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1.
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
2.
Forensic Sci Int ; 325: 110851, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1244737

ABSTRACT

BACKGROUND AND AIM: COVID-19 is an extremely challenging disease, both from a clinical and forensic point of view, and performing autopsies of COVID-19 deceased requires adequately equipped sectorial rooms and exposes health professionals to the risk of contagion. Among one of the categories that are most affected by SARS-Cov-2 infection are the elderly residents. Despite the need for prompt diagnoses, which are essential to implement all isolation measures necessary to contain the infection spread, deceased subjects in long-term care facilities are still are often diagnosed post-mortem. In this context, our study focuses on the use of post-mortem computed tomography for the diagnosis of COVID-19 infection, in conjunction with post-mortem swabs. The aim of this study was to assess the usefulness of post-mortem whole CT-scanning in identifying COVID-19 pneumonia as a cause of death, by comparing chest CT-findings of confirmed COVID-19 fatalities to control cases. MATERIALS AND METHODS: The study included 24 deceased subjects: 13 subjects coming from long-term care facility and 11 subjects died at home. Whole body CT scans were performed within 48 h from death in all subjects to evaluate the presence and distribution of pulmonary abnormalities typical of COVID-19-pneumonia, including: ground-glass opacities (GGO), consolidation, and pleural effusion to confirm the post-mortem diagnosis. RESULTS: Whole-body CT scans was feasible and allowed a complete diagnosis in all subjects. In 9 (69%) of the 13 cases from long-term care facility the cause of death was severe COVID 19 pneumonia, while GGO were present in 100% of the study population. CONCLUSION: In the context of rapidly escalating COVID-19 outbreaks, given that laboratory tests for the novel coronavirus is time-consuming and can be falsely negative, the post-mortem CT can be considered as a reliable and safe modality to confirm COVID-19 pneumonia. This is especially true for specific postmortem chest CT-findings that are rather characteristic of COVID-19 fatalities.


Subject(s)
COVID-19/diagnosis , Lung/diagnostic imaging , Tomography, X-Ray Computed , Adult , Aged , Aged, 80 and over , Autopsy/methods , Case-Control Studies , Female , Humans , Male , Middle Aged , Pleural Effusion/diagnostic imaging , Retrospective Studies , Sensitivity and Specificity , Whole Body Imaging
3.
Forensic Imaging ; : 200454, 2021.
Article in English | ScienceDirect | ID: covidwho-1193318

ABSTRACT

We present the case of an elderly woman who died from COVID-19 during the first wave of the pandemic. The physicians in charge of the patient were later accused of medical malpractice resulting in the death of the patient. The article reviews the comprehensive medico-legal investigations into this case that included an analysis of the medical history, clinical imaging, post-mortem imaging, autopsy, histopathology, and microbiology as well as an assessment of the medical knowledge regarding transmission of the SARS-CoV-2 virus and the management of COVID-19 at the time of the patient's death. The investigation resulted in a verdict of not guilty. This case highlights the value of clinical and post-mortem imaging as well as various challenges of medico-legal investigations of COVID-19 related deaths.

5.
Eur J Radiol ; 131: 109217, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-735087

ABSTRACT

Due to its pandemic diffusion, SARS- CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) infection represents a global threat. Despite a multiorgan involvement has been described, pneumonia is the most common manifestation of COVID-19 (Coronavirus disease 2019) and it is associated with a high morbidity and a considerable mortality. Especially in the areas with high disease burden, chest imaging plays a crucial role to speed up the diagnostic process and to aid the patient management. The purpose of this comprehensive review is to understand the diagnostic capabilities and limitations of chest X-ray (CXR) and high-resolution computed tomography (HRCT) in defining the common imaging features of COVID-19 pneumonia and correlating them with the underlying pathogenic mechanisms. The evolution of lung abnormalities over time, the uncommon findings, the possible complications, and the main differential diagnosis occurring in the pandemic phase of SARS-CoV-2 infection are also discussed.


