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    Performance SERO of serum SERO apolipoprotein-A1 as a sentinel of Covid-19

    Authors: Thierry Poynard; Olivier Deckmyn; Marika Rudler; Valentina Peta; Yen Ngo; Mathieu Vautier; Sepideh Akhavan; Vincent Calvez; Clemence Franc; Jean Marie Castille; Fabienne Drane; Mehdi Sakka; Dominique Bonnefont-Rousselot; Jean Marc Lacorte; David Saadoun; Yves Allenbach; Olivier Benveniste; Frederique Gandjbakhch; Julien Mayaux; Olivier Lucidarme; Bruno Fautrel; Vlad Ratziu; Chantal Housset; Dominique Thabut; Patrice Cacoub; Fredrik Nyberg; Jose D Posada; Christian G Reich; Lisa M Schilling; Karishma Shah; Nigham H Shah; Vignesh Subbian; Lin Zhang; Hong Zhu; Patrick Ryan; Daniel Prieto-Alhambra; Kristin Kostka; Talita Duarte-Salles

    doi:10.1101/2020.09.01.20186213 Date: 2020-09-03 Source: medRxiv

    Background Since 1920, a decrease in serum SERO cholesterol has been identified as a marker of severe pneumonia HP pneumonia MESHD. We have assessed the performance SERO of serum SERO apolipoprotein-A1, the main transporter of HDL-cholesterol, to identify the early spread of coronavirus disease MESHD 2019 (Covid-19) in the general population and its diagnostic performance SERO for the Covid-19. Methods We compared the daily mean serum SERO apolipoprotein-A1 during the first 34 weeks of 2020 in a population that is routinely followed for a risk of liver fibrosis MESHD risk in the USA (212,297 sera) and in France (20,652 sera) in relation to a local increase in confirmed cases TRANS, and in comparison to the same period in 2019 (266,976 and 28,452 sera, respectively). We prospectively assessed the sensitivity SERO of this marker in an observational study of 136 consecutive hospitalized cases and retrospectively evaluated its specificity in 7,481 controls representing the general population. Results The mean serum SERO apolipoprotein-A1 levels in the survey populations began decreasing in January 2020, compared to the same period in 2019. This decrease was highly correlated with the daily increase in confirmed Covid-19 cases in the following 34 weeks, both in France and USA, including the June and mid-July recovery periods in France. Apolipoprotein-A1 at the 1.25 g/L cutoff had a sensitivity SERO of 90.6% (95%CI84.2-95.1) and a specificity of 96.1% (95.7-96.6%) for the diagnosis of Covid-19. The area under the characteristics curve was 0.978 (0.957-0.988), and outperformed haptoglobin and liver function tests. The adjusted risk ratio of apolipoprotein-A1 for survival without transfer to intensive care unit was 5.61 (95%CI 1.02-31.0;P=0.04). Conclusion Apolipoprotein-A1 could be a sentinel of the pandemic in existing routine surveillance of the general population. NCT01927133, CER-2020-14.

    A Large-Scale Clinical Validation Study Using nCapp Cloud Plus Terminal by Frontline Doctors for the Rapid Diagnosis of COVID-19 and COVID-19 pneumonia HP pneumonia MESHD in China

    Authors: Dawei Yang; Tao Xu; Xun Wang; Deng Chen; Ziqiang Zhang; Lichuan Zhang; Jie Liu; Kui Xiao; Li Bai; Yong Zhang; Lin Zhao; Lin Tong; Chaomin Wu; Yaoli Wang; Chunling Dong; Maosong Ye; Yu Xu; Zhenju Song; Hong Chen; Jing Li; Jiwei Wang; Fei Tan; Hai Yu; Jian Zhou; Jinming Yu; Chunhua Du; Hongqing Zhao; Yu Shang; Linian Huang; Jianping Zhao; Yang Jin; Charles A. Powell; Yuanlin Song; Chunxue Bai

