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1.
Bulletin of the World Health Organization ; 100(2):161-167, 2022.
Article in English | CINAHL | ID: covidwho-1690495

ABSTRACT

Problem After Italy's first national restriction measures in 2020, a robust approach was needed to monitor the emerging epidemic of coronavirus disease 2019 (COVID-19) at subnational level and provide data to inform the strengthening or easing of epidemic control measures. Approach We adapted the European Centre for Disease Prevention and Control rapid risk assessment tool by including quantitative and qualitative indicators from existing national surveillance systems. We defined COVID-19 risk as a combination of the probability of uncontrolled transmission of severe acute respiratory syndrome coronavirus 2 and of an unsustainable impact of COVID-19 cases on hospital services, adjusted in relation to the health system's resilience. The monitoring system was implemented with no additional cost in May 2020. Local setting The infectious diseases surveillance system in Italy uses consistent data collection methods across the country's decentralized regions and autonomous provinces. Relevant changes Weekly risk assessments using this approach were sustainable in monitoring the epidemic at regional level from 4 May 2020 to 24 September 2021. The tool provided reliable assessments of when and where a rapid increase in demand for health-care services would occur if control or mitigation measures were not increased in the following 3 weeks. Lessons learnt Although the system worked well, framing the risk assessment tool in a legal decree hampered its flexibility, as indicators could not be changed without changing the law. The relative complexity of the tool, the impossibility of real-time validation and its use for the definition of restrictions posed communication challenges. Situación Tras las primeras medidas nacionales de restricción en Italia en 2020, se necesitaba un enfoque sólido para supervisar la epidemia emergente de la coronavirosis de 2019 (COVID-19) a nivel subnacional y proporcionar datos que informaran sobre el refuerzo o la flexibilización de las medidas de contención de la epidemia. Enfoque Se adaptó la herramienta de valoración rápida de riesgos del Centro Europeo para la Prevención y el Control de las Enfermedades, al incluir indicadores cuantitativos y cualitativos de los sistemas nacionales de vigilancia existentes. Se definió el riesgo de la COVID-19 como una combinación de la probabilidad de transmisión descontrolada del coronavirus del síndrome respiratorio agudo grave de tipo 2 y de un efecto no sostenible de los casos de la COVID-19 en los servicios hospitalarios, y se ajustó en relación con la capacidad de recuperación del sistema sanitario. El sistema de supervisión se aplicó sin costes adicionales en mayo de 2020. Marco regional El sistema de vigilancia de las enfermedades infecciosas en Italia aplica métodos de recopilación de datos coherentes en todas las regiones y provincias autónomas descentralizadas del país. Cambios importantes Las valoraciones semanales de los riesgos mediante este enfoque fueron sostenibles en la supervisión de la epidemia a nivel regional entre el 4 de mayo de 2020 y el 24 de septiembre de 2021. La herramienta proporcionó valoraciones fiables de cuándo y dónde se produciría un rápido aumento de la demanda de servicios sanitarios si no se incrementaban las medidas de contención o mitigación en las tres semanas siguientes. Lecciones aprendidas Aunque el sistema funcionó bien, el hecho de enmarcar la herramienta de valoración de los riesgos en un decreto legal dificultó su flexibilidad, ya que los indicadores no se podían modificar sin cambiar la ley. La relativa complejidad de la herramienta, la imposibilidad de validación en tiempo real y su uso para la definición de las restricciones plantearon problemas de comunicación. Problème Après avoir pris ses premières mesures de restriction nationales en 2020, l'Italie avait besoin d'une approche solide pour surveiller l'épidémie naissante de maladie à coronavirus 2019 (COVID-19) au niveau régional, et fournir les données permettant de renforcer ou d'alléger les mesures destinées à l'endiguer. Approche Nous avons adapté l'outil d'évaluation rapide des risques du Centre européen de prévention et de contrôle des maladies en y intégrant des indicateurs quantitatifs et qualitatifs issus des systèmes de surveillance nationaux existants. Pour définir le risque lié à la COVID-19, nous avons associé la probabilité d'une transmission incontrôlée du coronavirus 2 du syndrome respiratoire aigu sévère, à l'impact immédiat des cas de COVID-19 sur les services hospitaliers, en procédant à des ajustements selon la résilience du système de soins de santé. Le dispositif de surveillance a été mis en oeuvre en mai 2020 sans entraîner de coûts supplémentaires. Environnement local En Italie, le système de surveillance des maladies infectieuses repose sur des méthodes uniformes de collecte de données dans les provinces autonomes et régions décentralisées à travers le pays. Changements significatifs Les évaluations des risques réalisées toutes les semaines avec cette approche ont permis de surveiller l'épidémie à l'échelle régionale du 4 mai 2020 au 24 septembre 2021. L'outil a identifié les dates et lieux susceptibles de connaître une augmentation rapide de la demande en services de soins de santé si aucune mesure supplémentaire de contrôle et de lutte n'était prise dans les trois semaines. Leçons tirées Bien que le système ait fonctionné, inscrire l'outil d'évaluation des risques dans un décret législatif a réduit sa flexibilité, car les indicateurs ne pouvaient être modifiés sans réformer la loi. La relative complexité de l'outil, l'impossibilité de procéder à une validation en temps réel et son usage pour imposer des restrictions ont posé des problèmes de communication. Проблема После первых национальных ограничительных мер в Италии в 2020 году потребовался активный подход для мониторинга зарождающейся эпидемии коронавирусной инфекции 2019 года (COVID-19) на субнациональном уровне и для предоставления данных для обоснования усиления или ослабления мер по борьбе с эпидемией. Подход Авторы адаптировали инструмент для оперативных оценок рисков Европейского центра по контролю и профилактике заболеваний, включив в него количественные и качественные показатели из существующих национальных систем эпиднадзора. Авторы определили риск COVID-19 как комбинацию вероятности неконтролируемой передачи тяжелого острого респираторного синдрома, вызванного коронавирусом-2, и разрушительного воздействия случаев COVID-19 на больничное обслуживание, которая скорректирована с учетом устойчивости системы здравоохранения. Система мониторинга была внедрена без каких-либо дополнительных затрат в мае 2020 года. Местные условия В системе эпиднадзора за инфекционными заболеваниями в Италии используются последовательные методы сбора данных по децентрализованным регионам и автономным провинциям страны. Осуществленные перемены Еженедельные оценки рисков с использованием данного подхода регулярно применялись при мониторинге эпидемии на региональном уровне с 4 мая 2020 года по 24 сентября 2021 года. Инструмент обеспечил надежную оценку того, когда и где может произойти быстрое увеличение спроса на медицинские услуги, если меры по борьбе или смягчению последствий не будут усилены в течение следующих 3 недель. Выводы Несмотря на то что система работала эффективно, включение инструмента для оценок рисков в юридические постановления ограничивало его гибкость, поскольку показатели не могли быть изменены без изменения закона. Относительная сложность инструмента, невозможность проверки в реальном времени и его использование для определения ограничений создают проблемы коммуникации. 问题 2020 年意大利首次实施全国性限制措施后,需要 采取可靠方法以监测新型冠状病毒肺炎 (新冠肺炎) 疫情在地方层面的蔓延情况,并提供数据以表明是否 需要加强或放松疫情控制措施。 方法 通过纳入现有国家监测系统的定量和定性指 标,我们调整了欧洲疾病预防和控制中心的快速风险 评估工具。我们将新型冠状病毒肺炎风险综合定义为 严重急性呼吸系统综合症冠状病毒 2 不受控制传播 的可能性以及新型冠状病毒肺炎病例对医院服务的非持续性影响,并根据卫生系统的顺应力进行了调整。 2020 年 5 月,在没有产生额外成本的前提下实施了监 测系统。 当地状况 意大利传染病监测系统在全国各个分散 的地区和自治省统一使用相同的数据收集方法。 相关变化 在 2020 年 5 月 4 日至 2021 年 9 月 24 日 期间,使用这种方法开展的每周风险评估在监测区域 层面疫情情况方面具有可持续性。该工具能够可靠地 评估,如果在接下来的 3 周内没有加强控制或缓解措 施,何时何地医疗保健服务需求会迅速增加。 经验教训 尽管该系统运作良好,但将风险评估工 具纳入法令范畴限制了其灵活性,因为若不更改法律, 则无法变更指标。该工具的相对复杂性、实时验证的 不可能性及其在法规限定方面的用途导致产生了沟通 挑战。

