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Despotou G, Evans J, Nash W, Eavis A, Robbins T, Arvanitis TN. Evaluation of patient perception towards dynamic health data sharing using blockchain based digital consent with the Dovetail digital consent application: A cross sectional exploratory study. Digit Health 2020; 6:2055207620924949. [PMID: 32435503 PMCID: PMC7223864 DOI: 10.1177/2055207620924949] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Accepted: 04/16/2020] [Indexed: 11/29/2022] Open
Abstract
Background New patient-centric integrated care models are enabled by the capability to exchange the patient’s data amongst stakeholders, who each specialise in different aspects of the patient’s care. This requires a robust, trusted and flexible mechanism for patients to offer consent to share their data. Furthermore, new IT technologies make it easier to give patients more control over their data, including the right to revoke consent. These characteristics challenge the traditional paper-based, single-organisation-led consent process. The Dovetail digital consent application uses a mobile application and blockchain based infrastructure to offer this capability, as part of a pilot allowing patients to have their data shared amongst digital tools, empowering patients to manage their condition within an integrated care setting. Objective To evaluate patient perceptions towards existing consent processes, and the Dovetail blockchain based digital consent application as a means to manage data sharing in the context of diabetes care. Method Patients with diabetes at a General Practitioner practice were recruited. Data were collected using focus groups and questionnaires. Thematic analysis of the focus group transcripts and descriptive statistics of the questionnaires was performed. Results There was a lack of understanding of existing consent processes in place, and many patients did not have any recollection of having previously given consent. The digital consent application received favourable feedback, with patients recognising the value of the capability offered by the application. Patients overwhelmingly favoured the digital consent application over existing practice. Conclusions Digital consent was received favourably, with patients recognising that it addresses the main limitations of the current process. Feedback on potential improvements was received. Future work includes confirmation of results in a broader demographic sample and across multiple conditions.
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Griffiths F, Watkins JA, Huxley C, Harris B, Cave J, Pemba S, Chipwaza B, Lilford R, Ajisola M, Arvanitis TN, Bakibinga P, Billah M, Choudhury N, Davies D, Fayehun O, Kabaria C, Iqbal R, Omigbodun A, Owoaje E, Rahman O, Sartori J, Sayani S, Tabani K, Yusuf R, Sturt J. Mobile consulting (mConsulting) and its potential for providing access to quality healthcare for populations living in low-resource settings of low- and middle-income countries. Digit Health 2020; 6:2055207620919594. [PMID: 32341793 PMCID: PMC7175047 DOI: 10.1177/2055207620919594] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 03/12/2020] [Indexed: 12/11/2022] Open
Abstract
Objective The poorest populations of the world lack access to quality healthcare. We defined the key components of consulting via mobile technology (mConsulting), explored whether mConsulting can fill gaps in access to quality healthcare for poor and spatially marginalised populations (specifically rural and slum populations) of low- and middle-income countries, and considered the implications of its take-up. Methods We utilised realist methodology. First, we undertook a scoping review of mobile health literature and searched for examples of mConsulting. Second, we formed our programme theories and identified potential benefits and hazards for deployment of mConsulting for poor and spatially marginalised populations. Finally, we tested our programme theories against existing frameworks and identified published evidence on how and why these benefits/hazards are likely to accrue. Results We identified the components of mConsulting, including their characteristics and range. We discuss the implications of mConsulting for poor and spatially marginalised populations in terms of competent care, user experience, cost, workforce, technology, and the wider health system. Conclusions For the many dimensions of mConsulting, how it is structured and deployed will make a difference to the benefits and hazards of its use. There is a lack of evidence of the impact of mConsulting in populations that are poor and spatially marginalised, as most research on mConsulting has been undertaken where quality healthcare exists. We suggest that mConsulting could improve access to quality healthcare for these populations and, with attention to how it is deployed, potential hazards for the populations and wider health system could be mitigated.
