Improving appropriate polypharmacy for older people in primary care: selecting components of an evidence-based intervention to target prescribing and dispensing.

Background
The use of multiple medicines (polypharmacy) is increasingly common in older people. Ensuring that patients receive the most appropriate combinations of medications (appropriate polypharmacy) is a significant challenge. The quality of evidence to support the effectiveness of interventions to improve appropriate polypharmacy is low. Systematic identification of mediators of behaviour change, using the Theoretical Domains Framework (TDF), provides a theoretically robust evidence base to inform intervention design. This study aimed to (1) identify key theoretical domains that were perceived to influence the prescribing and dispensing of appropriate polypharmacy to older patients by general practitioners (GPs) and community pharmacists, and (2) map domains to associated behaviour change techniques (BCTs) to include as components of an intervention to improve appropriate polypharmacy in older people in primary care.

Methods
Semi-structured interviews were conducted with members of each healthcare professional (HCP) group using tailored topic guides based on TDF version 1 (12 domains). Questions covering each domain explored HCPs’ perceptions of barriers and facilitators to ensuring the prescribing and dispensing of appropriate polypharmacy to older people. Interviews were audio-recorded and transcribed verbatim. Data analysis involved the framework method and content analysis. Key domains were identified and mapped to BCTs based on established methods and discussion within the research team.

Results
Thirty HCPs were interviewed (15 GPs, 15 pharmacists). Eight key domains were identified, perceived to influence prescribing and dispensing of appropriate polypharmacy: ‘Skills’, ‘Beliefs about capabilities’, ‘Beliefs about consequences’, ‘Environmental context and resources’, ‘Memory, attention and decision processes’, ‘Social/professional role and identity’, ‘Social influences’ and ‘Behavioural regulation’. Following mapping, four BCTs were selected for inclusion in an intervention for GPs or pharmacists: ‘Action planning’, ‘Prompts/cues’, ‘Modelling or demonstrating of behaviour’ and ‘Salience of consequences’. An additional BCT (‘Social support or encouragement’) was selected for inclusion in a community pharmacy-based intervention in order to address barriers relating to interprofessional working that were encountered by pharmacists.

Conclusions
Selected BCTs will be operationalised in a theory-based intervention to improve appropriate polypharmacy for older people, to be delivered in GP practice and community pharmacy settings. Future research will involve development and feasibility testing of this intervention.

Cascaded multimodal biometric recognition framework

A practically viable multi-biometric recognition system should not only be stable, robust and accurate but should also adhere to real-time processing speed and memory constraints. This study proposes a cascaded classifier-based framework for use in biometric recognition systems. The proposed framework utilises a set of weak classifiers to reduce the enrolled users' dataset to a small list of candidate users. This list is then used by a strong classifier set as the final stage of the cascade to formulate the decision. At each stage, the candidate list is generated by a Mahalanobis distance-based match score quality measure. One of the key features of the authors framework is that each classifier in the ensemble can be designed to use a different modality thus providing the advantages of a truly multimodal biometric recognition system. In addition, it is one of the first truly multimodal cascaded classifier-based approaches for biometric recognition. The performance of the proposed system is evaluated both for single and multimodalities to demonstrate the effectiveness of the approach.

Using Graph Components Derived from an Associative Concept Dictionary to Predict fMRI Neural Activation Patterns that Represent the Meaning of Nouns

In this study, we introduce an original distance definition for graphs, called the Markov-inverse-F measure (MiF). This measure enables the integration of classical graph theory indices with new knowledge pertaining to structural feature extraction from semantic networks. MiF improves the conventional Jaccard and/or Simpson indices, and reconciles both the geodesic information (random walk) and co-occurrence adjustment (degree balance and distribution). We measure the effectiveness of graph-based coefficients through the application of linguistic graph information for a neural activity recorded during conceptual processing in the human brain. Specifically, the MiF distance is computed between each of the nouns used in a previous neural experiment and each of the in-between words in a subgraph derived from the Edinburgh Word Association Thesaurus of English. From the MiF-based information matrix, a machine learning model can accurately obtain a scalar parameter that specifies the degree to which each voxel in (the MRI image of) the brain is activated by each word or each principal component of the intermediate semantic features. Furthermore, correlating the voxel information with the MiF-based principal components, a new computational neurolinguistics model with a network connectivity paradigm is created. This allows two dimensions of context space to be incorporated with both semantic and neural distributional representations.