2.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-317743

ABSTRACT

Background: The ongoing outbreak of Coronavirus Disease 2019 (COVID-19) represents a major threat to human health, which impairs the functionality of several organs. One of the hardest challenges in the fight against COVID-19 is the development of wide-scale, effective, and rapid laboratory tests to control disease severity, progression, and possible sudden worsening. Monitoring patients in real-time is indeed highly demanded in this pandemic era when physicians need reliable and quantitative tools to prioritize patients’access to intensive care departments. In this regard, salivary biomarkers are extremely promising, as they allow for a fast and non-invasive specimens’collection, which can be repeated multiple times. Methods: We compare salivary levels of immunoglobulin A subclasses (IgA1 and IgA2) and free-light chains (FLC k and λ) in a cohort of 29 SARS-CoV-2 patients and 21 healthy subjects. Results: We found that each biomarkers differs significantly between the two groups, with p-values ranging from 10-8 to 10-4. The performance ranking of these markers, shows that λFLC level (p=1.4e-8) is the best-suited candidate to discriminate the two groups, with an accuracy of 0.94 (0.87-1.00 95% CI), a precision of 0.91 (0.81-1.00 95% CI), a sensitivity of 1.00 (0.96-1.00 95% CI) and a specificity of 0.86 (0.70-1.00 95% CI). Conclusion: These results suggest λFLC as an ideal indicator of patient conditions. This is more strengthened in consideration that λFLC half-life (approximately 6 hours) is significantly shorter than the IgA one (21 days): thus λFLC appears displaying the potential to effectively monitor patients fluctuation in real-time.

