LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 5 of total 5

Search options

  1. Article ; Online: Antimicrobial consumption and drug utilization patterns among COVID-19 and non-COVID-19 patients.

    Antunes, Bianca B P / Silva, Amanda A B / Nunes, Patricia H C / Martin-Loeches, Ignacio / Kurtz, Pedro / Hamacher, Silvio / Bozza, Fernando A

    The Journal of antimicrobial chemotherapy

    2023  Volume 78, Issue 3, Page(s) 840–849

    Abstract: Objectives: To understand differences in antimicrobial use between COVID-19 and non-COVID-19 patients. To compare two metrics commonly used for antimicrobial use: Defined Daily Dose (DDD) and Days of Therapy (DOT). To analyse the order in which ... ...

    Abstract Objectives: To understand differences in antimicrobial use between COVID-19 and non-COVID-19 patients. To compare two metrics commonly used for antimicrobial use: Defined Daily Dose (DDD) and Days of Therapy (DOT). To analyse the order in which antimicrobials were prescribed to COVID-19 patients using process mining techniques.
    Methods: We analysed data regarding all ICU admissions from 1 January 2018 to 14 September 2020, in 17 Brazilian hospitals. Our main outcome was the antimicrobial use estimated by the DDD and DOT (Days of Therapy). We compared clinical characteristics and antimicrobial consumption between COVID-19 and non-COVID-19 patients. We used process mining to evaluate the order in which the antimicrobial schemes were prescribed to each COVID-19 patient.
    Results: We analysed 68 405 patients admitted before the pandemic, 12 319 non-COVID-19 patients and 3240 COVID-19 patients. Comparing those admitted during the pandemic, the COVID-19 patients required advanced respiratory support more often (42% versus 12%). They also had longer ICU length of stay (6 versus 3 days), higher ICU mortality (18% versus 5.4%) and greater use of antimicrobials (70% versus 39%). Most of the COVID-19 treatments started with penicillins with ß-lactamase inhibitors (30%), third-generation cephalosporins (22%), or macrolides in combination with penicillins (19%).
    Conclusions: Antimicrobial prescription increased in Brazilian ICUs during the COVID-19 pandemic, especially during the first months of the epidemic. We identified greater use of broad-spectrum antimicrobials by COVID-19 patients. Overall, the DDD metric overestimated antimicrobial use compared with the DOT metric.
    MeSH term(s) Humans ; Pandemics ; COVID-19 ; Anti-Bacterial Agents/therapeutic use ; Anti-Infective Agents/therapeutic use ; Drug Utilization ; Penicillins
    Chemical Substances Anti-Bacterial Agents ; Anti-Infective Agents ; Penicillins
    Language English
    Publishing date 2023-02-06
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 191709-2
    ISSN 1460-2091 ; 0305-7453
    ISSN (online) 1460-2091
    ISSN 0305-7453
    DOI 10.1093/jac/dkad025
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    In stock of ZB MED Cologne/Königswinter

    Zs.A 1197: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)
    Zs.MO 124: Show issues

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  2. Article ; Online: Physiological and socioeconomic characteristics predict COVID-19 mortality and resource utilization in Brazil.

    Wollenstein-Betech, Salomón / Silva, Amanda A B / Fleck, Julia L / Cassandras, Christos G / Paschalidis, Ioannis Ch

    PloS one

    2020  Volume 15, Issue 10, Page(s) e0240346

    Abstract: Background: Given the severity and scope of the current COVID-19 pandemic, it is critical to determine predictive features of COVID-19 mortality and medical resource usage to effectively inform health, risk-based physical distancing, and work ... ...

