The authors reviewed 59 consecutive patients treated with plasma exchange (PE) for acute, severe attacks of CNS demyelination at Mayo Clinic from January 1984 through June 2000. Most patients had relapsing-remitting MS (n = 22, 37.3%), neuromyelitis optica (NMO) (n = 10, 16.9%), and acute disseminated encephalomyelitis (n = 10, 16.9%). PE was followed by moderate or marked functional improvement in 44.1% of treated patients. Male sex (p = 0.021), preserved reflexes (p = 0.019), and early initiation of treatment (p = 0.009) were associated with moderate or marked improvement. Successfully treated patients improved rapidly following PE, and improvement was sustained.

Background The clinical presentation of COVID-19 in patients admitted to hospital is heterogeneous. We aimed to determine whether clinical phenotypes of patients with COVID-19 can be derived from clinical data, to assess the reproducibility of these phenotypes and correlation with prognosis, and to derive and validate a simplified probabilistic model for phenotype assignment. Phenotype identification was not primarily intended as a predictive tool for mortality. MethodsIn this study, we used data from two cohorts: the COVID-19@Spain cohort, a retrospective cohort including 4035 consecutive adult patients admitted to 127 hospitals in Spain with COVID-19 between Feb 2 and March 17, 2020, and the COVID-19@HULP cohort, including 2226 consecutive adult patients admitted to a teaching hospital in Madrid between Feb 25 and April 19, 2020. The COVID-19@Spain cohort was divided into a derivation cohort, comprising 2667 randomly selected patients, and an internal validation cohort, comprising the remaining 1368 patients. The COVID-19@HULP cohort was used as an external validation cohort. A probabilistic model for phenotype assignment was derived in the derivation cohort using multinomial logistic regression and validated in the internal validation cohort. The model was also applied to the external validation cohort. 30-day mortality and other prognostic variables were assessed in the derived phenotypes and in the phenotypes assigned by the probabilistic model. Findings Three distinct phenotypes were derived in the derivation cohort (n=2667)-phenotype A (516 [19%] patients), phenotype B (1955 [73%]) and phenotype C (196 [7%])-and reproduced in the internal validation cohort (n=1368)phenotype A (233 [17%] patients), phenotype B (1019 [74%]), and phenotype C (116 [8%]). Patients with phenotype A were younger, were less frequently male, had mild viral symptoms, and had normal inflammatory parameters. Patients with phenotype B included more patients with obesity, lymphocytopenia, and moderately elevated inflammatory parameters. Patients with phenotype C included older patients with more comorbidities and even higher inflammatory parameters than phenotype B. We developed a simplified probabilistic model (validated in the internal validation cohort) for phenotype assignment, including 16 variables. In the derivation cohort, 30-day mortality rates were 2•5% (95% CI 1•4-4•3) for patients with phenotype A, 30•5% (28•5-32•6) for patients with phenotype B, and 60•7% (53•7-67•2) for patients with phenotype C (log-rank test p<0•0001). The predicted phenotypes in the internal validation cohort and external validation cohort showed similar mortality rates to the assigned phenotypes (internal validation cohort: 5•3% [95% CI 3•4-8•1] for phenotype A, 31•3% [28•5-34•2] for phenotype B, and 59•5% [48•8-69•3] for phenotype C; external validation cohort: 3•7% [2•0-6•4] for phenotype A, 23•7% [21•8-25•7] for phenotype B, and 51•4% [41•9-60•7] for phenotype C).Interpretation Patients admitted to hospital with COVID-19 can be classified into three...

Objective: To explore the long-term outcomes of patients with clinically isolated syndromes from the Barcelona cohort. Methods: We selected patients with a follow-up longer than 10 years to (1) estimate the risks of multiple sclerosis (MS) and disability accumulation according to the baseline number of T2 lesions and to compare treated versus untreated patients and early versus delayed treatment, and (2) to study baseline features of patients with aggressive MS (Expanded Disability Status Scale (EDSS) ⩾6.0 at 10 years). Results: In all, 401 patients were included (mean follow-up of 14.4 (standard deviation of 2.9) years). A higher number of T2 lesions was associated with an earlier MS diagnosis and an earlier risk of irreversible disability. Early treatment was associated with a decreased risk of EDSS of 3.0: adjusted hazard ratio = 0.4, 95% confidence interval = (0.2, 0.7). Patients with aggressive MS differed in their baseline brain magnetic resonance images: The median (interquartile range) number of T2 lesions and contrastenhancing lesions (CEL) was 71 (28-95) versus 7 (1-19) and 3 (1-24) versus 0 (0-1), respectively. The cut-offs that better classified patients with aggressive MS were 20 for T2 lesions and 2 for CEL. Conclusion: Although MS natural history is changing, a high lesion load at onset is helpful to identify patients at risk of presenting an aggressive MS.

The authors studied the association of an exon 4 (E4*epsilon2/3/4) and three promoter polymorphisms of APOE with disease course and severity stratified by gender in 221 patients with multiple sclerosis from two overlapping population-based prevalence cohorts. Women carriers of the E4*epsilon2 allele took longer to attain an Expanded Disability Status Scale score of 6 (p = 0.015) and had more favorable ranked severity scores than noncarriers (p = 0.009). There was no association in men. Alleles epsilon3 or epsilon4 and promoter polymorphisms were not associated with disease course or severity.