3.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-317607

ABSTRACT

Background: The COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models have been validated but few of them are implemented in daily practice. The objective of the study was to validate a machine-learning risk prediction model using easy-to-obtain parameters, potentially available at home, to help identifying patients with COVID-19 who are at higher risk of death. Methods: The training cohort included all patients admitted to Fondazione Policlinico Gemelli with COVID-19 from March 5, 2020 to November 5, 2020. Afterwards, the model was tested on all patients admitted to the same hospital with COVID-19 from November 6, 2020 to February 5 2021. The primary outcome was in-hospital mortality.The out-of-sample performance of the model was estimated from the training set in terms of Area under the Receiving Operator Curve (AUROC) and classification matrix statistics by averaging the results of 5-fold cross validation repeated 3-times and comparing the results with those obtained on the test set. An explanation analysis of the model, based on the SHapley Additive exPlanations (SHAP), is also presented. To assess the subsequent time evolution, the change in paO2/FiO2 (P/F) at 48 hours after the baseline measurement was plotted against its baseline value. Results: Among the 921 patients included in the training cohort, 120 died (13%). Variables selected for the model were age, platelet count, SpO2, blood urea nitrogen (BUN), hemoglobin, C-reactive protein, neutrophil count, and sodium. The results of the 5-fold cross-validation repeated 3-times gave AUROC of 0.87, and statistics of the classification matrix to the Youden index as follows: sensitivity 0.840, specificity 0.774, negative predictive value 0.971. Then, the model was tested on a new population (n=1463) in which the mortality rate was 22.6 %. The test model showed AUROC 0.818, sensitivity 0.813, specificity 0.650, negative predictive value 0.922. Considering the first quartile of the predicted risk score (low-risk score group), the mortality rate was 1.6%, 17.8% in the second and third quartile (high-risk score group) and 53.5% in the fourth quartile (very high-risk score group). The three risk score groups showed good discrimination for the P/F value at admission, and a positive correlation was found for the low-risk class to P/F at 48 hours after admission (adjusted R-squared= 0.48). Conclusions: We developed a predictive model of death for people with SARS-CoV-2 infection by including only easy-to-obtain variables (abnormal blood count, BUN, C-reactive protein, sodium and lower SpO2). It demonstrated good accuracy and high power of discrimination. The simplicity of the model makes the risk prediction applicable for patients at home, in the Emergency Department, or during hospitalization.

4.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-316218

ABSTRACT

Background: The Envelope (E) protein of SARS-CoV-2 is the most enigmatic protein among the four structural ones on the viral genome. Most of the current knowledge on the E protein is based on the direct comparison to the SARS E protein, initially mistakenly undervalued and subsequently proved to be a key factor in the ER-Golgi localization and in tight junction disruption. Methods: : We compared the genomic sequences of E protein of SARS-CoV-2, SARS-CoV and the closely related genomes of bats and pangolins obtained from the GISAID and GenBank databases. Multiple sequence alignments were done with the Geneious software using the MAFFT algorithm. In silico modelling analyses of E proteins conformation and docking with PALS1 were performed with the Schrodinger Suite. Results: : When compared to the known SARS E protein, we observed a different amino acidic sequence in the C-terminal of SARS-CoV-2 E protein which might have a key role in the current COVID-19 pathogenesis. In silico docking results provide evidence of a strengthened binding of SARS-CoV-2 E protein with the tight junction-associated PALS1 protein. Conclusions: : We suggest that SARS-CoV-2 E protein may interfere with the tight junction stability and formation leading to an enhanced epithelial barrier disruption, amplifying the inflammatory processes, and promoting tissue remodelling. These findings raise a warning on the underestimated role of the E protein in the pathogenic mechanism and could open the route to detailed experimental investigations.

5.
Bull World Health Organ ; 100(2): 161-167, 2022 Feb 01.
Article in English | MEDLINE | ID: covidwho-1674216

ABSTRACT

Problem: After Italy's first national restriction measures in 2020, a robust approach was needed to monitor the emerging epidemic of coronavirus disease 2019 (COVID-19) at subnational level and provide data to inform the strengthening or easing of epidemic control measures. Approach: We adapted the European Centre for Disease Prevention and Control rapid risk assessment tool by including quantitative and qualitative indicators from existing national surveillance systems. We defined COVID-19 risk as a combination of the probability of uncontrolled transmission of severe acute respiratory syndrome coronavirus 2 and of an unsustainable impact of COVID-19 cases on hospital services, adjusted in relation to the health system's resilience. The monitoring system was implemented with no additional cost in May 2020. Local setting: The infectious diseases surveillance system in Italy uses consistent data collection methods across the country's decentralized regions and autonomous provinces. Relevant changes: Weekly risk assessments using this approach were sustainable in monitoring the epidemic at regional level from 4 May 2020 to 24 September 2021. The tool provided reliable assessments of when and where a rapid increase in demand for health-care services would occur if control or mitigation measures were not increased in the following 3 weeks. Lessons learnt: Although the system worked well, framing the risk assessment tool in a legal decree hampered its flexibility, as indicators could not be changed without changing the law. The relative complexity of the tool, the impossibility of real-time validation and its use for the definition of restrictions posed communication challenges.


Subject(s)
COVID-19 , Epidemics , Humans , Italy/epidemiology , Risk Assessment , SARS-CoV-2
6.
Comput Methods Programs Biomed ; 217: 106655, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1654240