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Robbins T, Hudson S, Ray P, Sankar S, Patel K, Randeva H, Arvanitis TN. COVID-19: A new digital dawn? Digit Health 2020; 6:2055207620920083. [PMID: 32313668 PMCID: PMC7153182 DOI: 10.1177/2055207620920083] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
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Khan O, Ahmed I, Cottingham J, Rahhal M, Arvanitis TN, Elliott MT. Timing and correction of stepping movements with a virtual reality avatar. PLoS One 2020; 15:e0229641. [PMID: 32109252 PMCID: PMC7048307 DOI: 10.1371/journal.pone.0229641] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Accepted: 02/11/2020] [Indexed: 12/17/2022] Open
Abstract
Research into the ability to coordinate one's movements with external cues has focussed on the use of simple rhythmic, auditory and visual stimuli, or interpersonal coordination with another person. Coordinating movements with a virtual avatar has not been explored, in the context of responses to temporal cues. To determine whether cueing of movements using a virtual avatar is effective, people's ability to accurately coordinate with the stimuli needs to be investigated. Here we focus on temporal cues, as we know from timing studies that visual cues can be difficult to follow in the timing context. Real stepping movements were mapped onto an avatar using motion capture data. Healthy participants were then motion captured whilst stepping in time with the avatar's movements, as viewed through a virtual reality headset. The timing of one of the avatar step cycles was accelerated or decelerated by 15% to create a temporal perturbation, for which participants would need to correct to, in order to remain in time. Step onset times of participants relative to the corresponding step-onsets of the avatar were used to measure the timing errors (asynchronies) between them. Participants completed either a visual-only condition, or auditory-visual with footstep sounds included, at two stepping tempo conditions (Fast: 400ms interval, Slow: 800ms interval). Participants' asynchronies exhibited slow drift in the Visual-Only condition, but became stable in the Auditory-Visual condition. Moreover, we observed a clear corrective response to the phase perturbation in both the fast and slow tempo auditory-visual conditions. We conclude that an avatar's movements can be used to influence a person's own motion, but should include relevant auditory cues congruent with the movement to ensure a suitable level of entrainment is achieved. This approach has applications in physiotherapy, where virtual avatars present an opportunity to provide the guidance to assist patients in adhering to prescribed exercises.
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Robbins T, Zucker K, Abdulhussein H, Chaplin V, Maguire J, Arvanitis TN. Supporting early clinical careers in digital health: Nurturing the next generation. Digit Health 2020; 6:2055207619899798. [PMID: 32010451 PMCID: PMC6971955 DOI: 10.1177/2055207619899798] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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Despotou G, Her J, Arvanitis TN. Nurses’ Perceptions of Joint Commission International Accreditation on Patient Safety in Tertiary Care in South Korea: A Pilot Study. JOURNAL OF NURSING REGULATION 2020. [DOI: 10.1016/s2155-8256(20)30011-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Bhalodiya JM, Palit A, Ferrante E, Tiwari MK, Bhudia SK, Arvanitis TN, Williams MA. Hierarchical Template Matching for 3D Myocardial Tracking and Cardiac Strain Estimation. Sci Rep 2019; 9:12450. [PMID: 31462651 PMCID: PMC6713749 DOI: 10.1038/s41598-019-48927-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 08/14/2019] [Indexed: 11/09/2022] Open
Abstract
Myocardial tracking and strain estimation can non-invasively assess cardiac functioning using subject-specific MRI. As the left-ventricle does not have a uniform shape and functioning from base to apex, the development of 3D MRI has provided opportunities for simultaneous 3D tracking, and 3D strain estimation. We have extended a Local Weighted Mean (LWM) transformation function for 3D, and incorporated in a Hierarchical Template Matching model to solve 3D myocardial tracking and strain estimation problem. The LWM does not need to solve a large system of equations, provides smooth displacement of myocardial points, and adapt local geometric differences in images. Hence, 3D myocardial tracking can be performed with 1.49 mm median error, and without large error outliers. The maximum error of tracking is up to 24% reduced compared to benchmark methods. Moreover, the estimated strain can be insightful to improve 3D imaging protocols, and the computer code of LWM could also be useful for geo-spatial and manufacturing image analysis researchers.
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Traore L, Assele-Kama A, Keung SNLC, Karni L, Klein GO, Lilja M, Scandurra I, Verdoy D, Yuksel M, Arvanitis TN, Tsopra R, Jaulent MC. User-Centered Design of the C3-Cloud Platform for Elderly with Multiple Diseases - Functional Requirements and Application Testing. Stud Health Technol Inform 2019; 264:843-847. [PMID: 31438043 DOI: 10.3233/shti190342] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The number of patients with multimorbidity has been steadily increasing in the modern aging societies. The European C3-Cloud project provides a multidisciplinary and patient-centered "Collaborative Care and Cure-system" for the management of elderly with multimorbidity, enabling continuous coordination of care activities between multidisciplinary care teams (MDTs), patients and informal caregivers (ICG). In this study various components of the infrastructure were tested to fulfill the functional requirements and the entire system was subjected to an early application testing involving different groups of end-users. MDTs from participating European regions were involved in requirement elicitation and test formulation, resulting in 57 questions, distributed via an internet platform to 48 test participants (22 MDTs, 26 patients) from three pilot sites. The results indicate a high level of satisfaction with all components. Early testing also provided feedback for technical improvement of the entire system, and the paper points out useful evaluation methods.
