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Identification of patients at risk for poor outcome after mTBI
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Lamberink HJ, Otte WM, Geerts AT, et al. Individualised prediction model of seizure recurrence and long-term outcomes after withdrawal of antiepileptic drugs in seizure-free patients: a systematic review and individual participant data meta-analysis. Lancet Neurol 2017; published online May 5. http://dx.doi.org/10.1016/ S1474-4422(17)30114-X. French JA, Pedley TA. Clinical practice. Initial management of epilepsy. N Engl J Med 2008; 359: 166–76.
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Strozzi I, Nolan SJ, Sperling MR, Wingerchuk DM, Sirven J. Early versus late antiepileptic drug withdrawal for people with epilepsy in remission. Cochrane Database Syst Rev 2015; 2: CD001902. Schmidt D, Sillanpää M. Stopping epilepsy treatment in seizure remission: good or bad or both? Seizure 2017; 44: 157–61.
Identification of patients at risk for poor outcome after mTBI
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The study by Joukje van der Naalt and colleagues1 in The Lancet Neurology aimed to develop a prognostic model for 6-month functional outcome in 679 patients with mild traumatic brain injury (mTBI). In their model, the authors used a multifactorial approach by including sociodemographic, injury-related, and pre-injury factors, as well as indicators of stress after injury and coping strategies. Of the factors measured on admission to the emergency department, lower education, female sex, mental health problems before injury, neck pain, lower Glasgow Coma Scale scores, shorter post-traumatic amnesia, and the absence of alcohol intoxication were found to be associated with incomplete recovery at 6 months. Of factors measured 2 weeks after injury, depression, anxiety, post-traumatic complaints, and passive and avoidant coping styles were also associated with worse 6-month outcome. These were combined in two prognostic models to predict 6-month functional outcome: one applicable using only information recorded on admission to the emergency department,
and one using admission information and data collected at 2 weeks after injury. The predictor effects found in the study by van der Naalt and colleagues1 were broadly in line with findings from systematic reviews on prognosis following mTBI.2–4 However, two relatively novel predictors were identified. First, in previous analyses, van der Naalt and colleagues have been the first to show a prognostic effect of neck pain in a prospective multicentre study with an adequate sample size. Their findings were congruent with the emerging view that concomitant cervical spinal injury might contribute to prolonged symptom presentation after mTBI.5 Second, the authors now examined the mediating role of coping strategies. Although the importance of adequate coping following mTBI has been frequently proposed,6 the study by van der Naalt and colleagues provides the first evidence for the detrimental effect of passive coping and the possible protective effect of avoidant coping. These findings could have important consequences for clinical practice, since both predictors might be considered specific targets for treatment (ie, vestibular rehabilitation therapy to treat cervical spinal injury and neck pain, and cognitive behavioural therapy to train adaptive coping strategies). It is known that, even after mTBI, incomplete recovery and persistence of subjective complaints are highly prevalent.7,8 This clinical problem was also described by van der Naalt and colleagues; incomplete recovery, defined by a Glasgow Outcome Scale-Extended score of less than 8, was present in almost half of the patients at 6 months after injury. Early identification of these patients at high risk might provide opportunities for treatment, and thereby prevent or reduce long-term sequelae. However, no prognostic methods are available yet to identify patients at high risk. Ideally, prognostic methods in mTBI should be administered during the emergency department visit, since patients are rarely followed-up routinely.9 However, in line with a previous www.thelancet.com/neurology Vol 16 July 2017
Comment
