ABSTRACT
In intensive care units (ICUs), infection rates range from 18 to 54%, which is five to ten times higher than those observed in other hospital units, with a mortality rate of 9% to 60%. In recent decades, the susceptibility pattern has changed and Gram-Negative Bacteria (GNB) have become a threat due to their high frequency of multidrug resistance associated with a scarcity of therapeutic options. However, the drugs Ceftolozane/Tazobactam (C/T) and Ceftazidime/Avibactam (C/A) are demonstrating good clinical and microbiological response in the treatment of severe nosocomial infections. Therefore, this study aims to evaluate the clinical outcome of patients with severe infections caused by Multidrug-Resistant (MDR) GNB treated with C/T and C/A. Our study evaluates a total of 131 patients who received treatment with C/T and C/A due to infections caused by MDR GNB within the period from 2018 to 2021. The main infections were urinary tract (46,6%) and respiratory (26,7%) infections. Pseudomonas aeruginosa was the prevailing agent in the sample evaluation (34.3%), followed by Klebsiella pneumoniae (30,1%). About 54,9% of patients showed a favorable response, with culture negativation in 66,4% of the samples, with no discrepancy in negativations when comparing ages: 67,7% in young and 66% in elderly patients. Among the patients, 62,6% received monotherapy with C/T and C/A with a better response observed with monotherapy compared to combination therapy (58,6% vs 41,4%). The overall mortality rate was 45%, with MDR GNB infections responsible for 33,9% of these deaths, and the others (66,1%) due to factors such as oncological, hematological, and degenerative neurological diseases. In regards to hematological aspect, 35,1% of patients showed changes, with 28,2% of them presenting anemia, 4,5% thrombocytopenia, and 2,5% thrombocytosis. Concerning the use of invasive devices, higher mortality was observed in patients on mechanical ventilation (52%). In this manner, it was possible to observe that therapy with C/T and C/A yielded a favorable clinical outcome in patients with severe infections caused by MDR GNB in the study. These drugs also demonstrated good tolerability regardless of age or the presence of preexisting comorbidities and were deemed safe when assessing adverse effects. Our data also demonstrate the importance of determining the mechanism of resistance to carbapenems so that these drugs can be used more effectively and rationally.
Subject(s)
Anti-Bacterial Agents , Azabicyclo Compounds , Ceftazidime , Humans , Aged , Ceftazidime/therapeutic use , Ceftazidime/pharmacology , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/therapeutic use , Cephalosporins/pharmacology , Cephalosporins/therapeutic use , Tazobactam/therapeutic use , Tazobactam/pharmacology , Drug Resistance, Multiple, Bacterial , Gram-Negative Bacteria , Intensive Care Units , Microbial Sensitivity Tests , Pseudomonas aeruginosaABSTRACT
Abstract Objectives: train a Random Forest (RF) classifier to estimate death risk in elderly people (over 60 years old) diagnosed with COVID-19 in Pernambuco. A "feature" of this classifier, called feature importance, was used to identify the attributes (main risk factors) related to the outcome (cure or death) through gaining information. Methods: data from confirmed cases of COVID-19 was obtained between February 13 and June 19, 2020, in Pernambuco, Brazil. The K-fold Cross Validation algorithm (K=10) assessed RF performance and the importance of clinical features. Results: the RF algorithm correctly classified 78.33% of the elderly people, with AUC of 0.839. Advanced age was the factor representing the highest risk of death. The main comorbidity and symptom were cardiovascular disease and oxygen saturation ≤ 95%, respectively. Conclusion: this study applied the RF classifier to predict risk of death and identified the main clinical features related to this outcome in elderly people with COVID-19 in the state of Pernambuco.
Resumo Objetivos: treinar um classificador do tipo Random Forest (RF) para estimar o risco de óbito em idosos (com mais de 60 anos) diagnosticados com COVID-19 em Pernambuco. Uma "feature" deste classificador, chamada feature_importance, foi usada para identificar os atributos (principais fatores de risco) relacionados com o desfecho final (cura ou óbito) através do ganho de informação. Métodos: dados dos casos confirmados de COVID-19foram obtidos entre os dias 13 de fevereiro e 19 de junho de 2020, em Pernambuco, Brasil. O algoritmo K-fold Cross Validation, com K=10, foi usado para avaliar tanto o desempenho do RF quanto a importância das características clínicas. Resultados: o algoritmo RF classificou corretamente 78,33% dos idosos, com AUC de 0,839. A idade avançada é o fator que representa maior risco de evolução para óbito. Além disso, a principal comorbidade e sintoma também identificados, foram, respectivamente, doença cardiovascular e saturação de oxigênio ≤95%. Conclusão: este trabalho se dedicou à aplicação do classificador RF para previsão de óbito e identificou as principais características clínicas relacionadas com este desfecho em idosos com COVID-19 no estado de Pernambuco.