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Bennett CD, Gill SK, Kohe SE, Wilson MP, Davies NP, Arvanitis TN, Tennant DA, Peet AC. Ex vivo metabolite profiling of paediatric central nervous system tumours reveals prognostic markers. Sci Rep 2019; 9:10473. [PMID: 31324817 PMCID: PMC6642141 DOI: 10.1038/s41598-019-45900-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Accepted: 06/03/2019] [Indexed: 02/06/2023] Open
Abstract
Brain tumours are the most common cause of cancer death in children. Molecular studies have greatly improved our understanding of these tumours but tumour metabolism is underexplored. Metabolites measured in vivo have been reported as prognostic biomarkers of these tumours but analysis of surgically resected tumour tissue allows a more extensive set of metabolites to be measured aiding biomarker discovery and providing validation of in vivo findings. In this study, metabolites were quantified across a range of paediatric brain tumours using 1H-High-Resolution Magic Angle Spinning nuclear magnetic resonance spectroscopy (HR-MAS) and their prognostic potential investigated. HR-MAS was performed on pre-treatment frozen tumour tissue from a single centre. Univariate and multivariate Cox regression was used to examine the ability of metabolites to predict survival. The models were cross validated using C-indices and further validated by splitting the cohort into two. Higher concentrations of glutamine were predictive of a longer overall survival, whilst higher concentrations of lipids were predictive of a shorter overall survival. These metabolites were predictive independent of diagnosis, as demonstrated in multivariate Cox regression models. Whilst accurate quantification of metabolites such as glutamine in vivo is challenging, metabolites show promise as prognostic markers due to development of optimised detection methods and increasing use of 3 T clinical scanners.
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Bilici E, Despotou G, Arvanitis TN. Concurrent Execution of Multiple Computer-interpretable Clinical Practice Guidelines and Their Interrelations. Stud Health Technol Inform 2019; 262:7-10. [PMID: 31349252 DOI: 10.3233/shti190003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Execution of multiple computer-interpretable guidelines (CIGs), enables the creation of patient-centered care plans for multimorbidity, which can be monitored by clinical decision support systems. This paper introduces an execution framework to manage multiple, concurrently implemented CIGs, also discussing the approaches used such as constraint satisfaction.
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Despotou G, Yuksel M, Sarigul B, Arvanitis TN. Drug Interaction Advisory Service for Clinical Decision Support of Multimordity Patient Centric Care Plans in the C3-Cloud System. Stud Health Technol Inform 2019; 262:388-391. [PMID: 31349249 DOI: 10.3233/shti190100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
C3-Cloud is a project aiming to provide an ICT infrastructure, which will allow patient centric and integrated care, based on best practice guideline, for patients with multi-morbidity. Clinical Decision Support, by checking the patient's record for known adverse interactions when the medication changes. The drug interaction advisory service provides recommendations in the three languages used in the project's pilot sites, for over 1000 substances, based on the UK's NICE BNF body of knowledge.
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Laleci Erturkmen GB, Yuksel M, Sarigul B, Arvanitis TN, Lindman P, Chen R, Zhao L, Sadou E, Bouaud J, Traore L, Teoman A, Lim Choi Keung SN, Despotou G, de Manuel E, Verdoy D, de Blas A, Gonzalez N, Lilja M, von Tottleben M, Beach M, Marguerie C, Klein GO, Kalra D. A Collaborative Platform for Management of Chronic Diseases via Guideline-Driven Individualized Care Plans. Comput Struct Biotechnol J 2019; 17:869-885. [PMID: 31333814 PMCID: PMC6614507 DOI: 10.1016/j.csbj.2019.06.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 03/18/2019] [Accepted: 06/04/2019] [Indexed: 11/19/2022] Open
Abstract
Older age is associated with an increased accumulation of multiple chronic conditions. The clinical management of patients suffering from multiple chronic conditions is very complex, disconnected and time-consuming with the traditional care settings. Integrated care is a means to address the growing demand for improved patient experience and health outcomes of multimorbid and long-term care patients. Care planning is a prevalent approach of integrated care, where the aim is to deliver more personalized and targeted care creating shared care plans by clearly articulating the role of each provider and patient in the care process. In this paper, we present a method and corresponding implementation of a semi-automatic care plan management tool, integrated with clinical decision support services which can seamlessly access and assess the electronic health records (EHRs) of the patient in comparison with evidence based clinical guidelines to suggest personalized recommendations for goals and interventions to be added to the individualized care plans. We also report the results of usability studies carried out in four pilot sites by patients and clinicians.
