This report found that sleep problems in the acute post-TBI period (within 3 months of injury) generally worsened compared to recall of sleep problems before the injury in most domains (other than snoring). Sleep problems in the immediate TBI period can be secondary to numerous factors: injury to sleep regulating centres [11
], pain, comorbid medical problems, side effects of medications, or a symptom of a mood and/or anxiety disorder [12
]. From this report, new onset anxiety disorder with generalized anxiety features that developed for the first time after TBI (GADGMCC) was the most consistent correlate of various specific sleep disturbances and of the global measures of sleep problems (Sleep Problems Index 1 and 2). Mood disorder with major depressive-like episode that developed for the first time after TBI also appeared to be related to overall sleep problems, but the relationship was not as consistent.
Other TBI studies have also found a significant association between sleep problems and anxiety/depression [10
]. In a retrospective analysis of 60 patients 3 months to 2 years post-TBI, Verma et al. [10
] found that patients with sleep onset insomnia had higher anxiety scores as assessed by the Hamilton Anxiety Scale (HAS) and sleep maintenance insomnia was associated with higher Beck Depression scores. Similarly, Parcell et al. [13
] have also found increased levels of anxiety and depression as measured by the Hamilton Anxiety and Depression scale (HADS) in chronic TBI patients compared to age and gender matched controls. However, both these studies did not use structured psychiatric interviews to diagnose depression or anxiety. While scales such as the HAS and HADS measure the severity of anxiety or depression, they are not diagnostic of these disorders. This is particularly important in brain injured patients who present with a number of somatic symptoms which could be secondary to the brain injury itself. Despite this important finding of anxiety as a predictor of sleep disturbance, the authors are unable to comment on the direction of the relationship as anxiety can be both a cause and consequence of sleep disturbance.
Severity of TBI (as assessed by GCS) has previously been reported in the TBI literature as a significant factor in sleep disturbances [4
], but it was not significant in this study. These findings are, on the other hand, supportive of a study by Castriotta et al. [14
], who found no relationship between severity of TBI and daytime sleepiness in a study of 87 chronic TBI patients using objective measures to assess sleep disturbances. Similarly, Baumann et al. [15
] found that in a sample of 76 TBI patients in the chronic stage of injury, there was a high prevalence of sleep disturbance but no association between sleep problems and severity or localization of TBI.
This study also did not find the presence of body injury or medical comorbidity to be significantly correlated with sleep disturbances. However, other studies have found medical problems and pain to be significant contributors to sleep problems [1
]. The lack of association between medical burden and sleep disturbance in this study could be because the presence of pain, number of medications and nature and severity of medical problems were grouped under one category, the GMHR scale. Future studies should better define medical problems and also rate the severity of pain.
This study also did not find any association between sleep adequacy and any of the demographic or clinical variables. This may be due to not specifically collecting data on variables that correlate with poor sleep adequacy in the general population, including increased use of health services [17
], use of hypnotic agents [18
], impaired functional capabilities and poor health-related quality of life [19
Additionally, some of the other sleep variables such as snoring were only associated with increase in age in this study. Studies in the general population have found older age to be a risk factor for snoring [20
]. However, other well known risk factors for snoring such as body mass index and oropharyngeal abnormalities were not analysed in this study [21
]. Additionally, brain pathology causes of snoring, such as stroke, are often localized to the brainstem [22
]. Neuroimaging was not part of this research study and hence one is unable to comment on the brain pathology associated with post-TBI snoring.
Female gender was the only significant predictor of shortness of breath and headache in this study. Even though it is well known that females tend to somatize more males [23
] and post-traumatic headaches are more common in women [26
], other mechanisms affecting this variable (such as pulmonary, cardiac, or muscular factors; use of analgesics) should be looked into.
The major limitations of this paper are that a subjective measure was used to assess sleep disturbance and the assessment of baseline sleep disturbances may have been subject to recall bias. Another limitation is the lack of information on presence/absence of pain, nature and severity of medical problems and medications used by the subjects before and after injury. It is well known that these factors contribute to sleep problems in both TBI and non-TBI patients [1
]. Even though the GMHR is a global measure of medical problems, its use has not been validated in the TBI population and may not capture the different components of medical burden (nature and severity of medical problems, types and frequency of medication use, presence/severity of pain).
Despite these limitations, the study has several strengths. It is one of the few studies to analyse sleep problems in the acute TBI period other than Keshavan et al. [28
] and Dikmen et al. [29
]. This study is the first to evaluate sleep problems in the pre- and post-TBI period in adults with varying TBI severity. Parsons and Van Beek [30
] have done similar comparisons of pre-TBI and post-TBI sleep problems, but restricted their study to mild TBI in the age group 16-30. This study is also the first to look at new-onset anxiety and depressive disorders using structured psychiatric interviews. Other strengths include the use of validated measures and the use of regression to determine predictors