Using a Discrete Hidden Markov Model Kernel for lip-based biometric identification

In this paper, a novel and effective lip-based biometric identification approach with the Discrete Hidden Markov Model Kernel (DHMMK) is developed. Lips are described by shape features (both geometrical and sequential) on two different grid layouts: rectangular and polar. These features are then specifically modeled by a DHMMK, and learnt by a support vector machine classifier. Our experiments are carried out in a ten-fold cross validation fashion on three different datasets, GPDS-ULPGC Face Dataset, PIE Face Dataset and RaFD Face Dataset. Results show that our approach has achieved an average classification accuracy of 99.8%, 97.13%, and 98.10%, using only two training images per class, on these three datasets, respectively. Our comparative studies further show that the DHMMK achieved a 53% improvement against the baseline HMM approach. The comparative ROC curves also confirm the efficacy of the proposed lip contour based biometrics learned by DHMMK. We also show that the performance of linear and RBF SVM is comparable under the frame work of DHMMK.

Investigation into DCT Feature Selection for Visual Lip-Based Biometric Authentication

This paper investigated using lip movements as a behavioural biometric for person authentication. The system was trained, evaluated and tested using the XM2VTS dataset, following the Lausanne Protocol configuration II. Features were selected from the DCT coefficients of the greyscale lip image. This paper investigated the number of DCT coefficients selected, the selection process, and static and dynamic feature combinations. Using a Gaussian Mixture Model - Universal Background Model framework an Equal Error Rate of 2.20% was achieved during evaluation and on an unseen test set a False Acceptance Rate of 1.7% and False Rejection Rate of 3.0% was achieved. This compares favourably with face authentication results on the same dataset whilst not being susceptible to spoofing attacks.

Two-year changes in refractive error and related biometric factors in an adult Chinese population

Importance: This article provides, to our knowledge, the first longitudinal population-based data on refractive error (RE) in Chinese persons.

Objective: To study cohort effects and changes associated with aging in REs among Chinese adults.

Design, Setting, and Participants: A 2-year, longitudinal population-based cohort study was conducted in southern China. Participants, identified using cluster random sampling, included residents of Yuexiu District, Guangzhou, China, aged 35 years or older who had undergone no previous eye surgery.

Methods: Participants underwent noncycloplegic automated refraction and keratometry in December 2008 and December 2010; in a random 50% sample of the participants, anterior segment ocular coherence tomography measurement of lens thickness, as well as measurement of axial length and anterior chamber depth by partial coherence laser interferometry, were performed.

Main Outcomes and Measures: Two-year change in spherical equivalent refraction (RE), lens thickness, axial length, and anterior chamber depth in the right eye.

Results: A total of 745 individuals underwent biometric testing in both 2008 and 2010 (2008 mean [SD] age, 52.2 [11.5] years; 53.7% women). Mean RE showed a 2-year hyperopic shift from −0.44 (2.21) to −0.31 (2.26) diopters (D) (difference, +0.13; 95% CI, 0.11 to 0.16). A consistent 2-year hyperopic shift of 0.09 to 0.22 D was observed among participants aged 35 to 64 years when stratifying by decade, suggesting that a substantial change in RE with aging may occur during this 30-year period. Cross-sectionally, RE increased only in the cohort younger than 50 years (0.11 D/y; 95% CI, 0.06 to 0.16). In the cross-sectional data, axial length decreased at −0.06 mm/y (95% CI, −0.09 to −0.04), although the 2-year change in axial length was positive and thus could not explain the cross-sectional difference. These latter results suggest a cohort effect, with greater myopia developing among younger persons.

Conclusions and Relevance: This first Chinese population-based longitudinal study of RE provides evidence for both important longitudinal aging changes and cohort effects, most notably greater myopia prevalence among younger persons.

