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1.
Bone Joint J ; 102-B(9): 1219-1228, 2020 09.
Article in English | MEDLINE | ID: covidwho-844187

ABSTRACT

AIMS: The primary aim was to assess the independent influence of coronavirus disease (COVID-19) on 30-day mortality for patients with a hip fracture. The secondary aims were to determine whether: 1) there were clinical predictors of COVID-19 status; and 2) whether social lockdown influenced the incidence and epidemiology of hip fractures. METHODS: A national multicentre retrospective study was conducted of all patients presenting to six trauma centres or units with a hip fracture over a 46-day period (23 days pre- and 23 days post-lockdown). Patient demographics, type of residence, place of injury, presentation blood tests, Nottingham Hip Fracture Score, time to surgery, operation, American Society of Anesthesiologists (ASA) grade, anaesthetic, length of stay, COVID-19 status, and 30-day mortality were recorded. RESULTS: Of 317 patients with acute hip fracture, 27 (8.5%) had a positive COVID-19 test. Only seven (26%) had suggestive symptoms on admission. COVID-19-positive patients had a significantly lower 30-day survival compared to those without COVID-19 (64.5%, 95% confidence interval (CI) 45.7 to 83.3 vs 91.7%, 95% CI 88.2 to 94.8; p < 0.001). COVID-19 was independently associated with increased 30-day mortality risk adjusting for: 1) age, sex, type of residence (hazard ratio (HR) 2.93; p = 0.008); 2) Nottingham Hip Fracture Score (HR 3.52; p = 0.001); and 3) ASA (HR 3.45; p = 0.004). Presentation platelet count predicted subsequent COVID-19 status; a value of < 217 × 109/l was associated with 68% area under the curve (95% CI 58 to 77; p = 0.002) and a sensitivity and specificity of 63%. A similar number of patients presented with hip fracture in the 23 days pre-lockdown (n = 160) and 23 days post-lockdown (n = 157) with no significant (all p ≥ 0.130) difference in patient demographics, residence, place of injury, Nottingham Hip Fracture Score, time to surgery, ASA, or management. CONCLUSION: COVID-19 was independently associated with an increased 30-day mortality rate for patients with a hip fracture. Notably, most patients with hip fracture and COVID-19 lacked suggestive symptoms at presentation. Platelet count was an indicator of risk of COVID-19 infection. These findings have implications for the management of hip fractures, in particular the need for COVID-19 testing. Cite this article: Bone Joint J 2020;102-B(9):1219-1228.


Subject(s)
Cause of Death , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Hip Fractures/epidemiology , Hospital Mortality , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , Aged , Aged, 80 and over , Clinical Laboratory Techniques , Cohort Studies , Female , Hip Fractures/diagnosis , Hip Fractures/surgery , Humans , Incidence , Male , Pandemics , Predictive Value of Tests , Proportional Hazards Models , Reference Values , Retrospective Studies , Risk Assessment , Survival Rate , Trauma Centers
2.
Radiology ; 297(1): E197-E206, 2020 10.
Article in English | MEDLINE | ID: covidwho-817842

ABSTRACT

Background Chest radiography has not been validated for its prognostic utility in evaluating patients with coronavirus disease 2019 (COVID-19). Purpose To analyze the prognostic value of a chest radiograph severity scoring system for younger (nonelderly) patients with COVID-19 at initial presentation to the emergency department (ED); outcomes of interest included hospitalization, intubation, prolonged stay, sepsis, and death. Materials and Methods In this retrospective study, patients between the ages of 21 and 50 years who presented to the ED of an urban multicenter health system from March 10 to March 26, 2020, with COVID-19 confirmation on real-time reverse transcriptase polymerase chain reaction were identified. Each patient's ED chest radiograph was divided into six zones and examined for opacities by two cardiothoracic radiologists, and scores were collated into a total concordant lung zone severity score. Clinical and laboratory variables were collected. Multivariable logistic regression was used to evaluate the relationship between clinical parameters, chest radiograph scores, and patient outcomes. Results The study included 338 patients: 210 men (62%), with median age of 39 years (interquartile range, 31-45 years). After adjustment for demographics and comorbidities, independent predictors of hospital admission (n = 145, 43%) were chest radiograph severity score of 2 or more (odds ratio, 6.2; 95% confidence interval [CI]: 3.5, 11; P < .001) and obesity (odds ratio, 2.4 [95% CI: 1.1, 5.4] or morbid obesity). Among patients who were admitted, a chest radiograph score of 3 or more was an independent predictor of intubation (n = 28) (odds ratio, 4.7; 95% CI: 1.8, 13; P = .002) as was hospital site. No significant difference was found in primary outcomes across race and ethnicity or those with a history of tobacco use, asthma, or diabetes mellitus type II. Conclusion For patients aged 21-50 years with coronavirus disease 2019 presenting to the emergency department, a chest radiograph severity score was predictive of risk for hospital admission and intubation. © RSNA, 2020 Online supplemental material is available for this article.


