Oral Presentations (Paediatrics)

Xin Yang, Yingchao Liu, Lijuan Wang, Suyun Qian, Kaihu Yao

CLONAL AND DRUG RESISTANCE DYNAMICS OF MRSA IN PEDIATRIC POPULATIONS IN CHINA
  1. Pediatric Intensive Care Unit, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
  2. MOE Key Laboratory of Major Diseases in Children, National Key Discipline of Pediatrics (Capital Medical University), National Clinical Research Center for Respiratory Diseases, Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Pediatric Research Institute, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China

Correspondence

Suyun Qian, Pediatric Intensive Care Unit, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing 100045, China

Email: syqian1211@163.com

Kaihu Yao, Beijing Pediatric Research Institute, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing 100045, China

Email: jiuhu2655@sina.com

*These authors contributed equally to this work.

Funding source

This study was funded by National Natural Science Foundation of China (No. 81571948) and the Beijing Natural Science Foundation (No.7172075).

Objective:

To evaluate the clonal and drug resistance dynamics of methicillin-resistant Staphylococcus aureus (MRSA) in Chinese children from 2010 to 2017.

Methods:

MRSA was isolated from patients in Beijing Children’s Hospital from 2010 to 2013 and from 2016 to 2017.The molecular characteristics andantibiotic resistance were determined.

Results:

In total, 211 MRSA isolates were collected, and 104 isolates were classified as community-associated MRSA (CA-MRSA). ST59-SCCmec IV was the most prevalent type in both CA-MRSA (65.4%) and healthcare-associated-MRSA (HA-MRSA) (46.7%). ST239-SCCmec III accounted for 21.5% of all HA-MRSA, which were not detected in 2016, and only three isolates were detected in 2017. The pvl genecarrying rate of CA-MRSA was significantly higher than that of HA-MRSA (42.3% vs. 29.0%, P = 0.0456). Among CA-MRSA, resistance rate to all tested antibiotics excluding chloramphenicol remained stable over the periods of 2010–2013 and 2016–2017. HA-MRSA displayed an overall trend of decreased resistance to oxacillin, gentamicin, tetracycline, ciprofloxacin, and rifampin, and increased resistance to chloramphenicol, consistent with the difference of antibiotic resistance patterns between ST59-SCCmec IV and ST239-SCCmec III isolates. Vancomycin minimal inhibitory concentration (MIC) creep was found in the study period in all MRSA and ST59-SCCmec IV isolates.

Conclusions:

ST59-SCCmec IV has spread to hospitals and replaced the traditional ST239-SCCmec III clone, accompanied by changes in drug resistance. Furthermore, vancomycin MIC creep indicated that the rational use of antibiotics should be seriously considered.

Keywords

MRSA, Clonal lineage, Drug resistance, Pediatric, China

Farah W Aziz, Gan CS, Eg KP

COMPARISON OF PEDIATRIC INDEX OF MORTALITY 2 AND PEDIATRIC INDEX OF MORTALITY 3 SCORING IN A PAEDIATRIC INTENSIVE CARE UNIT IN A TERTIARY CENTRE IN MALAYSIA
  1. University Malaya Medical Center

Background

Paediatric Intensive Care Unit (PICU) is an important subspecialty which provides support and intensive care for ill children who has potentially reversible acute life-threatening illness. Having a scoring system to predict mortality would be useful to give more supportive treatment to those with higher risk as well as for the usage of treatment modalities available in the PICU.

Aim

To assess the effectiveness of PIM2 and PIM3 scores in predicting mortality in children admitted to PICU in a tertiary centre in Kuala Lumpur, Malaysia.

Methods

This is a retrospective study involving admissions of children between the age of 1 day  to 18 years old to PICU of University Malaya Medical Centre from 1st January 2016 to 31st December 2017. The PIM2 and PIM3 scores were calculated using formula available online and results were tabulated. Actual outcome was noted as survivor and non-survivor

Results

The final study sample comprised of 929 admissions. More than half (58.8%) of them were males and of Malay ethnicity (55.8%). A higher proportion (76%) of them were less than 5 years old and the most common age group were between 1 month to 1 year old (29.5%). About 62.9% of the admissions were from the in-patient wards. The main reasons for admission were for respiratory support (48.5%), followed by post-surgery/procedure and observation. The most common diagnostic categories were respiratory illness (25.9%) and neurological cases (11.4%). Nearly 28.5% of the admissions were less than 24 hours followed by an average length of stay of 4 to 7 days (27.3%). The observed mortality rate was 5.1%. The expected mortality rate was 7.28% (PIM2) and 6.04% (PIM3) while the Standardized Mortality Ratio, SMR was 0.7231 (PIM2) and 0.8393 (PIM3). The main cause of death was septic shock (38%), followed by respiratory failure, haemorrhage and liver failure. The majority of deaths were from the age group of more than 12 years old (13.58%). Most of the deaths in older age group were oncology cases (47.3%). Both of the scoring systems underpredict mortality among the older age group of more than 5 years old, oncology and hepatology cases. There is also an association between respiratory, oncology, hepatology and surgical cases with death outcome as chi square test and p-value was <0.001. It was also found that there is a significant association between length of stay in PICU and survival outcome (c2 = 3.419, p-value < 0.001). The Area Under Receiver Operating Curve (AUROC) was 0.857 (95%CI: 0.807, 0.906) for PIM2 and was 0.85 (95%CI: 0.798, 0.903) for PIM3 showing good discrimination values. Hosmer-Lemeshow Goodness of Fit test for PIM2 showed c2 value of 2.938 with a p-value of 0.938 (p> 0.05) while PIM3 showed c2value of 11.31 with a p-value of 0.185 (p> 0.05) which concludes that the model of fit is good with good calibration properties.

