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1.
Isr J Health Policy Res ; 11(1): 22, 2022 04 20.
Article in English | MEDLINE | ID: covidwho-1808383

ABSTRACT

The COVID-19 pandemic cast a dramatic spotlight on the use of data as a fundamental component of good decision-making. Evaluating and comparing alternative policies required information on concurrent infection rates and insightful analysis to project them into the future. Statisticians in Israel were involved in these processes early in the pandemic in some silos as an ad-hoc unorganized effort. Informal discussions within the statistical community culminated in a roundtable, organized by three past presidents of the Israel Statistical Association, and hosted by the Samuel Neaman Institute in April 2021. The meeting was designed to provide a forum for exchange of views on the profession's role during the COVID-19 pandemic, and more generally, on its influence in promoting evidence-based public policy. This paper builds on the insights and discussions that emerged during the roundtable meeting and presents a general framework, with recommendations, for involving statisticians and statistics in decision-making.


Subject(s)
COVID-19 , Humans , Israel/epidemiology , Pandemics/prevention & control , Public Policy
3.
Front Immunol ; 12: 772239, 2021.
Article in English | MEDLINE | ID: covidwho-1528825

ABSTRACT

This contribution explores in a new statistical perspective the antibody responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 141 coronavirus disease 2019 (COVID-19) patients exhibiting a broad range of clinical manifestations. This cohort accurately reflects the characteristics of the first wave of the SARS-CoV-2 pandemic in Italy. We determined the IgM, IgA, and IgG levels towards SARS-CoV-2 S1, S2, and NP antigens, evaluating their neutralizing activity and relationship with clinical signatures. Moreover, we longitudinally followed 72 patients up to 9 months postsymptoms onset to study the persistence of the levels of antibodies. Our results showed that the majority of COVID-19 patients developed an early virus-specific antibody response. The magnitude and the neutralizing properties of the response were heterogeneous regardless of the severity of the disease. Antibody levels dropped over time, even though spike reactive IgG and IgA were still detectable up to 9 months. Early baseline antibody levels were key drivers of the subsequent antibody production and the long-lasting protection against SARS-CoV-2. Importantly, we identified anti-S1 IgA as a good surrogate marker to predict the clinical course of COVID-19. Characterizing the antibody response after SARS-CoV-2 infection is relevant for the early clinical management of patients as soon as they are diagnosed and for implementing the current vaccination strategies.


Subject(s)
Antibodies, Neutralizing/blood , Antibodies, Viral/blood , COVID-19/blood , Immunoglobulin A/blood , SARS-CoV-2/immunology , Spike Glycoprotein, Coronavirus/immunology , Adult , Aged , Aged, 80 and over , COVID-19/immunology , Female , HEK293 Cells , Hospitalization , Humans , Immunoglobulin G/blood , Immunoglobulin M/blood , Male , Middle Aged , Young Adult
4.
Mol Med ; 27(1): 129, 2021 10 18.
Article in English | MEDLINE | ID: covidwho-1477255

ABSTRACT

BACKGROUND: Host inflammation contributes to determine whether SARS-CoV-2 infection causes mild or life-threatening disease. Tools are needed for early risk assessment. METHODS: We studied in 111 COVID-19 patients prospectively followed at a single reference Hospital fifty-three potential biomarkers including alarmins, cytokines, adipocytokines and growth factors, humoral innate immune and neuroendocrine molecules and regulators of iron metabolism. Biomarkers at hospital admission together with age, degree of hypoxia, neutrophil to lymphocyte ratio (NLR), lactate dehydrogenase (LDH), C-reactive protein (CRP) and creatinine were analysed within a data-driven approach to classify patients with respect to survival and ICU outcomes. Classification and regression tree (CART) models were used to identify prognostic biomarkers. RESULTS: Among the fifty-three potential biomarkers, the classification tree analysis selected CXCL10 at hospital admission, in combination with NLR and time from onset, as the best predictor of ICU transfer (AUC [95% CI] = 0.8374 [0.6233-0.8435]), while it was selected alone to predict death (AUC [95% CI] = 0.7334 [0.7547-0.9201]). CXCL10 concentration abated in COVID-19 survivors after healing and discharge from the hospital. CONCLUSIONS: CXCL10 results from a data-driven analysis, that accounts for presence of confounding factors, as the most robust predictive biomarker of patient outcome in COVID-19.


