Knowledge, Attitudes and Practices towards SARS-CoV-2 vaccination among morbid obese individuals: a pilot study.

BACKGROUND AND AIM: Vaccinations have dramatically impacted on the ongoing pandemic of COVID-19, the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As morbid obese (MO) individuals are at high risk for severe complications, their acceptance of SARS-CoV-2 vaccines is of certain public health interest. METHODS: We investigated the knowledge, attitudes and eventual acceptance of SARS-CoV-2/COVID-19 vaccination among MO individuals either in waiting list, or recipients of bariatric surgery from a reference center (Parma University Hospital) shortly before the inception of the Italian mass vaccination campaign (March 2021). Data were collected through a web-based questionnaire. Association of individual factors with acceptance of SARS-CoV-2 vaccine was assessed by means of a logistic regression analysis with eventual calculation of adjusted Odds Ratios (aOR) and corresponding 95% Confidence Intervals (95%CI). RESULTS: Adequate, general knowledge of SARS-CoV-2/COVID-19 was found in the majority of MO patients. High perception of SARS-CoV-2 risk was found in around 80% of participants (79.2% regarding its occurrence, 73.6% regarding its potential severity). Acceptance of SARS-CoV-2/COVID-19 vaccination was reported by 65.3% of participants, and was more likely endorsed by MO patients who were likely to accept some sort of payment/copayment (aOR 5.783; 1.426; 23.456), or who were more likely towards a vaccination mandate (aOR 7.920; 1.995; 31.444). CONCLUSIONS: Around one third of the MO individuals among potential recipient of bariatric surgery exhibited some significant hesitancy towards SARS-CoV-2 vaccine, and a rational approach may fail to capture and address specific barriers/motivators in this subset of individuals, stressing the importance for alternative interventions. (www.actabiomedica.it).

Antigen Detection Tests for SARS-CoV-2: a systematic review and meta-analysis on real world data.

Background and aim Rapid antigen detection (RAD) tests on nasopharyngeal specimens have been recently made available for SARS-CoV-2 infections, and early studies suggested their potential utilization as rapid screening and diagnostic testing. The present systematic review and meta-analysis was aimed to assess available evidence and to explore the reliability of antigenic tests in the management of the SARS-CoV-2 pandemic. MATERIALS AND METHODS: We reported our meta-analysis according to the PRISMA statement. We searched Pubmed, Embase, and pre-print archive medRxiv.og for eligible studies published up to November 5th, 2020. Raw data included true/false positive and negative tests, and the total number of tests. Sensitivity and specificity data were calculated for every study, and then pooled in a random-effects model. Heterogeneity was assessed using the I2 measure. Reporting bias was assessed by means of funnel plots and regression analysis. RESULTS: Based on 25 studies, we computed a pooled sensitivity of 72.8% (95%CI 62.4-81.3), a specificity of 99.4% (95%CI 99.0-99.7), with high heterogeneity and risk of reporting bias. More precisely, RAD tests exhibited higher sensitivity on samples with high viral load (i.e. <25 Cycle Threshold; 97.6%; 95%CI 94.1-99.0), compared to those with low viral load (≥25 Cycle Threshold; 43.6%; 95% 27.6-61.1). DISCUSSION: As the majority of collected reports were either cohort or case-control studies, deprived of preventive power analysis and often oversampling positive tests, overall performances may have been overestimated. Therefore, the massive referral to antigenic tests in place of RT-qPCR is currently questionable, and also their deployment as mass screening test may lead to intolerable share of missing diagnoses. On the other hand, RAD tests may find a significant role in primary care and in front-line settings (e.g. Emergency Departments). (www.actabiomedica.it).

Machine learning in perioperative medicine: a systematic review.

BACKGROUND: Risk stratification plays a central role in anesthetic evaluation. The use of Big Data and machine learning (ML) offers considerable advantages for collection and evaluation of large amounts of complex health-care data. We conducted a systematic review to understand the role of ML in the development of predictive post-surgical outcome models and risk stratification. METHODS: Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, we selected the period of the research for studies from 1 January 2015 up to 30 March 2021. A systematic search in Scopus, CINAHL, the Cochrane Library, PubMed, and MeSH databases was performed; the strings of research included different combinations of keywords: "risk prediction," "surgery," "machine learning," "intensive care unit (ICU)," and "anesthesia" "perioperative." We identified 36 eligible studies. This study evaluates the quality of reporting of prediction models using the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) checklist. RESULTS: The most considered outcomes were mortality risk, systemic complications (pulmonary, cardiovascular, acute kidney injury (AKI), etc.), ICU admission, anesthesiologic risk and prolonged length of hospital stay. Not all the study completely followed the TRIPOD checklist, but the quality was overall acceptable with 75% of studies (Rev #2, comm #minor issue) showing an adherence rate to TRIPOD more than 60%. The most frequently used algorithms were gradient boosting (n = 13), random forest (n = 10), logistic regression (LR; n = 7), artificial neural networks (ANNs; n = 6), and support vector machines (SVM; n = 6). Models with best performance were random forest and gradient boosting, with AUC > 0.90. CONCLUSIONS: The application of ML in medicine appears to have a great potential. From our analysis, depending on the input features considered and on the specific prediction task, ML algorithms seem effective in outcomes prediction more accurately than validated prognostic scores and traditional statistics. Thus, our review encourages the healthcare domain and artificial intelligence (AI) developers to adopt an interdisciplinary and systemic approach to evaluate the overall impact of AI on perioperative risk assessment and on further health care settings as well.

