ORCID Profile
0000-0003-1003-4637
Current Organisations
IRCCS Humanitas Research Hospital
,
Humanitas University
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Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 28-01-2021
DOI: 10.1097/CCM.0000000000004899
Abstract: The coronavirus disease 2019 pandemic continues to affect millions worldwide. Given the rapidly growing evidence base, we implemented a living guideline model to provide guidance on the management of patients with severe or critical coronavirus disease 2019 in the ICU. The Surviving Sepsis C aign Coronavirus Disease 2019 panel has expanded to include 43 experts from 14 countries all panel members completed an electronic conflict-of-interest disclosure form. In this update, the panel addressed nine questions relevant to managing severe or critical coronavirus disease 2019 in the ICU. We used the World Health Organization’s definition of severe and critical coronavirus disease 2019. The systematic reviews team searched the literature for relevant evidence, aiming to identify systematic reviews and clinical trials. When appropriate, we performed a random-effects meta-analysis to summarize treatment effects. We assessed the quality of the evidence using the Grading of Recommendations, Assessment, Development, and Evaluation approach, then used the evidence-to-decision framework to generate recommendations based on the balance between benefit and harm, resource and cost implications, equity, and feasibility. The Surviving Sepsis C aign Coronavirus Diease 2019 panel issued nine statements (three new and six updated) related to ICU patients with severe or critical coronavirus disease 2019. For severe or critical coronavirus disease 2019, the panel strongly recommends using systemic corticosteroids and venous thromboprophylaxis but strongly recommends against using hydroxychloroquine. In addition, the panel suggests using dexamethasone (compared with other corticosteroids) and suggests against using convalescent plasma and therapeutic anticoagulation outside clinical trials. The Surviving Sepsis C aign Coronavirus Diease 2019 panel suggests using remdesivir in nonventilated patients with severe coronavirus disease 2019 and suggests against starting remdesivir in patients with critical coronavirus disease 2019 outside clinical trials. Because of insufficient evidence, the panel did not issue a recommendation on the use of awake prone positioning. The Surviving Sepsis C aign Coronavirus Diease 2019 panel issued several recommendations to guide healthcare professionals caring for adults with critical or severe coronavirus disease 2019 in the ICU. Based on a living guideline model the recommendations will be updated as new evidence becomes available.
Publisher: Springer Science and Business Media LLC
Date: 21-05-2022
Publisher: Massachusetts Medical Society
Date: 30-06-2022
Publisher: MDPI AG
Date: 15-01-2023
DOI: 10.3390/DIAGNOSTICS13020317
Abstract: Background: Acute kidney injury (AKI) is highly prevalent in critical COVID-19 patients. The diagnosis and staging of AKI are based on serum creatinine (sCr) and urinary output criteria, with limitations in the functional markers. New cell-cycle arrest biomarkers [TIMP2]*[IGFBP7] have been proposed for early detection of AKI, but their role in critically ill COVID-19 patients is poorly understood. Methods: We conducted an observational study to assess the performance of [TIMP2]*[IGFBP7] for the detection of AKI in critical COVID-19 patients admitted to our intensive care unit (ICU). We s led urinary [TIMP2]*[IGFBP7] levels at ICU admission, 12 h, 24 h, and 48 h, and compared the results to the development of AKI, as well as baseline and laboratory data. Results: Forty-one patients were enrolled. The median age was 66 years [57–72] and most were males (85%). Thirteen patients (31.7%) developed no/mild stage AKI, 19 patients (46.3%) moderate AKI, and nine patients (22.0%) severe AKI. The ICU mortality was 29.3%. sCr levels in the Emergency Department or at ICU admission were not significantly different according to AKI stage. [TIMP-2]*[IGFBP-7] urinary levels were elevated in severe AKI at 12 h after ICU admission, but not at ICU admission or 24 h or 48 h after ICU admission. Conclusion: Urinary biomarkers [TIMP-2]*[IGFBP-7] were generally increased in this population with a high prevalence of AKI, and were higher in patients with severe AKI measured at 12 h from ICU admission. Further studies are needed to evaluate the best timing of these biomarkers in this population.