ABSTRACT

BACKGROUND: The COVID-19 pandemic affected healthcare systems worldwide. Predictive models developed by Artificial Intelligence (AI) and based on timely, centralized and standardized real world patient data could improve management of COVID-19 to achieve better clinical outcomes. The objectives of this manuscript are to describe the structure and technologies used to construct a COVID-19 Data Mart architecture and to present how a large hospital has tackled the challenge of supporting daily management of COVID-19 pandemic emergency, by creating a strong retrospective knowledge base, a real time environment and integrated information dashboard for daily practice and early identification of critical condition at patient level. This framework is also used as an informative, continuously enriched data lake, which is a base for several on-going predictive studies. METHODS: The information technology framework for clinical practice and research was described. It was developed using SAS Institute software analytics tool and SAS® Vyia® environment and Open-Source environment R ® and Python ® for fast prototyping and modeling. The included variables and the source extraction procedures were presented. RESULTS: The Data Mart covers a retrospective cohort of 5528 patients with SARS-CoV-2 infection. People who died were older, had more comorbidities, reported more frequently dyspnea at onset, had higher d-dimer, C-reactive protein and urea nitrogen. The dashboard was developed to support the management of COVID-19 patients at three levels: hospital, single ward and individual care level. INTERPRETATION: The COVID-19 Data Mart based on integration of a large collection of clinical data and an AI-based integrated framework has been developed, based on a set of automated procedures for data mining and retrieval, transformation and integration, and has been embedded in the clinical practice to help managing daily care. Benefits from the availability of a Data Mart include the opportunity to build predictive models with a machine learning approach to identify undescribed clinical phenotypes and to foster hospital networks. A real-time updated dashboard built from the Data Mart may represent a valid tool for a better knowledge of epidemiological and clinical features of COVID-19, especially when multiple waves are observed, as well as for epidemic and pandemic events of the same nature (e. g. with critical clinical conditions leading to severe pulmonary inflammation). Therefore, we believe the approach presented in this paper may find several applications in comparable situations even at region or state levels. Finally, models predicting the course of future waves or new pandemics could largely benefit from network of DataMarts.


Subject(s)
COVID-19 , Artificial Intelligence , COVID-19/epidemiology , Clinical Decision-Making , Humans , Pandemics , Retrospective Studies , SARS-CoV-2
7.
Sci Rep ; 11(1): 21136, 2021 10 27.
Article in English | MEDLINE | ID: covidwho-1493228

ABSTRACT

The COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models have been validated but few of them are implemented in daily practice. The objective of the study was to validate a machine-learning risk prediction model using easy-to-obtain parameters to help to identify patients with COVID-19 who are at higher risk of death. The training cohort included all patients admitted to Fondazione Policlinico Gemelli with COVID-19 from March 5, 2020, to November 5, 2020. Afterward, the model was tested on all patients admitted to the same hospital with COVID-19 from November 6, 2020, to February 5, 2021. The primary outcome was in-hospital case-fatality risk. The out-of-sample performance of the model was estimated from the training set in terms of Area under the Receiving Operator Curve (AUROC) and classification matrix statistics by averaging the results of fivefold cross validation repeated 3-times and comparing the results with those obtained on the test set. An explanation analysis of the model, based on the SHapley Additive exPlanations (SHAP), is also presented. To assess the subsequent time evolution, the change in paO2/FiO2 (P/F) at 48 h after the baseline measurement was plotted against its baseline value. Among the 921 patients included in the training cohort, 120 died (13%). Variables selected for the model were age, platelet count, SpO2, blood urea nitrogen (BUN), hemoglobin, C-reactive protein, neutrophil count, and sodium. The results of the fivefold cross-validation repeated 3-times gave AUROC of 0.87, and statistics of the classification matrix to the Youden index as follows: sensitivity 0.840, specificity 0.774, negative predictive value 0.971. Then, the model was tested on a new population (n = 1463) in which the case-fatality rate was 22.6%. The test model showed AUROC 0.818, sensitivity 0.813, specificity 0.650, negative predictive value 0.922. Considering the first quartile of the predicted risk score (low-risk score group), the case-fatality rate was 1.6%, 17.8% in the second and third quartile (high-risk score group) and 53.5% in the fourth quartile (very high-risk score group). The three risk score groups showed good discrimination for the P/F value at admission, and a positive correlation was found for the low-risk class to P/F at 48 h after admission (adjusted R-squared = 0.48). We developed a predictive model of death for people with SARS-CoV-2 infection by including only easy-to-obtain variables (abnormal blood count, BUN, C-reactive protein, sodium and lower SpO2). It demonstrated good accuracy and high power of discrimination. The simplicity of the model makes the risk prediction applicable for patients in the Emergency Department, or during hospitalization. Although it is reasonable to assume that the model is also applicable in not-hospitalized persons, only appropriate studies can assess the accuracy of the model also for persons at home.


Subject(s)
COVID-19/mortality , Machine Learning , Pandemics , SARS-CoV-2 , Aged , Aged, 80 and over , Blood Cell Count , Blood Chemical Analysis , COVID-19/blood , Cohort Studies , Female , Hospital Mortality , Humans , Male , Middle Aged , Models, Statistical , Multivariate Analysis , Oxygen/blood , Pandemics/statistics & numerical data , ROC Curve , Risk Factors , Rome/epidemiology
9.
Int J Cardiol ; 338: 278-285, 2021 09 01.
Article in English | MEDLINE | ID: covidwho-1275354

ABSTRACT

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a pandemic disease that is causing a public health emergency. Characteristics and clinical significance of myocardial injury remain unclear. METHODS: This retrospective single-center study analyzed 189 patients who received a COVID-19 diagnosis out of all 758 subjects with a high sensitive troponin I (Hs-TnI) measurement within the first 24 h of admission at the Policlinico A.Gemelli (Rome, Italy) between February 20th 2020 to April 09th 2020. RESULTS: The prevalence of myocardial injury in our COVID-19 population is of 16%. The patients with cardiac injury were older, had a greater number of cardiovascular comorbidities and higher values of acute phase and inflammatory markers and leucocytes. They required more frequently hospitalization in Intensive Care Unit (10 [32.3%] vs 18 [11.4%]; p = .003) and the mortality rate was significantly higher (17 [54.8%] vs. 15 [9.5%], p < .001). Among patients in ICU, the subjects with myocardial injury showed an increase need of endotracheal intubation (8 out of 9 [88%] vs 7 out of 19[37%], p = .042). Multivariate analyses showed that hs-TnI can significantly predict the degree of COVID-19 disease, the intubation need and in-hospital mortality. CONCLUSIONS: In this study we demonstrate that hs-Tn can significantly predict disease severity, intubation need and in-hospital death. Therefore, it may be reasonable to use Hs-Tn as a clinical tool in COVID-19 patients in order to triage them into different risk groups and can play a pivotal role in the detection of subjects at high risk of cardiac impairment during both the early and recovery stage.


