BackgroundThe Centers for Disease Control and Prevention (CDC) proposed standard definitions for acquired resistance in bacterias. Resistant bacteria were categorized as multidrug-resistant (MDR), extensively drug-resistant (XDR) and pandrug-resistant (PDR). This study describes the incidence of Gram-negative MDR, XDR and PDR in 12 private and adult intensive care units (ICU’s) from Belo Horizonte, Minas Gerais, the sixth most populated city in Brazil, with approximately 3 million inhabitants.MethodsData were collected between January/2013 to December/2017 from 12 ICU’s. The hospitals used prospective healthcare-associated infections (HAI) surveillance protocols, in accordance to the CDC. Antimicrobial resistance from six Gram-negatives, causing nosocomial infections, were evaluated: Acinetobacter sp., Klebsiella sp., Proteus sp., Enterobacter sp., Escherichia coli, and Pseudomonas sp.. We computed the three categories of drug-resistance (MDR+XDR+PDR) to define benchmarks for the resistance rate of each Gram-negative evaluated. Benchmarks were defined as the superior limits of 95% confidence interval for the resistance rate.ResultsAfter a 5 year surveillance, 6,242 HAI strains were tested: no pandrug-resistant bacteria (PDR) was found. Acinetobacter sp. was the most resistant Gram-negative: 206 strains from 1,858 were XDR (11%), and 1,638 were MDR (88%). Pseudomonas sp.: 41/1,159 = 3.53% XDR; 180/1,159 = 15.53% MDR. Klebsiella sp.: 2/1,566 = 0,1% XDR; 813/1,566 = 52% MDR. Proteus sp.: 0/507 = 0% XDR; 163/507 = 32% MDR. Enterobacter sp.: 0/471 = 0% XDR; 148/471 = 31% MDR. Escherichia coli: 0/681 = 0% XDR; 157/681 = 23% MDR. Benchmarks for the global resistance rate of each Gram-negative (MDR+XDR+PDR): Acinetobacter sp. = 92%; Klebsiella sp. = 62%; Proteus sp. = 40%; Enterobacter sp. = 48%; Escherichia coli = 33%; Pseudomonas sp. = 30%.ConclusionThis study has calculated the incidence of Gram-negative MDR, XDR and PDR, and found a higher incidence of MDR Acinetobacter sp., with an 88% multiresistance rate. Henceforth, developing countries healthcare institutions must be aware of an increased risk of infection by Acinetobacter sp.. Benchmarks have been defined, and can be used as indicators for healthcare assessment. Disclosures All authors: No reported disclosures.
Background A Ventriculoperitoneal shunt is the main treatment for communicating hydrocephalus. Surgical site infection associated with the shunt device is the most common complication and an expressive cause of morbidity and mortality of the treatment. The objective of our study is to answer three questions: a)What is the risk of meningitis after ventricular shunt operations? b) What are the risk factors for meningitis? c) What are the main microorganisms causing meningitis? Methods A retrospective cohort study assessed meningitis and risk factors in patients undergoing ventricular shunt operations between 2015/Jul and 2018/Jun from 12 hospitals at Belo Horizonte, Brazil. Data were gathered by standardized methods defined by the National Healthcare Safety Network (NHSN)/CDC procedure-associated protocols for routine SSI surveillance. Sample size = 926. 26 variables were evaluated by univariate and multivariate analysis (logistic regression). Results 71 patients were diagnosed with meningitis which represent a risk of 7.7% (C.I.95%= 6.1%; 9.6%). From the 26 variables, three were acknoleged as risk factors: age < two years old (OR = 3.20; p < 0.001), preoperative hospital length of stay > four days (OR = 2.02; p = 0.007) and more than one surgical procedure (OR = 3.23; p = 0.043). Patients two or more years old, who had surgery four days after hospital admission, had increased risk of meningitis from 4% to 6% (p = 0.140). If a patient < two years had surgery four days post hospital admission, the risk is increased from 9% to 18% (p = 0.026). 71 meningitis = > 45 (63%) the etiologic agent identified: Staphylococcus aureus (33%), Staphylococcus epidermidis (22%), Acinetobacter sp (7%), Enterococcus sp (7%), Pseudomonas sp (7%), and other (18%). Hospital length of stay in non-infected patients (days): mean = 21 (sd = 28), median = 9; hospital stay in infected patients: mean = 34 (sd = 37), median = 27 (p=0.025). Mortality rate in patients without infection was 10% while hospital death of infected patients was 13% (p=0.544). Conclusion Two intrinsic risk factors for meningitis post ventricular shunt, age under two years old and multiple surgeries, and one extrinsic risk factor, preoperative length of hospital stay, were identified. Incidence of meningitis post VP shunt decreases with urgent surgical treatment. Disclosures All Authors: No reported disclosures