Subject(s)
Coronavirus Infections , Lung/diagnostic imaging , Pandemics , Pneumonia, Viral , Adult , Betacoronavirus , Coronavirus Infections/diagnostic imaging , Coronavirus Infections/epidemiology , Coronavirus Infections/pathology , Female , Hospitalization/statistics & numerical data , Humans , Intubation, Intratracheal/statistics & numerical data , Lung/pathology , Male , Middle Aged , Pneumonia, Viral/diagnostic imaging , Pneumonia, Viral/epidemiology , Pneumonia, Viral/pathology , Predictive Value of Tests , Prognosis , Radiography, Thoracic , Retrospective Studies , Severity of Illness Index , Tomography, X-Ray Computed , Treatment Outcome , Young Adult
3.
Cardiol Rev ; 28(6): 295-302, 2020.
Article in English | MEDLINE | ID: covidwho-814183

ABSTRACT

The 2019 novel coronavirus, declared a pandemic, has infected 2.6 million people as of April 27, 2020, and has resulted in the death of 181,938 people. D-dimer is an important prognostic tool, is often elevated in patients with severe coronavirus disease-19 (COVID-19) infection and in those who suffered death. In this systematic review, we aimed to investigate the prognostic role of D-dimer in COVID-19-infected patients. We searched PubMed, Medline, Embase, Ovid, and Cochrane for studies reporting admission D-dimer levels in COVID-19 patients and its effect on mortality. Eighteen studies (16 retrospective and 2 prospective) with a total of 3682 patients met the inclusion criteria. The pooled weighted mean difference (WMD) demonstrated significantly elevated D-dimer levels in patients who died versus those who survived (WMD, 6.13 mg/L; 95% confidence interval [CI] 4.16-8.11; P < 0.001). Similarly, the pooled mean D-dimer levels were significantly elevated in patients with severe COVID-19 infection (WMD, 0.54 mg/L; 95% CI 0.28-0.80; P < 0.001). The risk of mortality was fourfold higher in patients with positive D-dimer versus negative D-dimer (risk ratio, 4.11; 95% CI, 2.48-6.84; P < 0.001) and the risk of developing severe disease was twofold higher in patients with positive D-dimer levels versus negative D-dimer (risk ratio, 2.04; 95% CI, 1.34-3.11; P < 0.001). Our meta-analysis demonstrates that patients with COVID-19 infection presenting with elevated D-dimer levels have an increased risk of severe disease and mortality.


Subject(s)
Coronavirus Infections , Fibrin Fibrinogen Degradation Products/analysis , Pandemics , Pneumonia, Viral , Betacoronavirus , Coronavirus Infections/blood , Coronavirus Infections/diagnosis , Coronavirus Infections/mortality , Humans , Mortality , Pneumonia, Viral/blood , Pneumonia, Viral/diagnosis , Pneumonia, Viral/mortality , Predictive Value of Tests , Prognosis , Risk Assessment/methods
6.
Respir Res ; 21(1): 245, 2020 Sep 22.
Article in English | MEDLINE | ID: covidwho-781468

ABSTRACT

BACKGROUND: The COVID-19 pandemic has led to more than 760,000 deaths worldwide (correct as of 16th August 2020). Studies suggest a hyperinflammatory response is a major cause of disease severity and death. Identitfying COVID-19 patients with hyperinflammation may identify subgroups who could benefit from targeted immunomodulatory treatments. Analysis of cytokine levels at the point of diagnosis of SARS-CoV-2 infection can identify patients at risk of deterioration. METHODS: We used a multiplex cytokine assay to measure serum IL-6, IL-8, TNF, IL-1ß, GM-CSF, IL-10, IL-33 and IFN-γ in 100 hospitalised patients with confirmed COVID-19 at admission to University Hospital Southampton (UK). Demographic, clinical and outcome data were collected for analysis. RESULTS: Age > 70 years was the strongest predictor of death (OR 28, 95% CI 5.94, 139.45). IL-6, IL-8, TNF, IL-1ß and IL-33 were significantly associated with adverse outcome. Clinical parameters were predictive of poor outcome (AUROC 0.71), addition of a combined cytokine panel significantly improved the predictability (AUROC 0.85). In those ≤70 years, IL-33 and TNF were predictive of poor outcome (AUROC 0.83 and 0.84), addition of a combined cytokine panel demonstrated greater predictability of poor outcome than clinical parameters alone (AUROC 0.92 vs 0.77). CONCLUSIONS: A combined cytokine panel improves the accuracy of the predictive value for adverse outcome beyond standard clinical data alone. Identification of specific cytokines may help to stratify patients towards trials of specific immunomodulatory treatments to improve outcomes in COVID-19.


