Universal Database Research Articles

Resource Management Solutions for Modern Law Firms: A Comprehensive Database

In the modern legal landscape, resource management plays a crucial role in the sustained development of law firms and in delivering high-quality legal services to clients. However, there are still law firms that have deviated from database technology and continue to rely on traditional resource management models, which cannot meet the needs of modern enterprise management. This paper aims to explore the current status of resource management in law firms and introduces the design of a universal resource database tailored to the needs of law firms, lawyers, and clients. This paper provides a detailed introduction to the design of the comprehensive resource management database from the perspectives of requirement analysis, conceptual level design, logical level design and physical level design. The comprehensive database primarily store data related to staffs, orders, and clients, providing efficient resource management, and allowing for further expansion on this foundation. Effective resource management is paramount for law firms to maintain their competitiveness and provide excellent legal services, ultimately enhancing the overall client experience.

Antifeedant, Antifungal Cryptic Polyketides with Six Structural Frameworks from Tea Endophyte Daldinia eschscholtzii Propelled by the Antagonistic Coculture with Phytopathogen Colletotrichum pseudomajus and Different Culture Methods.

The antagonistic coculture with tea phytopathogen Colletotrichum pseudomajus induces antifungal cryptic metabolites from isogenesis endophyte Daldinia eschscholtzii against tea phytopathogens. Sixteen new polyketides with six structural frameworks including ten cryptic ones, named coldaldols A-C (1-3), collediol (5), and daldinrins A-L (10-20 and 23), were found from the coculture of C. pseudomajus and D. eschscholtzii by different culture methods. The unique framework of compounds 11 and 12 featured a benzopyran-C7 polyketone hybrid, and compounds 13-16 were characterized by the novel benzopyran dimer. The structures were determined mainly by spectroscopic methods, including extensive one-dimensional (1D), two-dimensional (2D) NMR, high resolution electrospray ionisation mass spectroscopy (HRESIMS), ECD calculation, and single-crystal X-ray diffraction. The configuration of acyclic compounds 5 and 18 were determined by application of the universal NMR database. Most compounds showed significant antifungal activities against the tea pathogens C. pseudomajus and Alternaria sp. with MICs of 1-8 μg/mL. Compound 12 had stronger antifungal activity than that of positive drug nystatin. The ether bond at C-4 of the benzopyran derivative increased the antifungal activity. Compounds 4-9 and 11-23 showed antifeedant activities against silkworms with feeding deterrence indices of 15-100% at the concentration of 50 μg/cm2.

Evaluation of Reinforced Concrete Structures with Magnetic Method and ACO (Amplitude-Correlation-Offset) Decomposition.

The magnetic method is one of the very few nondestructive testing (NDT) techniques that provide the possibility to conduct area tests of reinforced concrete (RC) structures in a fast, cheap, and straightforward way. This paper aims to present a new approach to the simultaneous identification of rebars' diameter, alloy class, and thickness of the concrete cover tested with this method. Since rebars from different manufacturers may have different electromagnetic properties (standardization only for mechanical properties), preparing an effective and universal database is impossible. In this work, ACO decomposition is proposed, a new attributes extraction method designed to identify object parameters, even if it is impossible to collect a suitable training database (by pattern recognition and analysis of the deviation). Conducted tests prove that the ACO method enables accurate reflection of the waveform shape and limitation of attributes number to three or fewer (avoiding the curse of dimensionality). These properties, combined with the ability to analyze spatial components of magnetic induction (which only magnetic sensors provide), make the complex task of identification of three parameters more straightforward and the separation between the results received for different classes larger. This article presents the measurement results and the whole identification process.

Impact of COVID-19 Diagnosis on Mortality in Patients with Ischemic Stroke Admitted during the 2020 Pandemic in Italy.