Biometric measurements in highly myopic eyes

Purpose: To assess the repeatability and accuracy of optical biometry (Lenstar LS900 optical low-coherence reflectometry [OLCR] and IOLMaster partial coherence interferometry [PCI]) and applanation ultrasound biometry in highly myopic eyes. Setting: Division of Preventive Ophthalmology, Zhongshan Ophthalmic Center, Guangzhou, China. Design: Comparative evaluation of diagnostic technology. Methods: Biometric measurements were taken in highly myopic subjects with a spherical equivalent (SE) of -6.00 diopters (D) or higher and an axial length (AL) longer than 25.0 mm. Measurements of AL and anterior chamber depth (ACD) obtained by OLCR were compared with those obtained by PCI and applanation A-scan ultrasound. Right eyes were analyzed. Repeatability was evaluated using the coefficient of variation (CoV) and agreement, using Bland-Altman analyses. Results: The mean SE was -11.20 D ± 4.65 (SD). The CoVs for repeated AL measurements using OLCR, PCI, and applanation ultrasound were 0.06%, 0.07%, and 0.20%, respectively. The limits of agreement (LoA) for AL were 0.11 mm between OLCR and PCI, 1.01 mm between OLCR and applanation ultrasound, and 1.03 mm between PCI and ultrasound. The ACD values were 0.29 mm, 0.53 mm, and 0.51 mm, respectively. These repeatability and agreement results were comparable in eyes with extreme myopia (AL ≥27.0 mm) or posterior staphyloma. The mean radius of corneal curvature was similar between OLCR and PCI (7.66 ± 0.24 mm versus 7.64 ± 0.25 mm), with an LoA of 0.12 mm. Conclusion: Optical biometry provided more repeatable and precise measurements of biometric parameters, including AL and ACD, than applanation ultrasound biometry in highly myopic eyes. Financial Disclosure: No author has a financial or proprietary interest in any material or method mentioned. © 2012 ASCRS and ESCRS.

A proposed simple method for measurement in the anterior chamber angle: biometric gonioscopy

OBJECTIVE:

To design a system of gonioscopy that will allow greater interobserver reliability and more clearly defined screening cutoffs for angle closure than current systems while being simple to teach and technologically appropriate for use in rural Asia, where the prevalence of angle-closure glaucoma is highest.

DESIGN:

Clinic-based validation and interobserver reliability trial.

PARTICIPANTS:

Study 1: 21 patients 18 years of age and older recruited from a university-based specialty glaucoma clinic; study 2: 32 patients 18 years of age and older recruited from the same clinic.

INTERVENTION:

In study 1, all participants underwent conventional gonioscopy by an experienced observer (GLS) using the Spaeth system and in the same eye also underwent Scheimpflug photography, ultrasonographic measurement of anterior chamber depth and axial length, automatic refraction, and biometric gonioscopy with measurement of the distance from iris insertion to Schwalbe's line using a reticule based in the slit-lamp ocular. In study 2, all participants underwent both conventional gonioscopy and biometric gonioscopy by an experienced gonioscopist (NGC) and a medical student with no previous training in gonioscopy (JK).

MAIN OUTCOME MEASURES:

Study 1: The association between biometric gonioscopy and conventional gonioscopy, Scheimpflug photography, and other factors known to correlate with the configuration of the angle. Study 2: Interobserver agreement using biometric gonioscopy compared to that obtained with conventional gonioscopy.

RESULTS:

In study 1, there was an independent, monotonic, statistically significant relationship between biometric gonioscopy and both Spaeth angle (P = 0.001, t test) and Spaeth insertion (P = 0.008, t test) grades. Biometric gonioscopy correctly identified six of six patients with occludable angles according to Spaeth criteria. Biometric gonioscopic grade was also significantly associated with the anterior chamber angle as measured by Scheimpflug photography (P = 0.005, t test). In study 2, the intraclass correlation coefficient between graders for biometric gonioscopy (0.97) was higher than for Spaeth angle grade (0.72) or Spaeth insertion grade (0.84).

CONCLUSION:

Biometric gonioscopy correlates well with other measures of the anterior chamber angle, shows a higher degree of interobserver reliability than conventional gonioscopy, and can readily be learned by an inexperienced observer.

