The hidden information in patient-reported outcomes and clinician-assessed outcomes: multiple sclerosis as a proof of concept of a machine learning approach

Machine learning (ML) applied to patient-reported (PROs) and clinical-assessed outcomes (CAOs) could favour a more predictive and personalized medicine. Our aim was to confirm the important role of applying ML to PROs and CAOs of people with relapsing-remitting (RR) and secondary progressive (SP) form of multiple sclerosis (MS), to promptly identifying information useful to predict disease progression. For our analysis, a dataset of 3398 evaluations from 810 persons with MS (PwMS) was adopted. Three steps were provided: course classification; extraction of the most relevant predictors at the next time point; prediction if the patient will experience the transition from RR to SP at the next time point. The Current Course Assignment (CCA) step correctly assigned the current MS course with an accuracy of about 86.0%. The MS course at the next time point can be predicted using the predictors selected in CCA. PROs/CAOs Evolution Prediction (PEP) followed by Future Course Assignment (FCA) was able to foresee the course at the next time point with an accuracy of 82.6%. Our results suggest that PROs and CAOs could help the clinician decision-making in their practice

Antibody response elicited by the SARS-CoV-2 vaccine booster in patients with multiple sclerosis: Who gains from it?

Background and purpose: Although two doses of COVID-19 vaccine elicited a protective humoral response in most persons with multiple sclerosis (pwMS), a significant group of them treated with immunosuppressive disease-modifying therapies (DMTs) showed less efficient responses. Methods: This prospective multicenter observational study evaluates differences in immune response after a third vaccine dose in pwMS. Results: Four hundred seventy-three pwMS were analyzed. Compared to untreated patients, there was a 50-fold decrease (95% confidence interval [CI] = 14.3–100.0, p < 0.001) in serum SARS-CoV-2 antibody levels in those on rituximab, a 20-fold decrease (95% CI = 8.3–50.0, p < 0.001) in those on ocrelizumab, and a 2.3-fold decrease (95% CI = 1.2–4.6, p = 0.015) in those on fingolimod. As compared to the antibody levels after the second vaccine dose, patients on the anti-CD20 drugs rituximab and ocrelizumab showed a 2.3-fold lower gain (95% CI = 1.4–3.8, p = 0.001), whereas those on fingolimod showed a 1.7-fold higher gain (95% CI = 1.1–2.7, p = 0.012), compared to patients treated with other DMTs. Conclusions: All pwMS increased their serum SARS-CoV-2 antibody levels after the third vaccine dose. The mean antibody values of patients treated with ocrelizumab/rituximab remained well below the empirical "protective threshold" for risk of infection identified in the CovaXiMS study (>659 binding antibody units/mL), whereas for patients treated with fingolimod this value was significantly closer to the cutoff

Disease-Modifying Therapies and Coronavirus Disease 2019 Severity in Multiple Sclerosis

Objective: This study was undertaken to assess the impact of immunosuppressive and immunomodulatory therapies on the severity of coronavirus disease 2019 (COVID-19) in people with multiple sclerosis (PwMS). Methods: We retrospectively collected data of PwMS with suspected or confirmed COVID-19. All the patients had complete follow-up to death or recovery. Severe COVID-19 was defined by a 3-level variable: mild disease not requiring hospitalization versus pneumonia or hospitalization versus intensive care unit (ICU) admission or death. We evaluated baseline characteristics and MS therapies associated with severe COVID-19 by multivariate and propensity score (PS)-weighted ordinal logistic models. Sensitivity analyses were run to confirm the results. Results: Of 844 PwMS with suspected (n = 565) or confirmed (n = 279) COVID-19, 13 (1.54%) died; 11 of them were in a progressive MS phase, and 8 were without any therapy. Thirty-eight (4.5%) were admitted to an ICU; 99 (11.7%) had radiologically documented pneumonia; 96 (11.4%) were hospitalized. After adjusting for region, age, sex, progressive MS course, Expanded Disability Status Scale, disease duration, body mass index, comorbidities, and recent methylprednisolone use, therapy with an anti-CD20 agent (ocrelizumab or rituximab) was significantly associated (odds ratio [OR] = 2.37, 95% confidence interval [CI] = 1.18-4.74, p = 0.015) with increased risk of severe COVID-19. Recent use (<1 month) of methylprednisolone was also associated with a worse outcome (OR = 5.24, 95% CI = 2.20-12.53, p = 0.001). Results were confirmed by the PS-weighted analysis and by all the sensitivity analyses. Interpretation: This study showed an acceptable level of safety of therapies with a broad array of mechanisms of action. However, some specific elements of risk emerged. These will need to be considered while the COVID-19 pandemic persists

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France

We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR = 2.05, 95%CI = 1.39–3.02, p < 0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR = 0.42, 95%CI = 0.18–0.99, p = 0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon

[A year of blood cultures at the Associated Hospitals of Trieste: a critical evaluation of the clinico-laboratory approach to the patient with suspected bacteremia].

The authors evaluated the 2956 blood cultures performed in a multispecialist hospital in Trieste (Italy) during a whole year. A computer assisted analysis of the data pointed out that a single blood culture performed in a bacteremic patient could reveal 93\% of positivities, two blood cultures in the same day at least 96.6\% and three at least 98.3\%. Furthermore, in suspected bacteremic patients who received several blood cultures in subsequent days, the chance for a second day culture to reveal a bacteremia not pointed out in the first day was less than 4\%, while it was 0\% for the following days. These results assess the importance of a correct approach to the suspected bacteremic patient, and point out the usefulness of performing at most three blood cultures in the first day of clinical suspicion of bacteremia

Multivariate analysis of antibiograms for typing Pseudomonas aeruginosa.

A method for typing Pseudomonas aeruginosa using antibiotic susceptibility patterns is presented, which allows recognition of clusters of the same strain among clinical isolates from different patients, thus indicating whether cross infection has occurred. An index of similarity (the euclidean or the oblique distance), which includes all the differences of disk zone sizes among isolates, is computed and then elaborated by a clustering algorithm that successively groups all the isolates in larger clusters. The results of clustering are presented as dendrograms, whose terminal branches are pruned down to a level below which differences are casual; isolates that still appear on a common branch are considered identical. The reliability of this technique for detecting nosocomial cross infections was assessed by comparing its results with that of serotyping and pyocin typing. Only 2 of 31 (6.4\%) clusters detected by multivariate analysis were not confirmed, while 4 of 33 (12.1\%) clusters were recognized by serotyping and pyocin typing, but not by multivariate analysis. In at least two instances the differences in susceptibility patterns were due to cytoplasmic R factors. The routine use of antibiogram data for typing purposes should be considered an essential part of nosocomial infection control