Predictors of clinical evolution of SARS-CoV-2 infection in hematological patients: A systematic review and meta-analysis.

Main aim of this systematic review is to quantify the risk and identify predictors of clinical evolution of SARS-CoV-2 in hematological patients compared to different control populations. Two independent reviewers screened the literature assessing clinical outcomes of SARS-CoV-2 infection in adult patients with active hematological malignancies published up to June 2021. Primary outcome was COVID-19 related mortality, secondary outcomes were hospital and intensive-care admission, mechanical ventilation (MV), and thromboembolic events. Variables related to study setting, baseline patients' demographic, comorbidities, underlying hematological disease, ongoing chemotherapy, COVID-19 presentation, and treatments were extracted. A total of 67 studies including 10,061 hematological patients and 111,143 controls were included. Most of the studies were retrospective cohorts (51 studies, 76%) and only 19 (13%) provided data for a control group. A significant increased risk of clinical progression in the hematological population compared to the controls was found in terms of COVID-19 related mortality (OR, 2.12; 95% CI, 1.77-2.54), hospitalization (OR, 1.98; 95% CI, 1.15-3.43), intensive-care admission (OR, 1.77; 95% CI, 1.38-2.26), and MV (OR, 2.17; 95% CI, 1.71-2.75). The risk remained significantly higher in the subgroup analysis comparing hematological patients versus solid cancer. Meta-regression analysis of uncontrolled studies showed that older age, male sex, and hypertension were significantly related to worse clinical outcomes of COVID-19 in hematological population. Older age and hypertension were found to be associated also to thromboembolic events. In conclusion, hematological patients have a higher risk of COVID-19 clinical progression compared to both the general population and to patients with solid cancer.

Circulating microRNA signatures associated with disease severity and outcome in COVID-19 patients.

Background: SARS-CoV-2 induces a spectrum of clinical conditions ranging from asymptomatic infection to life threatening severe disease. Host microRNAs have been involved in the cytokine storm driven by SARS-CoV-2 infection and proposed as candidate biomarkers for COVID-19. Methods: To discover signatures of circulating miRNAs associated with COVID-19, disease severity and mortality, small RNA-sequencing was performed on serum samples collected from 89 COVID-19 patients (34 severe, 29 moderate, 26 mild) at hospital admission and from 45 healthy controls (HC). To search for possible sources of miRNAs, investigation of differentially expressed (DE) miRNAs in relevant human cell types in vitro. Results: COVID-19 patients showed upregulation of miRNAs associated with lung disease, vascular damage and inflammation and downregulation of miRNAs that inhibit pro-inflammatory cytokines and chemokines, angiogenesis, and stress response. Compared with mild/moderate disease, patients with severe COVID-19 had a miRNA signature indicating a profound impairment of innate and adaptive immune responses, inflammation, lung fibrosis and heart failure. A subset of the DE miRNAs predicted mortality. In particular, a combination of high serum miR-22-3p and miR-21-5p, which target antiviral response genes, and low miR-224-5p and miR-155-5p, targeting pro-inflammatory factors, discriminated severe from mild/moderate COVID-19 (AUROC 0.88, 95% CI 0.80-0.95, p<0.0001), while high leukocyte count and low levels of miR-1-3p, miR-23b-3p, miR-141-3p, miR-155-5p and miR-4433b-5p predicted mortality with high sensitivity and specificity (AUROC 0.95, 95% CI 0.89-1.00, p<0.0001). In vitro experiments showed that some of the DE miRNAs were modulated directly by SARS-CoV-2 infection in permissive lung epithelial cells. Conclusions: We discovered circulating miRNAs associated with COVID-19 severity and mortality. The identified DE miRNAs provided clues on COVID-19 pathogenesis, highlighting signatures of impaired interferon and antiviral responses, inflammation, organ damage and cardiovascular failure as associated with severe disease and death.

Determinants of persistence of symptoms and impact on physical and mental wellbeing in Long COVID: A prospective cohort study.

