Early prognosis in traumatic brain injury: from prophecies to predictions

Lingsma, Hester F.; Roozenbeek, Bob; Steyerberg, Ewout W.; Murray, Gordon D.; Maas, Andrew I. R.

doi:10.1016/s1474-4422(10)70065-x

Cited by 371 publications

(304 citation statements)

References 119 publications

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“…There is wide heterogeneity in how people recover after mTBI, 11 even when people experience similar injuries. There is a need to better understand this variability in outcome, and to identify the factors, in particular, modifiable factors that contribute to recovery to ensure that appropriate and timely treatment is provided.…”

Section: Traumatic Brain Injury (Tbi) Occurs Whenmentioning

confidence: 99%

“…Existing prognostic models based on moderate to severe TBI perform poorly within the context of mTBI and it remains difficult to identify those at risk of developing persistent symptoms. 12,13 In a systematic review of mTBI models, pre-injury mental health and post-injury cognitive functioning were found to be the most robust prognostic factors on persistent symptoms post-injury, 12 although the authors note that many studies had suboptimal methodology including the exclusion of people who do not attend medical services after injury.…”

Section: Traumatic Brain Injury (Tbi) Occurs Whenmentioning

confidence: 99%

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Persistent problems 1 year after mild traumatic brain injury: a longitudinal population study in New Zealand

Parag²,

et al. 2015

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Section: Traumatic Brain Injury (Tbi) Occurs Whenmentioning

confidence: 99%

Section: Traumatic Brain Injury (Tbi) Occurs Whenmentioning

confidence: 99%

Persistent problems 1 year after mild traumatic brain injury: a longitudinal population study in New Zealand

Parag²,

et al. 2015

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“…3 Outcome prediction is however relevant for both clinical practice and research. Several prognostic models to predict outcome in TBI patients exist, but few meet the methodological requirements for valid prognostic model development, including a sufficiently large development sample and internal or external validation.…”

mentioning

confidence: 99%

Prognosis in moderate and severe traumatic brain injury

Lingsma

Andriessen

Haitsema

et al. 2013

Journal of Trauma and Acute Care Surgery

100

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BACKGROUND:Several prognostic models to predict outcome in traumatic brain injury (TBI) have been developed, but few are externally validated. We aimed to validate the International Mission on Prognosis and Analysis of Clinical Trials in TBI (IMPACT) prognostic models in a recent unselected patient cohort and to assess the additional prognostic value of extracranial injury. METHODS:The Prospective Observational COhort Neurotrauma (POCON) registry contains 508 patients with moderate or severe TBI, who were admitted in 2008 and 2009 to five trauma centers in the Netherlands. We predicted the probability of mortality and unfavorable outcome at 6 months after injury with the IMPACT prognostic models. We studied discrimination (area under the curve [AUC]) and calibration. We added the extracranial component of the Injury Severity Score (ISS) to the models and calculated the increase in AUC. RESULTS:The IMPACT models had an adequate discrimination in the POCON registry, with AUCs in the external validation between 0.85 and 0.90 for mortality and between 0.82 and 0.87 for unfavorable outcome. Observed outcomes agreed well with predicted outcomes. Adding extracranial injury slightly improved predictions in the overall population (unfavorable outcome: AUC increase of 0.002, p = 0.02; mortality: AUC increase of 0.000, p = 0.37) but more clearly in patients with moderate TBI (unfavorable outcome: AUC increase of 0.008, p G 0.01, mortality: AUC increase of 0.012, p = 0.02) and patients with minor computed tomographic result abnormalities (unfavorable outcome: AUC increase of 0.013, p G 0.01; mortality: AUC increase of 0.001, p = 0.08). CONCLUSION:The IMPACT models performed well in a recent series of TBI patients. We found some additional impact of extracranial injury on outcome, specifically in patients with less severe TBI or minor computed tomographic result abnormalities. (J Trauma Acute Care Surg. 2013;74: 639Y646.

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“…The predictive value ( R 2 ) of the IMPACT model is 0.35, with the remainder of the variability thought to be accounted for either genetically or by other biological factors yet to be identified 19. After adding mitochondrial haplogroups to the predictive terms of the IMPACT model, we found a significantly predictive effect of mtDNA genotype on the 6‐month GOS ( p = 0.008).…”

Section: Resultsmentioning

confidence: 84%

“…It is important to remember that age is a very strong determinant of outcome after TBI, with most studies showing a linear relationship between age and TBI mortality and disability after the 3rd decade of life 19. We therefore reasoned that mtDNA haplogroups might differentially affect resilience to TBI with advancing age.…”

Section: Discussionmentioning

confidence: 99%

Mitochondrial DNA and traumatic brain injury

Bulstrode

Nicoll

Hudson

et al. 2014

Annals of Neurology

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ObjectiveTraumatic brain injury (TBI) is a multifactorial pathology with great interindividual variability in response to injury and outcome. Mitochondria contain their own DNA (mtDNA) with genomic variants that have different physiological and pathological characteristics, including susceptibility to neurodegeneration. Given the central role of mitochondria in the pathophysiology of neurological injury, we hypothesized that its genomic variants may account for the variability in outcome following TBI.MethodsWe undertook an analysis of mitochondrial haplogroups in a large, well‐characterized cohort of 1,094 TBI patients. A proportional odds model including age, brain computed tomography characteristics, injury severity, pupillary reactivity, mitochondrial haplogroups, and APOE was applied to Glasgow Outcome Score (GOS) data.ResultsmtDNA had a significant association with 6‐month GOS (p = 0.008). Haplogroup K was significantly associated with favorable outcome (odds ratio = 1.64, 95% confidence interval = 1.08–2.51, p = 0.02). There was also a significant interaction between mitochondrial genome and age (p = 0.002), with a strong protective effect of both haplogroups T (p = 0.015) and K (p = 0.017) with advancing age. We also found a strong interaction between APOE and mitochondrial haplogroups (p = 0.001), indicating a protective effect of haplogroup K in carriers of the APOE ε4 allele.InterpretationThese findings reveal an interplay between mitochondrial DNA, pathophysiology of TBI, and aging. Haplogroups K and T, which share a common maternal ancestor, are shown as protective in TBI. The data also suggest that the APOE pathways interact with genetically regulated mitochondrial functions in the response to acute injury, as previously reported in Alzheimer disease. Ann Neurol 2014;75:186–195

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Early prognosis in traumatic brain injury: from prophecies to predictions

Cited by 371 publications

References 119 publications

Persistent problems 1 year after mild traumatic brain injury: a longitudinal population study in New Zealand

Persistent problems 1 year after mild traumatic brain injury: a longitudinal population study in New Zealand

Prognosis in moderate and severe traumatic brain injury

Mitochondrial DNA and traumatic brain injury

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