Subject(s)
COVID-19 , Pandemics , COVID-19 Testing , Hospital Mortality , Humans , Italy/epidemiology , Prevalence , Retrospective Studies , Rome , SARS-CoV-2 , Troponin
10.
Animals (Basel) ; 11(4)2021 Mar 31.
Article in English | MEDLINE | ID: covidwho-1232553

ABSTRACT

Antimicrobial resistance (AMR) represents one of the most critical challenges that humanity will face in the following years. In this context, a "One Health" approach with an integrated multidisciplinary effort involving humans, animals and their surrounding environment is needed to tackle the spread of AMR. One of the most common ways for bacteria to live is to adhere to surfaces and form biofilms. Staphylococcus aureus (S. aureus) can form biofilm on most surfaces and in a wide heterogeneity of environmental conditions. The biofilm guarantees the survival of the S. aureus in harsh environmental conditions and represents an issue for the food industry and animal production. The identification and characterization of biofilm-related proteins may provide interesting insights into biofilm formation mechanisms in S. aureus. In this regard, the aims of this study were: (i) to use proteomics to compare proteomes of S. aureus growing in planktonic and biofilm forms in order to investigate the common features of biofilm formation properties of different strains; (ii) to identify specific biofilm mechanisms that may be involved in AMR. The proteomic analysis showed 14 differentially expressed proteins among biofilm and planktonic forms of S. aureus. Moreover, three proteins, such as alcohol dehydrogenase, ATP-dependent 6-phosphofructokinase, and fructose-bisphosphate aldolase, were only differentially expressed in strains classified as high biofilm producers. Differentially regulated catabolites metabolisms and the switch to lower oxygen-related metabolisms were related to the sessile conformation analyzed.

11.
J Pers Med ; 11(5)2021 May 08.
Article in English | MEDLINE | ID: covidwho-1224056

ABSTRACT

The ongoing outbreak of coronavirus disease 2019 (COVID-19), which impairs the functionality of several organs, represents a major threat to human health. One of the hardest challenges in the fight against COVID-19 is the development of wide-scale, effective, and rapid laboratory tests to control disease severity, progression, and possible sudden worsening. Monitoring patients in real-time is highly demanded in this pandemic era when physicians need reliable and quantitative tools to prioritize patients' access to intensive care departments. In this regard, salivary biomarkers are extremely promising, as they allow for the fast and non-invasive collection of specimens and can be repeated multiple times. METHODS: We compare salivary levels of immunoglobulin A subclasses (IgA1 and IgA2) and free light chains (kFLC and λFLC) in a cohort of 29 SARS-CoV-2 patients and 21 healthy subjects. RESULTS: We found that each biomarker differs significantly between the two groups, with p-values ranging from 10-8 to 10-4. A Receiving Operator Curve analysis shows that λFLC level is the best-suited candidate to discriminate the two groups (AUC = 0.96), with an accuracy of 0.94 (0.87-1.00 95% CI), a precision of 0.91 (0.81-1.00 95% CI), a sensitivity of 1.00 (0.96-1.00 95% CI), and a specificity of 0.86 (0.70-1.00 95% CI). CONCLUSION: These results suggest λFLC as an ideal indicator of patient conditions. This hypothesis is strengthened by the consideration that the λFLC half-life (approximately 6 h) is significantly shorter than the IgA one (21 days), thus confirming the potential of λFLC for effectively monitoring patients' fluctuation in real-time.

12.
Mol Biol Rep ; 48(3): 2973-2978, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-1095719

ABSTRACT

The coronavirus disease 2019 (COVID-19) is until today a global health emergency. In an immense effort, effective drugs against COVID-19 are searched and intensive researches on possible repurposing of antiviral agents are performed. Since chloroquine (CQ) and hydroxychloroquine (HCQ) have shown in vitro anti- COVID-19 activities, the potential effect of CQ/HCQ to treat and/or prevent COVID-19 infection has caused global attention. However, concern regarding possible hemolysis in G6PD-deficient COVID-19 patients exists and for this reason, the association between HCQ and G6PD deficiency (G6PDD) is back in the limelight. This study aims to answer the question raised by Mastroianni et al. "Hydroxychloroquine: Culprit or Innocent Bystander in G6PD-Deficient Patients with COVID-19?", reporting all cases of HCQ in G6PD deficient COVID-19 patients published on PubMed (pubmed.ncbi.nlm.nih.gov), in addition to the Mastroianni's patient. In our opinion, after an accurate revision of these cases and responding the question raised by Mastroianni et al., we believe that it is difficult to reach a final verdict about the definitive role of HCQ in these patients. The COVID-19 pandemic has reopened attention on HCQ use and G6PDD. G6PD status is extremely important in modulating the level of reactive oxygen species and many cellular immune responses such as enhanced production of the pro-inflammatory cytokine and inflammasome activation. Since these processes are involved in COVID-19 infection, acute hemolytic anemia, a severe complication of the G6PDD, can occur in these patients. In this context, the role of HCQ, usually effective, safe, and well tolerated in G6PD deficient patients, must be redefined in these patients with COVID-19.As consequence, answering the question: "Hydroxychloroquine: Culprit or Innocent Bystander in G6PD-Deficient Patients with COVID-19?", we state that it is risky to believe that HCQ may be an "innocent bystander" in G6PD-deficient COVID-19 patients.