Subject(s)
Coronavirus Infections/blood , Coronavirus Infections/epidemiology , Cytokines/analysis , Hospital Mortality , Inflammation Mediators/blood , Pandemics/statistics & numerical data , Pneumonia, Viral/blood , Pneumonia, Viral/epidemiology , Age Factors , Analysis of Variance , Area Under Curve , Clinical Laboratory Techniques/methods , Cohort Studies , Coronavirus Infections/diagnosis , Coronavirus Infections/physiopathology , Female , Hospitalization/statistics & numerical data , Hospitals, University , Humans , Incidence , Male , Pandemics/prevention & control , Phenotype , Pneumonia, Viral/physiopathology , Predictive Value of Tests , ROC Curve , Retrospective Studies , Severity of Illness Index , Sex Factors , United Kingdom
7.
Lancet Gastroenterol Hepatol ; 5(8): 720, 2020 08.
Article in English | MEDLINE | ID: covidwho-678741
8.
Monaldi Arch Chest Dis ; 90(3)2020 Jul 15.
Article in English | MEDLINE | ID: covidwho-649882

ABSTRACT

Italy is currently experiencing an epidemic of coronavirus disease 2019 (Covid-19). Aim of our study is to identify the best predictors of Intensive Care Unit (ICU) admission in patients with Covid-19. We examined 28 patients admitted to the Emergency Department (ED) and subsequently confirmed as cases of Covid-19. Patients received, at the admission to the ED, a diagnostic work-up including: patient history, clinical examination, an arterial blood gas analysis (whenever possible performed on room air), laboratory blood tests, including serum concentrations of interleukin-6 (IL-6), lung ultrasound examination and a computed tomography (CT) scan of the thorax. For each patient, as gas exchange index through the alveolocapillary membrane, we determined the alveolar-arterial oxygen gradient (AaDO⁠2) and the alveolar-arterial oxygen gradient augmentation (AaDO⁠2 augmentation). For each patient, as measurement of hypoxemia, we determined oxygen saturation (SpO2), partial pressure of oxygen in arterial blood (PaO⁠2), PaO⁠2 deficit and the ratio between arterial partial pressure of oxygen by blood gas analysis and fraction of inspired oxygen (P/F). Patients were assigned to ICU Group or to Non-ICU Group basing on the decision to intubate. Areas under the curve (AUC) and receiver operating characteristic (ROC) curve were used to compare the performance of each test in relation to prediction of ICU admission. Comparing patients of ICU Group (10 patients) with patients of Non-ICU Group (18 patients), we found that the first were older, they had more frequently a medical history of malignancy and they were more frequently admitted to ED for dyspnea. Patients of ICU Group had lower oxygen saturation, PaO⁠2, P/F and higher heart rate, respiratory rate, AaDO⁠2, AaDO⁠2 augmentation and lactate than patients of Non-ICU Group. ROC curves demonstrate that age, heart rate, respiratory rate, dyspnea, lactate, AaDO2, AaDO2 augmentation, white blood cell count, neutrophil count and percentage, fibrinogen, C-reactive protein, lactate dehydrogenase, glucose level, international normalized ratio (INR), blood urea and IL-6 are useful predictors of ICU admission. We identified several predictors of ICU admission in patients with Covid-19. They can act as fast tools for the early identification and timely treatment of critical cases since their arrival in the ED.