The impact of the COVID-19 pandemic on the event rate of patients with ischemic stroke has been poorly investigated. We sought to evaluate the impact of the COVID-19 infection on mortality in patients with ischemic stroke admitted during the 2020 pandemic in Italy. We analyzed a nationwide, comprehensive, and universal administrative database of patients who were admitted for ischemic stroke during and after the national lockdown for the COVID-19 infection in 2020, and the equivalent periods over the previous 5 years in Italy. The 2020 observed hospitalization and mortality rates of stroke patients with and without COVID-19 infection were compared with the expected rates, in accordance with the trend of the previous 5 years. During the period of observation, 300,890 hospitalizations for ischemic stroke occurred in Italy. In 2020, 41,302 stroke patients (1102 with concomitant COVID-19 infection) were admitted at 771 centers. The rate of admissions for ischemic stroke during the 2020 pandemic was markedly reduced compared with previous years (percentage change vs. 2015: -23.5). Based on the 5 year trend, the 2020 expected 30 day and 1 year mortality rates were 9.8% and 23.9%, respectively, and the observed incidence of death rates were 12.2% and 26.7%, respectively (both p < 0.001). After multiple corrections, higher rates of mortality were observed among patients admitted for stroke with a concomitant COVID-19 diagnosis. During the COVID-19 pandemic in 2020 in Italy, the rate of hospitalizations for ischemic stroke was dramatically reduced, although both the 30 day and 1 year mortality rates increased compared with the previous 5 year trend.

Use of a taxon-specific reference database for accurate metagenomics-based pathogen detection of Listeria monocytogenes in turkey deli meat and spinach

BackgroundThe reliability of culture-independent pathogen detection in foods using metagenomics is contingent on the quality and composition of the reference database. The inclusion of microbial sequences from a diverse representation of taxonomies in universal reference databases is recommended to maximize classification precision for pathogen detection. However, these sizable databases have high memory requirements that may be out of reach for some users. In this study, we aimed to assess the performance of a foodborne pathogen (FBP)-specific reference database (taxon-specific) relative to a universal reference database (taxon-agnostic). We tested our FBP-specific reference database's performance for detecting Listeria monocytogenes in two complex food matrices—ready-to-eat (RTE) turkey deli meat and prepackaged spinach—using three popular read-based DNA-to-DNA metagenomic classifiers: Centrifuge, Kraken 2 and KrakenUniq.ResultsIn silico host sequence removal led to substantially fewer false positive (FP) classifications and higher classification precision in RTE turkey deli meat datasets using the FBP-specific reference database. No considerable improvement in classification precision was observed following host filtering for prepackaged spinach datasets and was likely a consequence of a higher microbe-to-host sequence ratio. All datasets classified with Centrifuge using the FBP-specific reference database had the lowest classification precision compared to Kraken 2 or KrakenUniq. When a confidence-scoring threshold was applied, a nearly equivalent precision to the universal reference database was achieved for Kraken 2 and KrakenUniq. Recall was high for both reference databases across all datasets and classifiers. Substantially fewer computational resources were required for metagenomics-based detection of L. monocytogenes using the FBP-specific reference database, especially when combined with Kraken 2.ConclusionsA universal (taxon-agnostic) reference database is not essential for accurate and reliable metagenomics-based pathogen detection of L. monocytogenes in complex food matrices. Equivalent classification performance can be achieved using a taxon-specific reference database when the appropriate quality control measures, classification software, and analysis parameters are applied. This approach is less computationally demanding and more attainable for the broader scientific and food safety communities.

Dactylides A-C, three new bioactive 22-membered macrolides produced by Dactylosporangium aurantiacum.

Three new 22-membered polyol macrolides, dactylides A-C (1-3), were isolated from Dactylosporangium aurantiacum ATCC 23491 employing repeated chromatographic separations, and their structures were established based on detailed analysis of NMR and MS data. The relative configurations at the stereocenters were established via vicinal 1H-1H coupling constants, NOE correlations, and by application of Kishi's universal NMR database. In order to get insights into the biosynthetic pathway of 1-3, the genome sequence of the producer strain D. aurantiacum was obtained and the putative biosynthetic gene cluster encoding their biosynthesis was identified through bioinformatic analysis using antiSMASH. Compounds 1-3 showed significant in-vitro antimycobacterial and cytotoxic activity.

