A Machine Learning Approach to Predict Weight Change in ART-Experienced People Living With HIV.

INTRODUCTION: The objective of the study was to develop machine learning (ML) models that predict the percentage weight change in each interval of time in antiretroviral therapy-experienced people living with HIV. METHODS: This was an observational study that comprised consecutive people living with HIV attending Modena HIV Metabolic Clinic with at least 2 visits. Data were partitioned in an 80/20 training/test set to generate 10 progressively parsimonious predictive ML models. Weight gain was defined as any weight change >5%, at the next visit. SHapley Additive exPlanations values were used to quantify the positive or negative impact of any single variable included in each model on the predicted weight changes. RESULTS: A total of 3,321 patients generated 18,322 observations. At the last observation, the median age was 50 years and 69% patients were male. Model 1 (the only 1 including body composition assessed with dual-energy x-ray absorptiometry) had an accuracy greater than 90%. This model could predict weight at the next visit with an error of <5%. CONCLUSIONS: ML models with the inclusion of body composition and metabolic and endocrinological variables had an excellent performance. The parsimonious models available in standard clinical evaluation are insufficient to obtain reliable prediction, but are good enough to predict who will not experience weight gain.

Quality of life and intrinsic capacity in patients with post-acute COVID-19 syndrome is in relation to frailty and resilience phenotypes.

The objective of this study was to characterize frailty and resilience in people evaluated for Post-Acute COVID-19 Syndrome (PACS), in relation to quality of life (QoL) and Intrinsic Capacity (IC). This cross-sectional, observational, study included consecutive people previously hospitalized for severe COVID-19 pneumonia attending Modena (Italy) PACS Clinic from July 2020 to April 2021. Four frailty-resilience phenotypes were built: "fit/resilient", "fit/non-resilient", "frail/resilient" and "frail/non-resilient". Frailty and resilience were defined according to frailty phenotype and Connor Davidson resilience scale (CD-RISC-25) respectively. Study outcomes were: QoL assessed by means of Symptoms Short form health survey (SF-36) and health-related quality of life (EQ-5D-5L) and IC by means of a dedicated questionnaire. Their predictors including frailty-resilience phenotypes were explored in logistic regressions. 232 patients were evaluated, median age was 58.0 years. PACS was diagnosed in 173 (74.6%) patients. Scarce resilience was documented in 114 (49.1%) and frailty in 72 (31.0%) individuals. Predictors for SF-36 score < 61.60 were the phenotypes "frail/non-resilient" (OR = 4.69, CI 2.08-10.55), "fit/non-resilient" (OR = 2.79, CI 1.00-7.73). Predictors for EQ-5D-5L < 89.7% were the phenotypes "frail/non-resilient" (OR = 5.93, CI 2.64-13.33) and "frail/resilient" (OR = 5.66, CI 1.93-16.54). Predictors of impaired IC (below the mean score value) were "frail/non-resilient" (OR = 7.39, CI 3.20-17.07), and "fit/non-resilient" (OR = 4.34, CI 2.16-8.71) phenotypes. Resilience and frailty phenotypes may have a different impact on wellness and QoL and may be evaluated in people with PACS to identify vulnerable individuals that require suitable interventions.

Detailed characterization of SARS-CoV-2-specific T and B cells after infection or heterologous vaccination.

The formation of a robust long-term antigen (Ag)-specific memory, both humoral and cell-mediated, is created following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or vaccination. Here, by using polychromatic flow cytometry and complex data analyses, we deeply investigated the magnitude, phenotype, and functionality of SARS-CoV-2-specific immune memory in two groups of healthy subjects after heterologous vaccination compared to a group of subjects who recovered from SARS-CoV-2 infection. We find that coronavirus disease 2019 (COVID-19) recovered patients show different long-term immunological profiles compared to those of donors who had been vaccinated with three doses. Vaccinated individuals display a skewed T helper (Th)1 Ag-specific T cell polarization and a higher percentage of Ag-specific and activated memory B cells expressing immunoglobulin (Ig)G compared to those of patients who recovered from severe COVID-19. Different polyfunctional properties characterize the two groups: recovered individuals show higher percentages of CD4+ T cells producing one or two cytokines simultaneously, while the vaccinated are distinguished by highly polyfunctional populations able to release four molecules, namely, CD107a, interferon (IFN)-γ, tumor necrosis factor (TNF), and interleukin (IL)-2. These data suggest that functional and phenotypic properties of SARS-CoV-2 adaptive immunity differ in recovered COVID-19 individuals and vaccinated ones.

