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Background: Extensive vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is now universally regarded as one of the most effective strategies for counteracting the current pandemic. The durability of the immune response of available vaccines is not known, therefore the quantitative dynamics of serum anti-S antibodies after Comirnaty vaccine in health care workers (HCW) of Desio Hospital was conducted. Methods: 51 previously infected and 198 not infected HCW, from Desio, Italy were enrolled in the study. Comirnaty double dose schedule was completed by each subject. Specific anti-S antibodies against the SARS-CoV-2 S protein were measured by ECLIA in sequential blood samples. Results: A significant difference was observed beginning at pre priming dose (T0) of the anti-S antibodies between the two subgroups which persisted throughout the study (4 months). A significant reduction occurred after 4 months post-priming dose (T3). Finally, a subgroup of low and late responders with an increasing trend was found. Conclusions: Specific anti-S antibodies are significantly decreased 4 months post priming dose of Comirnaty vaccine although prior COVID-19 infection seems to escalate humoral response. Further evaluation concerning antibody persistence beyond this point, and the proportion of neutralizing antibodies with higher affinity towards SARS-CoV-2 is needed, especially in naїve and immunosuppressed subjects.

Antimicrobial resistance is a worldwide problem, and resistance in Enterobacteriaceae, particularly Escherichia coli and Klebsiella pneumoniae, is a critical threat to human health. Inappropriate and unnecessary use of antibiotics in human health care is the most common cause for the development and spread of antimicrobial resistance. In this work, we retrospectively analyzed the antimicrobial data of E. coli strains isolated from midstream urinary samples over a 20-year period (2000-2019). The aim was to provide useful information to clinicians to prescribe a more appropriate empirical antibiotic therapy. A total of 30,955 unique E. coli isolates from positive midstream urine samples of inpatients (1,198) and outpatients (29,757) were collected. Except for carbapenems, over time all the antibiotics tested showed increasing resistance rates in both groups (p < 0.0001). On the other hand, fosfomycin and nitrofurantoin presented significant decreasing trends in resistance rate (p < 0.05). There were significant increases in extended-spectrum β-lactamases- and multidrug resistance positive isolates starting in 2000 (p < 0.0001), with similar results in both groups. Ciprofloxacin, gentamicin, trimethoprim/sulfamethoxazole, and third-generation cephalosporin resistances significantly increased with increasing age (p < 0.0001). Collectively, E. coli resistance rates severely increased during the study period, except for fosfomycin and nitrofurantoin. The need of monitoring studies about antibiotic nonsusceptibilities at local and regional levels are necessary to enhance the focus on antimicrobial stewardship, to reduce antimicrobial consumption and to detect alarming resistance mechanisms.

Background In two patients under treatment with various antibiotics, spheroplasts were detected with an automated urine sediment analyzer. Methods Urinalysis was performed by an AutionMAX AX 4030-sediMAX platform. Results Spheroplasts can be easily misclassified as yeasts or erythrocytes, but when automated urine sediment analyzers are used by well-trained, and experienced operators they can be correctly identified and classified. Conclusion Appropriate training of urine laboratory professionals in spheroplast detection and association with UTI, together with timely communication with the microbiologist and caring clinician, will provide prompt targeted treatment.

Antimicrobial resistance is a worldwide problem, and resistance in Enterobacteriaceae, particularly

The β-lactams have a central place in the antibacterial armamentarium, but the increasing resistance to these drugs, especially among Gram-negative bacteria, is becoming one of the major threats to public health worldwide. Treatment options are limited, and only a small number of novel antibiotics are in development. However, one of the responses to this threat is the combination of β-lactam antibiotics with β-lactamase inhibitors, which are successfully used in the clinic for overcoming resistance by inhibiting β-lactamases. The existing inhibitors inactivate most of class A and C serine β-lactamases, but several of class D and B (metallo-β-lactamase) are resistant. The present review provides the status and knowledge concerning current β-lactamase inhibitors and an update on research efforts to identify and develop new and more efficient β-lactamase inhibitors.