Subject(s)
COVID-19/diagnosis , Chemokine CXCL10/blood , Coronary Artery Disease/diagnosis , Diabetes Mellitus/diagnosis , Hypertension/diagnosis , Biomarkers/blood , C-Reactive Protein/metabolism , COVID-19/blood , COVID-19/immunology , COVID-19/mortality , Comorbidity , Coronary Artery Disease/blood , Coronary Artery Disease/immunology , Coronary Artery Disease/mortality , Creatine/blood , Diabetes Mellitus/blood , Diabetes Mellitus/immunology , Diabetes Mellitus/mortality , Female , Hospitalization , Humans , Hypertension/blood , Hypertension/immunology , Hypertension/mortality , Immunity, Humoral , Immunity, Innate , Inflammation , Intensive Care Units , L-Lactate Dehydrogenase/blood , Leukocyte Count , Lymphocytes/immunology , Lymphocytes/pathology , Male , Middle Aged , Neutrophils/immunology , Neutrophils/pathology , Prognosis , Prospective Studies , Retrospective Studies , SARS-CoV-2 , Severity of Illness Index , Survival Analysis
6.
Microbiol Spectr ; 9(2): e0025021, 2021 10 31.
Article in English | MEDLINE | ID: covidwho-1434908

ABSTRACT

During the last year, mass screening campaigns have been carried out to identify immunological response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and establish a possible seroprevalence. The obtained results gained new importance with the beginning of the SARS-CoV-2 vaccination campaign, as the lack of doses has persuaded several countries to introduce different policies for individuals who had a history of COVID-19. Lateral flow assays (LFAs) may represent an affordable tool to support population screening in low-middle-income countries, where diagnostic tests are lacking and epidemiology is still widely unknown. However, LFAs have demonstrated a wide range of performance, and the question of which one could be more valuable in these settings still remains. We evaluated the performance of 11 LFAs in detecting SARS-CoV-2 infection, analyzing samples collected from 350 subjects. In addition, samples from 57 health care workers collected at 21 to 24 days after the first dose of the Pfizer-BioNTech vaccine were also evaluated. LFAs demonstrated a wide range of specificity (92.31% to 100%) and sensitivity (50% to 100%). The analysis of postvaccination samples was used to describe the most suitable tests to detect IgG response against S protein receptor binding domain (RBD). Tuberculosis (TB) therapy was identified as a potential factor affecting the specificity of LFAs. This analysis identified which LFAs represent a valuable tool not only for the detection of prior SARS-CoV-2 infection but also for the detection of IgG elicited in response to vaccination. These results demonstrated that different LFAs may have different applications and the possible risks of their use in high-TB-burden settings. IMPORTANCE Our study provides a fresh perspective on the possible employment of SARS-CoV-2 LFA antibody tests. We developed an in-depth, large-scale analysis comparing LFA performance to enzyme-linked immunosorbent assay (ELISA) and electrochemiluminescence immunoassay (ECLIA) and evaluating their sensitivity and specificity in identifying COVID-19 patients at different time points from symptom onset. Moreover, for the first time, we analyzed samples of patients undergoing treatment for endemic poverty-related diseases, especially tuberculosis, and we evaluated the impact of this therapy on test specificity in order to assess possible performance in TB high-burden countries.


Subject(s)
Antibodies, Viral/blood , COVID-19 Serological Testing/methods , COVID-19 Vaccines/immunology , SARS-CoV-2/immunology , Spike Glycoprotein, Coronavirus/immunology , Adult , COVID-19/diagnosis , Electrochemical Techniques , Enzyme-Linked Immunosorbent Assay , Female , Humans , Immunoassay/methods , Immunoglobulin G/blood , Immunoglobulin M/blood , Male , Mass Screening/methods , Point-of-Care Testing , Sensitivity and Specificity , Tuberculosis/diagnosis , Young Adult
7.
Clin Imaging ; 77: 194-201, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1226279