Do All Critically Ill Patients with COVID-19 Disease Benefit from Adding Tocilizumab to Glucocorticoids? A Retrospective Cohort Study.

BACKGROUND: Treatment guidelines recommend the tocilizumab use in patients with a CRP of >7.5 mg/dL. We aimed to estimate the causal effect of glucocorticoids + tocilizumab on mortality overall and after stratification for PaO2/FiO2 ratio and CRP levels. METHODS: This was an observational cohort study of patients with severe COVID-19 pneumonia. The primary endpoint was day 28 mortality. Survival analysis was conducted to estimate the conditional and average causal effect of glucocorticoids + tocilizumab vs. glucocorticoids alone using Kaplan-Meier curves and Cox regression models with a time-varying variable for the intervention. The hypothesis of the existence of effect measure modification by CRP and PaO2/FiO2 ratio was tested by including an interaction term in the model. RESULTS: In total, 992 patients, median age 69 years, 72.9% males, 597 (60.2%) treated with monotherapy, and 395 (31.8%), adding tocilizumab upon respiratory deterioration, were included. At BL, the two groups differed for median values of CRP (6 vs. 7 mg/dL; p < 0.001) and PaO2/FiO2 ratio (276 vs. 235 mmHg; p < 0.001). In the unadjusted analysis, the mortality was similar in the two groups, but after adjustment for key confounders, a significant effect of glucocorticoids + tocilizumab was observed (adjusted hazard ratio (aHR) = 0.59, 95% CI: 0.38-0.90). Although the study was not powered to detect interactions (p = 0.41), there was a signal for glucocorticoids + tocilizumab to have a larger effect in subsets, especially participants with high levels of CRP at intensification. CONCLUSIONS: Our data confirm that glucocorticoids + tocilizumab vs. glucocorticoids alone confers a survival benefit only in patients with a CRP > 7.5 mg/dL prior to treatment initiation and the largest effect for a CRP > 15 mg/dL. Large randomized studies are needed to establish an exact cut-off for clinical use.

Patients Recovering from Severe COVID-19 Develop a Polyfunctional Antigen-Specific CD4+ T Cell Response.

Specific T cells are crucial to control SARS-CoV-2 infection, avoid reinfection and confer protection after vaccination. We have studied patients with severe or moderate COVID-19 pneumonia, compared to patients who recovered from a severe or moderate infection that had occurred about 4 months before the analyses. In all these subjects, we assessed the polyfunctionality of virus-specific CD4+ and CD8+ T cells by quantifying cytokine production after in vitro stimulation with different SARS-CoV-2 peptide pools covering different proteins (M, N and S). In particular, we quantified the percentage of CD4+ and CD8+ T cells simultaneously producing interferon-γ, tumor necrosis factor, interleukin (IL)-2, IL-17, granzyme B, and expressing CD107a. Recovered patients who experienced a severe disease display high proportions of antigen-specific CD4+ T cells producing Th1 and Th17 cytokines and are characterized by polyfunctional SARS-CoV-2-specific CD4+ T cells. A similar profile was found in patients experiencing a moderate form of COVID-19 pneumonia. No main differences in polyfunctionality were observed among the CD8+ T cell compartments, even if the proportion of responding cells was higher during the infection. The identification of those functional cell subsets that might influence protection can thus help in better understanding the complexity of immune response to SARS-CoV-2.

Molecular and cellular immune features of aged patients with severe COVID-19 pneumonia.