Subject(s)
Betacoronavirus , Coronavirus Infections/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Animals , COVID-19 , Diagnosis, Differential , Follow-Up Studies , Humans , Multimodal Imaging , Pandemics , SARS-CoV-2 , Tomography, X-Ray Computed/methods
6.
Eur Radiol ; 30(12): 6940-6949, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-618199

ABSTRACT

OBJECTIVES: To retrospectively analyze interventional radiology (IR) activity changes in the COVID-19 era and to describe how to safely and effectively reorganize IR activity. METHODS: All IR procedures performed between January 30 and April 8, 2020 (COVID-era group) and the same 2019 period (non-COVID-era group) were retrospectively included and compared. A sub-analysis for the lockdown period (LDP: 11 March-8 April) was also conducted. Demographic, hospitalization, clinical, and procedural data were obtained for both groups and statistically compared with univariable analysis. RESULTS: A total of 1496 procedures (non-COVID era, 825; COVID era, 671) performed in 1226 patients (64.9 ± 15.1 years, 618 women) were included. The number of procedures decreased by 18.6% between 2019 and 2020 (825 vs 671, p < .001), with a reduction by 48.2% in LDP (188 vs 363, p < .0001). In the LDP COVID era, bedside procedures were preferred (p = .013), with an increase in procedures from the intensive care unit compared with the emergency department and outpatients (p = .048), and an increased activity for oncological patients (p = .003). No incidents of cross-infection of non-infected from infected patients and no evidence of COVID-19 infection of healthcare workers in the IR service was registered. CONCLUSIONS: Coronavirus disease outbreak changed the interventional radiology activity with an overall reduction in the number of procedures. However, this study confirms that interventional radiology continuum of care can be safely performed also during the pandemic, following defined measures and protocols, taking care of all patients. KEY POINTS: • Coronavirus disease pandemic determined a reduction of interventional radiology activity as compared to the same period of the previous year. • Interventional radiology procedures for life-threatening conditions and non-deferrable oncologic treatments were prioritized as opposed to elective procedures. • Strict adoption of safe procedures allowed us to have until now no incidents of cross-infection of non-infected from infected patients and no evidence of COVID-19 infection of HCWs in the IR service.


Subject(s)
Betacoronavirus , Coronavirus Infections/diagnosis , Pandemics , Pneumonia, Viral/diagnosis , Radiography/methods , Tertiary Care Centers/statistics & numerical data , Aged , COVID-19 , Coronavirus Infections/epidemiology , Emergency Service, Hospital/statistics & numerical data , Female , Hospitalization/trends , Humans , Italy/epidemiology , Longitudinal Studies , Male , Middle Aged , Pneumonia, Viral/epidemiology , Radiology, Interventional/methods , Retrospective Studies , SARS-CoV-2
7.
J Stroke Cerebrovasc Dis ; 29(8): 104922, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-186315

ABSTRACT

While the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) spreads all over the world, the healthcare systems are facing the dramatic challenge of simultaneously fight against the outbreak and life-threating emergencies. In this biological setting, emergency departments and neurovascular teams are exposed to high risk of infection and should therefore be prepared to deal with neurological emergencies safely. The purpose of this article is to analyze the current evidence on COVID-19 in the context of acute ischemic stroke and to describe the model of behavior we are putting into action to maintain the stroke pathway both rapid for the patient and safe for the healthcare professionals. We reserve a specific focus on personal protection equipment, dress code and healthcare professional behavior.


Subject(s)
Betacoronavirus/pathogenicity , Brain Ischemia/therapy , Coronavirus Infections/prevention & control , Health Services Needs and Demand , Infection Control , Needs Assessment , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Stroke/therapy , Brain Ischemia/diagnostic imaging , COVID-19 , Coronavirus Infections/diagnosis , Coronavirus Infections/transmission , Coronavirus Infections/virology , Host Microbial Interactions , Humans , Infectious Disease Transmission, Patient-to-Professional/prevention & control , Infectious Disease Transmission, Professional-to-Patient/prevention & control , Occupational Exposure/adverse effects , Occupational Exposure/prevention & control , Occupational Health , Patient Safety , Pneumonia, Viral/diagnosis , Pneumonia, Viral/transmission , Pneumonia, Viral/virology , Risk Assessment , Risk Factors , SARS-CoV-2 , Stroke/diagnostic imaging
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