Predicting Depression Following Mild Traumatic Brain Injury

Levin, Harvey S.; McCauley, Stephen R.; Josic, Claudia Pedroza; Boake, Corwin; Brown, Sharon A.; Goodman, Heather S.; Merritt, Shirley G.; Brundage, Susan I.

doi:10.1001/archpsyc.62.5.523

Cited by 103 publications

(66 citation statements)

References 49 publications

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“…[78][79][80] Past studies have suggested that a concussion can cause lasting defi cits through changes in physiology (e.g., disrupted serotonin pathways), mood (e.g., posttraumatic stress disorder) or behaviour (e.g., disinhibition with impulsivity). [81][82][83][84] Cognitive dissonance could also lead patients and clinicians to attribute injuries after weekend recreation to misadventure, whereas injuries following weekday occupation might be attributed to the employer. [85][86][87] With hindsight, a difference in activity restriction or cognitive dissonance might arise if the injury event was self-initiated.…”

Section: Discussionmentioning

confidence: 99%

Risk of suicide after a concussion

Fralick

Thiruchelvam

Tien

et al. 2016

CMAJ

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Section: Discussionmentioning

confidence: 99%

Risk of suicide after a concussion

Fralick

Thiruchelvam

Tien

et al. 2016

CMAJ

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“…As seen in Figure 1, the post-injury environment could moderate recovery. A supportive environment in which the person gradually resumes activities may enhance resolution of PCS, whereas premature demands to resume full responsibilities despite residual PCS and cognitive deficit may lead to secondary anxiety and depression 66 and prolong secondary brain insult, such as inflammation and excitotoxicity. Empirical testing of current regimens, such as ''cognitive rest'' with gradual resumption of physical training, however, is needed to determine the optimal postinjury environment.…”

Section: Summary and Conceptual Model Of Mtbimentioning

confidence: 99%

Mild Traumatic Brain Injury in Translation

Levin

Robertson

2013

Journal of Neurotrauma

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This Introduction to a Special Issue on Mild Traumatic Brain Injury (mTBI) highlights the methodological challenges in outcome studies and clinical trials involving patients who sustain mTBI. Recent advances in brain imaging and portable, computerized cognitive tasks have contributed to protocols that are sensitive to the effects of mTBI and efficient in time for completion. Investigation of civilian mTBI has been extended to single and repeated injuries in athletes and blastrelated mTBI in service members and veterans. Despite differences in mechanism of injury, there is evidence for similar effects of acceleration-deceleration and blast mechanisms of mTBI on cognition. Investigation of repetitive mTBI suggests that the effects may be cumulative and that repeated mTBI and repeated subconcussive head trauma may lead to neurodegenerative conditions. Although animal models of mTBI using cortical impact and fluid percussion injury in rodents have been able to reproduce some of the cognitive deficits frequently exhibited by patients after mTBI, modeling post-concussion symptoms is difficult. Recent use of closed head and blast injury animal models may more closely approximate clinical mTBI. Translation of interventions that are developed in animal models to patients with mTBI is a priority for the research agenda. This Special Issue on mTBI integrates basic neuroscience studies using animal models with studies of human mTBI, including the cognitive sequelae, persisting symptoms, brain imaging, and host factors that facilitate recovery.

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“…34 In a study that evaluated the predicted value of multiple standard psychological distress questionnaires in predicting future depression in breast cancer patients, the best performance had a sensitivity and specifi city of 76.9% and 78.8%, respectively, without a validation sample. 35 Results of our study are also comparable with many other prediction rules and screening procedures currently used in primary care.…”

Section: -Specificitymentioning

confidence: 99%

Predicting Future Risk of Depressive Episode in Adolescents: The Chicago Adolescent Depression Risk Assessment (CADRA)

Voorhees¹,

Paunesku²,

Gollan³

et al. 2008

The Annals of Family Medicine

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PURPOSE A risk prediction index, similar to those used for other disorders, such as cardiovascular disease, would facilitate depression prevention by identifying those who would benefi t most from preventative measures in primary care settings. METHODSThe National Longitudinal Study of Adolescent Health enrolled a representative sample of US adolescents and included a baseline survey in 1995 and a 1-year follow-up survey in 1996 (n = 4,791). We used baseline risk factors (social and cognitive vulnerability and mood) to predict onset of a depressive episode at 1-year follow-up (eg, future risk of episode) and used boosted classifi cation and regression trees to develop a prediction index, The Chicago Adolescent Depression Risk Assessment, suitable for a personal computer or hand-held device. True and false positives and negatives were determined based on concordance and discordance, respectively, between the prediction-category-based index and actual classifi cation-category-based 1-year follow-up outcome. We evaluated the performance of the index for the entire sample and with several depressive episode outcomes using the standard Center for Epidemiologic Studies Depression (CES-D) scale cutoffs.RESULTS The optimal prediction model (including depressed mood and social vulnerability) was a 20-item model with an area under the receiver operating characteristics curve of 0.80 (95% CI, 0.714-0.870), a sensitivity of 75%, and a specifi city of 76.5%. For depressive episode, the positive predictive values in the highest risk group (level 4) was from 13.75% for a depressive episode to 63.57% for CES-D score of greater than 16 (mild to moderate depressed mood or above) at follow-up. Conversely, the negative predictive value of being in the lowest 2 levels (0 or 1) was 99.38% for a depressive episode and 89.19% for a CES-D score of greater than 16.CONCLUSIONS Our model predicts a depressive episode and other depressive outcomes at 1-year follow-up. Positive and negative predictive values could enable primary care physicians and families to intervene on adolescents at highest risk.

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Predicting Depression Following Mild Traumatic Brain Injury

Abstract: This study supports the feasibility of identifying patients with mild traumatic brain injury who are at high risk for developing major depressive episode by 3 months' postinjury, which could facilitate selective referral for potential treatment and reduction of negative outcomes.

Cited by 103 publications

References 49 publications

Risk of suicide after a concussion

Risk of suicide after a concussion

Mild Traumatic Brain Injury in Translation

Predicting Future Risk of Depressive Episode in Adolescents: The Chicago Adolescent Depression Risk Assessment (CADRA)

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