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  • 1
    In: BMC Health Services Research, Springer Science and Business Media LLC, Vol. 16, No. S3 ( 2016-7)
    Type of Medium: Online Resource
    ISSN: 1472-6963
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2016
    detail.hit.zdb_id: 2050434-2
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  • 2
    In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 9, No. Supplement_2 ( 2022-12-15)
    Abstract: How to start optimal antibiotic therapy before the results of cultures and antimicrobial susceptibility tests are available? Here, we use the law of total probability to present a probabilistic approach based on antibiograms of bacterial isolates from healthcare and community-acquired infections to optimizing empiric antibiotic therapy. Methods Data on the microbiology of healthcare and community-acquired infections were analyzed from hospitals in Belo Horizonte, a three million inhabitants city from Brazil. Healthcare infections were defined by the National Healthcare Safety Network (NHSN)/CDC protocols. Only data obtained from infections with positive culture, both hospital and community, were considered. The success rate of an antibiotic (ATB) regimen, considering just one drug individually (monotherapy), was calculated by Law of Total Probability (Fig 1). In this sense, if a microorganism has not been tested for a specific antimicrobial, then, by definition, it was considered an antibiotic failure. For a regimen with more than one antibiotic, if the microorganism is sensitive to one of them, then it was considered a success of the scheme. For calculating the success probability of two or three antimicrobials A, B, and C, simultaneously (Fig 2), i.e., P(A and B) or P(A and B and C), the sensitivity to an antimicrobial was considered independent of sensitivity to any other. Then, P(A and B) = P(A) * P(B), and P(A and B and C) = P(A)*P(B) *P(C). Figure 1– Law of total probability: success rate of an antibiotic considering just one drug individually (monotherapy).Figure 2– Probability of the union of two events, success of ATB A or ATB B, and union of three events, success of ATB A or ATB B or ATB C. Results Microbiologic data from hospital acquired infections (HAI) and community-acquired infections (CAI) are analyzed once a year. Empiric antibiotic therapy to HAI were proposed for urinary tract infections (UTI), bloodstream infections (BSI), and pneumonia (Figures 2 and 3). Empiric antibiotic therapy to community-acquired infections were developed for UTI, pneumonia, gastrointestinal system infection, bone and joint infection, and skin and soft tissue infection. Figure 3– Success rate of each antibiotic alone, considering just one drug individually (monotherapy): analysis of hospital-acquired pneumonia.Figure 4– Success rate of one, two or three antibiotics: analysis of hospital-acquired pneumonia.Fig 5- Probability of the antimicrobial regimen being successful in treating an infection according to the length of stay at hospital. Conclusion We presented here a probabilistic approach to empiric antibiotic therapy. The next step is to validate all proposed regimens, that can be used to improve the success likelihood of empiric antibiotic decision making. Disclosures All Authors: No reported disclosures.
    Type of Medium: Online Resource
    ISSN: 2328-8957
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 2757767-3
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  • 3
    In: Infection Control & Hospital Epidemiology, Cambridge University Press (CUP), Vol. 41, No. S1 ( 2020-10), p. s221-s222
    Abstract: Background: The ventriculoperitoneal shunt is the main procedure used for to treat communicating hydrocephalus. Surgical site infection associated with the shunt device is the most common complication and a cause of morbidity and mortality of related to the treatment. We sought to answer 3 questions: (1) What is the risk of meningitis after ventricular shunt operations? (2) What are the risk factors for meningitis? (3) What are the main microorganisms causing meningitis? Methods: We conducted a retrospective cohort study of patients undergoing ventricular shunt operations between July 2015 and June 2018 from 12 hospitals at Belo Horizonte, Brazil. Data were gathered by standardized methods defined by the CDC NHSN. Our sample size was 926, and we evaluated 26 preoperative and operative variables by univariate and multivariate analysis. Our outcome variables of interest were meningitis and hospital death. Results: In total, 71 cases of meningitis were diagnosed (risk, 7.7%; 95% CI, 6.1%–9.6%). The mortality