Distributed lags time series analysis versus linear correlation analysis (Pearson's r) in identifying the relationship between antipseudomonal antibiotic consumption and the susceptibility of Pseudomonas aeruginosa isolates in a single Intensive Care Unit of a tertiary hospital

2011 ◽  
Vol 37 (5) ◽  
pp. 467-471 ◽  
Author(s):  
Viktorija Erdeljić ◽  
Igor Francetić ◽  
Zrinka Bošnjak ◽  
Ana Budimir ◽  
Smilja Kalenić ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Time Series ◽  
Pseudomonas Aeruginosa ◽  
Intensive Care ◽  
Correlation Analysis ◽  
Linear Correlation ◽  
Antibiotic Consumption ◽  
Tertiary Hospital ◽  
Linear Correlation Analysis ◽  
The Relationship

scholarly journals Antimicrobial Resistance Profile of MDR & Non-MDR Meropenem-Resistant Pseudomonas aeruginosa Isolates of Patients in Intensive Care Unit of Tertiary Hospital

2021 ◽  
Vol 9 (3) ◽  
pp. 152
Author(s):  
Imaculata Sonia Vidaryo Lameng ◽  
Ni Nyoman Sri Budayanti ◽  
Luh Inta Prilandari ◽  
I Ketut Agus Indra Adhiputra
Keyword(s):  
Intensive Care Unit ◽  
Pseudomonas Aeruginosa ◽  
Intensive Care ◽  
Antimicrobial Resistance ◽  
Empirical Therapy ◽  
Tertiary Hospital ◽  
Clinical Microbiology Laboratory ◽  
Cross Sectional ◽  
Resistance Profile ◽  
Control Programs

Pseudomonas aeruginosa is one of the gram-negative bacteria that causes infection in the Intensive Care Unit (ICU) which is easily resistant. Patients infected with carbapenem-resistant P. aeruginosa are predicted to have a poor prognosis. This study aims to know the resistance profile of meropenem-resistant P. aeruginosa in the ICU. The results of this study can be used as a measure on the success of antimicrobial resistance control, infection control programs and become a reference for empirical therapy in the ICU. This study used a cross-sectional retrospective descriptive research method and was carried out at the Clinical Microbiology Laboratory of Sanglah Hospital Denpasar for three years, from 2018 to 2020. The results showed 38 of the 93 isolates of P. aeruginosa in the ICU were resistant to meropenem and were derived from sputum and urine. The percentage of meropenem-resistant P. aeruginosa isolates was higher in the multi-drug-resistant group and mostly came from sputum specimens. In 2018, Non-MDR meropenem-resistant P. aeruginosa isolates was that 100% sensitive to all other antibiotics used to treat P. aeruginosa infections, including; ceftazidime, cefepime, ciprofloxacin, gentamicin, amikacin, and piperacillin-tazobactam. In 2019 no meropenem-resistant P. aeruginosa isolates were found. In 2020, its sensitivity to antibiotics ceftazidime and piperacillin-tazobactam was 20.0%, ciprofloxacin 60.0% and to antibiotics gentamicin and amikacin 100%. MDR meropenem-resistant P. aeruginosa isolates in 2018 were still sensitive to ceftazidime (15.4%) and amikacin (69.2%) antibiotics, while in 2019 they were only sensitive to amikacin (37.5%). In 2020, P. aeruginosa isolates were sensitive to the antibiotics ceftazidime and cefepime (11.1%), piperacillin-tazobactam (22.2%), and amikacin (88.9%). Amikacin may be the choice of treatment for MDR meropenem-resistant P. aeruginosa.

scholarly journals Antibiotic Consumption and Its Relationship with Bacterial Resistance Profiles in ESKAPE Pathogens in a Peruvian Hospital

Antibiotics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1221
Author(s):  
Giancarlo Pérez-Lazo ◽  
Susan Abarca-Salazar ◽  
Renata Lovón ◽  
Rocío Rojas ◽  
José Ballena-López ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Pseudomonas Aeruginosa ◽  
Intensive Care ◽  
Bacterial Resistance ◽  
Antibiotic Consumption ◽  
Antimicrobial Consumption ◽  
Carbapenem Resistant ◽  
Resistance Patterns ◽  
Medical Wards ◽  
Eskape Pathogens

A descriptive design was carried out studying the correlation between antimicrobial consumption and resistance profiles of ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp.) in a Peruvian hospital, including the surgical, clinical areas and the intensive care unit (ICU) during the time period between 2015 and 2018. There was a significant correlation between using ceftazidime and the increase of carbapenem-resistant Pseudomonas aeruginosa isolations (R = 0.97; p < 0.05) and the resistance to piperacillin/tazobactam in Enterobacter spp. and ciprofloxacin usage (R = 0.97; p < 0.05) in the medical wards. The Pseudomonas aeruginosa resistance to piperacillin/tazobactam and amikacin in the intensive care unit (ICU) had a significant reduction from 2015 to 2018 (67% vs. 28.6%, 65% vs. 34.9%, p < 0.001). These findings give valuable information about the rates and dynamics in the relationship between antibiotic usage and antimicrobial resistance patterns in a Peruvian hospital and reinforce the need for continuous support and assessment of antimicrobial stewardship strategies, including microbiological indicators and antimicrobial consumption patterns.