Aging is a major risk factor for developing severe COVID-19, but few detailed data are available concerning immunological changes after infection in aged individuals. Here we describe main immune characteristics in 31 patients with severe SARS-CoV-2 infection who were >70 years old, compared to 33 subjects <60 years of age. Differences in plasma levels of 62 cytokines, landscape of peripheral blood mononuclear cells, T cell repertoire, transcriptome of central memory CD4+ T cells, specific antibodies are reported along with features of lung macrophages. Elderly subjects have higher levels of pro-inflammatory cytokines, more circulating plasmablasts, reduced plasmatic level of anti-S and anti-RBD IgG3 antibodies, lower proportions of central memory CD4+ T cells, more immature monocytes and CD56+ pro-inflammatory monocytes, lower percentages of circulating follicular helper T cells (cTfh), antigen-specific cTfh cells with a less activated transcriptomic profile, lung resident activated macrophages that promote collagen deposition and fibrosis. Our study underlines the importance of inflammation in the response to SARS-CoV-2 and suggests that inflammaging, coupled with the inability to mount a proper anti-viral response, could exacerbate disease severity and the worst clinical outcome in old patients.

Plasma Cytokine Atlas Reveals the Importance of TH2 Polarization and Interferons in Predicting COVID-19 Severity and Survival.

Although it is now widely accepted that host inflammatory response contributes to COVID-19 immunopathogenesis, the pathways and mechanisms driving disease severity and clinical outcome remain poorly understood. In the effort to identify key soluble mediators that characterize life-threatening COVID-19, we quantified 62 cytokines, chemokines and other factors involved in inflammation and immunity in plasma samples, collected at hospital admission, from 80 hospitalized patients with severe COVID-19 disease who were stratified on the basis of clinical outcome (mechanical ventilation or death by day 28). Our data confirm that age, as well as neutrophilia, lymphocytopenia, procalcitonin, D-dimer and lactate dehydrogenase are strongly associated with the risk of fatal COVID-19. In addition, we found that cytokines related to TH2 regulations (IL-4, IL-13, IL-33), cell metabolism (lep, lep-R) and interferons (IFNα, IFNß, IFNγ) were also predictive of life-threatening COVID-19.

Metabolic-Associated Fatty Liver Disease Is Highly Prevalent in the Postacute COVID Syndrome.

BACKGROUND: A proposal has recently been advanced to change the traditional definition of nonalcoholic fatty liver disease to metabolic-associated fatty liver disease (MAFLD), to reflect the cluster of metabolic abnormalities that may be more closely associated with cardiovascular risk. Long coronavirus disease 2019 (COVID-19) is a smoldering inflammatory condition, characterized by several symptom clusters. This study aims to determine the prevalence of MAFLD in patients with postacute COVID syndrome (PACS) and its association with other PACS-cluster phenotypes. METHODS: We included 235 patients observed at a single university outpatient clinic. The diagnosis of PACS was based on ≥1 cluster of symptoms: respiratory, neurocognitive, musculoskeletal, psychological, sensory, and dermatological. The outcome was prevalence of MAFLD detected by transient elastography during the first postdischarge follow-up outpatient visit. The prevalence of MAFLD at the time of hospital admission was calculated retrospectively using the hepatic steatosis index. RESULTS: Of 235 patients, 162 (69%) were men (median age 61). The prevalence of MAFLD was 55.3% at follow-up and 37.3% on admission (P < .001). Insulin resistance (odds ratio [OR] = 1.5; 95% confidence interval [CI], 1.14-1.96), body mass index (OR = 1.14; 95% CI, 1.04-1.24), and the metabolic syndrome (OR = 2.54; 95% CI, 1.13-5.68) were independent predictors of MAFLD. The number of PACS clusters was inversely associated with MAFLD (OR = 0.86; 95% CI, .76-0.97). Thirty-one patients (13.2%) had MAFLD with no other associated PACS clusters. All correlations between MAFLD and other PACS clusters were weak. CONCLUSIONS: Metabolic-associated fatty liver disease was highly prevalent after hospital discharge and may represent a specific PACS-cluster phenotype, with potential long-term metabolic and cardiovascular health implications.