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Robbins TD, Lim Choi Keung SN, Sankar S, Randeva H, Arvanitis TN. Risk factors for readmission of inpatients with diabetes: A systematic review. J Diabetes Complications 2019; 33:398-405. [PMID: 30878296 DOI: 10.1016/j.jdiacomp.2019.01.004] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Revised: 01/04/2019] [Accepted: 01/22/2019] [Indexed: 12/16/2022]
Abstract
AIM We have limited understanding of which risk factors contribute to increased readmission rates amongst people discharged from hospital with diabetes. We aim to complete the first review of its kind, to identify, in a systematic way, known risk factors for hospital readmission amongst people with diabetes, in order to better understand this costly complication. METHOD The review was prospectively registered in the PROSPERO database. Risk factors were identified through systematic review of literature in PubMed, EMBASE & SCOPUS databases, performed independently by two authors prior to data extraction, with quality assessment and semi-quantitative synthesis according to PRISMA guidelines. RESULTS Eighty-three studies were selected for inclusion, predominantly from the United States, and utilising retrospective analysis of local or regional data sets. 76 distinct statistically significant risk factors were identified across 48 studies. The most commonly identified risk factors were; co-morbidity burden, age, race and insurance type. Few studies conducted power calculations; unstandardized effect sizes were calculated for the majority of statistically significant risk factors. CONCLUSION This review is important in assessing the current state of the literature and in supporting development of interventions to reduce readmission risk. Furthermore, it provides an important foundation for development of rigorous, pre-specified risk prediction models.
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Carlin D, Babourina-Brooks B, Arvanitis TN, Wilson M, Peet AC. Short-acquisition-time JPRESS and its application to paediatric brain tumours. MAGMA (NEW YORK, N.Y.) 2019; 32:247-258. [PMID: 30460431 PMCID: PMC6424926 DOI: 10.1007/s10334-018-0716-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/09/2018] [Revised: 10/26/2018] [Accepted: 10/29/2018] [Indexed: 12/01/2022]
Abstract
OBJECTIVE To develop and assess a short-duration JPRESS protocol for detection of overlapping metabolite biomarkers and its application to paediatric brain tumours at 3 Tesla. MATERIALS AND METHODS The short-duration protocol (6 min) was optimised and compared for spectral quality to a high-resolution (38 min) JPRESS protocol in a phantom and five healthy volunteers. The 6-min JPRESS was acquired from four paediatric brain tumours and compared with short-TE PRESS. RESULTS Metabolite identification between the 6- and 38-min protocols was comparable in phantom and volunteer data. For metabolites with Cramer-Rao lower bounds > 50%, interpretation of JPRESS increased confidence in assignment of lactate, myo-Inositol and scyllo-Inositol. JPRESS also showed promise for the detection of glycine and taurine in paediatric brain tumours when compared to short-TE MRS. CONCLUSION A 6-min JPRESS protocol is well tolerated in paediatric brain tumour patients. Visual inspection of a 6-min JPRESS spectrum enables identification of a range of metabolite biomarkers of clinical interest.
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Robbins T, Lim Choi Keung SN, Sankar S, Randeva H, Arvanitis TN. Diabetes and the direct secondary use of electronic health records: Using routinely collected and stored data to drive research and understanding. Digit Health 2018; 4:2055207618804650. [PMID: 30305917 PMCID: PMC6176528 DOI: 10.1177/2055207618804650] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2018] [Accepted: 09/05/2018] [Indexed: 12/19/2022] Open
Abstract
Introduction Electronic health records provide an unparalleled opportunity for the use of
patient data that is routinely collected and stored, in order to drive
research and develop an epidemiological understanding of disease. Diabetes,
in particular, stands to benefit, being a data-rich, chronic-disease state.