study,7 van der Naalt and colleagues found that a model based only on variables measured at the emergency department was poor at identifying patients with incomplete recovery (Area Under the Curve [AUC] after bootstrap validation=0·69). The addition of psychological symptoms and coping strategy, measured 2 weeks after injury, significantly improved the model, and that model has a fair discriminative ability (AUC after bootstrap validation=0·77). On the basis of these results, van der Naalt and colleagues discuss the possibility of contacting patients (by phone or mail) identified at the emergency department as being at high risk for incomplete recovery to inquire about the patients’ stress and coping 2 weeks after injury. However, since the discriminative ability of the emergency department model is poor, this strategy is likely to result in large numbers of false-positive and false-negative findings, and can put into question the usefulness of this strategy for clinical practice. Future research should investigate how such a two-step approach could be improved. Furthermore, van der Naalt and colleagues report that the prevalence of anxiety, depression, and post-traumatic stress remained stable between 2 weeks and 6 months after injury. Therefore, it can be debated whether prediction modelling of 6-month outcome is the most effective strategy in identifying patients prone to worsening after mTBI. An alternative strategy would be to schedule appointments for all patients experiencing substantial symptoms during the first weeks after injury. This could probably be done by general practitioners who can be trained to provide patient education, assess symptoms,
examine potential concomitant diseases, and refer to specific treatment facilities if necessary. The feasibility and effectiveness of different follow-up approaches after mTBI should be investigated in future studies. *Hester F Lingsma, Maryse C Cnossen Center for Medical Decision Making, Department of Public Health, Erasmus Medical Center Rotterdam, 3000 CA Rotterdam, Netherlands [email protected] We declare no competing interests. 1 2 3
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van der Naalt J, Timmermans ME, de Koning ME, et al. Early predictors of outcome after mild traumatic brain injury (UPFRONT): an observational cohort study. Lancet Neurol 2017; 16: 532–40. Silverberg ND, Gardner AJ, Brubacher JR, Panenka WJ, Li JJ, Iverson GL. Systematic review of multivariable prognostic models for mild traumatic brain injury. J Neurotrauma 2015; 32: 517–26. Carroll L, Cassidy JD, Cancelliere C, et al. A systematic review of the prognosis after mild traumatic brain injury in adults: cognitive, psychiatric and mortality outcomes. Results of the International Collaboration on mTBI Prognosis (ICoMP). Brain Injury 2014; 28: 729. Cassidy JD, Cancelliere C, Carroll LJ, et al. Systematic review of self-reported prognosis in adults after mild traumatic brain injury: results of the International Collaboration on Mild Traumatic Brain Injury Prognosis. Arch Phys Med Rehabil 2014; 95 (suppl): S132–51. Marshall CM, Vernon H, Leddy JJ, Baldwin BA. The role of the cervical spine in post-concussion syndrome. Phys Sportsmed 2015; 43: 274–84. Silverberg ND, Iverson GL. Etiology of the post-concussion syndrome: physiogenesis and psychogenesis revisited. NeuroRehabilitation 2011; 29: 317–29. Cnossen MC, Winkler EA, Yue JK, et al. Development of a Prediction model for post-concussive symptoms following mild traumatic brain injury: a TRACK-TBI pilot study. J Neurotrauma 2017; published online March 27. DOI:10.1089/neu.2016.4819. Lingsma HF, Yue JK, Maas AI, Steyerberg EW, Manley GT. Outcome prediction after mild and complicated mild traumatic brain injury: external validation of existing models and identification of new predictors using the TRACK-TBI pilot study. J Neurotrauma 2015; 32: 83–94. Foks KA, Cnossen MC, Dippel DW, et al. Management of mild traumatic brain injury at the emergency department and hospital admission in Europe: a survey of 71 neurotrauma centers participating in the CENTER-TBI study. J Neurotrauma 2017; published online April 11. DOI:10.1089/neu.2016.4919.
Gadolinium deposition: practical guidelines in the face of uncertainty Gadolinium-based contrast agents (GBCAs) are commonly used in MRI examinations to highlight tissues after intravenous injection. These contrast agents have proven indispensable for the diagnosis and monitoring of neurological diseases and are an invaluable research tool for the development of treatments and in the investigation of pathophysiology. For example, in patients with multiple sclerosis, gadolinium-enhancing lesions are a surrogate marker www.thelancet.com/neurology Vol 16 July 2017
of disease activity and their identification can hasten diagnosis.1 GBCAs, like all administered drugs, have potential side-effects, including allergic reactions. Importantly, GBCAs are contraindicated in patients with renal failure, in whom these agents are associated with development of nephrogenic systemic fibrosis. A new concern over the safety of GBCAs arose following reports of a link between hyperintensity in deep grey matter structures
See Personal View page 564
495
2
3
Lamberink HJ, Otte WM, Geerts AT, et al. Individualised prediction model of seizure recurrence and long-term outcomes after withdrawal of antiepileptic drugs in seizure-free patients: a systematic review and individual participant data meta-analysis. Lancet Neurol 2017; published online May 5. http://dx.doi.org/10.1016/ S1474-4422(17)30114-X. French JA, Pedley TA. Clinical practice. Initial management of epilepsy. N Engl J Med 2008; 359: 166–76.
