) (OR 0.89; 95%CI 0.7–1.13). (4) Conclusion: Our data suggest that MPV is an independent predictor of LVO in patients with an acute ischemic stroke.