    doi:10.1101/2020.08.07.20163402 Date: 2020-08-11 Source: medRxiv

    Background The outbreak of coronavirus disease MESHD 2019 (COVID-19) has become a global pandemic acute infectious disease MESHD, especially with the features of possible asymptomatic TRANS carriers TRANS and high contagiousness. It causes acute respiratory distress HP respiratory distress MESHD syndrome and results in a high mortality rate if pneumonia HP is involved. Currently, it is difficult to quickly identify asymptomatic TRANS cases or COVID-19 patients with pneumonia HP pneumonia MESHD due to limited access to reverse transcription-polymerase chain reaction (RT-PCR) nucleic acid tests and CT scans, which facilitates the spread of the disease TRANS at the community level, and contributes to the overwhelming of medical resources in intensive care units. Goal This study aimed to develop a scientific and rigorous clinical diagnostic tool for the rapid prediction of COVID-19 cases based on a COVID-19 clinical case database in China, and to assist global frontline doctors to efficiently and precisely diagnose asymptomatic TRANS COVID-19 patients and cases who had a false-negative RT-PCR test result. Methods With online consent, and the approval of the ethics committee of Zhongshan Hospital Fudan Unversity (approval number B2020-032R) to ensure that patient privacy is protected, clinical information has been uploaded in real-time through the New Coronavirus Intelligent Auto-diagnostic Assistant Application of cloud plus terminal (nCapp) by doctors from different cities (Wuhan, Shanghai, Harbin, Dalian, Wuxi, Qingdao, Rizhao, and Bengbu) during the COVID-19 outbreak in China. By quality control and data anonymization on the platform, a total of 3,249 cases from COVID-19 high-risk groups were collected. These patients had SARS-CoV-2 RT-PCR test results and chest CT scans, both of which were used as the gold standard for the diagnosis of COVID-19 and COVID-19 pneumonia HP pneumonia MESHD. In particular, the dataset included 137 indeterminate cases who initially did not have RT-PCR tests and subsequently had positive RT-PCR results, 62 suspected cases who initially had false-negative RT-PCR test results and subsequently had positive RT-PCR results, and 122 asymptomatic TRANS cases who had positive RT-PCR test results, amongst whom 31 cases were diagnosed. We also integrated the function of a survey in nCapp to collect user feedback from frontline doctors. Findings We applied the statistical method of a multi-factor regression model to the training dataset (1,624 cases) and developed a prediction model for COVID-19 with 9 clinical indicators that are fast and accessible: 'Residing or visiting history in epidemic regions', 'Exposure history to COVID-19 patient', 'Dry cough HP', ' Fatigue HP', 'Breathlessness', 'No body temperature decrease after antibiotic treatment', 'Fingertip blood SERO oxygen saturation<=93%', ' Lymphopenia HP Lymphopenia MESHD', and 'C-reactive protein (CRP) increased'. The area under the receiver operating characteristic (ROC) curve (AUC) for the model was 0.88 (95% CI: 0.86, 0.89) in the training dataset and 0.84 (95% CI: 0.82, 0.86) in the validation dataset (1,625 cases). To ensure the sensitivity SERO of the model, we used a cutoff value of 0.09. The sensitivity SERO and specificity of the model were 98.0% (95% CI: 96.9%, 99.1%) and 17.3% (95% CI: 15.0%, 19.6%), respectively, in the training dataset, and 96.5% (95% CI: 95.1%, 98.0%) and 18.8% (95% CI: 16.4%, 21.2%), respectively, in the validation dataset. In the subset of the 137 indeterminate cases who initially did not have RT-PCR tests and subsequently had positive RT-PCR results, the model predicted 132 cases, accounting for 96.4% (95% CI: 91.7%, 98.8%) of the cases. In the subset of the 62 suspected cases who initially had false-negative RT-PCR test results and subsequently had positive RT-PCR results, the model predicted 59 cases, accounting for 95.2% (95% CI: 86.5%, 99.0%) of the cases. Considering the specificity of the model, we used a cutoff value of 0.32. The sensitivity SERO and specificity of the model were 83.5% (95% CI: 80.5%, 86.4%) and 83.2% (95% CI: 80.9%, 85.5%), respectively, in the training dataset, and 79.6% (95% CI: 76.4%, 82.8%) and 81.3% (95% CI: 78.9%, 83.7%), respectively, in the validation dataset, which is very close to the published AI model. The results of the online survey 'Questionnaire Star' showed that 90.9% of nCapp users in WeChat mini programs were 'satisfied' or 'very satisfied' with the tool. The WeChat mini program received a significantly higher satisfaction rate than other platforms, especially for 'availability and sharing convenience of the App' and 'fast speed of log-in and data entry'. Discussion With the assistance of nCapp, a mobile-based diagnostic tool developed from a large database that we collected from COVID-19 high-risk groups in China, frontline doctors can rapidly identify asymptomatic TRANS patients and avoid misdiagnoses of cases with false-negative RT-PCR results. These patients require timely isolation or close medical supervision. By applying the model, medical resources can be allocated more reasonably, and missed diagnoses can be reduced. In addition, further education and interaction among medical professionals can improve the diagnostic efficiency for COVID-19, thus avoiding the transmission TRANS of the disease from asymptomatic TRANS patients at the community level.