rate among patients without infection was 10%, whereas hospital mortality of infected patients was 13% ( P = .544). The 3 main risk factors for meningitis after ventricular shunt were identified by logistic regression model: age 〈 2 years (OR, 3.20; P 〈 .001), preoperative hospital stay 〉 4 days (OR, 2.02; P = .007) and 〉 1 surgical procedure, in addition to ventricular shunt (OR, 3.23; P = .043). Almost 1 of 3 of all patients was 〈 2 years old (290, 31%). Also, 430 patients had 〉 4 preoperative days (46%). Patients aged ≥2 years who underwent surgery 4 days after hospital admission had an increased risk of meningitis, from 4% to 6% ( P = .140). If a patient 〈 2 years old underwent surgery 4 or more days after hospital admission, the risk of meningitis increased from 9% to 18% ( P = .026; Fig. 1). We built a risk index using the number of main risk factors based on a logistic regression model (0, 1, 2 or 3; Fig. 2). Conclusions: We identified 2 intrinsic risk factors for meningitis after ventricular shunt, age 〈 2 years and multiple surgical procedures, and 1 extrinsic risk factor, the preoperative length of hospital stay. Funding: None Disclosures: None
    Type of Medium: Online Resource
    ISSN: 0899-823X , 1559-6834
    Language: English
    Publisher: Cambridge University Press (CUP)
    Publication Date: 2020
    detail.hit.zdb_id: 2106319-9
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  • 4
    In: Revista de Epidemiologia e Controle de Infecção, APESC - Associacao Pro-Ensino em Santa Cruz do Sul, Vol. 11, No. 3 ( 2021-07-05)
    Abstract: Justificativa e Objetivos: Após o início da pandemia de COVID-19, meios mais efetivos e eficazes foram necessários para desinfetar materiais hospitalares. Este trabalho visa avaliar a eficácia in vitro e a efetividade econômica de luz ultravioleta tipo C (UVC) para desinfecção de materiais usados em pacientes com COVID-19. Métodos: Quatro placas bipartidas de Cled foram inoculadas com suspensões de 10.000 ufc/mL de cepas de Escherichia coli e Staphylococcus aureus, expostas a duas lâmpadas de 18W, colocadas dentro de um fluxo laminar e incubadas para avaliações quantitativas de crescimento. O equipamento germicida foi construído: uma “caixa UVC” com duas lâmpadas de 18W para materiais da farmácia e um “armário UVC” com duas lâmpadas 60W para exposição de capotes. A efetividade econômica foi avaliada comparando os custos de estoque, com quarentena de materiais versus custos de uso da UVC. Resultados: A inativação microbiológica nas placas se iniciou a partir de 4 minutos, com eficácia próxima a 100% aos 8 minutos. A “caixa de UVC” reduziu o tempo para liberação do material de 9 dias para imediato, gerando uma economia de aproximadamente R$ 68.400,00, e o “armário de UVC” alterou o uso de capotes para 0,7/paciente, comparado ao uso habitual de 1,5, gerando uma economia de 3.000 reais/mês. O custo de instalação e manutenção foi de R$ 1.500,00. Conclusão:Foi comprovada a eficácia e efetividade dos sistemas UVC, além da economia promovida por sua instalação.
    Type of Medium: Online Resource
    ISSN: 2238-3360
    Language: Unknown
    Publisher: APESC - Associacao Pro-Ensino em Santa Cruz do Sul
    Publication Date: 2021
    detail.hit.zdb_id: 2734894-5
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  • 5
    In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 7, No. Supplement_1 ( 2020-12-31), p. S479-S481
    Abstract: Surgical site infections (SSIs) can account for 25% of all nosocomial infections and contribute significantly to the economic burden resulting from infectious complications. To control this problem, an active surveillance program with the feedback of SSI rates to surgeons can reduce subsequent rates by up to 40%, since 19% to 65% of these infections are diagnosed after patient discharge. However, there is no standard method for conducting surveillance outside the hospital and the best methodology is still unknown. For many hospitals, SSI surveillance has three main objectives: to feedback surgeons with their SSI rates; to evaluate SSI rates over time, identifying outbreaks; and to compare data among different institutions. This study aims to answer the crucial question: is surveillance after patient discharge worthwhile? Methods Prospective surveillance according to the National Healthcare Safety Network (NHSN) protocol of the Centers for Disease Control and Prevention (CDC) at Hospital Lifecenter, Hospital Madre Teresa and Hospital Universitário Ciências Médicas, tertiary care centers, which serve the metropolitan area of Belo Horizonte, Brazil. The data were collected between Jan/2017 and Dec/2019. Results In