P279 IMPACT OF COVID–19 DIAGNOSIS ON HOSPITALIZATION AND MORTALITY RATES IN PATIENTS WITH ISCHEMIC STROKE ADMITTED DURING THE 2020 PANDEMIC IN ITALY

Abstract Background and purpose. We sought to evaluate the impact of the Covid–19 infection on hospitalization and mortality rates in patients with ischemic stroke admitted during the 2020 pandemic in Italy. Methods We analysed a nationwide, comprehensive, and universal administrative database of consecutive patients admitted for ischemic stroke during and after the national lockdown for Covid–19 infection in 2020 and the equivalent periods of the previous 5 years in Italy. The 2020 observed rates of hospitalizations and mortality of stroke patients with and without Covid–19 infection were compared with the expected rates, according to the trend of the previous 5 years. Results During the period of observation, 300,890 hospitalizations for ischemic stroke occurred in Italy. In 2020, 41,302 stroke patients (1102 with concomitant Covid–19 infection) were admitted at 771 centers. The rate of admissions for ischemic stroke during the 2020 pandemic was markedly reduced compared to the previous years (percentage change –23.5). Based on the 5–year trend, the 2020 expected rate of 30–day and 1–year mortality was 9.8% and 23.9%, while the observed incidence of death was 12.2% and 26.7%, respectively (both p&amp;lt;0.001). After multiple corrections, the higher rate of mortality was observed among patients admitted for stroke with a concomitant Covid–19 diagnosis. Conclusions During the Covid–19 pandemic in 2020 in Italy, the rate of hospitalizations for ischemic stroke was dramatically reduced, while both 30–day and 1–year mortality was increased, especially in those with a Covid–19 diagnosis, compared to the previous 5–year trend.

Innovation in the peripheries: Counter-flows of students to second tier cities in Portugal

Each year, student migration flow to small and medium cities in peripheral regions in Portugal to enter higher education, because they are unable to get into the more prestigious and larger universities in the main cities. Those are small counter-flows of the main flows from the periphery to larger cities. This study argues that these flows of students constitute potential flows of talent, drivers of innovation and economic growth, a means of enhancing human capital and regional upgrading and can contribute to the institutional change of remote areas. They are not exclusive to Portugal but take place in other countries where offer and demand differs between central and peripheral cities. The Portuguese case benefits from a unique process of access to public higher education, with a centralized process of allocation of vacancies linked with numerus clausus for all programmes, managed by the Ministry and is registered on a universal database each year. The analysis of the allocation of the students by place of origin, field of study and institution of enrolment, grades and other characteristics of the students offers evidence to support the argument of this paper.

A Comprehensive Review of Noise Measurement, Standards, Assessment, Geospatial Mapping and Public Health

Noise pollution is an emerging issue in cities around the world. Noise is a pernicious pollutant in urban landscapes mainly due to the increasing number of city inhabitants, road and aviation traffic, industrial and construction activities, and appliances or machinery used in daily life. The objective of this paper is to present a comprehensive review of noise measurement, guidelines/standards, and parameters used in noise monitoring; noise assessment associated with the area characteristics and the violations of guidelines/standards; noise geospatial mapping in urban planning; and physiological and psychological effects of noise exposure on public health. The review results revealed that standard methodology was lacking in many of the reviewed studies for noise measurement in various land-use patterns, especially the duration of noise monitoring; noise levels exceeded the prescribed noise standards in almost every noise assessment study across the globe irrespective of land-use or designated zone, and are exhibiting rising trends particularly due to traffic-induced noise; the majority of the urban population has been exposed to the noisy environment and affected with significant physiological and psychological health impacts; noise geospatial mapping has demonstrated high potential in noise abatement and management; and marked drop in noise levels in an urban environment during COVID-19 lockdown period. Based on the review results, the present study has suggested some future research perspectives of noise abatement and management that include a focus on – methodical noise assessment with prescribed guidelines of noise measurement and standards; geospatial noise mapping of urban areas, and real-time information system; universal database management software (DBMS) such as SQL and Improvado to compile data in single storage that will allow multiple users to access data despite different geographical locations; awareness programs using multi-media approaches in urban areas; and strict implementation of noise laws and regulations, that leads to the development of advanced technologies, integrated strategies, and sustainable environmental planning to mitigate the menace of noise pollution.  

RACBase: A cloud-based database of recycled aggregate concrete durability

This paper presents the first universal cloud-based database of recycled aggregate concrete (RAC) durability, named RACBase. The database collects experimental data on the durability of RAC from published literature all over the globe. Each set of data consists of the literature source, materials information, and the unified test result. The resistance to chloride ion attack, carbonation, sulfate attack, and freeze-thaw for RAC is quantified by the passed electric charge, carbonation depth, compressive strength loss, and durability factor, respectively. Based on the web interface, RACBase provides the functions of searching, adding, acquiring, and storing data, and gives the statistical distribution of data for each durability test. Users can freely access RACBase at https://www.racbase.com and browse and upload their data after online registration. One illustration of building a machine learning model for predicting the chloride resistance of RAC is presented to show the potential application of the database. The extreme gradient boosting model shows superiority to the artificial neural network and random forest models with the R2 of 0.975, RMSE of 246.719, and MAPE of 0.081. RACBase enriches the way for users to conduct in-depth research on the durability of RAC and construct performance prediction models.

