First Results of an External Quality Assessment (EQA) Scheme for Molecular, Serological and Antigenic Diagnostic Test for SARS-CoV-2 Detection in Lombardy Region (Northern Italy), 2020-2022.

For diagnosing SARS-CoV-2 infection and for monitoring its spread, the implementation of external quality assessment (EQA) schemes is mandatory to assess and ensure a standard quality according to national and international guidelines. Here, we present the results of the 2020, 2021, 2022 EQA schemes in Lombardy region for assessing the quality of the diagnostic laboratories involved in SARS-CoV-2 diagnosis. In the framework of the Quality Assurance Programs (QAPs), the routinely EQA schemes are managed by the regional reference centre for diagnostic laboratories quality (RRC-EQA) of the Lombardy region and are carried out by all the diagnostic laboratories. Three EQA programs were organized: (1) EQA of SARS-CoV-2 nucleic acid detection; (2) EQA of anti-SARS-CoV-2-antibody testing; (3) EQA of SARS-CoV-2 direct antigens detection. The percentage of concordance of 1938 molecular tests carried out within the SARS-CoV-2 nucleic acid detection EQA was 97.7%. The overall concordance of 1875 tests carried out within the anti-SARS-CoV-2 antibody EQA was 93.9% (79.6% for IgM). The overall concordance of 1495 tests carried out within the SARS-CoV-2 direct antigens detection EQA was 85% and it was negatively impacted by the results obtained by the analysis of weak positive samples. In conclusion, the EQA schemes for assessing the accuracy of SARS-CoV-2 diagnosis in the Lombardy region highlighted a suitable reproducibility and reliability of diagnostic assays, despite the heterogeneous landscape of SARS-CoV-2 tests and methods. Laboratory testing based on the detection of viral RNA in respiratory samples can be considered the gold standard for SARS-CoV-2 diagnosis.

First Results of an External Quality Assessment (EQA) Scheme for Molecular, Serological and Antigenic Diagnostic Test for SARS-CoV-2 Detection in Lombardy Region (Northern Italy), 2020–2022

For diagnosing SARS-CoV-2 infection and for monitoring its spread, the implementation of external quality assessment (EQA) schemes is mandatory to assess and ensure a standard quality according to national and international guidelines. Here, we present the results of the 2020, 2021, 2022 EQA schemes in Lombardy region for assessing the quality of the diagnostic laboratories involved in SARS-CoV-2 diagnosis. In the framework of the Quality Assurance Programs (QAPs), the routinely EQA schemes are managed by the regional reference centre for diagnostic laboratories quality (RRC-EQA) of the Lombardy region and are carried out by all the diagnostic laboratories. Three EQA programs were organized: (1) EQA of SARS-CoV-2 nucleic acid detection;(2) EQA of anti-SARS-CoV-2-antibody testing;(3) EQA of SARS-CoV-2 direct antigens detection. The percentage of concordance of 1938 molecular tests carried out within the SARS-CoV-2 nucleic acid detection EQA was 97.7%. The overall concordance of 1875 tests carried out within the anti-SARS-CoV-2 antibody EQA was 93.9% (79.6% for IgM). The overall concordance of 1495 tests carried out within the SARS-CoV-2 direct antigens detection EQA was 85% and it was negatively impacted by the results obtained by the analysis of weak positive samples. In conclusion, the EQA schemes for assessing the accuracy of SARS-CoV-2 diagnosis in the Lombardy region highlighted a suitable reproducibility and reliability of diagnostic assays, despite the heterogeneous landscape of SARS-CoV-2 tests and methods. Laboratory testing based on the detection of viral RNA in respiratory samples can be considered the gold standard for SARS-CoV-2 diagnosis.

Algorithm for Individual Prediction of COVID-19-Related Hospitalization Based on Symptoms: Development and Implementation Study.