Subject(s)
Antiviral Agents , COVID-19 , Glucosephosphate Dehydrogenase Deficiency , Hydroxychloroquine , Adult , Aged , Antiviral Agents/adverse effects , Antiviral Agents/therapeutic use , COVID-19/complications , COVID-19/drug therapy , COVID-19/physiopathology , Glucosephosphate Dehydrogenase Deficiency/complications , Glucosephosphate Dehydrogenase Deficiency/physiopathology , Hemolysis , Humans , Hydroxychloroquine/adverse effects , Hydroxychloroquine/therapeutic use , Male , Middle Aged
13.
Mol Biol Rep ; 48(1): 983-987, 2021 Jan.
Article in English | MEDLINE | ID: covidwho-973586

ABSTRACT

Recently, our lab, part of a referral center in Italy, reported its experience regarding the execution of germline BRCA1/2 (gBRCA) testing during the first months of the coronavirus disease-2019 (COVID-19) pandemic, which highlights a substantial reduction (about 60%) compared with the first 2 months of the current year. This evidence appeared to be a lockdown effect due to extraordinary restriction measures to slow down the spread of SARS-CoV-2. In this study, we aimed to evaluate the overall effects of the ongoing pandemic on gBRCA testing in our institution and to understand how COVID-19 has influenced testing after the complete lockdown (March 8-May 5, 2020). Additionally, we compared this year's trend with trends of the last 3 years to better monitor gBRCA testing progress. This detailed analysis highlights two important findings: (1) gBRCA testing did not increase significantly after the lockdown period (May-October 2020) compared with the lockdown period (March-April 2020), emphasizing that even after the lockdown period testing remained low. (2) Comparing the total tests per year (January-October 2017, 2018, 2019, with 2020), the impact of COVID-19 on gBRCA testing is apparent, with similarities of trends registered in 2017. These evidences reveal a gBRCA testing delay for cancer patients and healthy patients at this moment, and the new era of gBRCA testing in the management of ovarian, breast, pancreas and prostate cancer patients has been seriously questioned due to the COVID-19 pandemic. As consequence, we underline that measures to guarantee oncogenetic testing (e.g., gBRCA testing) along with new diagnostic/clinic strategies are mandatory. For these reasons, several proposals are presented in this study.


Subject(s)
BRCA1 Protein/blood , Breast Neoplasms/diagnosis , COVID-19/epidemiology , Ovarian Neoplasms/diagnosis , Pancreatic Neoplasms/diagnosis , Pandemics , Prostatic Neoplasms/diagnosis , Biomarkers, Tumor/blood , COVID-19/psychology , Delayed Diagnosis/ethics , Early Detection of Cancer/statistics & numerical data , Female , Health Policy , Humans , Italy/epidemiology , Male , Physical Distancing , Quarantine/psychology , SARS-CoV-2/pathogenicity
14.
J Proteome Res ; 19(11): 4233-4241, 2020 11 06.
Article in English | MEDLINE | ID: covidwho-960284

ABSTRACT

Progress of the omics platforms widens their application to diverse fields, including immunology. This enables a deeper level of knowledge and the provision of a huge amount of data for which management and fruitful integration with the past evidence requires a steadily growing computational effort. In light of this, immunoinformatics emerges as a new discipline placed in between the traditional lab-based investigations and the computational analysis of the biological data. Immunoinformatics make use of tailored bioinformatics tools and data repositories to facilitate the analysis of data from a plurality of disciplines and help drive novel research hypotheses and in silico screening investigations in a fast, reliable, and cost-effective manner. Such computational immunoproteomics studies may as well prepare and guide lab-based investigations, representing valuable technology for the investigation of novel pathogens, to tentatively evaluate specificity of diagnostic products, to forecast on potential adverse effects of vaccines and to reduce the use of animal models. The present manuscript provides an overview of the COVID-19 pandemic and reviews the state of the art of the omics technologies employed in fighting SARS-CoV-2 infections. A comprehensive description of the immunoinformatics approaches and its potential role in contrasting COVID-19 pandemics is provided.


Subject(s)
Betacoronavirus/immunology , Coronavirus Infections/immunology , Pneumonia, Viral/immunology , Proteomics , COVID-19 , Coronavirus Infections/therapy , Epitopes, B-Lymphocyte/immunology , Epitopes, T-Lymphocyte/immunology , Host-Pathogen Interactions/immunology , Humans , Pandemics , Pneumonia, Viral/therapy , SARS-CoV-2
15.
SSRN; 2020.
Preprint | SSRN | ID: ppcovidwho-1447

ABSTRACT

Background: SARS-CoV-2 belongs to a subgrouof coronaviruses rampant in bats for centuries. It has caused the COVID-19 pandemic. Most patients recover, but a m