Frailty and subsequent adverse outcomes in older patients with atrial fibrillation treated with oral anticoagulants: The Shizuoka study

BackgroundIn older patients with atrial fibrillation (AF), frailty is frequently prevalent. However, the prognostic value of frailty for adverse events after initiation of oral anticoagulants (OACs) is unclear. ObjectivesWe assessed whether frailty at the time of OAC initiation is associated with subsequent bleeding or embolic events. MethodsWe extracted patients aged ≥65 years with nonvalvular AF in whom OACs were initiated from a universal administrative claims database incorporating primary and hospital care records in Shizuoka, Japan, between 2012 and 2018. Frailty was assessed using the electronic frailty index (eFI). The association of frailty with bleeding events and ischemic stroke/transient ischemic attack were evaluated using the Fine-Gray model and restricted cubic spline model. ResultsAmong 12,585 patients with AF, 7.8% were categorized as fit, 31.5% as mildly frail, 34.8% as moderately frail, and 25.9% as severely frail. The risk of bleeding was associated with a higher eFI (adjusted subdistribution hazard ratio [95% CI] for fit or mild frailty: 1.15 [1.02-1.30]; moderate frailty: 1.42 [1.24-1.61]; and severe frailty: 1.86 [1.61-2.15]), whereas the association was weaker for ischemic stroke/transient ischemic attack. The spline models demonstrated that the relative hazard for bleeding increased steeply with increasing eFI. ConclusionPatients with frailty in whom OAC therapy is initiated have higher risk of bleeding, highlighting the importance of discussing this increased risk with patients with AF who have frailty and assessing frailty at the time of OAC initiation.

AN UPGRADED ART MARKET FOR A DIGITAL AGE

The traditional art market suffers from systemic market failures resulting in inefficiencies. There is no universal system or database to keep track of provenance information. The lack of provenance results in authentication issues, raising risk within the market. Additionally, the physical form of traditional art presents numerous problems including theft and transaction costs. Copyright and trademark laws attempt to address these market failures through regulation and enforcement mechanisms. However, these legal mechanisms are inefficient tools to regulate the art market because they rely on voluntary record keeping and retroactive enforcement through the judicial system. In contrast, blockchain technology, as an efficient regulatory and enforcement system, solves the art market problems that the law cannot fix. This innovative technology can solve the complex legal problems that the art market faces daily. Blockchains are immutable ledgers that store impeccable provenance information. Several blockchains have a native form of artwork—non-fungible tokens (NFTs)—that work seamlessly with the technology. NFTs take the physical aspect out of art, allowing art to exist digitally on the blockchain, where they cannot be damaged, stolen, or forged. Blockchain technology presents a novel solution to the physicality, authenticity, and provenance problems in the art market.

Analiza zmian zagospodarowania osiedla Kozanów we Wrocławiu w latach 1934–2020 na podstawie wybranych źródeł kartograficznych

The purpose of the work was to conduct the analysis covering the area of Kozanów neighborhood before and after the occurrence of the commonly named “Millennium flood” in 1997. The scope of the work included the analysis of four time states presented on old maps from 1934, 1979 and 1997 and a fragment of the OpenStreetMap database (OSM) current for 2020. The research included quantitative analyses, consisting of comparing all feature classes among the analyzed time states, as well as qualitative analyses, relating to the detailed characteristics of the maps and the OSM database. In order to ensure the comparability of all types of land use, old maps were georeferenced, and then the data contained on the maps were vectorized, which allowed to obtain a universal vector database for all tested time states. This enabled the design of maps of the Kozanów neighborhood for individual years and maps of changes presenting quantitative changes by feature classes. The output maps show an increase in the area of buildings and length of roads as well as a decrease of green areas and wastelands. The results of the work allowed us to draw conclusions regarding the severe negative effects of the flood that occurred in this neighborhood and the evaluation of the use of the OSM database in such analyses.