Background Infection by SARS-CoV-2 can lead to dyspnea, edema, deposition of intra alveolar fibrin, thrombosis and hemorrhages. During the COVID-19. outbreak, several questions were raised about the risks for the pediatric population. Pediatric patients appeared to be relatively safe, with only minor symptoms and a quick recovery. However, there have been reports of a relationship between COVID 19 and a Kawasaki-like inflammatory disease in this population. Kawasaki’s disease (KD) is a rheumatological vasculitis prevalent in childhood characterized mainly by diffuse inflammation of the arteries associated with skin rash, changes in the mucosa and its main complication is coronary aneurysms. Methods A systematic literature review was performed in the PubMED database using the keywords “Kawasaki disease”, “COVID-19” and “Pediatrics”. The selected filters were “Case reports”, “Multicenter study”, “Clinical Study”, “Observational study”, “Human” and “English”. A total of 18 articles were seleted. Results There seems to be a convergence between the literature published so far, pointing to a greater propensity for pediatric patients infected with Sars-Cov-2 to develop KD. The number of patients with KD symptoms seen at a specific center increased from 2 to 17 in 11 days (MOREIRA, 2020). In a sample space of 21 patients diagnosed with KD, 91% had previous contact with SARS-CoV-2 (TOUBIANA, 2020) whereas other studies point to a 30-fold increase in the prevalence of KD since the beginning of 2020 (VERDONI, 2020). There is already an established relationship between DK and HCoV-NH, describing that 4.5% of patients with this infection develop KD. Therefore, it was suggested that infection with another Coronavirus strain could have a similar relationship. Conclusion Despite the relationship described between pediatric patients infected with COVID-19 being more likely to develop KD, further studies are needed to prove a statistical relationship between both condition. Disclosures All Authors: No reported disclosures
BackgroundMeningitis after craniotomy can be devastating. The objective of our study is to answer four questions: (a) what is the risk of meningitis after craniotomy? (b) What are the main microorganisms causing meningitis after craniotomy? (c) What is the impact of meningitis in the hospital length of stay and mortality? (d) What are risk factors for meningitis after craniotomy?MethodsSurveillance data based on NHSN/CDC protocols were collected between 2013 and 2017 from nine hospitals at Belo Horizonte, Brazil. Outcome: meningitis, hospital death and total length of hospital stay. Twenty-three independent variables were analyzed using Epi Info and applying statistical two-tailed test hypothesis with significance level of 5%.ResultsA sample of 4,549 patients submitted to craniotomy was analyzed: risk of meningitis = 1.9% (IC 95% = 1.6%; 2.4%). Mortality rate in patients without infection was 9% rising to 33% in infected patients (P < 0.01). Hospital length of stay in non-infected patients (days): mean = 18, median = 7, std. dev. = 36. Hospital stay in infected patients: mean = 56, median = 37, std. dev. = 63 (P < 0.001). The duration of procedure was the main risk factor for meningitis: 1.5% risk of meningitis in surgery less than or equal to 4 hours vs. 2.5% if the duration of procedure was more than 4 hours (relative risk = 1.7; P = 0.041). From 88 meningitis, in 68 (77%) the etiologic agent was identified: Klebsiella pneumoniae (20%), Staphylococcus aureus (16%), Acinetobacter baumannii (13%), Pseudomonas aeruginosa (9%), Staphylococcus sp. (8%), Acinetobacter sp. (7%), Staphylococcus epidermidis (5%), and other (20%).ConclusionThe study showed how much meningitis is devastating, rising the death risk and length of hospital stay.Disclosures All authors: No reported disclosures.
