Changes of corneal biomechanics with keratoconus

PURPOSE: To perform advanced analysis of the corneal deformation response to air pressure in keratoconics compared with age- and sex-matched controls. METHODS: The ocular response analyzer was used to measure the air pressure-corneal deformation relationship of 37 patients with keratoconus and 37 age (mean 36 ± 10 years)- and sex-matched controls with healthy corneas. Four repeat air pressure-corneal deformation profiles were averaged, and 42 separate parameters relating to each element of the profiles were extracted. Corneal topography and pachymetry were performed with the Orbscan II. The severity of the keratoconus was graded based on a single metric derived from anterior corneal curvatures, difference in astigmatism in each meridian, anterior best-fit sphere, and posterior best-fit sphere. RESULTS: Most of the biomechanical characteristics of keratoconic eyes were significantly different from normal eyes (P <0.001), especially during the initial corneal applanation. With increasing keratoconus severity, the cornea was thinner (r = -0.407, P <0.001), the speed of corneal concave deformation past applanation was quicker (dive; r = -0.314, P = 0.01), and the tear film index was lower (r = -0.319, P = 0.01). The variance in keratoconus severity could be accounted for by the corneal curvature and central corneal thickness (r = 0.80) with biomechanical characteristics contributing an additional 4% (total r = 0.84). The area under the receiver operating characteristic curve was 0.919 ± 0.025 for keratometry alone, 0.965 ± 0.014 with the addition of pachymetry, and 0.972 ± 0.012 combined with ocular response analyzer biomechanical parameters. CONCLUSIONS: Characteristics of the air pressure-corneal deformation profile are more affected by keratoconus than the traditionally extracted corneal hysteresis and corneal resistance factors. These biomechanical metrics slightly improved the detection and severity prediction of keratoconus above traditional keratometric and pachymetric assessment of corneal shape.

Development of a questionnaire to assess the relative subjective benefits of presbyopia correction

Purpose To develop a standardized questionnaire of near visual function and satisfaction to complement visual function evaluations of presbyopic corrections. Setting Eye Clinic, School of Life and Health Sciences, Aston University, Midland Eye Institute and Solihull Hospital, Birmingham, United Kingdom. Design Questionnaire development. Methods A preliminary 26-item questionnaire of previously used near visual function items was completed by patients with monofocal intraocular lenses (IOLs), multifocal IOLs, accommodating IOLs, multifocal contact lenses, or varifocal spectacles. Rasch analysis was used for item reduction, after which internal and test–retest reliabilities were determined. Construct validity was determined by correlating the resulting Near Activity Visual Questionnaire (NAVQ) scores with near visual acuity and critical print size (CPS), which was measured using the Minnesota Low Vision Reading Test chart. Discrimination ability was assessed through receiver-operating characteristic (ROC) curve analysis. Results One hundred fifty patients completed the questionnaire. Item reduction resulted in a 10-item NAVQ with excellent separation (2.92), internal consistency (Cronbach a = 0.95), and test–retest reliability (intraclass correlation coefficient = 0.72). Correlations of questionnaire scores with near visual acuity (r = 0.32) and CPS (r = 0.27) provided evidence of validity, and discrimination ability was excellent (area under ROC curve = 0.91). Conclusion Results show the NAVQ is a reliable, valid instrument that can be incorporated into the evaluation of presbyopic corrections.

To link or not to link: a test of the case linkage principles using serial car theft data

The purpose of the present study is to test the case linkage principles of behavioural consistency and behavioural distinctiveness using serial vehicle theft data. Data from 386 solved vehicle thefts committed by 193 offenders were analysed using Jaccard's, regression and Receiver Operating Characteristic analyses to determine whether objectively observable aspects of crime scene behaviour could be used to distinguish crimes committed by the same offender from those committed by different offenders. The findings indicate that spatial behaviour, specifically the distance between theft locations and between dump locations, is a highly consistent and distinctive aspect of vehicle theft behaviour; thus, intercrime and interdump distance represent the most useful aspects of vehicle theft for the purpose of case linkage analysis. The findings have theoretical and practical implications for understanding of criminal behaviour and for the development of decision-support tools to assist police investigation and apprehension of serial vehicle theft offenders.