BACKGROUND: The COVID-19 pandemic has placed a huge strain on the health care system globally. The metropolitan area of Milan, Italy, was one of the regions most impacted by the COVID-19 pandemic worldwide. Risk prediction models developed by combining administrative databases and basic clinical data are needed to stratify individual patient risk for public health purposes. OBJECTIVE: This study aims to develop a stratification tool aimed at improving COVID-19 patient management and health care organization. METHODS: A predictive algorithm was developed and applied to 36,834 patients with COVID-19 in Italy between March 8 and the October 9, 2020, in order to foresee their risk of hospitalization. Exposures considered were age, sex, comorbidities, and symptoms associated with COVID-19 (eg, vomiting, cough, fever, diarrhea, myalgia, asthenia, headache, anosmia, ageusia, and dyspnea). The outcome was hospitalizations and emergency department admissions for COVID-19. Discrimination and calibration of the model were also assessed. RESULTS: The predictive model showed a good fit for predicting COVID-19 hospitalization (C-index 0.79) and a good overall prediction accuracy (Brier score 0.14). The model was well calibrated (intercept -0.0028, slope 0.9970). Based on these results, 118,804 patients diagnosed with COVID-19 from October 25 to December 11, 2020, were stratified into low, medium, and high risk for COVID-19 severity. Among the overall study population, 67,030 (56.42%) were classified as low-risk patients; 43,886 (36.94%), as medium-risk patients; and 7888 (6.64%), as high-risk patients. In all, 89.37% (106,179/118,804) of the overall study population was being assisted at home, 9% (10,695/118,804) was hospitalized, and 1.62% (1930/118,804) died. Among those assisted at home, most people (63,983/106,179, 60.26%) were classified as low risk, whereas only 3.63% (3858/106,179) were classified at high risk. According to ordinal logistic regression, the odds ratio (OR) of being hospitalized or dead was 5.0 (95% CI 4.6-5.4) among high-risk patients and 2.7 (95% CI 2.6-2.9) among medium-risk patients, as compared to low-risk patients. CONCLUSIONS: A simple monitoring system, based on primary care data sets linked to COVID-19 testing results, hospital admissions data, and death records may assist in the proper planning and allocation of patients and resources during the ongoing COVID-19 pandemic.

Results of the RENAISSANCE Study: REsponse to BNT162b2 COVID-19 vacciNe-short- And long-term Immune reSponSe evAluatioN in health Care workErs.

OBJECTIVE: To evaluate the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) anti-spike (S) IgG antibody production after vaccination with BNT162b2 and the protection from symptomatic breakthrough infections in health care workers. METHODS: This prospective observational study (RENAISSANCE) had as a primary end point the evaluation of serologic response to BNT162b2 14 days after a second dose. SARS-CoV-2 anti-S IgG antibodies were evaluated with LIAISON SARS-CoV-2 TrimericS IgG assay (DiaSorin S.p.A.), which is able to detect the presence of both binding and neutralizing antibodies for trimeric spike glycoprotein. Participants were recruited from February 1, 2021, to February 22, 2021. Occurrence of vaccine breakthrough infections was assessed by reverse transcription-polymerase chain reaction on symptomatic and contact cases up to June 6, 2021. RESULTS: Of 2569 staff evaluated, only 4 were nonresponders (0.16%; 95% CI, 0.04% to 0.41%). All 4 nonresponders were severely immunosuppressed and receiving treatment with mycophenolate mofetil or mycophenolic acid. At 14 days after the second dose, 67.5% (1733) of staff had anti-S IgG titers of 2000 BAU/mL or higher; 19.2% (494), between 1500 and 2000 BAU/mL; 9.8% (251), between 1000 and 1500 BAU/mL; and 3.4% (87), 1000 BAU/mL or lower. Women had a higher probability of having higher titers than men (64.5% [1044/1618] vs 58.3% [410/703]; P=.005). This was confirmed after adjustment for age group (odds ratio, 1.275; 95% CI, 1.062 to 1.531; P=.009). Four months after the end of the vaccination program, only 13 participants (0.26%) had experienced a breakthrough SARS-CoV-2 infection, including 1 nonresponder. This was the only participant requiring hospitalization for severe COVID-19. CONCLUSION: The vaccination campaign among health care workers at the ASST GOM Niguarda has resulted in a marked serologic response and reduction of incident COVID-19 cases. Yet, the lack of protection should not be overlooked in immunocompromised individuals.