Conclusion

PIM3 was a more accurate scoring as a mortality predictor compared to PIM2 and can be used in the current PICU setting.

Keywords

PIM2, PIM3, paediatric mortality scoring

Zhengzheng Zhang, Weili Yan, Yi Zhang, Guoping Lu

DEVELOPMENT AND VALIDATION OF A SIMPLE MODEL TO PREDICT MORTALITY IN PICU: A MULTICENTER COHORT STUDY
  1. Children’ Hospital of Fudan University,Shanghai,201102

Objective

To develop and validate an early warning model for predicting in-hospital mortality in PICU.

Method

A prospective observational cohort study was carried out in 8 PICUs. Patients aged over 28 days and below 18 years on admission, and staying in PICU over 24 hours were eligible. A total of 4770 eligible patients admitted to these PICUs were consecutively recruited between Aug 1, 2016 and Jul 31, 2017. A death risk prediction model was derived using Cox regression on a non-randomly selected subsample (n=2575) from five hospitals. The model was validated in another subsample (n=1382) from the other three hospitals by using discrimination (C statistics) and calibration.

Result

Within three months after admission, 226 (4.8%) patients died in hospital, 3731 (78.2%) recovered and were transferred to general wards, and 813 (17.0%) were discharged against medical suggestion. Cox regression model identified that organ failures, lactic acid concentration, Glasgow score, PaO2/FiO2 ratio and platelet counts were significant predictors for death risk. C statistics for the constructed model was 0.84 (95% CI 0.79-0.88) in the derivation subsample, and was 0.78 (95%CI 0.71-0.85) in the validation sample. The C statistics of the model using PRISM III score as single predictor, 0.78 (95%CI 0.71-0.85), did not significantly differ from our proposed model (difference in C statistics: 0.00, 95%CI -0.05-0.06). Calibration analysis on Day 5, 10, 15 and 20 showed that the intercepts did not significantly differ from 0 (P=0.84) and the slopes did not significantly differ from 1 (P=0.57).

Conclusion

We propose a new model with good accuracy in predicting death risk in PICU. This model involves five predictors and is considered more feasible and low-cost for risk assessment of mortality in practice.

Saptadi Yuliarto, Antonius H. Pudjiadi, Abdul Latief

HEMODYNAMIC PROFILES OF PEDIATRIC SHOCK REGARDING THE CLINICAL CLASSIFICATION: AN PROSPECTIVE OBSERVATIONAL STUDY
  1. Division of Pediatric Emergency and Intensive Care, Department of Pediatrics
  2. Faculty of Medicine, University of Brawijaya, Saiful Anwar Hospital, Malang, Indonesia
  3. Division of Pediatric Emergency and Intensive Care, Department of Pediatrics
  4. Faculty of Medicine, University of Indonesia, Cipto Mangunkusumo Hospital, Jakarta, Indonesia

Background

Four types of shock are widely recognized: hypovolemic, cardiogenic, distributive, and obstructive. Every type has specific treatment. But, in some cases, the types cannot be clearly distinguished; it leads to challenging management. Therefore, complete hemodynamic parameters are required to guide adequate treatment.

Objectives

To describe fluid responsiveness, contractility, stroke volume index (SVI) cardiac index (CI),  and systemic vascular resistance (SVRI) in each type of pediatric shock following fluid resuscitation.

Methods

It was a prospective observational study conducted at tertiary level emergency room (ER) and pediatric intensive care unit (PICU) of national centre hospital. Clinically shock children were consecutively recruited. We classified into groups according to history taking and clinical manifestation, thenmeasured fluid responsiveness, contractility (inotropy index), SVI, CI, and SVRI with USCOM™ after fluid bolus therapy (FBT). Data were presented in frequency table.

Results

A total 50 patients (25 boys) were eligible. Their median age was 35 months. Septic shock was 64%, hypovolemic was 30% and cardiogenic was 6%. The survival rate was 74%. FBT volume were not different between groups (p = 0.72), with median <40 ml/kg to achieve fluid-refractory condition. There were no differences of SVI, CI, and SVRI. Inotropy index was lower in cardiogenic than septic or hypovolemic shock (SMII 0.72 [0.7-1.6]; 1.3 [0.4-3.3]; and 1.4 [0.8-2.8] respectively; p=0.05). Most cases in septic, hypovolemic, and cardiogenic shock was fluid-refractory (53.1%, 60%, and 100%, respectively) and low SVI (75%, 53.3%, and 100%, respectively). Nonetheless, only in septic and cardiogenic shock, most subjects revealed low contractility (59.4% and 66.6%, respectively) and high SVRI (50% and 66.7%, respectively).

Conclusion

Pediatric septic and cardiogenic shock was non-fluid responder, low contractility, and high resistance. It has to bear in mind that most cases was refractory in 40 ml/kg of FBT.

Keywords

Shock, fluid, hemodynamic parameter