Medicine (RMH Academic Centre) - Research Publications

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Type: Journal Article × Start date: 2016 × End date: 2017 × Author: Berk, Michael ×

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    Staging in bipolar disorder: from theoretical framework to clinical utility
    Berk, M ; Post, R ; Ratheesh, A ; Gliddon, E ; Singh, A ; Vieta, E ; Carvalho, AF ; Ashton, MM ; Berk, L ; Cotton, SM ; McGorry, PD ; Fernandes, BS ; Yatham, LN ; Dodd, S (WILEY, 2017-10)
    Illness staging is widely utilized in several medical disciplines to help predict course or prognosis, and optimize treatment. Staging models in psychiatry in general, and bipolar disorder in particular, depend on the premise that psychopathology moves along a predictable path: an at-risk or latency stage, a prodrome progressing to a first clinical threshold episode, and one or more recurrences with the potential to revert or progress to late or end-stage manifestations. The utility and validity of a staging model for bipolar disorder depend on its linking to clinical outcome, treatment response and neurobiological measures. These include progressive biochemical, neuroimaging and cognitive changes, and potentially stage-specific differences in response to pharmacological and psychosocial treatments. Mechanistically, staging models imply the presence of an active disease process that, if not remediated, can lead to neuroprogression, a more malignant disease course and functional deterioration. Biological elements thought to be operative in bipolar disorder include a genetic diathesis, physical and psychic trauma, epigenetic changes, altered neurogenesis and apoptosis, mitochondrial dysfunction, inflammation, and oxidative stress. Many available agents, such as lithium, have effects on these targets. Staging models also suggest the utility of stage-specific treatment approaches that may not only target symptom reduction, but also impede illness neuroprogression. These treatment approaches range from prevention for at-risk individuals, to early intervention strategies for prodromal and newly diagnosed individuals, complex combination therapy for rapidly recurrent illness, and palliative-type approaches for those at chronic, late stages of illness. There is hope that prompt initiation of potentially disease modifying therapies may preclude or attenuate the cognitive and structural changes seen in the later stages of bipolar disorder. The aims of this paper are to: a) explore the current level of evidence supporting the descriptive staging of the syndromal pattern of bipolar disorder; b) describe preliminary attempts at validation; c) make recommendations for the direction of further studies; and d) provide a distillation of the potential clinical implications of staging in bipolar disorder within a broader transdiagnostic framework.
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    Getting RID of the blues: Formulating a Risk Index for Depression (RID) using structural equation modeling
    Dipnall, JF ; Pasco, JA ; Berk, M ; Williams, LJ ; Dodd, S ; Jacka, FN ; Meyer, D (SAGE PUBLICATIONS LTD, 2017-11)
    OBJECTIVE: While risk factors for depression are increasingly known, there is no widely utilised depression risk index. Our objective was to develop a method for a flexible, modular, Risk Index for Depression using structural equation models of key determinants identified from previous published research that blended machine-learning with traditional statistical techniques. METHODS: Demographic, clinical and laboratory variables from the National Health and Nutrition Examination Study (2009-2010, N = 5546) were utilised. Data were split 50:50 into training:validation datasets. Generalised structural equation models, using logistic regression, were developed with a binary outcome depression measure (Patient Health Questionnaire-9 score ⩾ 10) and previously identified determinants of depression: demographics, lifestyle-environs, diet, biomarkers and somatic symptoms. Indicative goodness-of-fit statistics and Areas Under the Receiver Operator Characteristic Curves were calculated and probit regression checked model consistency. RESULTS: The generalised structural equation model was built from a systematic process. Relative importance of the depression determinants were diet (odds ratio: 4.09; 95% confidence interval: [2.01, 8.35]), lifestyle-environs (odds ratio: 2.15; 95% CI: [1.57, 2.94]), somatic symptoms (odds ratio: 2.10; 95% CI: [1.58, 2.80]), demographics (odds ratio:1.46; 95% CI: [0.72, 2.95]) and biomarkers (odds ratio:1.39; 95% CI: [1.00, 1.93]). The relationships between demographics and lifestyle-environs and depression indicated a potential indirect path via somatic symptoms and biomarkers. The path from diet was direct to depression. The Areas under the Receiver Operator Characteristic Curves were good (logistic:training = 0.850, validation = 0.813; probit:training = 0.849, validation = 0.809). CONCLUSION: The novel Risk Index for Depression modular methodology developed has the flexibility to add/remove direct/indirect risk determinants paths to depression using a structural equation model on datasets that take account of a wide range of known risks. Risk Index for Depression shows promise for future clinical use by providing indications of main determinant(s) associated with a patient's predisposition to depression and has the ability to be translated for the development of risk indices for other affective disorders.