Detection of signals corrupted by the combination of Gaussian and Non-Gaussian noise

The detection of signals in the presence of noise is one of the most basic and important problems encountered by communication engineers. Although the literature abounds with analyses of communications in Gaussian noise, relatively little work has appeared dealing with communications in non-Gaussian noise. In this thesis several digital communication systems disturbed by non-Gaussian noise are analysed. The thesis is divided into two main parts. In the first part, a filtered-Poisson impulse noise model is utilized to calulate error probability characteristics of a linear receiver operating in additive impulsive noise. Firstly the effect that non-Gaussian interference has on the performance of a receiver that has been optimized for Gaussian noise is determined. The factors affecting the choice of modulation scheme so as to minimize the deterimental effects of non-Gaussian noise are then discussed. In the second part, a new theoretical model of impulsive noise that fits well with the observed statistics of noise in radio channels below 100 MHz has been developed. This empirical noise model is applied to the detection of known signals in the presence of noise to determine the optimal receiver structure. The performance of such a detector has been assessed and is found to depend on the signal shape, the time-bandwidth product, as well as the signal-to-noise ratio. The optimal signal to minimize the probability of error of; the detector is determined. Attention is then turned to the problem of threshold detection. Detector structure, large sample performance and robustness against errors in the detector parameters are examined. Finally, estimators of such parameters as. the occurrence of an impulse and the parameters in an empirical noise model are developed for the case of an adaptive system with slowly varying conditions.

Development of a near activity visual questionnaire to assess accommodating intraocular lenses

Purpose: To develop a questionnaire that subjectively assesses near visual function in patients with 'accommodating' intraocular lenses (IOLs). Methods: A literature search of existing vision-related quality-of-life instruments identified all questions relating to near visual tasks. Questions were combined if repeated in multiple instruments. Further relevant questions were added and item interpretation confirmed through multidisciplinary consultation and focus groups. A preliminary 19-item questionnaire was presented to 22 subjects at their 4-week visit post first eye phacoemulsification with 'accommodative' IOL implantation, and again 6 and 12 weeks post-operatively. Rasch Analysis, Frequency of Endorsement, and tests of normality (skew and kurtosis) were used to reduce the instrument. Cronbach's alpha and test-retest reliability (intraclass correlation coefficient, ICC) were determined for the final questionnaire. Construct validity was obtained by Pearson's product moment correlation (PPMC) of questionnaire scores to reading acuity (RA) and to Critical Print Size (CPS) reading speed. Criterion validity was obtained by receiver operating characteristic (ROC) curve analysis and dimensionality of the questionnaire was assessed by factor analysis. Results: Rasch Analysis eliminated nine items due to poor fit statistics. The final items have good separation (2.55), internal consistency (Cronbach's α = 0.97) and test-retest reliability (ICC = 0.66). PPMC of questionnaire scores with RA was 0.33, and with CPS reading speed was 0.08. Area under the ROC curve was 0.88 and Factor Analysis revealed one principal factor. Conclusion: The pilot data indicates the questionnaire to be internally consistent, reliable and a valid instrument that could be useful for assessing near visual function in patients with 'accommodating' IOLS. The questionnaire will now be expanded to include other types of presbyopic correction. © 2007 British Contact Lens Association.

