Predicting paediatric traumatic brain injuries

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The biggest challenge in managing a child with a mild to moderate head injury is deciding whether to organise a CT scan or not. Balancing the risk of ionising radiation (and with it the small, but definite, risk of a future brain tumour or leukaemia) against the risk of missing a significant brain injury is mitigated to some extent by using a clinical decision rule, like the PECARN, CATCH or CHALICE rules. These rules are extremely sensitive with very few false negatives and excellent negative prediction values, meaning if you follow them, you’re unlikely to miss a clinically important brain injury (cTBI). Their problem is their specificity is low with plenty of false positives, meaning most of the children who have a scan won’t actually have a brain injury. (If you’d like a refresher on sensitivity, specificity, NPV and PPV in head injury decision rules, check out Damian’s critical appraisal talks in DFTB Essentials.)

Over the last 6 years, Australasia’s PREDICT network has been a publishing powerhouse on paediatric head injuries from their Australasian Paediatric Head Injury Research Study (APHIRST for short). In their cohort of 20,000 children the team have been able to tell us that of PECARN, CATCH and CHALICE, the PECARN rule has the highest sensitivity. They’ve also shown that planned observation leads to significantly lower CT rates, with no difference in missed cTBI. And probably most telling of all, they’ve told us  that, without using any rules, their clinicians are already very good at identifying children with a cTBI with a sensitivity almost as high as PECARN’s, but with a very low baseline CT rate.

Nonetheless, clinical decision rules do play their role. And so, when they asked their network what an ideal decision rule would tell them, their clinicians highlighted the gaps in the existing guidelines: What should we do with a child with a delayed presentation up to 72 hours after the head injury? What about a child with a bleeding disorder and a head injury? What about a child with a VP shunt and a head injury? Or an intoxicated child with a head injury? The list goes on.

And so, in true PREDICT style, they decided to develop their own guideline.

This week marks a landmark day for paediatric head injury management worldwide as PREDICT launch their guideline for mild to moderate head injuries in children. The risk criteria from the PECARN rule, the best performing prediction rule in the APHIRST study, play a central role, supported by an extensive literature search, including studies from PECARN and PREDICT on the risk associated with VP shunts and bleeding risks. PREDICT have pulled all the data into one comprehensive, evidence-based guideline for managing, what has previously been considered, some of the less clear-cut paediatric head injury presentations. Let’s explore the algorithm and run through a series of cases.

Babl FE, Tavender E, Dalziel S. On behalf of the Guideline Working Group for the Paediatric Research in Emergency Departments International Collaborative (PREDICT). Australian and New Zealand Guideline for Mild to Moderate Head injuries in Children – Algorithm (2021). PREDICT, Melbourne, Australia.

How was the guideline derived?

Building on the existing high-quality clinical decision rules, the PREDICT group conducted a systematic review of the literature to include more recently published evidence. To develop the new PREDICT guideline, they used a GRADE-ADOLOPMENT approach, adopting, adapting or developing new recommendations, which are labelled in the main guideline as ‘evidence-informed recommendations’, ‘consensus-based recommendations’ or ‘practice points’.

What does it say?

This guideline is here to tell us what to do with children with a mild or moderate head injury, with a GCS of 14 or 15, or a child with a GCS ≤ 13 with a normal CT scan. The ‘who to discharge, who to observe and who to scan’ part of the guideline is succinctly summarised with a two-page algorithm. Page 1 has an easy to follow flowchart, supplemented by footnotes and Appendix with modified guidance for special conditions on page 2.

Page 1
Page 2

The bottom line

What I like so much about this guideline is that it answers so many of our “what about the child with a head injury plus…?” questions. With the evidence-based recognition that senior clinicians who choose to observe rather than scan a child reduce the CT rate without increasing the number of missed cTBIs, this guideline also allows senior clinicians to make a risk assessment on a case by case basis, while remaining fluid enough to upgrade or downgrade a child’s risk if their clinical picture changes. Although designed for use in Australia and New Zealand, I can see it being immensely useful outside Australasia and am looking forward to putting its pearls of wisdom to use.

Case 1

Case 2

Case 3

Case 4

Case 5

Cases 6 and 7

Case 8

Cases 9 and 10

Case 11

Case 12

Case 13

Case 14

Case 15

References

 Babl FE, Tavender E, Dalziel S. On behalf of the Guideline Working Group for the Paediatric Research in Emergency Departments International Collaborative (PREDICT). Australian and New Zealand Guideline for Mild to Moderate Head injuries in Children – Algorithm (2020). PREDICT, Melbourne, Australia.

Babl FE et al. Accuracy of PECARN, CATCH, and CHALICE head injury decision rules in children: a prospective cohort study. 2017. 389;10087:2393-2402. DOI: https://doi.org/10.1016/S0140-6736(17)30555-X

Babl FE et al. A prospective observational study to assess the diagnostic accuracy of clinical decision rules for children presenting to emergency departments after head injuries (protocol): the Australasian Paediatric Head Injury Rules Study (APHIRST). BMC Pediatr. 2014. 13;14:148. DOI: 10.1186/1471-2431-14-148

Singh S et al. The Effect of Patient Observation on Cranial Computed Tomography Rates in Children With Minor Head Trauma. Acad Emerg Med. 2020. 27:832–843. DOI: 10.1111/acem.13942

Borland M et al. Delayed Presentations to Emergency Departments of Children With Head Injury: A PREDICT Study. Ann Emerg Med. 2019. 74:1-10. DOI: 10.1016/j.annemergmed.2018.11.035

About the authors

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