    Abstract Background: Given the severity and scope of the current COVID-19 pandemic, it is critical to determine predictive features of COVID-19 mortality and medical resource usage to effectively inform health, risk-based physical distancing, and work accommodation policies. Non-clinical sociodemographic features are important explanatory variables of COVID-19 outcomes, revealing existing disparities in large health care systems.
    Methods and findings: We use nation-wide multicenter data of COVID-19 patients in Brazil to predict mortality and ventilator usage. The dataset contains hospitalized patients who tested positive for COVID-19 and had either recovered or were deceased between March 1 and June 30, 2020. A total of 113,214 patients with 50,387 deceased, were included. Both interpretable (sparse versions of Logistic Regression and Support Vector Machines) and state-of-the-art non-interpretable (Gradient Boosted Decision Trees and Random Forest) classification methods are employed. Death from COVID-19 was strongly associated with demographics, socioeconomic factors, and comorbidities. Variables highly predictive of mortality included geographic location of the hospital (OR = 2.2 for Northeast region, OR = 2.1 for North region); renal (OR = 2.0) and liver (OR = 1.7) chronic disease; immunosuppression (OR = 1.7); obesity (OR = 1.7); neurological (OR = 1.6), cardiovascular (OR = 1.5), and hematologic (OR = 1.2) disease; diabetes (OR = 1.4); chronic pneumopathy (OR = 1.4); immunosuppression (OR = 1.3); respiratory symptoms, ranging from respiratory discomfort (OR = 1.4) and dyspnea (OR = 1.3) to oxygen saturation less than 95% (OR = 1.7); hospitalization in a public hospital (OR = 1.2); and self-reported patient illiteracy (OR = 1.1). Validation accuracies (AUC) for predicting mortality and ventilation need reach 79% and 70%, respectively, when using only pre-admission variables. Models that use post-admission disease progression information reach accuracies (AUC) of 86% and 87% for predicting mortality and ventilation use, respectively.
    Conclusions: The results highlight the predictive power of socioeconomic information in assessing COVID-19 mortality and medical resource allocation, and shed light on existing disparities in the Brazilian health care system during the COVID-19 pandemic.
    MeSH term(s) Brazil ; COVID-19 ; Comorbidity ; Coronavirus Infections/epidemiology ; Coronavirus Infections/mortality ; Demography/statistics & numerical data ; Facilities and Services Utilization/statistics & numerical data ; Healthcare Disparities/statistics & numerical data ; Humans ; Models, Statistical ; Pandemics ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/mortality ; Socioeconomic Factors
    Keywords covid19
    Language English
    Publishing date 2020-10-14
    Publishing country United States
    Document type Journal Article ; Multicenter Study ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0240346
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  3. Article ; Online: Vaccine effectiveness of ChAdOx1 nCoV-19 against COVID-19 in a socially vulnerable community in Rio de Janeiro, Brazil: a test-negative design study.

    Ranzani, Otavio T / Silva, Amanda A B / Peres, Igor T / Antunes, Bianca B P / Gonzaga-da-Silva, Thiago W / Soranz, Daniel R / Cerbino-Neto, José / Hamacher, Silvio / Bozza, Fernando A

    Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases

    2022  Volume 28, Issue 5, Page(s) 736.e1–736.e4

    Abstract: Objectives: To estimate vaccine effectiveness after the first and second dose of ChAdOx1 nCoV-19 against symptomatic COVID-19 and infection in a socially vulnerable community in Brazil when Gamma and Delta were the predominant variants circulating.: ... ...

    Abstract Objectives: To estimate vaccine effectiveness after the first and second dose of ChAdOx1 nCoV-19 against symptomatic COVID-19 and infection in a socially vulnerable community in Brazil when Gamma and Delta were the predominant variants circulating.
    Methods: We conducted a test-negative study in the community Complexo da Maré, the largest group of slums (n = 16) in Rio de Janeiro, Brazil, from January 17, 2021 to November 27, 2021. We selected RT-qPCR positive and negative tests from a broad community testing program. The primary outcome was symptomatic COVID-19 (positive RT-qPCR test with at least one symptom) and the secondary outcome was infection (any positive RT-qPCR test). Vaccine effectiveness was estimated as 1 - OR, which was obtained from adjusted logistic regression models.
    Results: We included 10 077 RT-qPCR tests (6,394, 64% from symptomatic and 3,683, 36% from asymptomatic individuals). The mean age was 40 (SD: 14) years, and the median time between vaccination and RT-qPCR testing among vaccinated was 41 (25-75 percentile: 21-62) days for the first dose and 36 (25-75 percentile: 17-59) days for the second dose. Adjusted vaccine effectiveness against symptomatic COVID-19 was 31.6% (95% CI, 12.0-46.8) 21 days after the first dose and 65.1% (95% CI, 40.9-79.4) 14 days after the second dose. Adjusted vaccine effectiveness against COVID-19 infection was 31.0% (95% CI, 12.7-45.5) 21 days after the first dose and 59.0% (95% CI, 33.1-74.8) 14 days after the second dose.
    Discussion: ChAdOx1 nCoV-19 was effective in reducing symptomatic COVID-19 in a socially vulnerable community in Brazil when Gamma and Delta were the predominant variants circulating.
    MeSH term(s) Adult ; BNT162 Vaccine ; Brazil/epidemiology ; COVID-19/diagnosis ; COVID-19/epidemiology ; COVID-19/prevention & control ; COVID-19 Vaccines ; ChAdOx1 nCoV-19 ; Humans ; SARS-CoV-2/genetics ; Vaccine Efficacy
    Chemical Substances COVID-19 Vaccines ; ChAdOx1 nCoV-19 (B5S3K2V0G8) ; BNT162 Vaccine (N38TVC63NU)
    Language English
    Publishing date 2022-02-09
    Publishing country England
    Document type Journal Article
    ZDB-ID 1328418-6
    ISSN 1469-0691 ; 1470-9465 ; 1198-743X
    ISSN (online) 1469-0691
    ISSN 1470-9465 ; 1198-743X
    DOI 10.1016/j.cmi.2022.01.032
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    In stock of ZB MED Cologne/Königswinter

