Bariatric Surgery and COVID-19: a Change of Perspective in a New Phase of the Pandemic.

PURPOSE: The protective role of bariatric surgery (BS) against COVID-19 has been reported by several studies, showing, in the first pandemic waves, better outcome of the infection in patients that had undergone BS. With the virus progressive endemicity, BS benefits on COVID-19 clinical course could appear less evident, while COVID-19 effects on BS outcomes must be investigated. In this national multicentric cross-sectional study, we compared COVID-19 incidence and clinical course between a cohort of patients that had undergone BS (OP) and a cohort of candidates to BS (WS); moreover, we analyzed BS outcomes based on SARS-CoV-2 positivity/negativity. METHODS: From June to December 2021, 522 patients from five Italian referral centers were administered an 87-item telephonic questionnaire completing the analysis of electronic medical records. Demographics, COVID-19 "tested" incidence, suggestive symptoms and clinical outcome parameters of OP and WS were compared. BS outcomes parameters were compared between OP that developed the disease or not. RESULTS: COVID-19 incidence was the same in OP and WS, while symptoms and clinical course seemed milder in OP, with no data individually reaching statistical significance. OP who developed SARS-CoV-2 infection had higher excess weight loss than negative OP (66.8% ± 22.1 vs. 57.7% ± 22.8, p = 0.029). Positive OP had had gastric-bypass (RYGB/OAGB) more frequently than negative ones (38.4% vs. 18.2%, p = 0.025). CONCLUSION: With the disease becoming endemic, BS protective role against COVID-19 seems clinically less relevant. BS outcomes can be affected by COVID-19, thus imposing careful follow-up for positive patients, especially if undergoing gastric-bypass.

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).

Understanding of the Nutri-Score front-of-pack label by Italian Medical Professionals and its effect on food choices: a web-based study on knowledge, attitudes and practices.

BACKGROUND AND AIM: A growing number of European Countries have adopted front-of-pack nutrition labels (FPNL) in order to assist costumers' alimentary choices, and particularly Nutri-Score. While its acceptance in Italy has been slowed by ongoing debates, we assessed corresponding knowledge, attitudes and practices of a sample of Italian Medical Professionals (MP). METHODS: A total of 153 MP participated into an internet-based survey by completing a structured questionnaire. While 43.1% reported any knowledge of Nutri-Score, the overall understanding of its conceptual issues was quite low (50.8% after percentual normalization of the knowledge score). Only half of participants acknowledge some usefulness of FPNL, and their acceptance as a guide for nutritional choices was seemingly low (36.6%), being more likely in MP participants from Northern regions (Odds Ratio 9.610, 95% confidence intervals 2.667-34.637), living with children < 14 year or age (3.658, 1.463-9.145), and perceiving some usefulness in FPNL (3.595, 1.381-9.356). In turn, having any knowledge of Nutri-Score and being of male gender were negative effects. CONCLUSIONS: Nutri-Score is a useful instrument in guiding consumers' alimentary choices, but the actual understanding of its rationale by participants MP was insufficient. Specifically aimed interventions should be tailored in order to cope with a significant share of MP reporting false beliefs and misunderstanding.

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).

Current Applications of Artificial Intelligence in Bariatric Surgery.

The application of artificial intelligence technologies is growing in several fields of healthcare settings. The aim of this article is to review the current applications of artificial intelligence in bariatric surgery. We performed a review of the literature on Scopus, PubMed and Cochrane databases, screening all relevant studies published until September 2021, and finally including 36 articles. The use of machine learning algorithms in bariatric surgery is explored in all steps of the clinical pathway, from presurgical risk-assessment and intraoperative management to complications and outcomes prediction. The models showed remarkable results helping physicians in the decision-making process, thus improving the quality of care, and contributing to precision medicine. Several legal and ethical hurdles should be overcome before these methods can be used in common practice.

Analysis of Rates, Causes, and Risk Factors for 90-Day Readmission After Surgery for Large Hiatal Hernia: A Two-Center Study.

