Ventilator-Associated Pneumonia in Pediatric Intensive Care Unit: Correspondence

Tullu, Milind S.; Balasubramanian, Pooja

doi:10.1007/s12098-015-1773-8

Cited by 4 publications

(4 citation statements)

References 2 publications

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“…It was also observed that all cases of VAP occurred in the >72 hour group. Srinivasan et al observed 32% of VAP in their study, 10.7% by Casado et al, 17.5% by Kendirli et al, and 27.4% in the study done by Tullu et al 1,[7][8][9] Atelectasis was the commonest complication in the study by Kendirli et al attributing to 26.3%, whereas it was 13.8 % in the study by Wang, et al 1,10 In our study 3.6% of cases spontaneously extubated. The overall reintubation rate in our study was 3.8%.…”

Section: Discussionsupporting

confidence: 40%

Clinical profile of children mechanically ventilated in a pediatric intensive care unit of a limited resource setting

Anitha

Lakshmi

Shanthi

et al. 2016

Int J Contemp Pediatr

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Section: Discussionsupporting

confidence: 40%

Clinical profile of children mechanically ventilated in a pediatric intensive care unit of a limited resource setting

Anitha

Lakshmi

Shanthi

et al. 2016

Int J Contemp Pediatr

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“…pneumoniae is known as one of the significant causative agents of paediatric VAP worldwide [31][32][33][34][35]. In Egypt, K. pneumoniae is considered to be the commonest isolated microorganism for paediatric and neonatal VAP infection [6,7,34].…”

Section: Discussionmentioning

confidence: 99%

Epidemiological typing of multidrug-resistant Klebsiella pneumoniae, which causes paediatric ventilator-associated pneumonia in Egypt

Mohamed

Aly

Halby

et al. 2017

Journal of Medical Microbiology

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Purpose. Multidrug-resistant Klebsiella pneumoniae is a common nosocomial pathogen that plays an important role in ventilator-associated pneumonia (VAP). This study aimed to define the clonal relatedness of K. pneumoniae strains isolated from paediatric VAP in addition to those isolated from environmental samples.Methodology. This study included 19 clinical and 4 environmental K. pneumoniae isolates recovered from the paediatric intensive care unit (PICU) in Assiut University Children's Hospital. The K. pneumoniae isolates were confirmed by biotyping using API strips and subjected to antimicrobial susceptibility testing. The genes coding K1 and K2 capsular types were detected by PCR. The clonal relationships between the K. pneumoniae isolates were determined by pulsed-field gel electrophoresis (PFGE).Results. Ten resistotypes were detected among all the K. pneumoniae isolates, while PFGE identified seventeen K. pneumoniae pulsotypes. Similar PFGE patterns were found between environmental and clinical isolates and between isolates recovered from different patients, suggesting the circulation of K. pneumoniae pathogens in the PICU and the role of the environment in the spread of infection. No correlation was found between the resistotypes and pulsotypes of the K. pneumoniae isolates. PFGE showed higher discriminatory power for the typing of nosocomial K. pneumoniae [Simpson's diversity index (DI)=0.96] than resistotyping (DI=0.72).Conclusion. As far as we know, this is the first report of the isolation of the same multidrug-resistant (MDR) K. pneumoniae pulsotype from patients and environmental samples in the same hospital ward in Egypt. This study provides a step on the way to understanding the genotyping and epidemiology of MDR K. pneumoniae for enhanced prevention of bacterial transmission.

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“…However, delays in VAP diagnosis and, to some extent, in initiating anti-infectious therapy are observed and associated with worse outcomes [ 2 , 3 , 4 ]. Furthermore, subjective criteria included in the CDC pediatric definition for VAP results in a variability of VAP diagnosis and incidence (changes in the appearance and amount of sputum, worsening of an existing cough) [ 5 , 6 , 7 ]. To help physicians to prospectively diagnose VAP, the CDC developed the concept of Ventilator-Associated Events (VAE) in adults, but children have long been excluded from this definition [ 1 ].…”

Section: Introductionmentioning

confidence: 99%

“…However, delays in VAP diagnosis and, to some extent, in initiating anti-infectious therapy are observed and associated with worse outcomes [2][3][4]. Furthermore, subjective criteria included in the CDC pediatric definition for VAP results in a variability of VAP diagnosis and incidence (changes in the appearance and amount of sputum, worsening of an existing cough) [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Clinical Decision Support System to Detect the Occurrence of Ventilator-Associated Pneumonia in Pediatric Intensive Care

Rambaud,

Sajedi,

Al Omar

et al. 2023

Diagnostics

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Objectives: Ventilator-associated pneumonia (VAP) is a severe care-related disease. The Centers for Disease Control defined the diagnosis criteria; however, the pediatric criteria are mainly subjective and retrospective. Clinical decision support systems have recently been developed in healthcare to help the physician to be more accurate for the early detection of severe pathology. We aimed at developing a predictive model to provide early diagnosis of VAP at the bedside in a pediatric intensive care unit (PICU). Methods: We performed a retrospective single-center study at a tertiary-care pediatric teaching hospital. All patients treated by invasive mechanical ventilation between September 2013 and October 2019 were included. Data were collected in the PICU electronic medical record and high-resolution research database. Development of the clinical decision support was then performed using open-access R software (Version 3.6.1®). Measurements and main results: In total, 2077 children were mechanically ventilated. We identified 827 episodes with almost 48 h of mechanical invasive ventilation and 77 patients who suffered from at least one VAP event. We split our database at the patient level in a training set of 461 patients free of VAP and 45 patients with VAP and in a testing set of 199 patients free of VAP and 20 patients with VAP. The Imbalanced Random Forest model was considered as the best fit with an area under the ROC curve from fitting the Imbalanced Random Forest model on the testing set being 0.82 (95% CI: (0.71, 0.93)). An optimal threshold of 0.41 gave a sensitivity of 79.7% and a specificity of 72.7%, with a positive predictive value (PPV) of 9% and a negative predictive value of 99%, and with an accuracy of 79.5% (95% CI: (0.77, 0.82)). Conclusions: Using machine learning, we developed a clinical predictive algorithm based on clinical data stored prospectively in a database. The next step will be to implement the algorithm in PICUs to provide early, automatic detection of ventilator-associated pneumonia.

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Ventilator-Associated Pneumonia in Pediatric Intensive Care Unit: Correspondence

Cited by 4 publications

References 2 publications

Clinical profile of children mechanically ventilated in a pediatric intensive care unit of a limited resource setting

Clinical profile of children mechanically ventilated in a pediatric intensive care unit of a limited resource setting

Epidemiological typing of multidrug-resistant Klebsiella pneumoniae, which causes paediatric ventilator-associated pneumonia in Egypt

Clinical Decision Support System to Detect the Occurrence of Ventilator-Associated Pneumonia in Pediatric Intensive Care

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