almost three years of study, the infection rate data were calculated with and without surveillance. The monthly analysis by clinic showed that the inclusion of post-discharge patients in the computed rates increases its value, but not significantly. Of 22.009 patients analyzed, in Lifecenter Hospital, 229(1%) had SSI. This percentage refers to the infection rate with the post-discharge survey, while the rate of surgical infection without vigilance corresponds to 202(0,9%) (Table 1). The surveillance for Madre Teresa, those numbers were: 29.770, 382(1,3%) and 351(1,2%), respectively (Table 2). In Hospital Universitário Ciências Médicas: 20.286, 447 (2,2%) and 215(1,1%) (Table 3). Table 1 - Surgical site infection: data with and without post-discharge surveillance. Hospital Lifecenter (Jan/ 2017 to Jul/2019): month-by-month analysis. Table 2 - Surgical site infection: data with and without post-discharge surveillance. Hospital Madre Teresa (Jan/ 2017 to Dec/2019): month-by-month analysis. Table 3 - Surgical site infection: data with and without post-discharge surveillance. Hospital Universitário Ciências Médicas (Jan/ 2017 to Dec/2019): month-by-month analysis. Conclusion SSI post-discharge surveillance is indicated only for specific procedures. However, once the endemic curve with the infection rate did not change with the inclusion of post-discharge SSI, the study strongly suggests that surveillance after the discharge of the surgical patient is not necessary. Graph 1 - Surgical site infection: rates with and without post-discharge surveillance. Hospital Lifecenter (Jan/2017 to Jul/2019): endemic curve. Graph 2 - Surgical site infection: rates with and without post-discharge surveillance. Hospital Madre Teresa (Jan/2017 to Jul/2019): endemic curve. Graph 3 - Surgical site infection: rate with and without post-discharge surveillance. Hospital Universitário Ciências Médicas (Jan/2017 to Jul/2019): endemic curve. Disclosures All Authors: No reported disclosures
    Type of Medium: Online Resource
    ISSN: 2328-8957
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 2757767-3
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  • 6
    In: Memórias do Instituto Oswaldo Cruz, FapUNIFESP (SciELO), Vol. 116 ( 2021)
    Type of Medium: Online Resource
    ISSN: 1678-8060 , 0074-0276
    Language: English
    Publisher: FapUNIFESP (SciELO)
    Publication Date: 2021
    detail.hit.zdb_id: 2017165-1
    SSG: 12
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  • 7
    In: Clinica Chimica Acta, Elsevier BV, Vol. 523 ( 2021-12), p. 504-512
    Type of Medium: Online Resource
    ISSN: 0009-8981
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
    detail.hit.zdb_id: 1499920-1
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  • 8
    Online Resource
    Online Resource
    Cambridge University Press (CUP) ; 1998
    In:  Infection Control and Hospital Epidemiology Vol. 19, No. 11 ( 1998-11), p. 872-876
    In: Infection Control and Hospital Epidemiology, Cambridge University Press (CUP), Vol. 19, No. 11 ( 1998-11), p. 872-876
    Type of Medium: Online Resource
    ISSN: 0899-823X , 1559-6834
    URL: Issue
    Language: English
    Publisher: Cambridge University Press (CUP)
    Publication Date: 1998
    detail.hit.zdb_id: 2106319-9
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  • 9
    In: Infection Control & Hospital Epidemiology, Cambridge University Press (CUP), Vol. 41, No. S1 ( 2020-10), p. s135-s135
    Abstract: Background: In 5 hospitals located in Belo Horizonte city ( 〉 3,000,000 inhabitants) a focused survey on surgical site infection (SSI) was performed in patients undergoing CABG surgery. We statistically evaluated such incidences to enable study of the prediction power of SSI through pattern recognition algorithms, in this case the multilayer perceptron (MLP) artificial neural networks. Methods: Data were collected between July 2016 and June 2018 on SSI by the hospital infection control committees (CCIHs) of the hospitals involved in the research. We collected all data used in the analysis during their routine SSI surveillance procedures. The information was forwarded to the NOIS (Nosocomial Infection Study) Project, which uses the SACIH (Automated Hospital Infection Control System) software to collect data from a sample of hospitals participating voluntarily in the project. After data collection, 3 procedures were performed: (1) a treatment of the collected database for use of intact samples; (2) a statistical analysis on the profile of the hospitals collected; and (3) an assessment of the predictive power of 5 types of MLP (ie, backpropagation