Background: Hospital readmissions have become a more examined indicator of surgical care delivery and quality. There is scarcity of data in the literature on the rate, risk factors, and most common reasons of readmission following major hiatal hernia surgery. The primary endpoint was 90-day readmission after surgery for large hiatal hernia. Secondary endpoint was to examine which characteristics related with a higher risk of readmission. Methods: A retrospective review of two distinct institutional databases was performed for patients who had surgery for a large hiatal hernia between January 2012 and December 2019. Demographic, perioperative, and outpatient data were collected from the medical record. Results: A total of 71 patients met the inclusion criteria, most of them suffering from a type III hernia (66.2%). Mean operative time was 146 (±56.5) minutes and median length of stay (LOS) was 6 days (interquartile range = 3). The overall morbidity was 21.1% and the in-hospital mortality was 1.4%. The 30- and 90-day readmission rates were 7% and 8.5%, respectively. The mean time to readmission was 14.3 (±15.6) days. The reasons for 90-day hospital readmission were dysphagia (50%), pneumonia (16.7%), congestive heart failure (16.7%), and bowel obstruction (16.7%). Grade of esophagitis ≥2, presence of Barrett's esophagus, and LOS longer than 8 days were significant risk factors for unplanned readmission within 90 days. Conclusion: We observed that about 6 out of 71 patients who had surgery readmitted within 90 days (8.5%). Readmissions were most often linked to esophagitis ≥2, presence of Barrett's esophagus, and LOS longer than 8 days. These findings point to the necessity for focused treatments before, during, and after hospitalization to decrease morbidity and extra costs in this high-risk population.

Artificial intelligence and telemedicine in anesthesia: potential and problems.

The application of novel technologies like artificial intelligence (AI), machine learning (ML) and telemedicine in anesthesiology could play a role in transforming the future of health care. In the present review we discuss the current applications of AI and telemedicine in anesthesiology and perioperative care, exploring their potential influence and the possible hurdles. AI technologies have the potential to deeply impact all phases of perioperative care from accurate risk prediction to operating room organization, leading to increased cost-effective care quality and better outcomes. Telemedicine is reported as a successful mean within the anesthetic pathway, including preoperative evaluation, remote patient monitoring, and postoperative care. The utilization of AI and telemedicine is promising encouraging results in perioperative management, nevertheless several hurdles remain to be overcome before these tools could be integrated in our daily practice. AI models and telemedicine can significantly influence all phases of perioperative care, helping physicians in the development of precision medicine.

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.

Hantavirus infections in Italy: not reported doesn't mean inexistent.

BACKGROUND: Hantaviruses can cause serious human diseases including hemorrhagic fever with renal syndrome (HFRS) and Hantavirus Cardiopulmonary Syndrome (HCPS). European Hantavirus are usually associated with HFRS, and their geographical distribution mirrors the ecology of reservoir host species. Epidemiology of HFRS is well-studied in Western Europe, but data from Italy are fragmentary. METHODS: We searched into two different databases (PubMed and EMBASE), focusing on studies reporting the prevalence of Hantaviruses in Italy. Data were extracted using a standardized assessment form, and results of the analyses were systematically reported, summarized and compared. RESULTS: We identified a total of 18 articles, including 12 reports (total population: 5,336 subjects, 1981-2019) and 6 case reports (1984-2019). In total, 200 subjects exhibited some degree of seropositivity, with a pooled seroprevalence of 1.7% (95% confidence interval 0.7%-4.0%) in the general population. Higher occurrence was reported in selected subgroups, i.e. acute (28.7%, 95%CI 22.1-36.2) and chronic (6.6%, 95%CI 4.7-9.1) renal failure, forestry workers (3.0%, 95%CI 1.4-6.5, actual range 0.0 to 10.8%). CONCLUSIONS: In the last decade, no human cases of hantavirus infection have been officially reported in Italy. However, our analysis stresses the actual occurrence of Hantavirus among general population and in selected population groups. Further studies on hantavirus infection rates in reservoir host species (rodents, shrews, and bats) and virus transmission to humans are needed to prevent outbreaks in the future.

Safety and Outcomes of Laparoscopic Sleeve Gastrectomy in a General Surgery Residency Program.