The impact of tocilizumab on respiratory support states transition and clinical outcomes in COVID-19 patients. A Markov model multi-state study.

BACKGROUND: The benefit of tocilizumab on mortality and time to recovery in people with severe COVID pneumonia may depend on appropriate timing. The objective was to estimate the impact of tocilizumab administration on switching respiratory support states, mortality and time to recovery. METHODS: In an observational study, a continuous-time Markov multi-state model was used to describe the sequence of respiratory support states including: no respiratory support (NRS), oxygen therapy (OT), non-invasive ventilation (NIV) or invasive mechanical ventilation (IMV), OT in recovery, NRS in recovery. RESULTS: Two hundred seventy-one consecutive adult patients were included in the analyses contributing to 695 transitions across states. The prevalence of patients in each respiratory support state was estimated with stack probability plots, comparing people treated with and without tocilizumab since the beginning of the OT state. A positive effect of tocilizumab on the probability of moving from the invasive and non-invasive mechanical NIV/IMV state to the OT in recovery state (HR = 2.6, 95% CI = 1.2-5.2) was observed. Furthermore, a reduced risk of death was observed in patients in NIV/IMV (HR = 0.3, 95% CI = 0.1-0.7) or in OT (HR = 0.1, 95% CI = 0.0-0.8) treated with tocilizumab. CONCLUSION: To conclude, we were able to show the positive impact of tocilizumab used in different disease stages depicted by respiratory support states. The use of the multi-state Markov model allowed to harmonize the heterogeneous mortality and recovery endpoints and summarize results with stack probability plots. This approach could inform randomized clinical trials regarding tocilizumab, support disease management and hospital decision making.

Expansion of plasmablasts and loss of memory B cells in peripheral blood from COVID-19 patients with pneumonia.

Studies on the interactions between SARS-CoV-2 and humoral immunity are fundamental to elaborate effective therapies including vaccines. We used polychromatic flow cytometry, coupled with unsupervised data analysis and principal component analysis (PCA), to interrogate B cells in untreated patients with COVID-19 pneumonia. COVID-19 patients displayed normal plasma levels of the main immunoglobulin classes, of antibodies against common antigens or against antigens present in common vaccines. However, we found a decreased number of total and naïve B cells, along with decreased percentages and numbers of memory switched and unswitched B cells. On the contrary, IgM+ and IgM- plasmablasts were significantly increased. In vitro cell activation revealed that B lymphocytes showed a normal proliferation index and number of dividing cells per cycle. PCA indicated that B-cell number, naive and memory B cells but not plasmablasts clustered with patients who were discharged, while plasma IgM level, C-reactive protein, D-dimer, and SOFA score with those who died. In patients with pneumonia, the derangement of the B-cell compartment could be one of the causes of the immunological failure to control SARS-Cov2, have a relevant influence on several pathways, organs and systems, and must be considered to develop vaccine strategies.

Marked T cell activation, senescence, exhaustion and skewing towards TH17 in patients with COVID-19 pneumonia.

The immune system of patients infected by SARS-CoV-2 is severely impaired. Detailed investigation of T cells and cytokine production in patients affected by COVID-19 pneumonia are urgently required. Here we show that, compared with healthy controls, COVID-19 patients' T cell compartment displays several alterations involving naïve, central memory, effector memory and terminally differentiated cells, as well as regulatory T cells and PD1+CD57+ exhausted T cells. Significant alterations exist also in several lineage-specifying transcription factors and chemokine receptors. Terminally differentiated T cells from patients proliferate less than those from healthy controls, whereas their mitochondria functionality is similar in CD4+ T cells from both groups. Patients display significant increases of proinflammatory or anti-inflammatory cytokines, including T helper type-1 and type-2 cytokines, chemokines and galectins; their lymphocytes produce more tumor necrosis factor (TNF), interferon-γ, interleukin (IL)-2 and IL-17, with the last observation implying that blocking IL-17 could provide a novel therapeutic strategy for COVID-19.