Subject(s)
Betacoronavirus , Coronavirus Infections/diagnosis , Coronavirus Infections/therapy , Critical Care , Pneumonia, Viral/diagnosis , Pneumonia, Viral/therapy , Adult , Aged , Aged, 80 and over , Blood Gas Analysis , Coronavirus Infections/complications , Emergency Service, Hospital , Female , Hospitalization , Humans , Italy , Male , Middle Aged , Pandemics , Pneumonia, Viral/complications , Predictive Value of Tests , ROC Curve , Risk Factors
9.
Curr Opin Obstet Gynecol ; 32(5): 322-334, 2020 10.
Article in English | MEDLINE | ID: covidwho-629087

ABSTRACT

PURPOSE OF REVIEW: Gestational diabetes mellitus (GDM) is associated with adverse pregnancy complications. Accurate screening and diagnosis of gestational diabetes are critical to treatment, and in a pandemic scenario like coronavirus disease 2019 needing a simple test that minimises prolonged hospital stay. We undertook a meta-analysis on the screening and diagnostic accuracy of the haemoglobin A1c (HbA1c) test in women with and without risk factors for gestational diabetes. RECENT FINDINGS: Unlike the oral glucose tolerance test, the HbA1c test is simple, quick and more acceptable. There is a growing body of evidence on the accuracy of HbA1c as a screening and diagnostic test for GDM. We searched Medline, Embase and Cochrane Library and selected relevant studies. Accuracy data for different thresholds within the final 23 included studies (16 921 women) were pooled using a multiple thresholds model. Summary accuracy indices were estimated by selecting an optimal threshold that optimises either sensitivity or specificity according to different scenarios. SUMMARY: HbA1c is more useful as a specific test at a cut-off of 5.7% (39 mmol/mol) with a false positive rate of 10%, but should be supplemented by a more sensitive test to detect women with GDM.


Subject(s)
Diabetes, Gestational/diagnosis , Glycated Hemoglobin A/analysis , Case-Control Studies , Female , Humans , Predictive Value of Tests , Pregnancy , Risk Factors
10.
Acta Biomed ; 91(3): e2020006, 2020 09 07.
Article in English | MEDLINE | ID: covidwho-761239

ABSTRACT

BACKGROUND AND AIM: Digital epidemiology is increasingly used for supporting traditional epidemiology. This study was hence aimed to explore whether the Google search volume may have been useful to predict the trajectory of coronavirus disease 2019 (COVID-19) outbreak in Italy. MATERIALS AND METHODS: We accessed Google Trends for collecting data on weekly Google searches for the keywords "tosse" (i.e., cough), "febbre" (i.e., fever) and "dispnea" (dyspnea) in Italy, between February and May 2020. The number of new weekly cases of COVID-19 in Italy was also obtained from the website of the National Institute of Health. RESULTS: The peaks of Google searches for the three terms predicted by 3 weeks that of newly diagnosed COVID-19 cases. The peaks of weekly Google searches for "febbre" (fever), "tosse"( cough) and "dispnea" (dyspnea) were 1.7-, 2.2- and 7.7-fold higher compared to the week before the diagnosis of the first national case. No significant correlation was found between the number of newly diagnosed COVID-19 cases and Google search volumes of "tosse" (cough) and "febbre" (fever), whilst "dyspnea" (dyspnea) was significantly correlated (r= 0.50; p=0.034). The correlation between newly diagnosed COVID-19 cases and "tosse" (cough; r=0.65; p=0.008) or "febbre" (fever; 0.69; p=0.004) become statistically significant with a 3-week delay. All symptoms were also significantly inter-correlated. Conclusions; Continuously monitoring the volume of Google searches and mapping their origin can be a potentially valuable instrument to help predicting and identifying local recrudescence of COVID-19.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Disease Outbreaks/statistics & numerical data , Pneumonia, Viral/epidemiology , Search Engine/methods , Humans , Italy/epidemiology , Pandemics , Predictive Value of Tests
11.
Lung ; 198(5): 777-784, 2020 10.
Article in English | MEDLINE | ID: covidwho-754565

ABSTRACT

PURPOSE: SARS-CoV-2 (COVID-19) has infected more than 7 million people worldwide in the short time since it emerged in Wuhan, China in December 2019. The aim of this study was to investigate the relationship between serum interleukin 6 (IL-6) and surfactant protein D (SP-D) levels and the clinical course and prognosis of COVID-19. MATERIALS AND METHODS: The study included a total of 108 individuals: 88 patients who were diagnosed with COVID-19 by real-time PCR of nasopharyngeal swab samples and admitted to the Atatürk University Pulmonary Diseases and the Erzurum City Hospital Infectious Diseases department between March 24 and April 15, and 20 asymptomatic healthcare workers who had negative real-time PCR results during routine COVID-19 screening in our hospital. RESULTS: Patients who developed macrophage activation syndrome had significantly higher IL-6 and SP-D levels at the time of admission and on day 5 of treatment compared to the other patients (IL-6: p = 0.001 for both; SP-D: p = 0.02, p = 0.04). Patients who developed acute respiratory distress syndrome had significantly higher IL-6 and SP-D levels at both time points compared to those who did not (p = 0.001 for all). Both parameters at the time of admission were also significantly higher among nonsurvivors compared to survivors (IL-6: p = 0.001, SP-D: p = 0.03). CONCLUSION: In addition to IL-6, which has an important role in predicting course and planning treatment in COVID-19, SP-D may be a novel pneumoprotein that can be used in the clinical course, follow-up, and possibly in future treatments.


