Study design: Cross-section design. Objectives: The development of reliable screen technology for predicting those at risk of depression in the long-term remains a challenge. The objective of this research was to determine factors that classify correctly adults with spinal cord injury (SCI) with depressed mood and to develop a diagnostic algorithm that could be applied for prediction of depressed mood in the long-term. Setting: SCI rehabilitation unit, rehabilitation outpatient clinic and Australian community. Methods: Participants included 107 adults with SCI. The assessment regimen included demographic and injury variables, negative mood states, pain intensity, health-related quality of life and self-efficacy. Participants were divided into those with 'normal' mood versus those with elevated depressed mood. Discriminant function analysis (DFA) was then used to isolate factors that in combination, best classify the presence or absence of depressed mood. Results: At the time of assessment, 24 participants (22.4%) had elevated depressed mood. DFA identified six factors that discriminated between those with depressed mood (Po0.01) and those with normal mood, explaining 61% of the variance. Factors consisted of pain intensity, mental health, emotional and social functioning, self-efficacy and fatigue. DFA correctly classified 91.7% (n ¼ 22 of 24) of those with depressed mood and 95.2% (n ¼ 79 of 83) of those without. Demographic, injury and physical health function variables were not found to discriminate depressed mood. Conclusion: Clinical implications of applying a diagnostic algorithm for detecting depression in adults with SCI are discussed. Prospective research is needed to test the predictive efficacy of the algorithm.
Study design: Group cohort design. Objectives: To determine the influence of spinal cord injury (SCI) and neurological level on heart rate variability (HRV) and associations with fatigue. Setting: SCI rehabilitation outpatient and community settings in New South Wales, Australia. Methods: Participants included 45 adults with SCI living in the community and 44 able-bodied controls. Socio-demographic, neurological injury, psychological, HRV and eye blink variables were assessed. Multivariate analysis of variance and post hoc protected t-tests were used to determine differences in HRV and fatigue as a function of the neurological level. Pearson's correlation analysis was used to determine the relationships between these factors. Results: Participants with SCI had significantly reduced sympathetic activity. Those with tetraplegia had lowered sympathetic activity compared with those with paraplegia and able-bodied controls. Neither were differences in parasympathetic activity found between groups nor were there any significant differences found for the time domain or non-linear domains. Higher levels of fatigue were found in the SCI sample, and participants with tetraplegia had higher fatigue levels compared with those with paraplegia. Fatigued participants were more likely to have altered autonomic function--that is, reduced sympathetic activity. Conclusions: Higher levels of neurological impairment in people with SCI are more likely to result in disordered cardiovascular control involving reduced sympathetic activity, whereas elevated fatigue was found to be associated with increased sympathetic dysfunction. Findings highlight the need to address risks associated with this dysfunction, such as improved HRV and fatigue screening for people with SCI and improved education on cardiovascular risk factors.
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