Corpus overview


MeSH Disease

Human Phenotype


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    Personalized Predictive Models for Symptomatic COVID-19 Patients Using Basic Preconditions: Hospitalizations, Mortality, and the Need for an ICU or Ventilator

    Authors: Salomon Wollenstein-Betech; Christos G. Cassandras; Ioannis Ch. Paschalidis

    doi:10.1101/2020.05.03.20089813 Date: 2020-05-08 Source: medRxiv

    Background: The rapid global spread of the virus SARS-CoV-2 has provoked a spike in demand for hospital care. Hospital systems across the world have been over-extended, including in Northern Italy, Ecuador, and New York City, and many other systems face similar challenges. As a result, decisions on how to best allocate very limited medical resources have come to the forefront. Specifically, under consideration are decisions on who to test, who to admit into hospitals, who to treat in an Intensive Care Unit (ICU), and who to support with a ventilator. Given today's ability to gather, share, analyze and process data, personalized predictive models based on demographics and information regarding prior conditions can be used to (1) help decision-makers allocate limited resources, when needed, (2) advise individuals how to better protect themselves given their risk profile, (3) differentiate social distancing guidelines based on risk, and (4) prioritize vaccinations once a vaccine becomes available. Objective: To develop personalized models that predict the following events: (1) hospitalization, (2) mortality, (3) need for ICU, and (4) need for a ventilator. To predict hospitalization, it is assumed that one has access to a patient's basic preconditions, which can be easily gathered without the need to be at a hospital. For the remaining models, different versions developed include different sets of a patient's features, with some including information on how the disease is progressing (e.g., diagnosis of pneumonia HP pneumonia MESHD). Materials and Methods: Data from a publicly available repository, updated daily, containing information from approximately 91,000 patients in Mexico were used. The data for each patient include demographics, prior medical conditions, SARS-CoV-2 test results, hospitalization, mortality and whether a patient has developed pneumonia HP pneumonia MESHD or not. Several classification methods were applied, including robust versions of logistic regression, and support vector machines, as well as random forests and gradient boosted decision trees. Results: Interpretable methods (logistic regression and support vector machines) perform just as well as more complex models in terms of accuracy and detection rates, with the additional benefit of elucidating variables on which the predictions are based. Classification accuracies reached 61%, 76%, 83%, and 84% for predicting hospitalization, mortality, need for ICU and need for a ventilator, respectively. The analysis reveals the most important preconditions for making the predictions. For the four models derived, these are: (1) for hospitalization: age TRANS, gender TRANS, chronic renal insufficiency MESHD renal insufficiency HP, diabetes MESHD, immunosuppression; (2) for mortality: age TRANS, SARS-CoV-2 test status, immunosuppression and pregnancy; (3) for ICU need: development of pneumonia HP pneumonia MESHD (if available), cardiovascular disease MESHD, asthma HP asthma MESHD, and SARS-CoV-2 test status; and (4) for ventilator need: ICU and pneumonia HP pneumonia MESHD (if available), age TRANS, gender TRANS, cardiovascular disease MESHD, obesity HP obesity MESHD, pregnancy, and SARS-CoV-2 test result.

    SARS-COV-2 comorbidity network and outcome in hospitalized patients in Crema, Italy

    Authors: Gianpaolo Benelli; Elisabetta Buscarini; Ciro Canetta; Giuseppe La Piana; Guido Merli; Alessandro Scartabellati; Giovanni Vigano; Roberto Sfogliarini; Giovanni Melilli; Roberto Assandri; Daniele Cazzato; Davide Sebastiano Rossi; Susanna Usai; Guido Caldarelli; Tommaso Gili; Irene Tramacere; Germano Pellegata; Giuseppe Lauria