16.
Microbes Infect ; 22(10): 592-597, 2020.
Article in English | MEDLINE | ID: covidwho-744191

ABSTRACT

The Envelope (E) protein of SARS-CoV-2 is the most enigmatic protein among the four structural ones. Most of its current knowledge is based on the direct comparison to the SARS E protein, initially mistakenly undervalued and subsequently proved to be a key factor in the ER-Golgi localization and in tight junction disruption. We compared the genomic sequences of E protein of SARS-CoV-2, SARS-CoV and the closely related genomes of bats and pangolins obtained from the GISAID and GenBank databases. When compared to the known SARS E protein, we observed a significant difference in amino acid sequence in the C-terminal end of SARS-CoV-2 E protein. Subsequently, in silico modelling analyses of E proteins conformation and docking provide evidences of a strengthened binding of SARS-CoV-2 E protein with the tight junction-associated PALS1 protein. Based on our computational evidences and on data related to SARS-CoV, we believe that SARS-CoV-2 E protein interferes more stably with PALS1 leading to an enhanced epithelial barrier disruption, amplifying the inflammatory processes, and promoting tissue remodelling. These findings raise a warning on the underestimated role of the E protein in the pathogenic mechanism and open the route to detailed experimental investigations.


Subject(s)
COVID-19/metabolism , Membrane Proteins/chemistry , Nucleoside-Phosphate Kinase/chemistry , SARS-CoV-2/chemistry , Tight Junctions/chemistry , Viral Envelope Proteins/chemistry , Amino Acid Sequence , Animals , COVID-19/genetics , Chiroptera/virology , Databases, Genetic , Humans , Membrane Proteins/genetics , Membrane Proteins/metabolism , Molecular Dynamics Simulation , Nucleoside-Phosphate Kinase/genetics , Nucleoside-Phosphate Kinase/metabolism , Pangolins/virology , SARS Virus/chemistry , SARS Virus/genetics , SARS Virus/metabolism , SARS-CoV-2/genetics , SARS-CoV-2/metabolism , SARS-CoV-2/pathogenicity , Tight Junctions/metabolism , Viral Envelope Proteins/genetics , Viral Envelope Proteins/metabolism
17.
Crit Care ; 24(1): 529, 2020 08 28.
Article in English | MEDLINE | ID: covidwho-733031

ABSTRACT

BACKGROUND: Whether respiratory physiology of COVID-19-induced respiratory failure is different from acute respiratory distress syndrome (ARDS) of other etiologies is unclear. We conducted a single-center study to describe respiratory mechanics and response to positive end-expiratory pressure (PEEP) in COVID-19 ARDS and to compare COVID-19 patients to matched-control subjects with ARDS from other causes. METHODS: Thirty consecutive COVID-19 patients admitted to an intensive care unit in Rome, Italy, and fulfilling moderate-to-severe ARDS criteria were enrolled within 24 h from endotracheal intubation. Gas exchange, respiratory mechanics, and ventilatory ratio were measured at PEEP of 15 and 5 cmH2O. A single-breath derecruitment maneuver was performed to assess recruitability. After 1:1 matching based on PaO2/FiO2, FiO2, PEEP, and tidal volume, COVID-19 patients were compared to subjects affected by ARDS of other etiologies who underwent the same procedures in a previous study. RESULTS: Thirty COVID-19 patients were successfully matched with 30 ARDS from other etiologies. At low PEEP, median [25th-75th percentiles] PaO2/FiO2 in the two groups was 119 mmHg [101-142] and 116 mmHg [87-154]. Average compliance (41 ml/cmH2O [32-52] vs. 36 ml/cmH2O [27-42], p = 0.045) and ventilatory ratio (2.1 [1.7-2.3] vs. 1.6 [1.4-2.1], p = 0.032) were slightly higher in COVID-19 patients. Inter-individual variability (ratio of standard deviation to mean) of compliance was 36% in COVID-19 patients and 31% in other ARDS. In COVID-19 patients, PaO2/FiO2 was linearly correlated with respiratory system compliance (r = 0.52 p = 0.003). High PEEP improved PaO2/FiO2 in both cohorts, but more remarkably in COVID-19 patients (p = 0.005). Recruitability was not different between cohorts (p = 0.39) and was highly inter-individually variable (72% in COVID-19 patients and 64% in ARDS from other causes). In COVID-19 patients, recruitability was independent from oxygenation and respiratory mechanics changes due to PEEP. CONCLUSIONS: Early after establishment of mechanical ventilation, COVID-19 patients follow ARDS physiology, with compliance reduction related to the degree of hypoxemia, and inter-individually variable respiratory mechanics and recruitability. Physiological differences between ARDS from COVID-19 and other causes appear small.


Subject(s)
Coronavirus Infections/physiopathology , Pneumonia, Viral/physiopathology , Respiratory Distress Syndrome/physiopathology , Aged , Betacoronavirus , COVID-19 , Coronavirus Infections/therapy , Female , Humans , Intensive Care Units , Italy , Male , Middle Aged , Pandemics , Pneumonia, Viral/therapy , Positive-Pressure Respiration , Respiratory Distress Syndrome/therapy , Respiratory Function Tests , Respiratory Mechanics/physiology , SARS-CoV-2
18.
Microbes Infect ; 22(4-5): 182-187, 2020.
Article in English | MEDLINE | ID: covidwho-626674

ABSTRACT

Envelope protein of coronaviruses is a structural protein existing in both monomeric and homo-pentameric form. It has been related to a multitude of roles including virus infection, replication, dissemination and immune response stimulation. In the present study, we employed an immunoinformatic approach to investigate the major immunogenic domains of the SARS-CoV-2 envelope protein and map them among the homologue proteins of coronaviruses with tropism for animal species that are closely inter-related with the human beings population all over the world. Also, when not available, we predicted the envelope protein structural folding and mapped SARS-CoV-2 epitopes. Envelope sequences alignment provides evidence of high sequence homology for some of the investigated virus specimens; while the structural mapping of epitopes resulted in the interesting maintenance of the structural folding and epitope sequence localization also in the envelope proteins scoring a lower alignment score. In line with the One-Health approach, our evidences provide a molecular structural rationale for a potential role of taxonomically related coronaviruses in conferring protection from SARS-CoV-2 infection and identifying potential candidates for the development of diagnostic tools and prophylactic-oriented strategies.


