Letter to the Editor. Prognostication in traumatic brain injury

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TO THE EDITOR: The ability to predict the outcome after traumatic brain injury (TBI) adds to the clinical armamentarium of everyone involved in the care of such patients. This ability helps not only in planning better and more aggressive care of those patients with predicted borderline prognosis, but also in preparing the patient’s family in cases with grave prognosis. I read with interest the articles by Brennan et al.1 and Murray et al.2 (Brennan PM, Murray GD, Teasdale GM: Simplifying the use of prognostic information in traumatic brain injury. Part 1: The GCS-Pupils score: an

TO THE EDITOR: The ability to predict the outcome after traumatic brain injury (TBI) adds to the clinical armamentarium of everyone involved in the care of such patients. This ability helps not only in planning better and more aggressive care of those patients with predicted borderline prognosis, but also in preparing the patient’s family in cases with grave prognosis. I read with interest the articles by Brennan et al.1 and Murray et al.2 (Brennan PM, Murray GD, Teasdale GM: Simplifying the use of prognostic information in traumatic brain injury. Part 1: The GCS-Pupils score: an extended index of clinical severity. J Neurosurg 128:1612–1620, June 2018; Murray GD, Brennan PM, Teasdale GM: Simplifying the use of prognostic information in traumatic brain injury. Part 2: Graphical presentation of probabilities. J Neurosurg 128:1621–1634, June 2018).

In part 1, the authors modified the existing Glasgow Coma Scale (GCS) to improve the assessment of the severity of TBI. The pupillary reactivity to light is one of the most significant prognostic factors, next to only age and conscious level at admission. The addition of pupillary response to the GCS score will definitely improve the assessment of severity of TBI, and GCS-Pupils (GCS-P) score will be an important prognostic factor. The GCS-P score is definitely going to be used widely in the future. The original GCS score is a very easy-to-use bedside tool with a minimum interobserver variability. The impact of the addition of pupil score on interobserver variability remains to be determined.

In part 2, the authors included age, CT scan findings, and GCS-P; tried to formulate a prognostic model; and compared the results with the CRASH (Corticosteroid Randomization After Significant Head Injury) and IMPACT (International Mission for Prognosis and Clinical Trials in Traumatic Brain Injury) models. The authors found that the prognostication by all these models was comparable. This model probably needs to be simplified to avoid complex charts and grids for easy bedside application.

Some of the multivariate prognostic models are currently available in computer-based and mobile-based apps for easy use. One such model is the Madras Head Injury Prognostic Scale (MHIPS) introduced by the author.3 This model is based on six easily available bedside prognostic factors: age, motor response, pupillary reaction, oculocephalic response, CT scan findings, and other systemic injuries graded on a numeric scale similar to the GCS. The MHIPS is very easy to apply at the bedside and has a very high predictive value, as proved by both internal and external validation.3 It is available on a computer-based app (www.medicalalgorithms.com) and mobile app (“Medal”) for easy day-to-day application. The CRASH and IMPACT models are also available on computer-based apps. The proposed prognostic model including the GCS-P probably needs to be modified as an app (avoiding complex grids and charts) for easy application.

Disclosures

The author reports no conflict of interest.

References

  • 1

    Brennan PMMurray GDTeasdale GM: Simplifying the use of prognostic information in traumatic brain injury. Part 1: The GCS-Pupils score: an extended index of clinical severity. J Neurosurg 128:161216202018

  • 2

    Murray GDBrennan PMTeasdale GM: Simplifying the use of prognostic information in traumatic brain injury. Part 2: Graphical presentation of probabilities. J Neurosurg 128:162116342018

  • 3

    Ramesh VGThirumaran KPRaja MC: A new scale for prognostication in head injury. J Clin Neurosci 15:111011142008

INCLUDE WHEN CITING Published online November 2, 2018; DOI: 10.3171/2018.8.JNS182159.

Response

We thank Dr. Ramesh for his comments. We would like to clarify that the GCS-P is not adding new prognostic information to multivariate models. Instead it is a new, simple way of handling the combined effects of the GCS score and pupil reactivity without the need to make a calculation in a more complex model. In the pooled data for mortality, the R2 (a measure of the proportion of variability in outcome that is explained by the logistic regression model) for more complex models ranged from 22.7% to 23.2% and for the GCS-P ranged from 21.1% to 22.6%.

There are many well-developed prognostic models in TBI, all with broadly comparable performance, none of which are widely used in practice. We are fundamentally presenting a new means of implementation (charts) rather than yet another model. The very limited information available on the MHIPS indicates that neither its predictive performance nor its practical uptake is an improvement on existing methods.

We are disappointed that the author found the charts themselves complex. The charts present the effects of 3 features and their interactions with a clarity and transparency not achieved by production of a set of probabilities from multivariate modelling.

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Article Information

Correspondence Vengalathur Ganesan Ramesh: drvgramesh@hotmail.com.

INCLUDE WHEN CITING Published online November 2, 2018; DOI: 10.3171/2018.7.JNS182128.

Disclosures The author reports no conflict of interest.

© AANS, except where prohibited by US copyright law.

Headings

References

1

Brennan PMMurray GDTeasdale GM: Simplifying the use of prognostic information in traumatic brain injury. Part 1: The GCS-Pupils score: an extended index of clinical severity. J Neurosurg 128:161216202018

2

Murray GDBrennan PMTeasdale GM: Simplifying the use of prognostic information in traumatic brain injury. Part 2: Graphical presentation of probabilities. J Neurosurg 128:162116342018

3

Ramesh VGThirumaran KPRaja MC: A new scale for prognostication in head injury. J Clin Neurosci 15:111011142008

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