The impact of the COVID-19 emergency in a community mental health setting of a metropolitan hospital

Objectives: To evaluate the relationship between traumatic aspects of the COVID-19 emergency and clinical correlates in a sample of consecutive outpatients in a Community Mental Health setting in Milan, Italy. Methods: One hundred and forty subjects aged between 18 and 75 years were assessed with the Clinical Global Impression-Severity (CGI-S), Brief Psychiatric Rating Scale (BPRS-18), the 22-item Impact of Event Scale-Revised (IES-R) and the Self Report Questionnaire (SRQ-20). Data analysis were performed using SPSS version 16.0. Basic statistics were used to describe the demographic and clinical characteristics of the participants. The associations between sociodemographic and clinical variables were explored first by performing Pearson's correlation analysis followed by multivariate regression. IES-R total score was used as the dependent variable while sociodemographic variables, SRQ-20, CGI-S and BPRS total score were used as independent variables. Results: A considerable proportion of participants reported symptoms of distress measured by IES-R: 47 (33.6%) mild, 45 (32.1%) moderate and 37 (26.4%) severe. SRQ-20 total score was positive in 82 (58.6%) patients, particularly in the female population (p = 0.009) with an age between 45-65 years (p = 0.020). In multiple regression analysis, being actively working (Beta = 0.15, p = 0.03) and SRQ-20 (Beta = 0.56, p = 0.00) significantly predicted IES-R total score. Conclusions: Our data evidenced high level of distress among patients in contact with mental health services during Covid-19 emergency period suggesting the importance of maintaining continuous monitoring for a careful assessment of their condition from both a psychopathological and medical point of view. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

Neurological manifestations in patients hospitalized with COVID-19: A retrospective analysis from a large cohort in Northern Italy.

SARS-CoV2 infection is a systemic disease that may involve multiple organs, including the central nervous system (CNS). Aims of our study are to describe prevalence and clinical features of neurological manifestations, mortality and hospital discharge in subjects hospitalized with COVID-19. All individuals admitted for to our hospital COVID-19 were retrospectively included. Patients were classified according to the symptoms at hospital entry in (1) isolated respiratory, (2) combined respiratory and neurologic, (3) isolated neurologic and (4) stroke manifestations. Descriptive statistics and nonparametric tests to compare the groups were calculated. Kaplan Meier probability curves and multivariable Cox regression models for survival and hospital discharge were applied. The analysis included 901 patients: 42.6% showed a severe or critical disease with an overall mortality of 21.2%. At least one neurological symptom or disease was observed in 30.2% of subjects ranging from dysgeusia/anosmia (9.1%) to postinfective diseases (0.8%). Patients with respiratory symptoms experienced a more severe disease and a higher in-hospital mortality compared to those who showed only neurologic symptoms. Kaplan Meier estimates displayed a statistically significant different survival among groups (p = 0.003): subjects with stroke had the worst. After adjusting for risk factors such as age, sex and comorbidity, individuals with isolated neurologic manifestations exhibited a better survival (aHR 0.398, 95% CI [0.206, 0.769], p = 0.006). Neurologic manifestations in COVID-19 are common but heterogeneous and mortality in subjects with isolated neurologic manifestations seems lower than in those with respiratory symptoms.

Development of machine learning models to predict RT-PCR results for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in patients with influenza-like symptoms using only basic clinical data.

