Examination of the predictive value of structural magnetic resonance scans in bipolar disorder:a pattern classification approach

Background - Bipolar disorder (BD) is one of the leading causes of disability worldwide. Patients are further disadvantaged by delays in accurate diagnosis ranging between 5 and 10 years. We applied Gaussian process classifiers (GPCs) to structural magnetic resonance imaging (sMRI) data to evaluate the feasibility of using pattern recognition techniques for the diagnostic classification of patients with BD. Method - GPCs were applied to gray (GM) and white matter (WM) sMRI data derived from two independent samples of patients with BD (cohort 1: n = 26; cohort 2: n = 14). Within each cohort patients were matched on age, sex and IQ to an equal number of healthy controls. Results - The diagnostic accuracy of the GPC for GM was 73% in cohort 1 and 72% in cohort 2; the sensitivity and specificity of the GM classification were respectively 69% and 77% in cohort 1 and 64% and 99% in cohort 2. The diagnostic accuracy of the GPC for WM was 69% in cohort 1 and 78% in cohort 2; the sensitivity and specificity of the WM classification were both 69% in cohort 1 and 71% and 86% respectively in cohort 2. In both samples, GM and WM clusters discriminating between patients and controls were localized within cortical and subcortical structures implicated in BD. Conclusions - Our results demonstrate the predictive value of neuroanatomical data in discriminating patients with BD from healthy individuals. The overlap between discriminative networks and regions implicated in the pathophysiology of BD supports the biological plausibility of the classifiers.

Challenging the predictive ability of accounting techniques in modelling organizational futures

This article considers the role of accounting in organisational decision making. It challenges the rational nature of decisions made in organisations through the use of accounting models and the problems of predicting the future through the use of such models. The use of accounting in this manner is evaluated from an epochal postmodern stance. Issues raised by chaos theory and the uncertainty principle are used to demonstrate problems with the predictive ability of accounting models. The authors argue that any consideration of the predictive value of accounting needs to change to incorporate a recognition of the turbulent external environment, if it is to be of use for organisational decision making. Thus it is argued that the role of accounting as a mechanism for knowledge creation regarding the future is fundamentally flawed. We take this as a starting-point to argue for the real purpose of the use of the predictive techniques of accounting, using its ritualistic role in the context of myth creation to argue for the cultural benefits of the use of such flawed techniques.

The predictive ability of clinical tests for contact lens induced dry eye

Approximately half of current contact lens wearers suffer from dryness and discomfort, particularly towards the end of the day. Contact lens practitioners have a number of dry eye tests available to help them to predict which of their patients may be at risk of contact lens drop out and advise them accordingly. This thesis set out to rationalize them to see if any are of more diagnostic significance than others. This doctorate has found: (1) The Keratograph, a device which permits an automated, examiner independent technique for measuring non invasive tear break up time (NITBUT) measured NITBUT consistently shorter than measurements recorded with the Tearscope. When measuring central corneal curvature the spherical equivalent power of the cornea was measured as being significantly flatter than with a validated automated keratometer. (2) Non-invasive and invasive tear break-up times significantly correlated to each other, but not the other tear metrics. Symptomology, assessed using the OSDI questionnaire, correlated more with those tests indicating possible damage to the ocular surface (including LWE, LIPCOF and conjunctival staining) than with tests of either tear volume or stability. Cluster analysis showed some statistically significant groups of patients with different sign and symptom profiles. The largest cluster demonstrated poor tear quality with both non-invasive and invasive tests, low tear volume and more symptoms. (3) Care should be taken in fitting patients new to contact lenses if they have a NITBUT less than 10s or an OSDI comfort rating greater than 4.2 as they are more likely to drop-out within the first 6 months. Cluster analysis was not found to be beneficial in predicting which patients will succeed with lenses and which will not. A combination of the OSDI questionnaire and a NITBUT measurement was most useful both in diagnosing dry eye and in predicting contact lens drop out.