Publisher: MDPI AG
Date: 02-2023
DOI: 10.3390/A16020076
Abstract: Background: Sepsis is one of the major causes of in-hospital death, and is frequent in patients presenting to the emergency department (ED). Early identification of high-risk septic patients is critical. Machine learning (ML) techniques have been proposed for identification and prognostication of ED septic patients, but these models often lack pre-hospital data and lack validation against early sepsis identification scores (such as qSOFA) and scores for critically ill patients (SOFA, APACHE II). Methods We conducted an electronic health record (EHR) study to test whether interpretable and scalable ML models predict mortality in septic ED patients and compared their performance with clinical scores. Consecutive adult septic patients admitted to ED over 18 months were included. We built ML models, ranging from a simple-classifier model, to unbalanced and balanced logistic regression, and random forest, and compared their performance to qSOFA, SOFA, and APACHE II scores. Results: We included 425 sepsis patients after screening 38,500 EHR for sepsis criteria. Overall mortality was 15.2% and peaked in patients coming from retirement homes (38%). Random forest, like balanced (0.811) and unbalanced logistic regression (0.863), identified patients at risk of mortality (0.813). All ML models outperformed qSOFA, APACHE II, and SOFA scores. Age, mean arterial pressure, and serum sodium were major mortality predictors. Conclusions: We confirmed that random forest models outperform previous models, including qSOFA, SOFA, and APACHE II, in identifying septic patients at higher mortality risk, while maintaining good interpretability. Machine learning models may gain further adoption in the future with increasing diffusion and granularity of EHR data, yielding the advantage of increased scalability compared to standard statistical techniques.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 25-03-2020
DOI: 10.1097/CCM.0000000000004363
Abstract: The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of a rapidly spreading illness, Coronavirus Disease 2019 (COVID-19), affecting thousands of people around the world. Urgent guidance for clinicians caring for the sickest of these patients is needed. We formed a panel of 36 experts from 12 countries. All panel members completed the World Health Organization conflict of interest disclosure form. The panel proposed 53 questions that are relevant to the management of COVID-19 in the ICU. We searched the literature for direct and indirect evidence on the management of COVID-19 in critically ill patients in the ICU. We identified relevant and recent systematic reviews on most questions relating to supportive care. We assessed the certainty in the evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach, then generated recommendations based on the balance between benefit and harm, resource and cost implications, equity, and feasibility. Recommendations were either strong or weak, or in the form of best practice recommendations. The Surviving Sepsis C aign COVID-19 panel issued 54 statements, of which four are best practice statements, nine are strong recommendations, and 35 are weak recommendations. No recommendation was provided for six questions. The topics were: 1) infection control, 2) laboratory diagnosis and specimens, 3) hemodynamic support, 4) ventilatory support, and 5) COVID-19 therapy. The Surviving Sepsis C aign COVID-19 panel issued several recommendations to help support healthcare workers caring for critically ill ICU patients with COVID-19. When available, we will provide new evidence in further releases of these guidelines.
Publisher: Elsevier BV
Date: 08-2021
Publisher: Elsevier BV
Date: 04-2017
DOI: 10.1053/J.JVCA.2016.09.034
Abstract: Postoperative pulmonary complications (PPC) are among the most common complications after noncardiac surgery. Men, smokers, and elderly patients with chronic obstructive pulmonary disease or heart failure are more likely to experience PPC. The majority of patients undergoing vascular surgery belong in these categories and are at higher risk of developing PPC. Moreover, the surgical site is one of the most important risk factors associated with PPC, and aortic surgery carries the highest risk. The aim of this systematic review was to obtain an additional understanding of the real incidence of PPC after open abdominal aortic surgery and the impact of PPC on survival. Systematic review and meta-analysis. Hospitals PARTICIPANTS: Patients who underwent open abdominal aortic surgery. None. A literature search was performed on BioMedCentral, PubMed, Embase, and the Cochrane Register of clinical trials. All prospective or retrospective studies reporting data on PPC after open abdominal aortic surgery were included. Co-primary endpoints were the PPC rate and the correlation between PPC and perioperative mortality. The secondary endpoint was the difference in the PPC rate and mortality between elective and urgent surgery. Data on 269,637 patients from 213 studies were analyzed. The overall median incidence of PPC was 10.3% (interquartile range 5.55%-19.1%). Pneumonia, respiratory insufficiency, prolonged mechanical ventilation, need for unplanned mechanical ventilation, atelectasis, acute respiratory distress syndrome, pulmonary edema, and pleural effusions were the most common PPC reported in the literature. Occurrence of PPC was associated with postoperative mortality (r = 0.65, p<0.01) and was significantly higher in urgent procedures (p<0.001). Incidence of PPC after open abdominal aortic surgery is high and is associated with increased postoperative morbidity and mortality.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 08-2015
Publisher: Elsevier BV
Date: 04-2015
DOI: 10.1053/J.JVCA.2014.11.005
Abstract: High-quality evidence and derived guidelines, as typically published in major academic journals, are a major process that shapes physician decision-making worldwide. However, for many aspects of medical practice, there is a lack of High-quality evidence or an overload of somewhat contradictory low-quality information, which makes decision-making a difficult, uncertain, and unpredictable process. When the issues in question are important and evidence limited or controversial, the medical community seeks to establish common ground for "best practice" through consensus conferences and consensus statements or guidelines. Such consensus statements are seen as a useful tool to establish expert agreement, define the boundaries of acceptable practice, provide priorities for the research agenda, and obtain opinions from different countries and healthcare systems. This standard approach, however, can be criticized for being elitist, noninclusive, and poorly representative of the community of clinicians who will have to make decisions about the implementation of such recommendations. Accordingly, the authors propose a new model based on a combination of a local core meeting (detailed review and expert input) followed by a worldwide web-based network assessment (democracy-based consensus). The authors already have applied this approach to develop consensus on all nonsurgical interventions that increase or reduce perioperative mortality in critically ill patients and in those with acute kidney injury. The methodology was based on 5 sequential local and web-based steps. Both a panel of experts and a large number of professionals from all over the world were involved, giving birth to a new type of "democracy-based consensus." This new type of "democracy-based consensus" has the potential to increase grass-root clinician involvement, expand the reach to less-developed countries, provide a more global perspective on proposed interventions, and perhaps more importantly, increase awareness, ownership, and the statistical likelihood of subsequent implementation.
Publisher: Springer Science and Business Media LLC
Date: 28-03-2020
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for massimiliano greco.