Subject(s)
Betacoronavirus/isolation & purification , Coronavirus Infections , Interleukin-6/blood , Pandemics , Pneumonia, Viral , Pulmonary Surfactant-Associated Protein D/blood , Clinical Laboratory Techniques/methods , Coronavirus Infections/blood , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Female , Hospitalization/statistics & numerical data , Humans , Male , Middle Aged , Pneumonia, Viral/blood , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , Predictive Value of Tests , Prognosis , Risk Factors , Turkey/epidemiology
12.
BMJ ; 370: m3339, 2020 09 09.
Article in English | MEDLINE | ID: covidwho-751530

ABSTRACT

OBJECTIVE: To develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19). DESIGN: Prospective observational cohort study. SETTING: International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study (performed by the ISARIC Coronavirus Clinical Characterisation Consortium-ISARIC-4C) in 260 hospitals across England, Scotland, and Wales. Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited after model development between 21 May and 29 June 2020. PARTICIPANTS: Adults (age ≥18 years) admitted to hospital with covid-19 at least four weeks before final data extraction. MAIN OUTCOME MEASURE: In-hospital mortality. RESULTS: 35 463 patients were included in the derivation dataset (mortality rate 32.2%) and 22 361 in the validation dataset (mortality rate 30.1%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea level, and C reactive protein (score range 0-21 points). The 4C Score showed high discrimination for mortality (derivation cohort: area under the receiver operating characteristic curve 0.79, 95% confidence interval 0.78 to 0.79; validation cohort: 0.77, 0.76 to 0.77) with excellent calibration (validation: calibration-in-the-large=0, slope=1.0). Patients with a score of at least 15 (n=4158, 19%) had a 62% mortality (positive predictive value 62%) compared with 1% mortality for those with a score of 3 or less (n=1650, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (area under the receiver operating characteristic curve range 0.61-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). CONCLUSIONS: An easy-to-use risk stratification score has been developed and validated based on commonly available parameters at hospital presentation. The 4C Mortality Score outperformed existing scores, showed utility to directly inform clinical decision making, and can be used to stratify patients admitted to hospital with covid-19 into different management groups. The score should be further validated to determine its applicability in other populations. STUDY REGISTRATION: ISRCTN66726260.


Subject(s)
Betacoronavirus , Coronavirus Infections/diagnosis , Coronavirus Infections/mortality , Hospitalization , Pneumonia, Viral/diagnosis , Pneumonia, Viral/mortality , Aged , Aged, 80 and over , Clinical Protocols , Cohort Studies , Female , Hospital Mortality , Humans , Male , Middle Aged , Pandemics , Predictive Value of Tests , ROC Curve , Risk Assessment , Survival Rate , United Kingdom
13.
J Nippon Med Sch ; 87(4): 240-242, 2020.
Article in English | MEDLINE | ID: covidwho-751077

ABSTRACT

OBJECTIVE: Little is known about COVID-19 patients who have not traveled to infected areas or had direct contact with infected persons. This report describes the clinical features of 28 such patients with confirmed COVID-19 infection. METHODS: Data on clinical characteristics during hospitalization were collected. RESULTS: Epidemiological exposures were investigated among patients reporting no travel to infected areas or direct contact with a case-patient. Patients presented with various symptoms, increased levels of inflammatory markers, and consolidation or ground-glass opacification on computed tomography scans. CONCLUSIONS: The present report contributes critical information on the clinical presentation of COVID-19 patients without typical epidemiological exposures.