Occurrence of SARS-CoV-2 infection among healthcare personnel: results from an early systematic review and meta-analysis.

BACKGROUND: SARS-CoV-2 infection has become a global public health concern globally. Even though Healthcare Workers (HCWs) are supposedly at increased risk for SARS-CoV-2 infection, to date no pooled evidence has been collected. MATERIALS AND METHODS: We searched online electronic databases (PubMed, Embase, medRxiv.org for pre-prints) for all available contribution (up to May 20, 2019). Two Authors independently screened articles and extracted the data. The pooled prevalence of SARS-CoV-2 was analyzed using the random-effects model. The possible sources of heterogeneity were analyzed through subgroup analysis, and meta-regression. RESULTS: The overall pooled prevalence of SARS-CoV-2 was 3.5% (95%CI 1.8-6.6) for studies based on molecular assays, 5.5% (95%CI 2.1-14.1) for studies based on serological assays, and 6.5% (95%CI 2.5-15.6) for point-of-care capillary blood tests. Among subgroups, serological tests identified higher risk for SARS-CoV-2 seropositivity in physicians than in nurses (OR 1.436, 95%CI 1.026 to 2.008). Regression analysis indicated the possible presence of publication bias only for molecular tests (t -3.3526, p-value 0.002648). CONCLUSIONS: The overall pooled prevalence of SARS-CoV-2 was lower than previously expected, but available studies were affected by significant heterogeneity, and the molecular studies by significant publication bias. Therefore, further high-quality research in the field is warranted.

RT-qPCR assays based on saliva rather than on nasopharyngeal swabs are possible but should be interpreted with caution: results from a systematic review and meta-analysis.

BACKGROUND AND AIM OF THE WORK: The ongoing pandemic has elicited an increasing interest regarding the SARS-CoV-2 viral RNA detection in saliva specimens rather than through nasopharyngeal swabs. Our aim was to conduct a meta-analysis on the sensitivity and specificity of SARS-CoV-2 viral RNA detection through RT-qPCR based on salivary specimens compared to conventional nasopharyngeal swabs. METHODS: We reported our meta-analysis according to the PRISMA statement. We searched Pubmed, Embase, and pre-print archive medRxiv.og for eligible studies published up to June 1st, 2020. Raw data included true/false positive and negative tests, and the total number of tests. Sensitivity and specificity data were calculated for every study, and then pooled in a random-effects model. Heterogeneity was assessed using the I2 measure. Reporting bias was assessed by means of funnel plots and regression analysis. RESULTS: The systematic review eventually retrieved 14 studies including a total of 15 estimates, the were included in quantitative synthesis. We found a pooled specificity of 97.7% (95%CI 93.8-99.2) and a pooled sensitivity of 83.4% (95%CI 73.1-90.4), with an overall agreement assessed by means of Cohen's kappa equals to 0.750, 95%CI 0.62-0.88 (i.e. moderate agreement), with high heterogeneity and risk of reporting bias. CONCLUSIONS: In conclusion, diagnostic tests based on salivary specimens are somewhat reliable, but relatively few studies have been carried out. Moreover, such studies are characterized by low numbers and low sample power. Therefore, the of salivary samples is currently questionable for clinical purposes and cannot substitute other more conventional RT-qPCR based on nasopharyngeal swabs.

Effects of Bariatric Surgery on COVID-19: a Multicentric Study from a High Incidence Area.

INTRODUCTION: The favorable effects of bariatric surgery (BS) on overall pulmonary function and obesity-related comorbidities could influence SARS-CoV-2 clinical expression. This has been investigated comparing COVID-19 incidence and clinical course between a cohort of patients submitted to BS and a cohort of candidates for BS during the spring outbreak in Italy. MATERIALS AND METHODS: From April to August 2020, 594 patients from 6 major bariatric centers in Emilia-Romagna were administered an 87-item telephonic questionnaire. Demographics, COVID-19 incidence, suggestive symptoms, and clinical outcome parameters of operated patients and candidates to BS were compared. The incidence of symptomatic COVID-19 was assessed including the clinical definition of probable case, according to World Health Organization criteria. RESULTS: Three hundred fifty-three operated patients (Op) and 169 candidates for BS (C) were finally included in the statistical analysis. While COVID-19 incidence confirmed by laboratory tests was similar in the two groups (5.7% vs 5.9%), lower incidence of most of COVID-19-related symptoms, such as anosmia (p: 0.046), dysgeusia (p: 0.049), fever with rapid onset (p: 0.046) were recorded among Op patients, resulting in a lower rate of probable cases (14.4% vs 23.7%; p: 0.009). Hospitalization was more frequent in C patients (2.4% vs 0.3%, p: 0.02). One death in each group was reported (0.3% vs 0.6%). Previous pneumonia and malignancies resulted to be associated with symptomatic COVID-19 at univariate and multivariate analysis. CONCLUSION: Patients submitted to BS seem to develop less severe SARS-CoV-2 infection than subjects suffering from obesity.