Back Cover: ASBase: The universal database for aggregate science

The ASBase, which is a universal database for aggregate science, is connecting the nodes in laborotary, industry and individuals with information and scientific data. (e263)

A general neural network model co-driven by mechanism and data for the reliable design of gas-liquid T-junction microdevices.

In recent years, many models have been developed to describe the gas-liquid microdispersion process, which mainly rely on mechanistic analysis and may not be universally applicable. In order to provide a more comprehensive model and, most significantly, to provide a model for design, we have established a general database of microbubble generation in T-junction microdevices, including 854 data points from 12 pieces of literature. A neural network model that combines mechanistic and data modeling is developed. By transfer learning, more accurate results can be obtained. Additionally, we have proposed a design method that enables a relative deviation of less than 5% from the expected bubble size. A new device was designed and prepared to confirm the reliability of the method, which can prepare smaller bubbles than other common T-junction devices. In this way, a general and universal database and model are established and a design method for a gas-liquid T-junction microreactor is developed.

Forensic-Correctional Psychiatric Services in Abu Dhabi: Lessons From a Descriptive Analyis of the Attributes of a Sample of Service Users.

Forensic-correctional psychiatric services are an important component of the public mental health services that provide care to offenders with mental illness in the criminal justice system and conduct psycho-legal assessments. Although forensic-correctional psychiatric services have evolved in Abu Dhabi, more work is needed in providing adequate mental health care for offenders. This study provides a situational analysis of forensic-correctional psychiatric services in Abu Dhabi. We included a descriptive analysis of the data collected on service users admitted for psycho-legal assessments and treatment in the forensic-correctional units and those reviewed in the medical board units for issuing court reports. The study spanned the period between January 2019 to October 2020. A total of 398 males were included in the study. The participants' mean age was 35.3 (SD 9.27) years and were predominantly single, unemployed and high school graduates. The most prevalent diagnosis was schizophrenia spectrum disorder, (n=129, 31.6%). The mean length of stay in the forensic-correctional unit was 11.07 days. As many as 82.4% of the participants were referred for evaluation. The most common type of crime was categorized as "abnormal behaviour" under the code of practice number 511 of the list of crimes as per the general prosecutor of the United Arab Emirates followed by violence. Considering the level of demand for services and the limited number of forensic-correctional health professionals, there is a need for more resources to develop expertise, clinical services and infrastructures to expand the practice of forensic-correctional psychiatry. The creation of a universal database for all forensic-correctional psychiatric services is needed to better understand the unmet mental health needs. An additional investment of resources for research to inform mental health policy, laws and practice is indicated. Optimally, the lessons highlighted in this study can guide action plans for improving forensic-correctional mental health services in comparable settings.

HUMAN RESOURCE MANAGEMENT SOLUTIONS USING ODOO

Human resource management is the strategic and coherent approach to the management of an organization's most valued assets - the people working individually and collectively contribute to the achievement of the objectives of the business. HRM is the acronym for the term "Human Resource Management". Human Resource Management is the organizational function that deals with issues related such as compensation, hiring, employee performance management, organization development, safety, wellness, benefits, employee motivation, communication, administration, and training. HRM is a discipline and a basic HR activity and process in the information technology field, whereas the programming of data processing systems evolved into standardized routines and packages of enterprise resource planning (ERP) software of Odoo. On the whole, these ERP systems have their origin in software that integrates information from different applications into one universal database. The financial and human resource modules through one database are the most important distinction to the individually and proprietary developed predecessors, which makes this software application more rigid and flexible. Key Words: Human Resource Management, Open Enterprise Resource Planning, customer friendly investments, Odoo, Enterprise Resource Planning.

Impact of COVID-19 Diagnosis on Mortality in Patients with ST-Elevation Myocardial Infarction Hospitalized during the National Outbreak in Italy.