    Ocular findings and retinal involvement in COVID-19 pneumonia HP pneumonia MESHD patients: A cross-sectional study in an Italian referral centre

    Authors: Maria Pia Pirraglia; Giancarlo Ceccarelli; Alberto Cerini; Giacomo Visioli; Gabriella d'Ettorre; Claudio Maria Mastroianni; Francesco Pugliese; Alessandro Lambiase; Magda Gharbiya

    doi:10.21203/rs.3.rs-48240/v1 Date: 2020-07-23 Source: ResearchSquare

    Background: changes in immune and coagulation systems and possible viral spread through blood SERO-brain barrier have been described in SARS-CoV-2 infection MESHD. In this study, we evaluate the possible retinal involvement and ocular findings in severe COVID-19 pneumonia HP pneumonia MESHD patients.  Methods: a cross sectional study was conducted on 46 patients affected by severe COVID-19 who were hospitalized in one Intensive Care Unit (ICU) and in two Infectious Diseases wards, including a bedside eye screening, corneal sensitivity SERO assessment and retinography. Results: a total of 43 SARS-CoV-2 positive pneumonia MESHD pneumonia HP patients affected with COVID-19 pneumonia HP pneumonia MESHD were included, 25 males TRANS and 18 females TRANS, with a median age TRANS of 70 [IQR 59-78]. Except for one patient with unilateral posterior chorioretinitis HP of opportunistic origin, of whom aqueous tap was negative for SARS-CoV-2, no further retinal manifestation related to COVID-19 infection MESHD was found in our cohort. We found 3 patients (7%) with bilateral conjunctivitis MESHD conjunctivitis HP in whom PCR analysis on conjunctival swab provided negative results for SARS-CoV-2. No alterations of corneal sensitivity SERO were found.Conclusion: we demonstrated the absence of retinal involvement in SARS-CoV-2 pneumonia MESHD pneumonia HP patients. Ophthalmologic evaluation in COVID-19, particularly in patients hospitalized in an ICU setting, may be useful to reveal systemic co-infections MESHD infections by opportunistic HP pathogens. 

    Clinical Severity and CT Features of the COVID-19 Pneumonia HP: Focus on CT Score and Laboratory Parameters