Analysis of nocturnal oxygen saturation recordings using kernel entropy to assist in sleep apnea-hypopnea diagnosis

In this study, a new entropy measure known as kernel entropy (KerEnt), which quantifies the irregularity in a series, was applied to nocturnal oxygen saturation (SaO 2) recordings. A total of 96 subjects suspected of suffering from sleep apnea-hypopnea syndrome (SAHS) took part in the study: 32 SAHS-negative and 64 SAHS-positive subjects. Their SaO 2 signals were separately processed by means of KerEnt. Our results show that a higher degree of irregularity is associated to SAHS-positive subjects. Statistical analysis revealed significant differences between the KerEnt values of SAHS-negative and SAHS-positive groups. The diagnostic utility of this parameter was studied by means of receiver operating characteristic (ROC) analysis. A classification accuracy of 81.25% (81.25% sensitivity and 81.25% specificity) was achieved. Repeated apneas during sleep increase irregularity in SaO 2 data. This effect can be measured by KerEnt in order to detect SAHS. This non-linear measure can provide useful information for the development of alternative diagnostic techniques in order to reduce the demand for conventional polysomnography (PSG). © 2011 IEEE.

Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models

Background - The binding between peptide epitopes and major histocompatibility complex proteins (MHCs) is an important event in the cellular immune response. Accurate prediction of the binding between short peptides and the MHC molecules has long been a principal challenge for immunoinformatics. Recently, the modeling of MHC-peptide binding has come to emphasize quantitative predictions: instead of categorizing peptides as "binders" or "non-binders" or as "strong binders" and "weak binders", recent methods seek to make predictions about precise binding affinities. Results - We developed a quantitative support vector machine regression (SVR) approach, called SVRMHC, to model peptide-MHC binding affinities. As a non-linear method, SVRMHC was able to generate models that out-performed existing linear models, such as the "additive method". By adopting a new "11-factor encoding" scheme, SVRMHC takes into account similarities in the physicochemical properties of the amino acids constituting the input peptides. When applied to MHC-peptide binding data for three mouse class I MHC alleles, the SVRMHC models produced more accurate predictions than those produced previously. Furthermore, comparisons based on Receiver Operating Characteristic (ROC) analysis indicated that SVRMHC was able to out-perform several prominent methods in identifying strongly binding peptides. Conclusion - As a method with demonstrated performance in the quantitative modeling of MHC-peptide binding and in identifying strong binders, SVRMHC is a promising immunoinformatics tool with not inconsiderable future potential.

DSM-5 Autism Spectrum Disorder:in search of essential behaviours for diagnosis

Background: Despite initial concerns about the sensitivity of the proposed diagnostic criteria for DSM-5 Autism Spectrum Disorder (ASD; e.g. Gibbs et al., 2012; McPartland et al., 2012), evidence is growing that the DSM-5 criteria provides an inclusive description with both good sensitivity and specificity (e.g. Frazier et al., 2012; Kent, Carrington et al., 2013). The capacity of the criteria to provide high levels of sensitivity and specificity comparable with DSM-IV-TR however relies on careful measurement to ensure that appropriate items from diagnostic instruments map onto the new DSM-5 descriptions.Objectives: To use an existing DSM-5 diagnostic algorithm (Kent, Carrington et .al., 2013) to identify a set of ‘essential’ behaviors sufficient to make a reliable and accurate diagnosis of DSM-5 Autism Spectrum Disorder (ASD) across age and ability level. Methods: Specific behaviors were identified and tested from the recently published DSM-5 algorithm for the Diagnostic Interview for Social and Communication Disorders (DISCO). Analyses were run on existing DISCO datasets, with a total participant sample size of 335. Three studies provided step-by-step development towards identification of a minimum set of items. Study 1 identified the most highly discriminating items (p<.0001). Study 2 used a lower selection threshold than in Study 1 (p<.05) to facilitate better representation of the full DSM-5 ASD profile. Study 3 included additional items previously reported as significantly more frequent in individuals with higher ability. The discriminant validity of all three item sets was tested using Receiver Operating Characteristic curves. Finally, sensitivity across age and ability was investigated in a subset of individuals with ASD (n=190).Results: Study 1 identified an item set (14 items) with good discriminant validity, but which predominantly measured social-communication behaviors (11/14). The Study 2 item set (48 items) better represented the DSM-5 ASD and had good discriminant validity, but the item set lacked sensitivity for individuals with higher ability. The final Study 3 adjusted item set (54 items) improved sensitivity for individuals with higher ability and performance and was comparable to the published DISCO DSM-5 algorithm.Conclusions: This work represents a first attempt to derive a reduced set of behaviors for DSM-5 directly from an existing standardized ASD developmental history interview. Further work involving existing ASD diagnostic tools with community-based and well characterized research samples will be required to replicate these findings and exploit their potential to contribute to a more efficient and focused ASD diagnostic process.