Biometric gonioscopy and the effects of age, race, and sex on the anterior chamber angle.

AIM:

To utilise a novel method for making measurements in the anterior chamber in order to compare the anterior chamber angles of people of European, African, and east Asian descent aged 40 years and over.

METHODS:

A cross sectional study on 15 people of each sex from each decade from the 40s to the 70s, from each of three racial groups-black, white, and Chinese Singaporeans. Biometric gonioscopy (BG) utilises a slit lamp mounted reticule to make measurements from the apparent iris insertion to Schwalbe's line through a Goldmann one mirror goniolens. The main outcome measures were BG measurements of the anterior chamber angle as detailed above.

RESULTS:

There was no significant difference in angle measurement between black, white, and Chinese races in this study. However, at younger ages people of Chinese race appeared to have deeper angles than white or black people, whereas the angles of older Chinese were significantly narrower (p = 0.004 for the difference in slope of BG by age between Chinese and both black and white people).

CONCLUSION:

The failure to detect a difference in angle measurements between these groups was surprising, given the much higher prevalence of angle closure among Chinese. It appears that the overall apparent similarity of BG means between Chinese and Western populations may mask very different trends with age. The apparently more rapid decline in angle width measurements with age among Chinese may be due to the higher prevalence of cataract or "creeping angle closure." However, longitudinal inferences from cross sectional data are problematic, and this may represent a cohort phenomenon caused by the increasing prevalence of myopia in the younger Singaporean population.

In vitro bioassay investigations of the endocrine disrupting potential of steviol glycosides and their metabolite steviol, components of the natural sweetener Stevia

The food industry is moving towards the use of natural sweeteners such as those produced by Stevia rebaudiana due to the number of health and safety concerns surrounding artificial sweeteners. Despite the fact that these sweeteners are natural; they cannot be assumed safe. Steviol glycosides have a steroidal structure and therefore may have the potential to act as an endocrine disruptor in the body. Reporter gene assays (RGAs), H295R steroidogenesis assay and Ca(2+) fluorimetry based assays using human sperm cells have been used to assess the endocrine disrupting potential of two steviol glycosides: stevioside and rebaudioside A, and their metabolite steviol. A decrease in transcriptional activity of the progestagen receptor was seen following treatment with 25,000 ng/ml steviol in the presence of progesterone (157 ng/ml) resulting in a 31% decrease in progestagen response (p=<0.01). At the level of steroidogenesis, the metabolite steviol (500-25,000 ng/ml) increased progesterone production significantly by 2.3 fold when exposed to 10,000 ng/ml (p=<0.05) and 5 fold when exposed to 25,000 ng/ml (p=<0.001). Additionally, steviol was found to induce an agonistic response on CatSper, a progesterone receptor of sperm, causing a rapid influx of Ca(2+). The response was fully inhibited using a specific CatSper inhibitor. These findings highlight the potential for steviol to act as a potential endocrine disruptor.

Face Recognition in the Scrambled Domain via Salience-Aware Ensembles of Many Kernels

With the rapid development of internet-of-things (IoT), face scrambling has been proposed for privacy protection during IoT-targeted image/video distribution. Consequently in these IoT applications, biometric verification needs to be carried out in the scrambled domain, presenting significant challenges in face recognition. Since face models become chaotic signals after scrambling/encryption, a typical solution is to utilize traditional data-driven face recognition algorithms. While chaotic pattern recognition is still a challenging task, in this paper we propose a new ensemble approach – Many-Kernel Random Discriminant Analysis (MK-RDA) to discover discriminative patterns from chaotic signals. We also incorporate a salience-aware strategy into the proposed ensemble method to handle chaotic facial patterns in the scrambled domain, where random selections of features are made on semantic components via salience modelling. In our experiments, the proposed MK-RDA was tested rigorously on three human face datasets: the ORL face dataset, the PIE face dataset and the PUBFIG wild face dataset. The experimental results successfully demonstrate that the proposed scheme can effectively handle chaotic signals and significantly improve the recognition accuracy, making our method a promising candidate for secure biometric verification in emerging IoT applications.