    Authors: Jianghui Duan; Kunsong Su; Hongliang Sun; Yanyan Xu; Liangying Liu

    doi:10.21203/rs.3.rs-45453/v1 Date: 2020-07-18 Source: ResearchSquare

    Background: Although CT characteristics of Coronavirus Disease MESHD 2019 (COVID-19) pneumonia HP pneumonia MESHD between patients with mild and severe forms of the disease have already been reported in the literature, there was little attention to the correlation of imaging features and laboratory testing. We aimed to compare the laboratory and chest CT imaging features in patients with COVID-19 pneumonia HP pneumonia MESHD between non-severe cases and severe cases, and to analyze the correlation of CT score and laboratory testing.Methods: This study consecutively included 54 patients with COVID-19 pneumonia HP pneumonia MESHD (26 males TRANS and 28 females TRANS, 26 to 92 years of age TRANS, 43 cases with non-severe and 11 cases with severe group). Clinical, laboratory and image data were collected between two subgroups. A CT score system was used to evaluate the extent of disease. Correlation between the CT score and laboratory data were estimated. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance SERO of CT score and laboratory tests.Results: Compared with non-severe patients, severe patients had showed increased white blood SERO cell count, neutrophil count, neutrophil percentage, the neutrophil-to-lymphocyte ratio (NLR) and decreased lymphocyte percentage (all p < 0.05). Architectural distortion, pleural effusion HP pleural effusion MESHD, air bronchogram and consolidation-dominant pattern were more common in the severe group (all p < 0.05). CT score of the severe group was higher than the non-severe group (p < 0.001). For distribution characters of the lesions, diffuse pattern in the transverse distribution was more often seen in the severe group (p < 0.001). CT score was positively correlated with the white blood SERO cell counts, neutrophil counts, the percent of neutrophil, NLR, alanine aminotransferase, lactate dehydrogenase and C-reactive protein, and was inversely related to the lymphocyte, the percent of lymphocyte. ROC analysis showed that when the optimal threshold of CT score was 13, the area under the curve was the largest, which was 0.855, and the sensitivity SERO and specificity were 100% and 60% respectively for the diagnosis of the severe patients.Conclusion: CT score showed significant correlations with laboratory inflammatory markers, suggesting that chest CT and laboratory examination maybe provide a better reference for clinicians to judge the severity of diseases.

    Assessment of a Diagnostic Strategy Based on Chest Computed Tomography in Patients Hospitalized for COVID-19 Pneumonia HP: an observational study

    Authors: Marine Thieux; Anne Charlotte Kalenderian; Aurelie Chabrol; Laurent Gendt; Emma Giraudier; Herve Lelievre; Samir Lounis; Yves Mataix; Emeline Moderni; Laetitia Paradisi; Guillaume Ranchon; Carlos El Khoury

    doi:10.1101/2020.06.29.20140129 Date: 2020-06-30 Source: medRxiv

    Objectives: To assess the relevance of a diagnostic strategy for COVID-19 based on chest computed tomography (CT) in patients with hospitalization criteria. Setting: Observational study with retrospective analysis in a French emergency department (ED). Participants and intervention: From March 3 to April 2, 2020, 385 adult TRANS patients presenting to the ED for suspected COVID-19 underwent an evaluation that included history, physical examination, blood SERO tests, real-time reverse transcription-polymerase chain reaction (RT-PCR) and chest CT. When the time-interval between chest CT and RT-PCR assays was longer than 7 days, patients were excluded from the study. Only patients with hospitalization criteria were included. Diagnosis accuracy was assessed using the sensitivity SERO and specificity of RT-PCR. Outcomes: Sensitivity SERO and specificity of RT-PCR, chest CT (also accompanied by lymphopenia HP lymphopenia MESHD) were measured and were also analyzed by subgroups of age TRANS and sex. Results: Among 377 included subjects, RT-PCR was positive in 36%, while chest CT was compatible with a COVID-19 diagnosis in 59%. In the population with positive RT-PCR, there were more men (55% vs 37%, p=0.015), a higher frequency of reticular and, or, interlobular septal thickening (53% vs 31%, p=0.02) as well as a higher frequency of bilateral lesion distribution (98% vs 86%, p=0.01) compared to the population with negative RT-PCR. The proportion of lymphopenia HP lymphopenia MESHD was higher in men vs women (47% vs 39%, p=0.03) and varies between patients >80 versus 50-80 and p<0.001). Using CT as reference, RT-PCR obtained a sensitivity SERO of 61%, specificity of 93%. There was a significant difference between CT and RT-PCR diagnosis performance SERO (p<0.001). When CT was accompanied by lymphopenia HP lymphopenia MESHD, sensitivity SERO and specificity of RT-PCR were respectively 71% and 94%. CT abnormalities and lymphopenia HP lymphopenia MESHD provided diagnosis in 29% of patients with negative PCR. Conclusions: Chest CT had a superior yield than RT-PCR in COVID-19 hospitalized patients, especially when accompanied by lymphopenia HP lymphopenia MESHD.