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.
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Background Surgical site infection (SSI) in bariatric surgery can lead to devastating outcomes such as peritonitis, sepsis, septic shock and organ space infection. The objective of our study is to answer four questions: a) What is the SSI risk after bariatric surgery? b) What are the risk factors for SSI after bariatric surgery? c) What are the main outcomes to SSI in bariatric surgery? d) What are the main bacteria responsible for SSI in bariatric surgery? Methods A retrospective cohort study assessed 8,672 patients undergoing bariatric surgery between 2014/Jan and 2018/Dec from two hospitals at Belo Horizonte, Brazil. Data were gathered by standardized methods defined by the National Healthcare Safety Network (NHSN)/CDC procedure-associated protocols for routine SSI surveillance. Outcome: SSI, hospital death and total length of hospital stay. 20 preoperative and operative variables were evaluated by univariate and multivariate analysis (logistic regression). Results 77 SSI were diagnosed (risk = 0.9% [C.I.95% = 0.7%;1.1%]). Mortality rate in patients, without infection was only 0.03% (3/8,589) while hospital death of infected patients was 4% (3/77; RR = 112; p< 0.001). Hospital length of stay in non-infected patients (days): mean = 2, std.dev.= 0.9; hospital stay in infected patients: mean = 7, std. dev. = 15.6 (p< 0.001). Two main factors associated with SSI after bariatric surgery were identified by logistic regression: duration of procedure (hours), OR = 1.4;p=0.001, and laparoscopy procedure, OR = 0.3;p=0.020. From 77 SSIs, in 28 (36%) we identified 34 etiologic agents. The majority of SSI (59%) was caused by species of Streptococcus (32%), Klebsiella (15%), and Enterobacter (12%). Conclusion SSI is rare after bariatric surgery, however, when it happens, it’s a disaster for the patient. The incidence of SSI can be reduced significantly when laparoscopy procedure is used and the surgeon is able to perform a rapid surgery. Disclosures All Authors: No reported disclosures
Background: Meningitis after craniotomy can cause devastating outcomes. Objectives: Estimate the risk of meningitis after craniotomy (MAC). Find the most prevalent pathogens. Assess the impact of meningitis over length of stay and mortality. Find the main risk factor for MAC. Design and setting: Multicentric, longitudinal and quantitative analysis of data collected between 2013-2017 from nine different hospitals from Minas Gerais, Brazil. Methods: Surveillance data was based on NHSN/CDC protocols. Observed outcomes were meningitis, hospital death and total length of stay. Twentythree variables were analyzed in Epi-Info in a two-tailed statistical test with a significance level of 5%. Results: 4,549 patients were analyzed. Risk of MAC was 1.9% (95%CI=1.6%; 2.4%). The mortality rate in patients without infection was 9%, increasing to 33% in infected patients (P<0.01). Length of hospital stay (HS) in uninfected patients (in days): mean=18, median=7, standard deviation=36. HS in infected patients: mean=56, median=37, standard deviation=63 P<0.001).The duration of the procedure ≤4 hours presented a 1.5% risk of MAC compared to 2.5% versus ≥4 hours (RR=1.7; P=0.041). From 88 MAC cases, pathogen was identified in 68 (77%): K.pneumoniae (20%), S.aureus (16%), A.baumannii (13%), P.aeruginosa (9%), Staphylococcus sp . (8%), Acinetobacter sp. (7%), S.epidermidis (5%) among others (20%).Conclusion: MAC risk was 1.9%. Mortality rate was high compared to literature. Meningitis caused threefold increase on HS. Procedure duration ≥4 hours was the main risk factor, presenting RR of 1.7. The most prevalent etiologic agents were K.pneumoniae and S.aureus. Considering the findings, infectious surveillance is paramount for patient safety.
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