BACKGROUND: Reverse Transcription-Polymerase Chain Reaction (RT-PCR) for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) diagnosis currently requires quite a long time span. A quicker and more efficient diagnostic tool in emergency departments could improve management during this global crisis. Our main goal was assessing the accuracy of artificial intelligence in predicting the results of RT-PCR for SARS-COV-2, using basic information at hand in all emergency departments. METHODS: This is a retrospective study carried out between February 22, 2020 and March 16, 2020 in one of the main hospitals in Milan, Italy. We screened for eligibility all patients admitted with influenza-like symptoms tested for SARS-COV-2. Patients under 12 years old and patients in whom the leukocyte formula was not performed in the ED were excluded. Input data through artificial intelligence were made up of a combination of clinical, radiological and routine laboratory data upon hospital admission. Different Machine Learning algorithms available on WEKA data mining software and on Semeion Research Centre depository were trained using both the Training and Testing and the K-fold cross-validation protocol. RESULTS: Among 199 patients subject to study (median [interquartile range] age 65 [46-78] years; 127 [63.8%] men), 124 [62.3%] resulted positive to SARS-COV-2. The best Machine Learning System reached an accuracy of 91.4% with 94.1% sensitivity and 88.7% specificity. CONCLUSION: Our study suggests that properly trained artificial intelligence algorithms may be able to predict correct results in RT-PCR for SARS-COV-2, using basic clinical data. If confirmed, on a larger-scale study, this approach could have important clinical and organizational implications.

Safety and efficacy of anti-il6-receptor tocilizumab use in severe and critical patients affected by coronavirus disease 2019: A comparative analysis.

BACKGROUND: As the novel SARS-CoV-2 pandemic occurred, no specific treatment was yet available. Inflammatory response secondary to viral infection might be the driver of severe diseases. We report the safety and efficacy (in terms of overall survival and hospital discharge) of the anti-IL6 tocilizumab (TCZ) in subjects with COVID-19. METHODS: This retrospective, single-center analysis included all the patients consecutively admitted to our Hospital with severe or critical COVID-19 who started TCZ treatment from March 13th to April 03rd, 2020. A 1:2 matching to patients not treated with TCZ was performed according to age, sex, severity of disease, P/F, Charlson Comorbidity Index and length of time between symptoms onset and hospital admittance. Descriptive statistics and non-parametric tests to compare the groups were applied. Kaplan Meier probability curves and Cox regression models for survival, hospital discharge and orotracheal intubation were used. RESULTS: Seventy-four patients treated with TCZ were matched with 148 matched controls. They were mainly males (81.5%), Caucasian (82.0%) and with a median age of 59 years. The majority (69.8%) showed critical stage COVID-19 disease. TCZ use was associated with a better overall survival (HR 0.499 [95% CI 0.262-0.952], p = 0.035) compared to controls but with a longer hospital stay (HR 1.658 [95% CI 1.088-2.524], p = 0.019) mainly due to biochemical, respiratory and infectious adverse events. DISCUSSION: TCZ use resulted potentially effective on COVID-19 in terms of overall survival. Caution is warranted given the potential occurrence of adverse events. FINANCIAL SUPPORT: Some of the tocilizumab doses used in the subjects included in this analysis were provided by the "Multicenter study on the efficacy and tolerability of tocilizumab in the treatment of patients with COVID-19 pneumonia" (EudraCT Number: 2020-001110-38) supported by the Italian National Agency for Drugs (AIFA). No specific funding support was planned for study design, data collection and analysis and manuscript writing of this paper.

Mental Health Services in Lombardy during COVID-19 outbreak.

Lombardy is the Region in Italy the most heavily affected by coronavirus disease (COVID-19) contagion. The Regional Health Authority mandates that mental health services should be guaranteed, identifying mental health as a priority for their citizens. Recommendations for occupational and health safety have been provided to patients and hospital staff, including support for telemedicine activities and remote psychosocial interventions. Services of the Mental Health Departments of Milano "Niguarda" and Brescia "Spedali Civili" Hospitals are providing continued care at a community, residential and hospital level, and to positive COVID-19 psychiatric patients in need of hospitalization.