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Clinical characteristics and mortality risk prediction in critically ill children in Malaysian Borneo
Authors:Indra Ganesan  Terrence Thomas  Fon En Ng  Thian Lian Soo
Affiliation:1.Department of Paediatrics, KK Women’s and Children’s Hospital, Singapore.;2.Paediatric Department, Sabah Women’s and Children’s Hospital, Kota Kinabalu, Sabah, Malaysia
Abstract:

INTRODUCTION

Mortality risk prediction scores are important for benchmarking quality of care in paediatric intensive care units (PICUs). We aimed to benchmark PICU outcomes at our hospital against the Pediatric Index of Mortality 2 (PIM2) mortality risk prediction score, and evaluate differences in diagnosis on admission and outcomes between Malaysian and immigrant children.

METHODS

We prospectively collected demographic and clinical data on paediatric medical patients admitted to the PICU of Sabah Women’s and Children’s Hospital in Kota Kinabalu, Sabah, Malaysia. The PIM2 risk score for mortality was tabulated.

RESULTS

Of the 131 patients who met the inclusion criteria, data was available for 115 patients. The mean age of the patients was 2.6 ± 3.8 years, with 79% of the cohort aged less than five years. Patients were mainly of Kadazan (38%) and Bajau (30%) descent, and 26% of patients were non-citizens. Leading diagnoses on admission were respiratory (37%), neurological (18%) and infectious (17%) disorders. Out of the 29 patients who died, 23 (79%) were Malaysians and the main mortality diagnostic categories were respiratory disorder (22%), septicaemia (22%), haemato-oncological disease (17%) and neurological disorder (13%). Calculated standardised mortality ratios (SMRs) were not significantly > 1 for any patient category for variables such as age and admission diagnosis. However, infants less than two years old with comorbidities were significantly worse (SMR 2.61, 95% confidence interval 1.02–6.66).

CONCLUSION

The patient profile at our centre was similar to that reported from other PICUs in Asia. The PIM2 score is a useful mortality risk prediction model for our population.
Keywords:mortality risk prediction scores   paediatric intensive care
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