Dataset Information

Outcomes of COVID-19 infection in multiple sclerosis and related conditions: One-year pandemic experience of the multicenter New York COVID-19 Neuroimmunology Consortium (NYCNIC).

ABSTRACT:

Objective

To determine outcomes of COVID-19 in patients with Multiple Sclerosis (MS) and related conditions, and to determine predictors of these outcomes.

Methods

This was a multicenter, observational cohort study of patients with MS or related CNS autoimmune disorders who developed confirmed or highly suspected COVID-19 infection from 2/1/2020 to 12/31/2020.

Main outcome and measure

The primary outcome measure was hospitalization status due to COVID-19. Severity of infection was measured using a 4-point ordinal scale: 1. home care; 2. hospitalization without mechanical ventilation; 3. hospitalization and mechanical ventilation, and 4. death.

Results

Of 474 patients in the study, 63.3% had confirmed COVID-19 infection and 93.9% were diagnosed with an MS phenotype. Mean age was 45 ± 13 (mean±SD) years, 72% were female, and 86% were treated with a DMT at the time of infection. 58 patients (12.2%) were hospitalized. 24 patients (5.1%) were critically ill (requiring ICU care or outcome of death), of which 15 patients (3.2%) died. Higher neurological disability and older age independently predicted hospitalization. 85% (102/120) of patients with known antibody results not treated with anti-CD20 therapies were seropositive while only 39.5% (17/43) of patients treated with anti-CD20 demonstrated seropositivity (p < 0.0001). Only 25% (2/8) of patients with PCR-confirmed COVID-19 being treated with anti-CD20 therapies demonstrated seropositivity.

Conclusions

Neurological disability and older age independently predicted hospitalization due to COVID-19. Additionally, the results demonstrate that anti-CD20 therapies significantly blunt humoral responses post-infection, a finding that carries implications with regards to natural or vaccine-mediated immunity.

SUBMITTER: Klineova S

PROVIDER: S-EPMC8286899 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Background: Neuroimmunology has impressively expanded in the past decade. Novel assays, especially cell-based assays (CBAs) can detect conformational antibodies (Abs) recognizing antigens in their native conformation. Generally, the availability of in-house and of commercial tests has improved the diagnostics, but introduced demanding laboratory tasks. Hence, standardization and quality controls represent a key step to promote accuracy. We report on the results of the 2018 external quality assessment program (EQAP) organized by the Italian Neuroimmunology Association. Methods: EQAP regarded 10 schemes, including oligoclonal bands (OCBs), intracellular-neuronal (ICN)-Abs, neuronal-surface (NS)-Abs, aquaporin-4 (AQP4)-Abs, myelin oligodendrocyte glycoprotein (MOG)-Abs, myelin-associated glycoprotein (MAG)-Abs, ganglioside-Abs, acetylcholine-receptor (AChR)-Abs, and muscle-specific-kinase (MuSK)-Abs, and 34 laboratories. Assays were classified as tissue-based assays (TBAs), solid-phase assays (SPAs), liquid-phase assays (LPAs), and CBAs. Thirty-three samples were provided. Results: Three-quarter of the tests were commercial. Median accuracy for the laboratories was 75% (range 50-100). In 8/10 schemes, at least one sample provided discrepant results. Inter-laboratory "substantial agreement" was found in 6/10 schemes (AChR, MuSK, MAG, AQP4, MOG, and NS-Abs), whereas the worst agreements regarded OCBs and ganglioside-Abs. Both commercial and in-house assays performed better in experienced laboratories. Conclusions: Assays could be divided in (a) robust commercial tests with substantial inter-laboratory agreement (MAG-Abs; AChR- and MuSK-Abs); commercial/"in-house" tests with (b) partial inter-laboratory agreement (AQP4-Abs, MOG-Abs, NS-Abs, ICN-Abs), and (c) with large inter-laboratory disagreement (OCBs, ganglioside-Abs). This real-life snapshot of the neuroimmunology test performances highlights shortcomings attributable to technician-dependent performances, assay structural limitations, and errors in test interpretations.