Background and Objective Medical machine learning (ML) models tend to perform better on data from the same cohort than on new data, often due to overfitting, or co-variate shifts. For these reasons, external validation (EV) is a necessary practice in the evaluation of medical ML. However, there is still a gap in the literature on how to interpret EV results and hence assess the robustness of ML models. Methods We fill this gap by proposing a meta-validation method, to assess the soundness of EV procedures. In doing so, we complement the usual way to assess EV by considering both dataset cardinality, and the similarity of the EV dataset with respect to the training set. We then investigate how the notions of cardinality and similarity can be used to inform on the reliability of a validation procedure, by integrating them into two summative data visualizations. Results We illustrate our methodology by applying it to the validation of a state-of-the-art COVID-19 diagnostic model on 8 EV sets, collected across 3 different continents. The model performance was moderately impacted by data similarity (Pearson ρ = 0.38, p 0.001). In the EV, the validated model reported good AUC (average: 0.84), acceptable calibration (average: 0.17) and utility (average: 0.50). The validation datasets were adequate in terms of dataset cardinality and similarity, thus suggesting the soundness of the results. We also provide a qualitative guideline to evaluate the reliability of validation procedures, and we discuss the importance of proper external validation in light of the obtained results. Conclusions In this paper, we propose a novel, lean methodology to: 1) study how the similarity between training and validation sets impacts the generalizability of a ML model; 2) assess the soundness of EV evaluations along three complementary performance dimensions: discrimination, utility and calibration; 3) draw conclusions on the robustness of the model under validation. We applied this methodology to a state-of-the-art model for the diagnosis of COVID-19 from routine blood tests, and showed how to interpret the results in light of the presented framework.

The correlation of clinical, radiological and laboratory findings of patients at admission in the Emergency Department (ED) with clinical severity and risk of mortality was investigated. Adult coronavirus disease 2019 (COVID-19) patients hospitalized in March 2020 in Desio Hospital, Lombardy, were retrospectively included in the study, and categorized in terms of disease severity and adverse outcome. Out of the 175 patients enrolled, 79% presented one or more comorbidities, with cardiovascular disease being the most frequent (62%). More than half of the patients showed lymphocytopenia and 20% thrombocytopenia. The patients in the severe group presented higher absolute neutrophil count (ANC), C-reactive protein (CRP), AST, LDH, procalcitonin (PCT) and BUN values compared to the non-severe group (p 106.08 µmol/L (OR = 2.87; 95% CI 1.04–7.92) and creatine kinase > 2.90 µkat/L (OR = 3.80; 95% CI 1.31–10.9) were observed on admission (p

Background Public reporting (PR) of healthcare (HC) provider's quality was proposed as a public health instrument for providing transparency and accountability in HC. Our aim was to assess the impact of PR on five main domains: quality improvement; patient choice, service utilization and market share; provider's perspective; patient experience; and unintended consequences. Methods PubMed, Scopus, ISI WOS, and EconLit databases were searched to identify studies investigating relationships between PR and five main domains, published up to April 1, 2016. Results Sixty-two papers published between 1988 and 2015 were included. Nineteen studies investigated quality improvement, 19 studies explored the unintended consequences of PR, 10 explored the effects on market share, 10 on patients' choice, 7 evaluated the provider's perspective, 4 economic outcome, 4 service utilization, 2 purchasers' use of PR and 2 studies explored patient experiences. The effect of PR was diverse throughout the studies-mostly positive on: patient experience (100%), quality improvement (63%), patient choice, service utilization and market share (46%); mixed on provider's perspective and economic outcome (27%) and mainly negative on unintended consequences (68%). Conclusions Our research covering different outcomes and settings reported that PR is associated with changes in HC provider's behavior and can influence market share. Unintended consequences are a concern of PR and should be taken into account when allocating HC resources. The experiences collected in this paper could give a snapshot about the impact of PR on a HC user's perception of the providers' quality of care, helping them to make empowered choices.

Background To assess both qualitatively and quantitatively the impact of Public Reporting (PR) on clinical outcomes, we carried out a systematic review of published studies on this topic. Methods Pubmed, Web of Science and SCOPUS databases were searched to identify studies published from 1991 to 2014 that investigated the relationship between PR and clinical outcomes. Studies were considered eligible if they investigated the relationship between PR and clinical outcomes and comprehensively described the PR mechanism and the study design adopted. Among the clinical outcomes identified, meta-analysis was performed for overall mortality rate which quantitative data were exhaustively reported in a sufficient number of studies. Two reviewers conducted all data extraction independently and disagreements were resolved through discussion. The same reviewers evaluated also the quality of the studies using a GRADE approach. Results Twenty-seven studies were included. Mainly, the effect of PR on clinical outcomes was positive. Meta-analysis regarding overall mortality included, in a context of high heterogeneity, 10 studies with a total of 1,840,401 experimental events and 3,670,446 control events and resulted in a RR of 0.85 (95 % CI, 0.79-0.92). Conclusions The introduction of PR programs at different levels of the healthcare sector is a challenging but rewarding public health strategy. Existing research covering different clinical outcomes supports the idea that PR could, in fact, stimulate providers to improve healthcare quality. Electronic supplementary material The online version of this article (doi:10.1186/s12913-016-1543-y) contains supplementary material, which is available to authorized users.

Background Public reporting (PR) has been recommended as a useful public health strategy for stimulating improvement of quality and reduce inequalities in healthcare (HC) by adding transparency and addressing accountability in the interaction between HC providers and users. The aim of this study was to perform a systematic review of scientific literature in order to assess qualitatively and quantitatively the impact of PR on clinical outcomes. …