Subject(s)
Betacoronavirus/pathogenicity , Clinical Laboratory Techniques , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Adult , Aged , China/epidemiology , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Coronavirus Infections/virology , Female , Hospitalization , Host Microbial Interactions , Humans , Inflammation Mediators/blood , Male , Middle Aged , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Pneumonia, Viral/virology , Predictive Value of Tests , Risk Factors , Tomography, X-Ray Computed
14.
Drug Discov Ther ; 14(4): 153-160, 2020.
Article in English | MEDLINE | ID: covidwho-745655

ABSTRACT

The COVID-19 infection has been a matter of urgency to tackle around the world today, there exist 200 countries around the world and 54 countries in Africa that the COVID-19 infection cases have been confirmed. This situation prompted us to look into the challenges African laboratories are facing in the diagnosis of novel COVID-19 infection. A limited supply of essential laboratory equipment and test kits are some of the challenges faced in combatting the novel virus in Africa. Also, there is inadequate skilled personnel, which might pose a significant danger in case there is a surge in COVID-19 infection cases. The choice of diagnostic method in Africa is limited as there are only two available diagnostic methods being used out of the six methods used globally, thereby reducing the opportunity of supplementary diagnosis, which will further lead to inappropriate diagnosis and affect the accuracy of diagnostic reports. Furthermore, challenges like inadequate power supply, the method used in sample collection, storage and transportation of specimens are also significant as they also pose their respective implication. From the observations, there is an urgent need for more investment into the laboratories for proper, timely, and accurate diagnosis of COVID-19.


Subject(s)
Betacoronavirus/isolation & purification , Clinical Laboratory Techniques , Coronavirus Infections/diagnosis , Health Services Accessibility/organization & administration , Health Services Needs and Demand/organization & administration , Pneumonia, Viral/diagnosis , Virology/organization & administration , Betacoronavirus/pathogenicity , Budgets , Clinical Laboratory Techniques/economics , Coronavirus Infections/economics , Coronavirus Infections/epidemiology , Coronavirus Infections/virology , Health Care Costs , Health Services Accessibility/economics , Health Services Needs and Demand/economics , Humans , Nigeria/epidemiology , Pandemics/economics , Pneumonia, Viral/economics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , Predictive Value of Tests , Reproducibility of Results , Viral Load , Virology/economics , Workflow
16.
Eur Respir J ; 56(2)2020 08.
Article in English | MEDLINE | ID: covidwho-744960

ABSTRACT

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has globally strained medical resources and caused significant mortality. OBJECTIVE: To develop and validate a machine-learning model based on clinical features for severity risk assessment and triage for COVID-19 patients at hospital admission. METHOD: 725 patients were used to train and validate the model. This included a retrospective cohort from Wuhan, China of 299 hospitalised COVID-19 patients from 23 December 2019 to 13 February 2020, and five cohorts with 426 patients from eight centres in China, Italy and Belgium from 20 February 2020 to 21 March 2020. The main outcome was the onset of severe or critical illness during hospitalisation. Model performances were quantified using the area under the receiver operating characteristic curve (AUC) and metrics derived from the confusion matrix. RESULTS: In the retrospective cohort, the median age was 50 years and 137 (45.8%) were male. In the five test cohorts, the median age was 62 years and 236 (55.4%) were male. The model was prospectively validated on five cohorts yielding AUCs ranging from 0.84 to 0.93, with accuracies ranging from 74.4% to 87.5%, sensitivities ranging from 75.0% to 96.9%, and specificities ranging from 55.0% to 88.0%, most of which performed better than the pneumonia severity index. The cut-off values of the low-, medium- and high-risk probabilities were 0.21 and 0.80. The online calculators can be found at www.covid19risk.ai. CONCLUSION: The machine-learning model, nomogram and online calculator might be useful to access the onset of severe and critical illness among COVID-19 patients and triage at hospital admission.


Subject(s)
Coronavirus Infections/diagnosis , Hospital Mortality/trends , Machine Learning , Pneumonia, Viral/diagnosis , Triage/methods , Adult , Age Factors , Aged , Area Under Curve , Belgium , China , Clinical Laboratory Techniques , Cohort Studies , Coronavirus Infections/epidemiology , Decision Support Systems, Clinical , Female , Hospitalization/statistics & numerical data , Humans , Internationality , Italy , Male , Middle Aged , Pandemics/statistics & numerical data , Pneumonia, Viral/epidemiology , Predictive Value of Tests , ROC Curve , Reproducibility of Results , Retrospective Studies , Risk Assessment , Severity of Illness Index , Sex Factors , Survival Analysis
17.
ESMO Open ; 5(5)2020 09.
Article in English | MEDLINE | ID: covidwho-744875