    Accuracy of routine biomarkers and blood SERO leucocytes count to assist diagnosis of COVID-19-associated pneumonia HP pneumonia MESHD in adult TRANS patients visiting the emergency department

    Authors: Cécile Maincent; Frédéric Berthier; Ryan Lukas Farhad; Cristel Fissore-Magdelein; Claire Claire Dittlot; Nathalie Beau; Jérémy Lépine; Marjorie Lorillou; Matthieu Dietz; Mathieu Liberatore; Atul Pathak; Marc Marc Faraggi; Sylvie Chaillou-Orpitz; Olivia Keita-Perse; Gilles Chironi; Christophe Perrin; Yann-Erick Claessens

    doi:10.21203/rs.3.rs-34817/v1 Date: 2020-06-12 Source: ResearchSquare

    Background To investigate whether routine biomarkers and blood SERO leucocytes count could assist diagnosis of COVID-19-associated pneumonia HP pneumonia MESHD in adult TRANS patients visiting the emergency department (ED). Methods This monocentre retrospective study enrolled 254 patients with nasopharyngeal RT-PCR for SARS-COV-2, routine biomarkers (D-dimers, fibrinogen, C-reactive protein, procalcitonin, NTpro-BNP, cTnT-hs) and blood SERO cell counts. Sensitivity SERO and specificity were evaluated. An adjudication committee classified diagnostic probability as certain, probable, unlikely, and excluded, based on all available data, then distributed in 2 categories: high (certain and probable) and low probability (unlikely and excluded). Results Between 25 th of February and 15 th of April, 2020, 254 of 388 patients could be analyzed. The adjudication committee classified 46 patients as definite, 18 as probable, 64 as unlikely, and 126 as excluded, corresponding to 64 high and 190 low probability. High and low probability patients differed for fibrinogen (P<0.0005) and white blood SERO cell counts, notably leucocytes (P=0.0015), neutrophilic (P=0.0036), lymphocytes (P=0.0057), eosinophilic (P=0.027), and basophilic (P<0.001) counts. In a multivariate analysis, basophilic count < 25/µL (OR 3.048 [95%CI; 1.34-6.919]), neutrophilic count < 4000 /µL (OR 5.525 [95%CI; 2.20-13.855], and fibrinogen > 3g/L (OR 6355 [95%CI; 2.01-20.079] were independently associated with the diagnosis. Negative predictive values SERO were 0.98 and 0.93 combining fibrinogen ( < 3g/L) and eosinophilic count ( < 80/µL), and fibrinogen and basophilic count ( < 25/µL), respectively. Conclusion Changes in fibrinogen and white blood SERO cells, notably basophilic count, showed interesting performance SERO for the diagnosis COVID-19 associated pneumonia HP. Combining fibrinogen with either eosinophilic or basophilic count was helpful to exclude the diagnosis.

    Whole blood SERO immunophenotyping uncovers immature neutrophil-to-VD2 T-cell ratio as an early prognostic marker for severe COVID-19

    Authors: Guillaume Carissimo; Weili Xu; Immanuel Kwok; Mohammad Yazid Abdad; Yi Hao Chan; Siew Wai Fong; Kia Joo Puan; Cheryl Yi Pin Lee; Nicholas Kim-Wah Yeo; Siti Naqiah Amrun; Rhonda Sin-Ling Chee; Wilson How; Stephrene Chan; Eugene Bingwen Fan; Anand Andiappan; Bernett Lee; Olaf Rotzschke; Barnaby Edward Young; Yee-Sin Leo; David C Lye; Laurent Renia; Lai Guan Ng; Anis Larbi; Lisa FP Ng