    doi:10.1101/2020.04.14.20053090 Date: 2020-04-20 Source: medRxiv

    No systematic data on hospitalized SARS-COV-2 patients from Western countries are available. We report onset, course, correlations with comorbidities, and diagnostic accuracy of nasopharyngeal swab in 539 individuals suspected to carry SARS-COV-2 admitted to the hospital of Crema, Italy. All individuals underwent clinical and laboratory exams, SARS-COV-2 reverse transcriptase-polymerase chain reaction on nasopharyngeal swab, and chest X-ray and/or computed tomography (CT). Data on onset, course, comorbidities, number of drugs including angiotensin converting enzyme (ACE) inhibitors and angiotensin-II-receptor antagonists (sartans), follow-up swab, pharmacological treatments, non-invasive respiratory support, ICU admission, and deaths MESHD were recorded. Among 411 SARS-COV-2 patients (66.6% males TRANS) median age TRANS was 70.5 years (range 1-99). Chest CT was performed in 317 (77.2%) and showed interstitial pneumonia MESHD pneumonia HP in 304 (96%). Fatality rate was 17.5% (74% males TRANS), with 6.6% in 60-69 years old, 21.1% in 70-79 years old, 38.8% in 80-89 years old, and 83.3% above 90 years. No death occurred below 60 years. Non-invasive respiratory support rate was 27.2% and ICU admission 6.8%. Older age TRANS, cough HP and dyspnea HP dyspnea MESHD at onset, hypertension HP hypertension MESHD, cardiovascular diseases MESHD, diabetes MESHD, renal insufficiency HP renal insufficiency MESHD, >7 drugs intake and positive X-ray, low lymphocyte count, high C-reactive protein, aspartate aminotransferase and lactate dehydrogenase values, and low PO2 partial pressure with high lactate at arterial blood SERO gas analysis at admission were significantly associated with death MESHD. Use of ACE inhibitors or sartans was not associated with outcomes. Comorbidity network analysis revealed homogenous distribution of deceased and 60-80 aged TRANS SARS-COV-2 patients across diseases. Among 128 swab negative patients at admission (63.3% males TRANS) median age TRANS was 67.7 years (range 1-98). Chest CT was performed in 87 (68%) and showed interstitial pneumonia MESHD pneumonia HP in 76 (87.3%). Follow-up swab turned positive in 13 of 32 patients. Using chest CT at admission as gold standard on the entire study population of 539 patients, nasopharyngeal swab had 80% sensitivity SERO. SARS-CoV-2 caused high mortality among patients older than 60 years and correlated with pre-existing multiorgan impairment. ACE inhibitors and sartans did not influence patients' outcome.

    The epidemiological characteristics of 2019 novel coronavirus diseases MESHD (COVID-19) in Jingmen,Hubei,China

    Authors: Qijun Gao; yingfu hu; zhiguo dai Sr.; Jing wu; Feng Xiao; Jing wang

    doi:10.1101/2020.03.07.20031393 Date: 2020-03-10 Source: medRxiv

    Abstract Background:There is currently a global outbreak of coronavirus disease MESHD 2019 (COVID-19),and its epidemic characteristics in the areas where the outbreak has been successfully controlled are rarely reported. Objective: Describe the epidemic characteristics of COVID-19 in Jingmen,Hubei,introduce the local prevention and control experience,and observe the impact of various prevention and control measures on the number of new cases. Methods: All the COVID-19 patients diagnosed in the municipal districts of Jingmen from January 12 to February 29,2020 were enrolled in this study. We described epidemiological data and observed the impact of control measures on the epidemic. Findings: Of the 219 cases (110 men and 109 women), 88 (40%) had exposure to Wuhan. The median age TRANS was 48 years ( range,2-88 years;IQR,35-60). Thirty-three severe patients with a median age TRANS of 66 years(range,33-82 years,IQR,57-76) were treated in intensive care units; out of these patients, 66.7 %(22) were men and 19 (57.5%) had chronic diseases MESHD, including hypertension HP hypertension MESHD, diabetes MESHD, heart failure MESHD, stroke HP stroke MESHD, and renal insufficiency HP renal insufficiency MESHD. Under the control measures, the number of new patients gradually decreased and nearly disappeared after 18 days. Wearing masks in all kinds of situations prevents most infections MESHD and is one of the most effective prevention and control measures. Interpretation: In conclusion,all people are susceptible to COVID-19, and older males TRANS and those with comorbid conditions are more likely to become severe cases. Even though COVID-19 is highly contagious,control measures have proven to be very effective, particularly wearing masks,which could prevent most infections.

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MeSH Disease
Human Phenotype

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