Subject(s)
Betacoronavirus/metabolism , Computational Biology/methods , Coronavirus Infections/immunology , Coronavirus Infections/virology , Pneumonia, Viral/immunology , Pneumonia, Viral/virology , Viral Envelope Proteins/immunology , Animals , Betacoronavirus/classification , Betacoronavirus/genetics , Betacoronavirus/immunology , COVID-19 , Coronavirus Envelope Proteins , Epitope Mapping , Gene Expression Regulation, Viral , Humans , Models, Molecular , One Health , Pandemics , Phylogeny , Protein Conformation , SARS-CoV-2 , Sequence Alignment , Sequence Analysis, Protein
19.
Mol Biol Rep ; 47(6): 4857-4860, 2020 Jun.
Article in English | MEDLINE | ID: covidwho-209514

ABSTRACT

The first person-to-person transmission of the 2019-novel coronavirus in Italy on 21 February 2020 led to an infection chain that represents one of the largest known COVID-19 outbreaks outside Asia. Hospitals have been forced to reorganized their units in response to prepare for an unforeseen healthcare emergency. In this context, our laboratory (Molecular and Genomic Diagnostics Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS) re-modulated its priorities by temporarily interrupting most of the molecular tests guaranteeing only those considered "urgent" and not postponable. In particular, this paper details changes regarding the execution of germline BRCA (gBRCA) testing in our laboratory. A substantial reduction in gBRCA testing (about 60%) compared to the first 2 months of the current year was registered, but the requests have not been reset. The requesting physicians were mainly gynaecologists and oncologists. These evidences further emphasize the new era of gBRCA testing in the management of cancer patients and confirms definitively the integration of gBRCA testing/Next Generation Sequencing (NGS) into clinical oncology. Finally, a re-organization of gBRCA testing in our Unit, mainly related to delayed and reduced arrival of tests was necessary, ensuring, however, a high-quality standard and reliability, mandatory for gBRCA testing in a clinical setting.


Subject(s)
BRCA2 Protein/genetics , Breast Neoplasms/diagnosis , Coronavirus Infections/epidemiology , Early Detection of Cancer/statistics & numerical data , Ovarian Neoplasms/diagnosis , Pandemics , Pneumonia, Viral/epidemiology , Betacoronavirus/genetics , Betacoronavirus/pathogenicity , Biomarkers, Tumor/genetics , Breast Neoplasms/genetics , Breast Neoplasms/pathology , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques/statistics & numerical data , Coronavirus Infections/blood , Coronavirus Infections/diagnosis , Coronavirus Infections/pathology , Early Detection of Cancer/methods , Early Diagnosis , Female , Genomics/methods , High-Throughput Nucleotide Sequencing/statistics & numerical data , Humans , Italy/epidemiology , Mutation , Ovarian Neoplasms/genetics , Ovarian Neoplasms/pathology , Pneumonia, Viral/blood , Pneumonia, Viral/diagnosis , Pneumonia, Viral/pathology , Referral and Consultation/statistics & numerical data , SARS-CoV-2
20.
Microbes Infect ; 22(4-5): 188-194, 2020.
Article in English | MEDLINE | ID: covidwho-52542

ABSTRACT

Several research lines are currently ongoing to address the multitude of facets of the pandemic COVID-19. In line with the One-Health concept, extending the target of the studies to the animals which humans are continuously interacting with may favor a better understanding of the SARS-CoV-2 biology and pathogenetic mechanisms; thus, helping to adopt the most suitable containment measures. The last two decades have already faced severe manifestations of the coronavirus infection in both humans and animals, thus, circulating epitopes from previous outbreaks might confer partial protection from SARS-CoV-2 infections. In the present study, we provide an in-silico survey of the major nucleocapsid protein epitopes and compare them with the homologues of taxonomically-related coronaviruses with tropism for animal species that are closely inter-related with the human beings population all over the world. Protein sequence alignment provides evidence of high sequence homology for some of the investigated proteins. Moreover, structural epitope mapping by homology modelling revealed a potential immunogenic value also for specific sequences scoring a lower identity with SARS-CoV-2 nucleocapsid proteins. These evidence provide a molecular structural rationale for a potential role in conferring protection from SARS-CoV-2 infection and identifying potential candidates for the development of diagnostic tools and prophylactic-oriented strategies.


Subject(s)
Betacoronavirus/metabolism , Coronavirus/classification , Coronavirus/genetics , Epitopes , Nucleocapsid Proteins/metabolism , Amino Acid Sequence , Animals , Betacoronavirus/genetics , Computational Biology , Computer Simulation , Coronavirus Nucleocapsid Proteins , Gene Expression Regulation, Viral/immunology , Humans , Models, Molecular , Nucleocapsid Proteins/genetics , Phosphoproteins , Phylogeny , Protein Conformation , Protein Domains , SARS-CoV-2 , Species Specificity
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