4 5
Strozzi I, Nolan SJ, Sperling MR, Wingerchuk DM, Sirven J. Early versus late antiepileptic drug withdrawal for people with epilepsy in remission. Cochrane Database Syst Rev 2015; 2: CD001902. Schmidt D, Sillanpää M. Stopping epilepsy treatment in seizure remission: good or bad or both? Seizure 2017; 44: 157–61.
Identification of patients at risk for poor outcome after mTBI
Life in View/Science Photo Library
See Articles page 532
494
The study by Joukje van der Naalt and colleagues1 in The Lancet Neurology aimed to develop a prognostic model for 6-month functional outcome in 679 patients with mild traumatic brain injury (mTBI). In their model, the authors used a multifactorial approach by including sociodemographic, injury-related, and pre-injury factors, as well as indicators of stress after injury and coping strategies. Of the factors measured on admission to the emergency department, lower education, female sex, mental health problems before injury, neck pain, lower Glasgow Coma Scale scores, shorter post-traumatic amnesia, and the absence of alcohol intoxication were found to be associated with incomplete recovery at 6 months. Of factors measured 2 weeks after injury, depression, anxiety, post-traumatic complaints, and passive and avoidant coping styles were also associated with worse 6-month outcome. These were combined in two prognostic models to predict 6-month functional outcome: one applicable using only information recorded on admission to the emergency department,
and one using admission information and data collected at 2 weeks after injury. The predictor effects found in the study by van der Naalt and colleagues1 were broadly in line with findings from systematic reviews on prognosis following mTBI.2–4 However, two relatively novel predictors were identified. First, in previous analyses, van der Naalt and colleagues have been the first to show a prognostic effect of neck pain in a prospective multicentre study with an adequate sample size. Their findings were congruent with the emerging view that concomitant cervical spinal injury might contribute to prolonged symptom presentation after mTBI.5 Second, the authors now examined the mediating role of coping strategies. Although the importance of adequate coping following mTBI has been frequently proposed,6 the study by van der Naalt and colleagues provides the first evidence for the detrimental effect of passive coping and the possible protective effect of avoidant coping. These findings could have important consequences for clinical practice, since both predictors might be considered specific targets for treatment (ie, vestibular rehabilitation therapy to treat cervical spinal injury and neck pain, and cognitive behavioural therapy to train adaptive coping strategies). It is known that, even after mTBI, incomplete recovery and persistence of subjective complaints are highly prevalent.7,8 This clinical problem was also described by van der Naalt and colleagues; incomplete recovery, defined by a Glasgow Outcome Scale-Extended score of less than 8, was present in almost half of the patients at 6 months after injury. Early identification of these patients at high risk might provide opportunities for treatment, and thereby prevent or reduce long-term sequelae. However, no prognostic methods are available yet to identify patients at high risk. Ideally, prognostic methods in mTBI should be administered during the emergency department visit, since patients are rarely followed-up routinely.9 However, in line with a previous www.thelancet.com/neurology Vol 16 July 2017
Comment
study,7 van der Naalt and colleagues found that a model based only on variables measured at the emergency department was poor at identifying patients with incomplete recovery (Area Under the Curve [AUC] after bootstrap validation=0·69). The addition of psychological symptoms and coping strategy, measured 2 weeks after injury, significantly improved the model, and that model has a fair discriminative ability (AUC after bootstrap validation=0·77). On the basis of these results, van der Naalt and colleagues discuss the possibility of contacting patients (by phone or mail) identified at the emergency department as being at high risk for incomplete recovery to inquire about the patients’ stress and coping 2 weeks after injury. However, since the discriminative ability of the emergency department model is poor, this