BACKGROUND: Residual symptoms can be detected for several months after COVID-19. To better understand the predictors and impact of symptom persistence we analyzed a prospective cohort of COVID-19 patients. METHODS: Patients were followed for 9 months after COVID-19 onset. Duration and predictors of persistence of symptoms, physical health and psychological distress were assessed. RESULTS: 465 patients (54% males, 51% hospitalized) were included; 37% presented with at least 4 symptoms and 42% complained of symptom lasting more than 28 days. At month 9, 20% of patients were still symptomatic, showing mainly fatigue (11%) and breathlessness (8%). Hospitalization and ICU stay vs. non-hospitalized status increased the median duration of fatigue of 8 weeks. Age > 50 years (OR 2.50), ICU stay (OR 2.35), and presentation with 4 or more symptoms (OR 2.04) were independent predictors of persistence of symptoms at month 9. A total of 18% of patients did not return to optimal pre-COVID physical health, while 19% showed psychological distress at month 9. Hospital admission (OR 2.28) and persistence of symptoms at day 28 (OR 2.21) and month 9 (OR 5.16) were independent predictors of suboptimal physical health, while female gender (OR 5.27) and persistence of symptoms at day 28 (OR 2.42) and month 9 (OR 2.48) were risk factors for psychological distress. CONCLUSIONS: Patients with advanced age, ICU stay and multiple symptoms at onset were more likely to suffer from long-term symptoms, which had a negative impact on both physical and mental wellbeing. This study contributes to identify the target populations and Long COVID consequences for planning long-term recovery interventions.

Assessment of COVID-19 progression on day 5 from symptoms onset.

BACKGROUND: A major limitation of current predictive prognostic models in patients with COVID-19 is the heterogeneity of population in terms of disease stage and duration. This study aims at identifying a panel of clinical and laboratory parameters that at day-5 of symptoms onset could predict disease progression in hospitalized patients with COVID-19. METHODS: Prospective cohort study on hospitalized adult patients with COVID-19. Patient-level epidemiological, clinical, and laboratory data were collected at fixed time-points: day 5, 10, and 15 from symptoms onset. COVID-19 progression was defined as in-hospital death and/or transfer to ICU and/or respiratory failure (PaO2/FiO2 ratio < 200) within day-11 of symptoms onset. Multivariate regression was performed to identify predictors of COVID-19 progression. A model assessed at day-5 of symptoms onset including male sex, age > 65 years, dyspnoea, cardiovascular disease, and at least three abnormal laboratory parameters among CRP (> 80 U/L), ALT (> 40 U/L), NLR (> 4.5), LDH (> 250 U/L), and CK (> 80 U/L) was proposed. Discrimination power was assessed by computing area under the receiver operating characteristic (AUC) values. RESULTS: A total of 235 patients with COVID-19 were prospectively included in a 3-month period. The majority of patients were male (148, 63%) and the mean age was 71 (SD 15.9). One hundred and ninety patients (81%) suffered from at least one underlying illness, most frequently cardiovascular disease (47%), neurological/psychiatric disorders (35%), and diabetes (21%). Among them 88 (37%) experienced COVID-19 progression. The proposed model showed an AUC of 0.73 (95% CI 0.66-0.81) for predicting disease progression by day-11. CONCLUSION: An easy-to-use panel of laboratory/clinical parameters computed at day-5 of symptoms onset predicts, with fair discrimination ability, COVID-19 progression. Assessment of these features at day-5 of symptoms onset could facilitate clinicians' decision making. The model can also play a role as a tool to increase homogeneity of population in clinical trials on COVID-19 treatment in hospitalized patients.

Long-Term Patient-Centred Follow-up in a Prospective Cohort of Patients with COVID-19.

INTRODUCTION: To better define COVID-19 long-term impact we prospectively analysed patient-centred outcomes, including general health and symptom duration. METHODS: Barthel index (BI), St. George's Respiratory Questionnaire adapted to patients with COVID-19 (aSGRQ) and WHO Clinical Progression Scale (CPS) were measured at enrolment and at 6 weeks from the onset of symptoms. Persistence of most frequently reported symptoms was assessed at 6 weeks and, among symptomatic patients, at 12 weeks from the onset of symptoms. Predictors of impaired general health over time were identified using an ordinal multilevel multivariate model. RESULTS: A total of 448 patients (55% men, median age 56 years) were enrolled. WHO-CPS showed mild, moderate and severe disease in 48%, 42% and 10% of patients at admission and mild disease in all patients at follow-up, respectively. BI and aSGRQ were normal in 96% and 93% patients before COVID-19 but only in 47% and 16% at COVID-19 diagnosis and in 87% and 65% at 6-week follow-up. Male gender was identified by all three assessments as a predictor of impaired general health (BI, OR 2.14, p < 0.0001; aSGRQ, OR 0.53, p = 0.003; WHO-CPS, OR 1.56, p = 0.01). Other predictors included age, ICU admission and comorbidities (e.g. cardiovascular disease and cancer) for BI, hospital admission for aSGRQ, age and presence of comorbidities for WHO-CPS. At 6- and 12-week follow-up, 39% and 20% of patients, respectively, were still reporting symptoms. Fatigue and breathlessness were the most frequently reported symptoms. CONCLUSIONS: Long-term follow-up facilitates the monitoring of health impairment and symptom persistence and can contribute to plan tailored interventions.