    doi:10.1101/2020.06.11.147389 Date: 2020-06-12 Source: bioRxiv

    SARS-CoV-2 is the novel coronavirus responsible for the current COVID-19 pandemic. Severe complications are observed only in a small proportion of infected MESHD patients but the cellular mechanisms underlying this progression are still unknown. Comprehensive flow cytometry of whole blood SERO samples from 54 COVID-19 patients revealed a dramatic increase in the number of immature neutrophils. This increase strongly correlated with disease severity and was associated with elevated IL-6 and IP-10 levels, two key players in the cytokine storm. The most pronounced decrease in cell counts was observed for CD8 T-cells and VD2 {gamma}{delta} T-cells, which both exhibited increased differentiation and activation. ROC analysis revealed that the count ratio of immature neutrophils to CD8 or VD2 T-cells predicts pneumonia HP onset (0.9071) as well as hypoxia MESHD onset (0.8908) with high sensitivity SERO and specificity. It would thus be a useful prognostic marker for preventive patient management and improved healthcare resource management.

    Diagnostic classification of coronavirus disease MESHD 2019 (COVID-19) and other pneumonias HP pneumonias MESHD using radiomics features in CT chest images

    Authors: Ning Yang; Faming Liu; Chunlong Li; Wenqing Xiao; Shuangcong Xie; Shuyi Yuan; Wei Zuo; Xiaofen Ma; Guihua Jiang

    doi:10.21203/rs.3.rs-34648/v1 Date: 2020-06-11 Source: ResearchSquare

    We propose a classification method using the radiomics features of CT chest images to identify patients with coronavirus disease MESHD 2019 (COVID-19) and other pneumonias HP pneumonias MESHD. The chest CT images of two groups of participants (90 COVID-19 patients and 90 other pneumonias HP pneumonias MESHD patients) were collected, and the two groups of data were manually drawn to outline the region of interest (ROI) of pneumonias HP pneumonias MESHD. The radiomics method was used to extract textural features and histogram features of the ROI and obtain a radiomics features vector from each sample. Finally, using the radiomics features as an input, a support vector machine (SVM) model was constructed to classify patients with COVID-19 and patients with other pneumonias HP pneumonias MESHD. This model used 20 rounds of 10-fold cross-validation for training and testing. In the COVID-19 patients, correlation analysis (multiple comparison correction—Bonferroni correction, p<0.05/7) was also conducted to determine whether the textural and histogram features were correlated with the laboratory test index of blood SERO, i.e., blood SERO oxygen, white blood SERO cell, lymphocytes, neutrophils, C-reactive protein, hypersensitive C-reactive protein, and erythrocyte sedimentation rate. The results showed that the proposed method had a classification accuracy as high as 88.33%, sensitivity SERO of 83.56%, specificity of 93.11%, and an area under the curve of 0.947. This proved that the radiomics features were highly distinguishable, and this SVM model can effectively identify and diagnose patients with COVID-19 and other pneumonias HP pneumonias MESHD. The correlation analysis results showed that some texture features were positively correlated with WBC, NE, and CRP and also negatively related to SPO2H and NE.

    Machine learning in predicting respiratory failure HP respiratory failure MESHD in patients with COVID-19 pneumonia HP pneumonia MESHD - challenges, strengths, and opportunities in a global health emergency

    Authors: Davide Ferrari; Jovana Milic; Roberto Tonelli; Francesco Ghinelli; Marianna Meschiari; Sara Volpi; Matteo Faltoni; Giacomo Franceschi; Vittorio Iadisernia; Dina Yaacoub; Giacomo Ciusa; Erica Bacca; Carlotta Rogati; Marco Tutone; Giulia Burastero; Alessandro Raimondi; Marianna Menozzi; Erica Franceschini; Gianluca Cuomo; Luca Corradi; Gabriella Orlando; Antonella Santoro; Margherita Di Gaetano; Cinzia Puzzolante; Federica Carli; Andrea Bedini; Riccardo Fantini; Luca Tabbì; Ivana Castaniere; Stefano Busani; Enrico Clini; Massimo Girardis; Mario Sarti; Andrea Cossarizza; Cristina Mussini; Federica Mandreoli; Paolo Missier; Giovanni Guaraldi

