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Triage has an important role in providing suitable care to the largest number of casualties in a disaster setting, but there are no secondary triage methods suitable for children. This study developed a new secondary triage method named the Pediatric Physiological and Anatomical Triage Score (PPATS) and compared its accuracy with current triage methods.
A retrospective chart review of pediatric patients under 16 years old transferred to an emergency center from 2014 to 2016 was performed. The PPATS categorized the patients, defined the intensive care unit (ICU)-indicated patients if the category was highest, and compared the accuracy of prediction of ICU-indicated patients among PPATS, Physiological and Anatomical Triage (PAT), and Triage Revised Trauma Score (TRTS).
Among 137 patients, 24 (17.5%) were admitted to ICU. The median PPATS score of these patients was significantly higher than that of patients not admitted to ICU (11 [IQR: 9-13] versus three [IQR: 2-4]; P<.001). The optimal cut-off value of the PPTAS was six, yielding a sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 95.8%, 86.7%, 60.5%, and 99.0%. The area under the receiver-operating characteristic curve (AUC) was larger for PPTAS than for PAT or TRTS (0.95 [95% CI, 0.87-1.00] versus 0.65 [95% CI, 0.58-0.72]; P<.001 and 0.79 [95% CI, 0.69-0.89]; P=.003, respectively). Regression analysis showed a significant association between the PPATS and the predicted mortality rate (r2=0.139; P<.001), ventilation time (r2=0.320; P<.001), ICU stay (r2=0.362; P<.001), and hospital stay (r2=0.308; P<.001).
The accuracy of PPATS was superior to other methods for secondary triage of children.
ToidaC, MugurumaT, AbeT, ShinoharaM, GakumazawaM, YogoN, ShirasawaA, MorimuraN. Introduction of Pediatric Physiological and Anatomical Triage Score in Mass-Casualty Incident. Prehosp Disaster Med. 2018;33(2):147–152.
Reducing uncertainty about information on injury severity or number of patients is an important concern in managing equipment and rescue personnel in a disaster setting. A simplified disaster model was designed using Shannon’s Information Theory to study the uncertainty of information in a triage scenario.
A disaster triage scene with a specific number of injured patients represents a source of information regarding the extent of patients’ disability. It is possible to quantify uncertainty of information regarding patients’ incapacity as entropy if the information source and information arising from the source in Information Theory can be adapted to the disaster situation and the information on patients’ incapacity that arises.
Five different scenarios of a fire disaster in a hospital were modeled. Information on patients’ extent of impairment was converted to numerical values in relation to available equipment and the number of rescue personnel. Victims were 10 hospitalized patients with conditions of unknown severity. Triage criteria were created arbitrarily and consisted of four categories from Level 1 (able to walk) to Level 4 (cardiac arrest). The five situations were as follows: (1) Case 1: no triage officer; (2) Case 2: one triage officer; (3) Case 3: one triage officer and a message that six patients could walk; (4) Case 4: one triage officer and a message that all patients could obey commands; and (5) Case 5: one triage officer and a message that all patients could walk. Entropy in all cases and the amount of information newly given in Cases 2 through 5 were calculated.
Entropies in Cases 1 through 5 were 5.49, 2.00, 1.60, 1.00, and 0.00 bits/symbol, respectively. These values depict the uncertainty of probability of the triage categories arising in each situation. The amount of information for the triage was calculated as 3.49 bits (ie, 5.49 minus 2.00). In the same manner, the amount of information for the messages in Cases 3 through 5 was calculated as 0.4, 1.0, and 2.0 bits, respectively. These amounts of information indicate a reduction in uncertainty regarding the probability of the triage levels arising.
It was possible to quantify uncertainty of information about the extent of disability in patients at a triage location and to evaluate reduction of the uncertainty by using entropy based on Shannon’s Information Theory.
AjimiY, SasakiM, UchidaY, GakumazawaM, SasakiK, FujitaT, SakamotoT. Quantitative Evaluation for Uncertainty of Information About Patients’ Injury Severity in a Hospital Disaster: A Simulation Study Using Shannon’s Information Theory. Prehosp Disaster Med. 2015;30(4):1-4.
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