Objective: This study aimed to demonstrate the benefits of using SaTScan (Boston, MA, USA), a cluster-detection software programme, and whole genome sequencing to investigate a suspected outbreak of Serratia marcescens infections in a tertiary government hospital in the southern Philippines. The hospital is part of the national Antimicrobial Resistance Surveillance Program’s network of sentinel sites. Methods: The investigation followed national outbreak investigation protocols. In May 2022, when evaluation of daily hospital laboratory census data revealed an increase in the number of Serratia species in the hospital, an alert was triggered. A concurrent, routine SaTScan analysis of the hospital’s surveillance data by the Antimicrobial Resistance Surveillance Reference Laboratory confirmed a cluster of cases. The Reference Laboratory requested isolates from clinical specimens from the hospital for confirmation of bacterial identification, antimicrobial susceptibility testing and whole genome sequencing. Results: Six isolates were submitted for genomic analysis, two of which were from the identified cluster. Although originally identified as S. marcescens, five of the isolates were subsequently confirmed as S. sarumanii. Phylogenetic analysis showed that the two isolates from the cluster were closely related and belonged to the same clade, which may suggest a common source. Three antimicrobial resistance genes were identified, but their phenotypic expression was limited, with one isolate exhibiting resistance mechanisms. Discussion: This study highlighted the utility of SaTScan for the early detection of potential disease outbreaks. The use of whole genome sequencing enhanced the investigation by enabling the analysis of potential transmission pathways at the genetic level, identification of the outbreak source and the detection of novel species.

BACKGROUND

Pediatric Early Warning Scores (PEWS) help identify children at risk of clinical deterioration, but their accuracy across diverse settings, populations, interventions, and outcomes remains unexplored.

OBJECTIVE

To determine the accuracy of PEWS in detecting clinical deterioration events (CDE) among pediatric patients seen at the emergency department (ED).

DESIGN

Retrospective cohort study.

PARTICIPANTS

Pediatric patients aged 1 month to 18 years seen at the ED.

SETTING

Southern Philippines Medical Center Emergency Department, Davao City, Philippines from January 2021 to December 2022.

MAIN OUTCOME MEASURES

Area under the curve (AUC) of PEWS in detecting CDE; Brighton PEWS optimal cut-off and its sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (+LR), and negative likelihood ratio (-LR).

MAIN RESULTS

Among the 345 patients, 56 experienced CDE and 289 did not. Patients with CDE had significantly lower median age (1.00 year vs 5.00 years; p < 0.001), oxygen saturation (93.00% vs 98.00%; p < 0.001), and pediatric Glasgow Coma Scale scores (8.00 vs 15.00; p < 0.0001) compared to those without CDE. Heart rate (135.00 vs 111.00 beats per minute; p < 0.001), and respiratory rate (32.50 vs 24.00 breaths per minute; p < 0.001) were significantly higher in patients with CDE. The two groups also differed significantly in terms of comorbidity distribution (p < 0.001) and diagnosis (p < 0.001). The AUC of Brighton PEWS was 0.9064 (95% CI 0.8716 to 0.9357), with an optimal cut-off score of ≥4.00. This threshold yielded 76.79% sensitivity, 88.58% specificity, 56.60% PPV, 95.20% NPV, 6.72 LR+, and 0.26 LR-.

CONCLUSION

The Brighton PEWS demonstrates strong diagnostic accuracy in predicting CDE among pediatric patients. A cut-off score of ≥4.00 offers a balanced combination of sensitivity, specificity, and likelihood ratios for ED application.

Human ; Emergency Departments ; Emergency Service, Hospital ; Resuscitation ; Mortality