We sought to assess the clinical impact of COVID-19 infection on mortality in patients with ST-elevation myocardial infarction (STEMI) admitted during the national outbreak in Italy. We analysed a nationwide, comprehensive, and universal administrative database of consecutive STEMI patients admitted during lockdown for COVID-19 infection (11 March-3 May 2020) and the equivalent periods of the previous 5 years in Italy. The observed rate of 30-day and 6-month all-cause mortality of STEMI patients with and without COVID-19 infection during the lockdown was compared with the expected rate of death, according to the trend of the previous 5 years. During the study period, 32.910 STEMI hospitalizations occurred in Italy. Among these, 4048 STEMI patients were admitted during the 2020 outbreak: 170 (4.2%) with and 3878 (95.8%) without a COVID-19 diagnosis. According to the 5-year trend, the 2020 expected rates of 30-day and 6-month all-cause mortality were 9.2% and 12.6%, while the observed incidences of death were 10.8% (p = 0.016) and 14.4% (p = 0.017), respectively. Excluding STEMI patients with a COVID-19 diagnosis, the mortality rate resulted in accordance with the prior 5-year trend. After multiple corrections, the presence of COVID-19 diagnosis was an independent predictor of all-cause mortality at 30 days [adjusted odds ratio (OR) 4.5; 95% confidence intervals (CI) 3.09-6.45; p &lt; 0.0001] and 6 months (adjusted OR 3.6; 95% CI: 2.47-5.12; p &lt; 0.0001). During the 2020 national outbreak in Italy, COVID-19 infection significantly increased the mortality trend in patients with STEMI.

Evaluation of the Compressive Strength of CFRP-Wrapped Circular Concrete Columns Using Artificial Intelligence Techniques

The wrapping of concrete structures with fiber polymers has been an essential part of concrete technology aimed at the improvement of concrete performance indices during the construction and lifelong usage of the structures. In this paper, a universal representative database was collected from multiple literature materials on the effect of different fiber-reinforced polymers on the confined compressive strength of wrapped concrete columns (Fcc). The collected data show that the Fcc value depends on the FRP thickness (t), tensile strength (Ftf), and elastic modulus (Ef), in addition to the column diameter (d) and the confined compressive strength of concrete (Fco). Five AI techniques were applied on the collected database, namely genetic programming (GP), three artificial neural networks (ANN) trained using three different algorithms, “back Propagation BP, gradually reduced gradient GRG and genetic algorithm GA”, and evolutionary polynomial regression (EPR). The results of the five developed predictive models show that (t) and Ftf have a major impact on the Fcc value, which presents the effect of confinement stress (t. Ftf/d) on the confined compressive strength (Fcc). Comparing the predicted values with the experimental ones showed that the GP model is the least accurate one, and the EPR model is the next least accurate, while the three ANN models have almost the same level of high accuracy, with an average error percentage of 5.8% and a coefficient of determination R2 of 0.961. The ANN model is more accurate than the EPR and GP predictive models, but they are suitable for manual calculation because they are closed-form equations.

Covid-19 diagnosis and mortality in patients with non-ST-elevation myocardial infarction admitted in Italy during the national outbreak

IntroductionWe sought to assess the clinical impact of Covid-19 infection on mortality in patients with Non-ST elevation myocardial infarction (NSTEMI) admitted during the national outbreak in Italy. MethodsWe analysed a nationwide, comprehensive, and universal administrative database of consecutive NSTEMI patients admitted during lockdown for Covid-19 infection (March,11st - May 3rd, 2020) and the equivalent periods of the previous 5 years in Italy. The observed rate of 30-day and 6-month all-cause mortality of NSTEMI patients with and without Covid-19 infection during the lockdown was compared with the expected rate of death according to the trend of the previous 5 years. ResultsDuring the period of observation, 48.447 NSTEMI hospitalizations occurred in Italy. Among these, 4981 NSTEMI patients were admitted during the 2020 outbreak: 173 (3.5%) with and 4808 (96.5%) without a Covid-19 diagnosis. According to the 5-year trend, the 2020 expected rate of 30-day and 6-month all-cause mortality was 6.5% and 12.2%, while the observed incidence of death was 8.3% (p = 0.001) and 13.6% (p = 0.041), respectively. Excluding NSTEMI patients with a Covid-19 diagnosis, the 6-month mortality rate resulted in accordance with the prior 5-year trend. After multiple corrections, the presence of Covid-19 diagnosis resulted one of the independent predictors of all-cause mortality at 30 days [adjusted odds ratio (OR) 4.3; 95% confidence intervals (CI) 2.90–6.23; p < 0.0001] and 6 months (adjusted OR 3.5; 95% CI: 2.43–5.03; p < 0.0001). ConclusionsDuring the 2020 national outbreak in Italy, a concomitant diagnosis of Covid-19 in NSTEMI was associated with a significantly higher rate of mortality.