    Zs.A 4541: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)
    Zs.MO 284: Show issues

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  4. Article: Physiological and socioeconomic characteristics predict COVID-19 mortality and resource utilization in Brazil

    Wollenstein-Betech, Salomón / Silva, Amanda A B / Fleck, Julia L / Cassandras, Christos G / Paschalidis, Ioannis Ch

    PLoS One

    Abstract: BACKGROUND: Given the severity and scope of the current COVID-19 pandemic, it is critical to determine predictive features of COVID-19 mortality and medical resource usage to effectively inform health, risk-based physical distancing, and work ... ...

    Abstract BACKGROUND: Given the severity and scope of the current COVID-19 pandemic, it is critical to determine predictive features of COVID-19 mortality and medical resource usage to effectively inform health, risk-based physical distancing, and work accommodation policies. Non-clinical sociodemographic features are important explanatory variables of COVID-19 outcomes, revealing existing disparities in large health care systems. METHODS AND FINDINGS: We use nation-wide multicenter data of COVID-19 patients in Brazil to predict mortality and ventilator usage. The dataset contains hospitalized patients who tested positive for COVID-19 and had either recovered or were deceased between March 1 and June 30, 2020. A total of 113,214 patients with 50,387 deceased, were included. Both interpretable (sparse versions of Logistic Regression and Support Vector Machines) and state-of-the-art non-interpretable (Gradient Boosted Decision Trees and Random Forest) classification methods are employed. Death from COVID-19 was strongly associated with demographics, socioeconomic factors, and comorbidities. Variables highly predictive of mortality included geographic location of the hospital (OR = 2.2 for Northeast region, OR = 2.1 for North region); renal (OR = 2.0) and liver (OR = 1.7) chronic disease; immunosuppression (OR = 1.7); obesity (OR = 1.7); neurological (OR = 1.6), cardiovascular (OR = 1.5), and hematologic (OR = 1.2) disease; diabetes (OR = 1.4); chronic pneumopathy (OR = 1.4); immunosuppression (OR = 1.3); respiratory symptoms, ranging from respiratory discomfort (OR = 1.4) and dyspnea (OR = 1.3) to oxygen saturation less than 95% (OR = 1.7); hospitalization in a public hospital (OR = 1.2); and self-reported patient illiteracy (OR = 1.1). Validation accuracies (AUC) for predicting mortality and ventilation need reach 79% and 70%, respectively, when using only pre-admission variables. Models that use post-admission disease progression information reach accuracies (AUC) of 86% and 87% for predicting mortality and ventilation use, respectively. CONCLUSIONS: The results highlight the predictive power of socioeconomic information in assessing COVID-19 mortality and medical resource allocation, and shed light on existing disparities in the Brazilian health care system during the COVID-19 pandemic.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #868675
    Database COVID19

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  5. Article ; Online: One-dose ChAdOx1 nCoV-19 Vaccine Effectiveness Against Symptomatic COVID-19 in a vulnerable community in Rio de Janeiro, Brazil: test-negative design study

    Ranzani, Otavio T / Silva, Amanda A. B. / Peres, Igor T / Antunes, Bianca B. P. / Gonzaga-da-Silva, Thiago W / Soranz, Daniel R / Cerbino-Neto, Jose / Hamacher, Silvio / Bozza, Fernando A

    medRxiv

    Abstract: We conducted a test-negative study design at the community "Complexo da Maré", the largest group of favelas in Rio de Janeiro, Brazil, when Gamma and Delta were the predominant variants circulating. We estimated 42.4% (95% CI, 24.6, 56.0) protection ... ...

    Abstract We conducted a test-negative study design at the community "Complexo da Maré", the largest group of favelas in Rio de Janeiro, Brazil, when Gamma and Delta were the predominant variants circulating. We estimated 42.4% (95% CI, 24.6, 56.0) protection against symptomatic COVID-19 after 21 days of one dose of ChAdOx1.
    Keywords covid19
    Language English
    Publishing date 2021-10-20
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2021.10.16.21265095
    Database COVID19

    Full text online

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

To top