BACKGROUND: With the escalation of surgical treatment of morbid obesity, there is a growing interest in the training of bariatric surgeons. Laparoscopic sleeve gastrectomy (LSG) gained popularity both as a first-stage approach and as a stand-alone procedure. OBJECTIVES: The aim of this study was to assess detectable differences in LSG with intra-operative resident involvement. METHODS: We reviewed obese patients, who had undergone LSG between January 1, 2017 and January 31, 2020. Collected data reported demographic factors, operative time, postoperative complications, and outcomes. RESULTS: Among 313 patients who met the inclusion criteria, 94 were men and 219 were women. The procedures were performed either by an expert bariatric surgeon (group 1), or a general surgery resident (group 2), respectively in 228 and 85 cases. Mean operative time of the first group was 65.3 ± 18.8 minutes, while it was 74.3 ± 17.2 among trainees (p < 0.001). Perioperative complications were diagnosed in 13 patients (10 in group 1 and 3 in group 2). Mean excess body weight loss after 12 months was 87.7 ± 28.2% in the first group and 81.1 ± 31.6% in the residents group. Between the two groups, we found no differences in the incidence of perioperative complications and in surgical outcomes. Trainee involvement was associated with increased operative time, with no correlation with a worse postoperative course. CONCLUSIONS: Residents can safely perform LSG in referral centers under the supervision of an expert bariatric surgeon. Trainee involvement is not related to increased leak rate, nor to suboptimal short-term outcome.

Laparoscopic Banded Sleeve Gastrectomy: Single-Center Experience with a Four-Year Follow-Up.

Introduction: Laparoscopic sleeve gastrectomy (LSG) is now the most common bariatric procedure to treat morbidly obese patients. The main concern of LSG lies in the long-term weight regain, which is reported to happen in up to 75.6% of patients after 6 years. In this study, we report our overall experience with Laparoscopic Banded Sleeve Gastrectomy (LBSG) using the MiniMizer® over a 6-year period. Materials and Methods: We performed a retrospective review of data from a prospectively collected database. All patients submitted to primary LBSG were examined. Patients were submitted to LBSG between February 2014 and January 2020. Collected data included demographic factors, preoperative body mass index (BMI), operative time, surgical complications, and clinical outcomes. Results: Two hundred nine patients were submitted to primary LBSG in the study period. They were 136 females (65%) and 73 males (35%) with a median age of 43.0 years (range, 18-65 years). Median preoperative BMI was 48.4 kg/m2 (range, 36.2-65.5 kg/m2). Median operative time was 72.0 minutes (range, 40-142 minutes). Median time for ring placement was 8.0 minutes. Median postoperative hospital stay was 2.8 days. Seven major complications occurred in the postoperative period (3.3%): five gastric leaks (2.3%) and two major bleedings (0.9%). There was no postoperative mortality in the 209 patients. Long-term major complications occurred in 2 patients (0.9%). Median follow-up was 49.2 months (range, 2-72 months). Median postoperative BMI was 29.6 kg/m2 (range, 22-42 kg/m2). Median %excess weight loss (%EWL) at 1 year after surgery was 52.0%. Median %EWL at last follow-up visit was 64.0%. Conclusion: LBSG is as safe as standard LSG with excellent results in terms of postoperative morbidity and weight loss outcomes. Whether this procedure may result superior to standard LSG in the long-term period needs to be evaluated in randomized trials. Clinical Study Registration Number: NCT04354532.

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.

Artificial intelligence in thoracic surgery: a narrative review.

OBJECTIVE: The aim of this article is to review the current applications of artificial intelligence in thoracic surgery, from diagnosis and pulmonary disease management, to preoperative risk-assessment, surgical planning, and outcomes prediction. BACKGROUND: Artificial intelligence implementation in healthcare settings is rapidly growing, though its widespread use in clinical practice is still limited. The employment of machine learning algorithms in thoracic surgery is wide-ranging, including all steps of the clinical pathway. METHODS: We performed a narrative review of the literature on Scopus, PubMed and Cochrane databases, including all the relevant studies published in the last ten years, until March 2021. CONCLUSION: Machine learning methods are promising encouraging results throughout the key issues of thoracic surgery, both clinical, organizational, and educational. Artificial intelligence-based technologies showed remarkable efficacy to improve the perioperative evaluation of the patient, to assist the decision-making process, to enhance the surgical performance, and to optimize the operating room scheduling. Still, some concern remains about data supply, protection, and transparency, thus further studies and specific consensus guidelines are needed to validate these technologies for daily common practice. KEYWORDS: Artificial intelligence (AI); thoracic surgery; machine learning; lung resection; perioperative medicine.