Emergency department crowding in pediatric settings impairs quality of care. Triage systems are used to prioritize patients and allocate resources efficiently. Although several pediatric triage scales have been validated internationally, there are few validation studies from Latin America. This study evaluates the validity of a locally adapted Canadian Pediatric Triage and Acuity Scale (CPTAS) in predicting hospitalization and resource utilization in a pediatric emergency department (PED) in Argentina.
The investigators performed a retrospective validation study using triage-classified visits to a single pediatric hospital emergency department between April 2021 and February 2022. During that interval, 56,843 consultations were triaged. From those, a randomized sample of 1,500 visits was selected for review; 1,159 of these were analyzed. The abstract does not specify reasons for exclusion of the remaining sampled visits, nor does it report patient demographic breakdowns or diagnostic categories in the analyzed sample.
The study tested an institutionally adapted version of the CPTAS. The scale assigns patients to urgency levels 1 through 5. The abstract presents outcomes stratified by these urgency levels, but it does not provide the adaptation details, the specific criteria used for each level in the local version, or any training or calibration procedures performed for triage staff.
Primary outcomes assessed were hospital admission and consumption of clinical resources. Resource use was reported as the proportion of patients who required two or more resources, though the abstract does not define which procedures, tests, or treatments were counted as resources. Safety outcomes reported in the abstract include admission to the Intensive Care Unit (ICU) and in-hospital mortality.
The analysis evaluated the association between CPTAS urgency level and both hospital admission and resource utilization. Odds ratios (ORs) with 95% confidence intervals were calculated to compare admission likelihood across urgency levels. Discrimination of the scale for predicting admission was summarized by the area under the receiver operating characteristic curve (AUC). Specific statistical modeling details (covariate adjustment, handling of missing data) are not provided in the abstract.
Sample and overall admission rate: Of the 1,159 analyzed visits, the overall hospitalization rate was 15.27%.
Hospitalization by urgency level: admission rates differed significantly across urgency categories (p < 0.01):
Predictive associations for admission: comparing higher-urgency levels to level 5, the OR for admission was 49.15 (95% CI 26.51–91.10) for level 2 and 5.23 (95% CI 2.97–9.19) for level 3 (p < 0.01). The reported discriminative ability for admission prediction was AUC = 0.83.
Resource utilization (use of ≥2 resources): proportions by level were: Level 1, 50%; Level 2, 42.96%; Level 3, 19.60%; Level 4, 10.63%; Level 5, 1.92% (p < 0.01). Levels 2 and 3 showed significantly higher ORs for consuming ≥2 resources (p < 0.01).
Safety outcomes: five patients in the analyzed sample required ICU admission; no deaths were recorded.
In this single-center retrospective sample, the locally adapted CPTAS showed strong discrimination for predicting hospital admission (AUC 0.83) and a clear, statistically significant gradient of both admission rates and resource consumption across urgency levels. Level 1 and level 2 patients had substantially higher admission and resource use than lower urgency categories. The authors conclude that the adapted CPTAS performed well for assessing urgency at their institution and suggest that its use could be considered at other centers in the region.
The abstract reports core performance metrics but omits several details relevant to broader interpretation and implementation: exact criteria used in the adaptation of CPTAS; triage training and inter-rater reliability; precise definition of what constituted a resource and which interventions/tests qualified toward the ≥2 resources metric; reasons for exclusion of sampled visits; patient demographics and presenting complaints; calibration metrics beyond AUC; and information on how missing data were handled. These items may be available in the full text but are not reported in the abstract.
Overall, based on the abstract, the adapted CPTAS demonstrated good predictive validity for admission and higher resource consumption in this Argentine PED sample, supporting consideration of its local use and prompting the need for fuller reporting of adaptation methods and implementation fidelity for wider adoption.