strategy is likely to result in large numbers of false-positive and false-negative findings, and can put into question the usefulness of this strategy for clinical practice. Future research should investigate how such a two-step approach could be improved. Furthermore, van der Naalt and colleagues report that the prevalence of anxiety, depression, and post-traumatic stress remained stable between 2 weeks and 6 months after injury. Therefore, it can be debated whether prediction modelling of 6-month outcome is the most effective strategy in identifying patients prone to worsening after mTBI. An alternative strategy would be to schedule appointments for all patients experiencing substantial symptoms during the first weeks after injury. This could probably be done by general practitioners who can be trained to provide patient education, assess symptoms,
examine potential concomitant diseases, and refer to specific treatment facilities if necessary. The feasibility and effectiveness of different follow-up approaches after mTBI should be investigated in future studies. *Hester F Lingsma, Maryse C Cnossen Center for Medical Decision Making, Department of Public Health, Erasmus Medical Center Rotterdam, 3000 CA Rotterdam, Netherlands [email protected] We declare no competing interests. 1 2 3
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5 6 7
8
9
van der Naalt J, Timmermans ME, de Koning ME, et al. Early predictors of outcome after mild traumatic brain injury (UPFRONT): an observational cohort study. Lancet Neurol 2017; 16: 532–40. Silverberg ND, Gardner AJ, Brubacher JR, Panenka WJ, Li JJ, Iverson GL. Systematic review of multivariable prognostic models for mild traumatic brain injury. J Neurotrauma 2015; 32: 517–26. Carroll L, Cassidy JD, Cancelliere C, et al. A systematic review of the prognosis after mild traumatic brain injury in adults: cognitive, psychiatric and mortality outcomes. Results of the International Collaboration on mTBI Prognosis (ICoMP). Brain Injury 2014; 28: 729. Cassidy JD, Cancelliere C, Carroll LJ, et al. Systematic review of self-reported prognosis in adults after mild traumatic brain injury: results of the International Collaboration on Mild Traumatic Brain Injury Prognosis. Arch Phys Med Rehabil 2014; 95 (suppl): S132–51. Marshall CM, Vernon H, Leddy JJ, Baldwin BA. The role of the cervical spine in post-concussion syndrome. Phys Sportsmed 2015; 43: 274–84. Silverberg ND, Iverson GL. Etiology of the post-concussion syndrome: physiogenesis and psychogenesis revisited. NeuroRehabilitation 2011; 29: 317–29. Cnossen MC, Winkler EA, Yue JK, et al. Development of a Prediction model for post-concussive symptoms following mild traumatic brain injury: a TRACK-TBI pilot study. J Neurotrauma 2017; published online March 27. DOI:10.1089/neu.2016.4819. Lingsma HF, Yue JK, Maas AI, Steyerberg EW, Manley GT. Outcome prediction after mild and complicated mild traumatic brain injury: external validation of existing models and identification of new predictors using the TRACK-TBI pilot study. J Neurotrauma 2015; 32: 83–94. Foks KA, Cnossen MC, Dippel DW, et al. Management of mild traumatic brain injury at the emergency department and hospital admission in Europe: a survey of 71 neurotrauma centers participating in the CENTER-TBI study. J Neurotrauma 2017; published online April 11. DOI:10.1089/neu.2016.4919.
Gadolinium deposition: practical guidelines in the face of uncertainty Gadolinium-based contrast agents (GBCAs) are commonly used in MRI examinations to highlight tissues after intravenous injection. These contrast agents have proven indispensable for the diagnosis and monitoring of neurological diseases and are an invaluable research tool for the development of treatments and in the investigation of pathophysiology. For example, in patients with multiple sclerosis, gadolinium-enhancing lesions are a surrogate marker www.thelancet.com/neurology Vol 16 July 2017
of disease activity and their identification can hasten diagnosis.1 GBCAs, like all administered drugs, have potential side-effects, including allergic reactions. Importantly, GBCAs are contraindicated in patients with renal failure, in whom these agents are associated with development of nephrogenic systemic fibrosis. A new concern over the safety of GBCAs arose following reports of a link between hyperintensity in deep grey matter structures
See Personal View page 564
495