ABSTRACT

BACKGROUND: The aim of this study was to quantify COVID-19 pneumonia features using CT performed at time of admission to emergency department in order to predict patients' hypoxia during the hospitalization and outcome. METHODS: Consecutive chest CT performed in the emergency department between March 1st and April 7th 2020 for COVID-19 pneumonia were analyzed. The three features of pneumonia (GGO, semi-consolidation and consolidation) and the percentage of well-aerated lung were quantified using a HU threshold based software. ROC curves identified the optimal cut-off values of CT parameters to predict hypoxia worsening and hospital discharge. Multiple Cox proportional hazards regression was used to analyze the capability of CT quantitative features, demographic and clinical variables to predict the time to hospital discharge. RESULTS: Seventy-seven patients (median age 56-years-old, 51 men) with COVID-19 pneumonia at CT were enrolled. The quantitative features of COVID-19 pneumonia were not associated to age, sex and time-from-symptoms onset, whereas higher number of comorbidities was correlated to lower well-aerated parenchyma ratio (rho = -0.234, p = 0.04) and increased semi-consolidation ratio (rho = -0.303, p = 0.008). Well-aerated lung (≤57%), semi-consolidation (≥17%) and consolidation (≥9%) predicted worst hypoxemia during hospitalization, with moderate areas under curves (AUC 0.76, 0.75, 0.77, respectively). Multiple Cox regression identified younger age (p < 0.01), female sex (p < 0.001), longer time-from-symptoms onset (p = 0.049), semi-consolidation ≤17% (p < 0.01) and consolidation ≤13% (p = 0.03) as independent predictors of shorter time to hospital discharge. CONCLUSION: Quantification of pneumonia features on admitting chest CT predicted hypoxia worsening during hospitalization and time to hospital discharge in COVID-19 patients.


Subject(s)
COVID-19 , Female , Hospitalization , Humans , Hypoxia/diagnostic imaging , Lung/diagnostic imaging , Male , Middle Aged , Retrospective Studies , SARS-CoV-2 , Tomography, X-Ray Computed
8.
Proc Natl Acad Sci U S A ; 118(1)2021 01 07.
Article in English | MEDLINE | ID: covidwho-1066040

ABSTRACT

As the COVID-19 pandemic is spreading around the world, increasing evidence highlights the role of cardiometabolic risk factors in determining the susceptibility to the disease. The fragmented data collected during the initial emergency limited the possibility of investigating the effect of highly correlated covariates and of modeling the interplay between risk factors and medication. The present study is based on comprehensive monitoring of 576 COVID-19 patients. Different statistical approaches were applied to gain a comprehensive insight in terms of both the identification of risk factors and the analysis of dependency structure among clinical and demographic characteristics. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus enters host cells by binding to the angiotensin-converting enzyme 2 (ACE2), but whether or not renin-angiotensin-aldosterone system inhibitors (RAASi) would be beneficial to COVID-19 cases remains controversial. The survival tree approach was applied to define a multilayer risk stratification and better profile patient survival with respect to drug regimens, showing a significant protective effect of RAASi with a reduced risk of in-hospital death. Bayesian networks were estimated, to uncover complex interrelationships and confounding effects. The results confirmed the role of RAASi in reducing the risk of death in COVID-19 patients. De novo treatment with RAASi in patients hospitalized with COVID-19 should be prospectively investigated in a randomized controlled trial to ascertain the extent of risk reduction for in-hospital death in COVID-19.


Subject(s)
Antiviral Agents , COVID-19 , SARS-CoV-2 , Aged , Aged, 80 and over , Angiotensin-Converting Enzyme Inhibitors , COVID-19/drug therapy , COVID-19/mortality , COVID-19/physiopathology , COVID-19/virology , Female , Hospitalization , Humans , Male , Middle Aged , Pandemics , Protective Agents , Renin-Angiotensin System/drug effects , Renin-Angiotensin System/physiology , Risk Factors , Survival Analysis
9.
Eur Radiol ; 31(6): 4031-4041, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-996387