ABSTRACT

BACKGROUND: During the COVID-19 outbreak, healthcare professionals (HCP) are at the frontline of clinical management and at increased risk for infection. The SARS-CoV-2 seroprevalence of oncological HCP and their patients has significant implications for oncological care. METHODS: HCP and patients with cancer at the Division of Oncology, Medical University of Vienna were included between 21 March and 4 June and tested for total antibodies against SARS-CoV-2 employing the Roche Elecsys Anti-SARS-CoV-2 immunoassay. Reactive samples were confirmed or disproved by the Abbott SARS-CoV-2 IgG test. Additionally, a structured questionnaire regarding basic demographic parameters, travel history and COVID-19-associated symptoms had to be completed by HCP. RESULTS: 146 subjects (62 HCP and 84 patients with cancer) were enrolled. In the oncological HCP cohort, 20 (32.3%) subjects were medical oncologists, 28 (45.2%) nurses at our ward and 14 (22.6%) fulfil other functions such as study coordinators. In the patient cohort, most individuals are on active anticancer treatment (96.4%). 26% of the HCP and 6% of the patients had symptoms potentially associated with COVID-19 since the end of February 2020. However, only in 2 (3.2%) HCP and in 3 (3.6%) patients, anti-SARS-Cov-2 total antibodies were detected. The second assay for anti-SARS-Cov-2 IgG antibodies confirmed the positive result in all HCP and in 2 (2.4%) patients, suggesting an initial assay's unspecific reaction in one case. In individuals with a confirmed test result, an active COVID-19 infection was documented by a positive SARS-CoV-2 RNA PCR test. CONCLUSION: Specific anti-SARS-CoV-2 antibodies were found solely in persons after a documented SARS-CoV-2 viral infection, thus supporting the test methods' high sensitivity and specificity. The low prevalence of anti-SARS-CoV-2 antibodies in our cohorts indicates a lack of immunity against SARS-CoV-2. It highlights the need for continued strict safety measures to prevent uncontrolled viral spread among oncological HCPs and patients with cancer.


Subject(s)
Antibodies, Viral/blood , Betacoronavirus/immunology , Clinical Laboratory Techniques , Coronavirus Infections/diagnosis , Medical Staff, Hospital , Oncology Service, Hospital , Patients , Pneumonia, Viral/diagnosis , Serologic Tests , Tertiary Care Centers , Adolescent , Adult , Aged , Aged, 80 and over , Austria/epidemiology , Betacoronavirus/pathogenicity , Biomarkers/blood , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Coronavirus Infections/virology , Female , Host-Pathogen Interactions , Humans , Male , Middle Aged , Nursing Staff, Hospital , Oncologists , Oncology Nursing , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Pneumonia, Viral/virology , Predictive Value of Tests , Prospective Studies , Reproducibility of Results , Retrospective Studies , Seroepidemiologic Studies , Young Adult
18.
J Comput Assist Tomogr ; 44(5): 627-632, 2020.
Article in English | MEDLINE | ID: covidwho-744641

ABSTRACT

OBJECTIVE: To determine the predictive computed tomography (CT) and clinical features for diagnosis of COVID-19 pneumonia. METHODS: The CT and clinical data including were analyzed using univariate analysis and multinomial logistic regression, followed by receiver operating characteristic curve analysis. RESULTS: The factors including size of ground grass opacity (GGO), GGO with reticular and/or interlobular septal thickening, vascular enlargement, "tree-in-bud" opacity, centrilobular nodules, and stuffy or runny nose were associated with the 2 groups of viral pneumonia, as determined by univariate analysis (P < 0.05). Only GGO with reticular and/or interlobular septal thickening, centrilobular nodules, and stuffy or runny nose remained independent risk factors in multinomial logistic regression analysis. Receiver operating characteristic curve analysis showed that the area under curve of the obtained logistic regression model was 0.893. CONCLUSION: Computed tomography and clinical features including GGO with reticular and/or interlobular septal thickening, absence of centrilobular nodules, and absence of stuffy or runny nose are potential patients with COVID-19 pneumonia.


Subject(s)
Betacoronavirus , Clinical Laboratory Techniques/methods , Coronavirus Infections/diagnosis , Lung/diagnostic imaging , Pneumonia, Viral/diagnosis , Tomography, X-Ray Computed/methods , Adult , Diagnosis, Differential , Female , Humans , Male , Middle Aged , Pandemics , Predictive Value of Tests , Reproducibility of Results , Retrospective Studies
19.
Int J Med Sci ; 17(14): 2225-2231, 2020.
Article in English | MEDLINE | ID: covidwho-742970