DSM-5 Autism Spectrum Disorder:in search of essential behaviours for diagnosis

The objective of this study was to identify a set of 'essential' behaviours sufficient for diagnosis of DSM-5 Autism Spectrum Disorder (ASD). Highly discriminating, 'essential' behaviours were identified from the published DSM-5 algorithm developed for the Diagnostic Interview for Social and Communication Disorders (DISCO). Study 1 identified a reduced item set (48 items) with good predictive validity (as measured using receiver operating characteristic curves) that represented all symptom sub-domains described in the DSM-5 ASD criteria but lacked sensitivity for individuals with higher ability. An adjusted essential item set (54 items; Study 2) had good sensitivity when applied to individuals with higher ability and performance was comparable to the published full DISCO DSM-5 algorithm. Investigation at the item level revealed that the most highly discriminating items predominantly measured social-communication behaviours. This work represents a first attempt to derive a reduced set of behaviours for DSM-5 directly from an existing standardised ASD developmental history interview and has implications for the use of DSM-5 criteria for clinical and research practice. © 2014 The Authors.

Regularity analysis of nocturnal oximetry recordings to assist in the diagnosis of sleep apnoea syndrome

The relationship between sleep apnoea–hypopnoea syndrome (SAHS) severity and the regularity of nocturnal oxygen saturation (SaO2) recordings was analysed. Three different methods were proposed to quantify regularity: approximate entropy (AEn), sample entropy (SEn) and kernel entropy (KEn). A total of 240 subjects suspected of suffering from SAHS took part in the study. They were randomly divided into a training set (96 subjects) and a test set (144 subjects) for the adjustment and assessment of the proposed methods, respectively. According to the measurements provided by AEn, SEn and KEn, higher irregularity of oximetry signals is associated with SAHS-positive patients. Receiver operating characteristic (ROC) and Pearson correlation analyses showed that KEn was the most reliable predictor of SAHS. It provided an area under the ROC curve of 0.91 in two-class classification of subjects as SAHS-negative or SAHS-positive. Moreover, KEn measurements from oximetry data exhibited a linear dependence on the apnoea–hypopnoea index, as shown by a correlation coefficient of 0.87. Therefore, these measurements could be used for the development of simplified diagnostic techniques in order to reduce the demand for polysomnographies. Furthermore, KEn represents a convincing alternative to AEn and SEn for the diagnostic analysis of noisy biomedical signals.

Optimising the diagnostic performance of the Geriatric Depression Scale

The aim of this work is to empirically generate a shortened version of the Geriatric Depression Scale (GDS), with the intention of maximising the diagnostic performance in the detection of depression compared with previously GDS validated versions, while optimizing the size of the instrument. A total of 233 individuals (128 from a Day Hospital, 105 randomly selected from the community) aged 60 or over completed the GDS and other measures. The 30 GDS items were entered in the Day Hospital sample as independent variables in a stepwise logistic regression analysis predicting diagnosis of Major Depression. A final solution of 10 items was retained, which correctly classified 97.4% of cases. The diagnostic performance of these 10 GDS items was analysed in the random sample with a receiver operating characteristic (ROC) curve. Sensitivity (100%), specificity (97.2%), positive (81.8%) and negative (100%) predictive power, and the area under the curve (0.994) were comparable with values for GDS-30 and higher compared with GDS-15, GDS-10 and GDS-5. In addition, the new scale proposed had excellent fit when testing its unidimensionality with CFA for categorical outcomes (e.g., CFI=0.99). The 10-item version of the GDS proposed here, the GDS-R, seems to retain the diagnostic performance for detecting depression in older adults of the GDS-30 items, while increasing the sensitivity and predictive values relative to other shortened versions.