scholarly journals Lung ultrasound presentation of COVID-19 patients: phenotypes and correlations

2021 ◽  
Author(s):  
Gianmarco Secco ◽  
◽  
Marzia Delorenzo ◽  
Francesco Salinaro ◽  
Caterina Zattera ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Lung Ultrasound ◽  
Structure And Function ◽  
General Ward ◽  
Prognostic Role ◽  
Interstitial Syndrome ◽  
Lung Structure ◽  
And Function ◽  
The Relationship

AbstractBedside lung ultrasound (LUS) can play a role in the setting of the SarsCoV2 pneumonia pandemic. To evaluate the clinical and LUS features of COVID-19 in the ED and their potential prognostic role, a cohort of laboratory-confirmed COVID-19 patients underwent LUS upon admission in the ED. LUS score was derived from 12 fields. A prevalent LUS pattern was assigned depending on the presence of interstitial syndrome only (Interstitial Pattern), or evidence of subpleural consolidations in at least two fields (Consolidation Pattern). The endpoint was 30-day mortality. The relationship between hemogasanalysis parameters and LUS score was also evaluated. Out of 312 patients, only 36 (11.5%) did not present lung involvment, as defined by LUS score < 1. The majority of patients were admitted either in a general ward (53.8%) or in intensive care unit (9.6%), whereas 106 patients (33.9%) were discharged from the ED. In-hospital mortality was 25.3%, and 30-day survival was 67.6%. A LUS score > 13 had a 77.2% sensitivity and a 71.5% specificity (AUC 0.814; p < 0.001) in predicting mortality. LUS alterations were more frequent (64%) in the posterior lower fields. LUS score was related with P/F (R2 0.68; p < 0.0001) and P/F at FiO2 = 21% (R2 0.59; p < 0.0001). The correlation between LUS score and P/F was not influenced by the prevalent ultrasound pattern. LUS represents an effective tool in both defining diagnosis and stratifying prognosis of COVID-19 pneumonia. The correlation between LUS and hemogasanalysis parameters underscores its role in evaluating lung structure and function.

scholarly journals Epidemiology and characterisation of carbapenem-non-susceptible Pseudomonas aeruginosa in a large intensive care unit in Jakarta, Indonesia

2019 ◽  
Vol 54 (5) ◽  
pp. 655-660 ◽  
Author(s):  
Yulia Rosa Saharman ◽  
Andreu Coello Pelegrin ◽  
Anis Karuniawati ◽  
Rudyanto Sedono ◽  
Dita Aditianingsih ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Pseudomonas Aeruginosa ◽  
Intensive Care

scholarly journals Understanding vasopressor intervention and weaning: risk prediction in a public heterogeneous clinical time series database

2016 ◽  
Vol 24 (3) ◽  
pp. 488-495 ◽  
Author(s):  
Mike Wu ◽  
Marzyeh Ghassemi ◽  
Mengling Feng ◽  
Leo A Celi ◽  
Peter Szolovits ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Time Series ◽  
Intensive Care ◽  
Receiver Operating Curve ◽  
Post Discharge ◽  
Control Hypotension ◽  
Health Records ◽  
Physiological Time ◽  
Large Populations ◽  
Switching State

Background: The widespread adoption of electronic health records allows us to ask evidence-based questions about the need for and benefits of specific clinical interventions in critical-care settings across large populations. Objective: We investigated the prediction of vasopressor administration and weaning in the intensive care unit. Vasopressors are commonly used to control hypotension, and changes in timing and dosage can have a large impact on patient outcomes. Materials and Methods: We considered a cohort of 15 695 intensive care unit patients without orders for reduced care who were alive 30 days post-discharge. A switching-state autoregressive model (SSAM) was trained to predict the multidimensional physiological time series of patients before, during, and after vasopressor administration. The latent states from the SSAM were used as predictors of vasopressor administration and weaning. Results: The unsupervised SSAM features were able to predict patient vasopressor administration and successful patient weaning. Features derived from the SSAM achieved areas under the receiver operating curve of 0.92, 0.88, and 0.71 for predicting ungapped vasopressor administration, gapped vasopressor administration, and vasopressor weaning, respectively. We also demonstrated many cases where our model predicted weaning well in advance of a successful wean. Conclusion: Models that used SSAM features increased performance on both predictive tasks. These improvements may reflect an underlying, and ultimately predictive, latent state detectable from the physiological time series.

scholarly journals Mechanisms of carbapenem resistance in endemic Pseudomonas aeruginosa isolates after an SPM-1 metallo-β-lactamase producing strain subsided in an intensive care unit of a teaching hospital in Brazil

2016 ◽  
Vol 111 (9) ◽  
pp. 551-558 ◽  
Author(s):  
Luciana Camila Cacci ◽  
Stephanie Gomes Chuster ◽  
Natacha Martins ◽  
Pâmella Rodrigues do Carmo ◽  
Valéria Brígido de Carvalho Girão ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Pseudomonas Aeruginosa ◽  
Intensive Care ◽  
Teaching Hospital ◽  
Carbapenem Resistance
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