ABSTRACT

Background: Lactate dehydrogenase (LDH) has been proved to be a prognostic factor for the severity and poor outcomes of coronavirus disease 2019 (COVID-19). In most studies, patients with various levels of COVID-19 severity were pooled and analyzed which may prevent accurate evaluation of the relationship between LDH and disease progression and in-hospital death. In this study, we aimed to evaluate the association of LDH with in-hospital mortality in severe and critically ill patients with COVID-19. Methods: This single-center retrospective study enrolled 119 patients. Survival curves were plotted using Kaplan-Meier method and compared by log-rank test. Multivariate Cox regression models were used to determine the independent risk factors for in-hospital mortality. Receiver-operator curves (ROCs) were constructed to evaluate the predictive accuracy of LDH and other prognostic biomarkers. Results: Compared to the survival group, LDH levels in the dead group were significantly higher [559.5 (172, 7575) U/L vs 228 (117, 490) U/L, (P < 0.001)]. In Multivariate Cox regression, it remained an independent risk factor for in-hospital mortality (Hazard ratio 5.985, 95.0%CI: 1.498-23.905; P=0.011). A cutoff value of 353.5 U/L predicted the in-hospital mortality with a sensitivity of 94.4% and a specificity of 89.2% respectively. Conclusion: LDH is a favorable prognostic biomarker with high accuracy for predicting in-hospital mortality in severe and critically ill patients with COVID-19. This may direct physicians worldwide to effectively prioritize resources for patients at high risk of death and to implement more aggressive treatments at an earlier phase to save patients' lives.


Subject(s)
Coronavirus Infections/mortality , Critical Illness/mortality , Hospital Mortality , L-Lactate Dehydrogenase/blood , Pneumonia, Viral/mortality , Severity of Illness Index , Adult , Aged , Aged, 80 and over , Betacoronavirus/isolation & purification , Betacoronavirus/pathogenicity , Biomarkers/blood , China/epidemiology , Coronavirus Infections/blood , Coronavirus Infections/diagnosis , Coronavirus Infections/drug therapy , Coronavirus Infections/therapy , Female , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/blood , Pneumonia, Viral/diagnosis , Pneumonia, Viral/therapy , Predictive Value of Tests , Prognosis , ROC Curve , Retrospective Studies , Risk Factors
20.
Monaldi Arch Chest Dis ; 90(3)2020 Sep 02.
Article in English | MEDLINE | ID: covidwho-740518

ABSTRACT

Lung Ultrasound (LUS) is regarded to be potentially useful to diagnose lung injury in older adults living in nursing homes with suspected COVID-19 pneumonia. We aimed at evaluating presence lung injury among senior nursing home residents by LUS performed with portable wireless scanner echography. The study population consisted of 150 residents with a mean age of 88 years (85% female) residing in 12 nursing homes in Northern Italy. Subjects had to have a history of recent onset of symptoms compatible with COVID-19 pneumonia or have been exposed to the contagion of patients carrying the disease. COVID-19 testing was performed with SARS-CoV-2 nasal-pharyngeal (NP) swabs. Positive subjects to LUS scanning were considered those with non-coascelent B-lines in >3 zones, coalescent B-lines in >3 zones and with iperdensed patchy non-consolidated lungs. Sixty-three percent had positive NP testing and 65% had LUS signs of pulmonary injury. LUS had a sensitivity of 79% in predicting positive NP testing. Sixteen percent of residents tested negative for SARSCoV-2 carried the signs of COVID-19 lung injury at LUS. There were 92 patients (61%) with current or recent symptoms.Positivity to LUS scanning was reported in 73% of residents with symptoms, while it was 53% in those without (P=0.016). A positive NP testing was observed in 66% of residents with symptoms and in 57% of those without (P=0.27). We conclude that assessment of LUS by portable wireless scanner echography can be profitability utilized to diagnose lung injury among senior nursing home residents with or without symptoms compatible with COVID-19 pneumonia.


Subject(s)
Coronavirus Infections , Lung Injury/diagnostic imaging , Pandemics , Pneumonia, Viral/diagnosis , Point-of-Care Testing , Ultrasonography , Aged, 80 and over , Betacoronavirus/isolation & purification , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Coronavirus Infections/physiopathology , Female , Homes for the Aged/statistics & numerical data , Humans , Italy/epidemiology , Male , Nursing Homes/statistics & numerical data , Pneumonia, Viral/epidemiology , Pneumonia, Viral/etiology , Pneumonia, Viral/physiopathology , Predictive Value of Tests , Sensitivity and Specificity , Ultrasonography/instrumentation , Ultrasonography/methods , Wireless Technology
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