    doi:10.1101/2020.05.30.20107888 Date: 2020-06-02 Source: medRxiv

    Background Machine learning can assist clinicians in forecasting patients with COVID-19 who develop respiratory failure HP respiratory failure MESHD requiring mechanical ventilation. This analysis aimed to determine a 48 hours prediction of moderate to severe respiratory failure HP respiratory failure MESHD, as assessed with PaO2/FiO2 < 150 mmHg, in hospitalized patients with COVID-19 pneumonia HP pneumonia MESHD. Methods This was an observational study that comprised all consecutive adult TRANS patients with COVID-19 pneumonia HP pneumonia MESHD admitted to the Infectious Diseases Clinic of the University Hospital of Modena, Italy from 21 February to 6 April 2020. COVID-19 was confirmed with PCR positive nasopharyngeal swabs while the presence of pneumonia HP pneumonia MESHD was radiologically confirmed. Patients received standard of care according to national guidelines for clinical management of SARS-CoV-2 infection MESHD. The patients' full medical history, demographic and epidemiological features, clinical data, complete blood SERO count, coagulation, inflammatory and biochemical markers were routinely collected and aggregated in a clinically-oriented logical framework in order to build different datasets. The dataset was used to train a learning framework relying on Microsoft LightGBM and leveraging a hybrid approach, where clinical expertise is applied alongside a data-driven analysis. Shapley Additive exPlanations (SHAP) values were used to quantify the positive or negative impact of each variable included in the model on the predicted outcome. The study outcome was the onset of moderate to severe respiratory failure HP respiratory failure MESHD defined as PaO2/FiO2 ratio < 150 mmHg ([≥] 13.3 kPa) in at least one of two consecutive arterial blood SERO gas analyses in the following 48 hours. Results A total of 198 patients contributed to generate 1068 valuable observations which allowed to build 3 prediction models based respectively on 31-variables signs and symptoms, 39-variables laboratory biomarkers and 91-variables as a composition of the two. A fourth boosted mixed model which included 20 variables was selected from the model 3, achieved the best predictive performance SERO (AUC=0.84). Its clinical performance SERO was applied in a narrative case report as an example. Conclusion This study developed a machine learning algorithm, with a 84% prediction accuracy, which is potentially able to assist clinicians in decision making process with therapeutic implications.

    An increased pretreatment neutrophil-to-lymphocyte ratio predicts severe novel coronavirus-infected pneumonia MESHD pneumonia HP

    Authors: Xiaoyue Wang; Desheng Jiang; Huang Huang; Xiaofeng Chen; Chunlei Zhou; Dongsheng Jiao; Ping Fan; Qian Cui; Hui Liao; Binbin Shi

    doi:10.21203/rs.3.rs-31796/v1 Date: 2020-05-26 Source: ResearchSquare

    Objective The aim of this study was to identify early warning signs for severe novel coronavirus-infected pneumonia MESHD pneumonia HP (COVID-19).Methods We retrospectively analyzed the clinical data of 90 patients with COVID-19 at the Guanggu District of Hubei Women and Children TRANS Medical and Healthcare Center comprising 60 mild cases and 30 severe cases. The demographic data, underlying diseases, clinical manifestations and laboratory blood SERO test results were compared between the two groups. Logistic regression analysis was performed to identify the independent risk factors that predicted severe COVID-19. The receiver-operating characteristic (ROC) curve of independent risk factors was calculated, and the area under the curve (AUC) was used to evaluate the efficiency of the prediction of severe COVID-19.Results The patients with mild and severe COVID-19 showed significant differences in terms of cancer MESHD incidence, age TRANS, pretreatment neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP) and the serum SERO albumin (ALB) level (P<0.05). The severity of COVID-19 was correlated positively with the comorbidity of cancer MESHD, age TRANS, NLR, and CRP but was negatively correlated with the ALB level (P<0.05). Multivariate logistic regression analysis showed that the NLR and ALB level were independent risk factors for severe COVID-19 (OR=1.319, 95% CI: 1.043-1.669, P=0.021; OR=0.739, 95% CI: 0.616-0.886, P=0.001), with AUCs of 0.851 and 0.128, respectively. An NLR of 4.939 corresponded to the maximum joint sensitivity SERO and specificity according to the ROC curve (0.700 and 0.917, respectively).Conclusion An increased NLR can serve as an early warning sign of severe COVID-19.

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