ABSTRACT

OBJECTIVES: Enlarged main pulmonary artery diameter (MPAD) resulted to be associated with pulmonary hypertension and mortality in a non-COVID-19 setting. The aim was to investigate and validate the association between MPAD enlargement and overall survival in COVID-19 patients. METHODS: This is a cohort study on 1469 consecutive COVID-19 patients submitted to chest CT within 72 h from admission in seven tertiary level hospitals in Northern Italy, between March 1 and April 20, 2020. Derivation cohort (n = 761) included patients from the first three participating hospitals; validation cohort (n = 633) included patients from the remaining hospitals. CT images were centrally analyzed in a core-lab blinded to clinical data. The prognostic value of MPAD on overall survival was evaluated at adjusted and multivariable Cox's regression analysis on the derivation cohort. The final multivariable model was tested on the validation cohort. RESULTS: In the derivation cohort, the median age was 69 (IQR, 58-77) years and 537 (70.6%) were males. In the validation cohort, the median age was 69 (IQR, 59-77) years with 421 (66.5%) males. Enlarged MPAD (≥ 31 mm) was a predictor of mortality at adjusted (hazard ratio, HR [95%CI]: 1.741 [1.253-2.418], p < 0.001) and multivariable regression analysis (HR [95%CI]: 1.592 [1.154-2.196], p = 0.005), together with male gender, old age, high creatinine, low well-aerated lung volume, and high pneumonia extension (c-index [95%CI] = 0.826 [0.796-0.851]). Model discrimination was confirmed on the validation cohort (c-index [95%CI] = 0.789 [0.758-0.823]), also using CT measurements from a second reader (c-index [95%CI] = 0.790 [0.753;0.825]). CONCLUSION: Enlarged MPAD (≥ 31 mm) at admitting chest CT is an independent predictor of mortality in COVID-19. KEY POINTS: • Enlargement of main pulmonary artery diameter at chest CT performed within 72 h from the admission was associated with a higher rate of in-hospital mortality in COVID-19 patients. • Enlargement of main pulmonary artery diameter (≥ 31 mm) was an independent predictor of death in COVID-19 patients at adjusted and multivariable regression analysis. • The combined evaluation of clinical findings, lung CT features, and main pulmonary artery diameter may be useful for risk stratification in COVID-19 patients.


Subject(s)
COVID-19 , Pulmonary Artery , Aged , Cohort Studies , Female , Humans , Italy/epidemiology , Male , Pulmonary Artery/diagnostic imaging , Retrospective Studies , SARS-CoV-2 , Tomography, X-Ray Computed
10.
Proc Natl Acad Sci U S A ; 118(1)2021 01 07.
Article in English | MEDLINE | ID: covidwho-972264

ABSTRACT

As the COVID-19 pandemic is spreading around the world, increasing evidence highlights the role of cardiometabolic risk factors in determining the susceptibility to the disease. The fragmented data collected during the initial emergency limited the possibility of investigating the effect of highly correlated covariates and of modeling the interplay between risk factors and medication. The present study is based on comprehensive monitoring of 576 COVID-19 patients. Different statistical approaches were applied to gain a comprehensive insight in terms of both the identification of risk factors and the analysis of dependency structure among clinical and demographic characteristics. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus enters host cells by binding to the angiotensin-converting enzyme 2 (ACE2), but whether or not renin-angiotensin-aldosterone system inhibitors (RAASi) would be beneficial to COVID-19 cases remains controversial. The survival tree approach was applied to define a multilayer risk stratification and better profile patient survival with respect to drug regimens, showing a significant protective effect of RAASi with a reduced risk of in-hospital death. Bayesian networks were estimated, to uncover complex interrelationships and confounding effects. The results confirmed the role of RAASi in reducing the risk of death in COVID-19 patients. De novo treatment with RAASi in patients hospitalized with COVID-19 should be prospectively investigated in a randomized controlled trial to ascertain the extent of risk reduction for in-hospital death in COVID-19.


Subject(s)
Antiviral Agents , COVID-19 , SARS-CoV-2 , Aged , Aged, 80 and over , Angiotensin-Converting Enzyme Inhibitors , COVID-19/drug therapy , COVID-19/mortality , COVID-19/physiopathology , COVID-19/virology , Female , Hospitalization , Humans , Male , Middle Aged , Pandemics , Protective Agents , Renin-Angiotensin System/drug effects , Renin-Angiotensin System/physiology , Risk Factors , Survival Analysis
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