standard, momentum, resilient propagation, weight decay, and quick propagation) for SSI prediction. MLPs were tested with 3, 5, 7, and 10 hidden layer neurons and a database split for the resampling process (65% or 75% for testing and 35% or 25% for validation). They were compared by measuring the AUC (area under the curve; range, 0–1) presented for each of the configurations. Results: From 666 initial data, only 278 were able for analysis. We obtained the following statistics: 9.35% manifested SSIs; length of stay varied from 1 to 119 days, with ~40% staying between 10 and 19 days; 15.1% of the patients died. Regarding the prediction power of SSI, the experiments have a maximum value of 0.713. Conclusions: Despite the considerable loss rate of 〉 50% of the database samples due to the presence of noise, it was possible to have a relevant sampling to evaluate the profile of hospitals in Belo Horizonte. In addition, for the predictive process, although some configurations had results equal to 0.5, others reached 0.713, which indicates that the automated SSI monitoring framework for patients undergoing coronary artery bypass grafting surgery is promising. To optimize data collection and to enable other hospitals to use the SSI prediction tool (available at www.sacihweb.com), a mobile application was developed. Funding: None Disclosures: None
    Type of Medium: Online Resource
    ISSN: 0899-823X , 1559-6834
    Language: English
    Publisher: Cambridge University Press (CUP)
    Publication Date: 2020
    detail.hit.zdb_id: 2106319-9
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  • 10
    In: Infection Control & Hospital Epidemiology, Cambridge University Press (CUP), Vol. 41, No. S1 ( 2020-10), p. s377-s378
    Abstract: Background: Trauma is defined by the NHSN as “blunt or penetrating traumatic injury.” Therefore, if the surgery was performed because of a recent fall, for example, then it is a trauma surgery. Here, we investigated which preoperative and operative parameters are associated with surgical site infection (SSI) after orthopedic trauma surgery. Objective: We aimed to answer 3 main questions: What is the risk of wound infection for patients undergoing trauma surgery? What are the main etiologic agents of SSI after trauma surgery? And what are the risk factors associated with SSI after trauma surgery? Methods: This prospective multicenter cohort study included 2,035 patients undergoing trauma surgery between July 2016 and June 2018 in 4 hospitals in Belo Horizonte, Brazil. Outcome variables were SSI, hospital mortality, and length of hospital stay. The following preoperative and operative parameters were evaluated: age, length of hospital stay before surgery, duration of surgery, number of professionals at surgery, number of hospital admissions, surgical wound classification, American Society of Anesthesiologists (ASA) preoperative assessment score, type of surgery (elective, emergency), general anesthesia (yes, no), trauma surgery (yes, no), and the 3-point prediction Nosocomial Infections Surveillance (NNIS) risk index. Results: The overall estimated SSI risk was 2.8% (95% CI, 2.0%–3.6%). Hospital mortality risk after trauma surgery was 3.4% (95% CI, 2.8%–4.4%). Hospital length of stay parameters in noninfected patients were as follows: mean, 8 days; median, 3 days; SD, 12 days. Hospital length of stay parameters in infected patients were mean, 30 days; median, 23 days; with SD, 31 days. The parameters for hospital stay in infected patients were mean, 10 days; median, 3 days, and SD, 15.9 ( P 〈 .001). Trauma orthopedic surgery lasting 〉 2 hours was associated with approximately twice the risk (RR, 2.2) of developing an SSI compared to ≤2 hours of surgery: 27 of 739 (3.7%) versus 21 of 1,290 (1.6%), respectively, ( P = .005) (Fig. 1). The NNIS risk index predicts the risk of SSI after trauma surgery ( P = .003): 13 of 737 SSIs (1.8%) had an NNIS risk index of 0; 20 of 736 SSIs (2.7%) had an NNIS risk index of 1; 8 of 211 SSIs (3.8%) had an NNIS risk index of 2; and 2 of 11 SSIs (18.2%) had an NNIS risk index of 3 (Fig. 2). Conclusions: We identified intrinsic risk factors for SSI after orthopedic trauma surgery. The identification of the actual SSI incidence after trauma surgery in developing country hospitals and associated risk factors may support actions to minimize the complications caused by SSI. Funding: None Disclosures: None
    Type of Medium: Online Resource
    ISSN: 0899-823X , 1559-6834
    Language: English
    Publisher: Cambridge University Press (CUP)
    Publication Date: 2020
    detail.hit.zdb_id: 2106319-9
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