This article aims to provide an understanding of the extent to which the
healthcare sector is using routinely collected and stored data to inform
research and epidemiological understanding of diabetes mellitus. Methods Narrative literature review of articles, published in both the medical- and
engineering-based informatics literature. Results There has been a significant increase in the number of papers published,
which utilise electronic health records as a direct data source for diabetes
research. These articles consider a diverse range of research questions.
Internationally, the secondary use of electronic health records, as a
research tool, is most prominent in the USA. The barriers most commonly
described in research studies include missing values and misclassification,
alongside challenges of establishing the generalisability of results. Discussion Electronic health record research is an important and expanding area of
healthcare research. Much of the research output remains in the form of
conference abstracts and proceedings, rather than journal articles. There is
enormous opportunity within the United Kingdom to develop these research
methodologies, due to national patient identifiers. Such a healthcare
context may enable UK researchers to overcome many of the barriers
encountered elsewhere and thus to truly unlock the potential of electronic
health records.
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Manias KA, Harris LM, Davies NP, Natarajan K, MacPherson L, Foster K, Brundler MA, Hargrave DR, Payne GS, Leach MO, Morgan PS, Auer D, Jaspan T, Arvanitis TN, Grundy RG, Peet AC. Prospective multicentre evaluation and refinement of an analysis tool for magnetic resonance spectroscopy of childhood cerebellar tumours. Pediatr Radiol 2018; 48:1630-1641. [PMID: 30062569 PMCID: PMC6153873 DOI: 10.1007/s00247-018-4182-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2017] [Revised: 05/10/2018] [Accepted: 06/10/2018] [Indexed: 10/28/2022]
Abstract
BACKGROUND A tool for diagnosing childhood cerebellar tumours using magnetic resonance (MR) spectroscopy peak height measurement has been developed based on retrospective analysis of single-centre data. OBJECTIVE To determine the diagnostic accuracy of the peak height measurement tool in a multicentre prospective study, and optimise it by adding new prospective data to the original dataset. MATERIALS AND METHODS Magnetic resonance imaging (MRI) and single-voxel MR spectroscopy were performed on children with cerebellar tumours at three centres. Spectra were processed using standard scanner software and peak heights for N-acetyl aspartate, creatine, total choline and myo-inositol were measured. The original diagnostic tool was used to classify 26 new tumours as pilocytic astrocytoma, medulloblastoma or ependymoma. These spectra were subsequently combined with the original dataset to develop an optimised scheme from 53 tumours in total. RESULTS Of the pilocytic astrocytomas, medulloblastomas and ependymomas, 65.4% were correctly assigned using the original tool. An optimized scheme was produced from the combined dataset correctly assigning 90.6%. Rare tumour types showed distinctive MR spectroscopy features. CONCLUSION The original diagnostic tool gave modest accuracy when tested prospectively on multicentre data. Increasing the dataset provided a diagnostic tool based on MR spectroscopy peak height measurement with high levels of accuracy for multicentre data.
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Robbins TD, Lim Choi Keung SN, Arvanitis TN. E-health for active ageing; A systematic review. Maturitas 2018; 114:34-40. [PMID: 29907244 DOI: 10.1016/j.maturitas.2018.05.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Revised: 05/21/2018] [Accepted: 05/29/2018] [Indexed: 11/25/2022]
Abstract
Enabling successful active ageing is an international priority to meet the challenges of increasing life expectancy. Digital strategies, such as telemedicine and e-health, offer the potential to deliver active ageing in a cost-effective manner at scale. This article aims to establish the extent to which the research literature considers e-health-based and telemedicine-based active ageing interventions. A systematic review was conducted according to PRISMA standards. Independently, two authors searched the Cochrane, EMBASE & CINAHL databases, with subsequent independent extraction and semi-quantitative analysis. We report a considerable breadth in digital active ageing research, which is truly international in its scope. There is a diverse range of both interventions and technologies, including a reassuring focus on community-based interventions. Whilst there are a number of quantitative studies, sample sizes are small, with a limited amount of statistical testing of the results. There is significant variation in the outcome measures reported and little consensus as to the most effective intervention strategies. Overall, whilst there is considerable breadth to the research published in the literature, there is a clear restriction in the depth of this research. There is little overall consensus. This lack of depth and consensus may be due to the need to recognize the important role of technical research elements alongside more traditional research methodologies, such as randomized controlled trials. Enabling both technical and clinical research methods to be recognized, in tandem, has enormous potential to support individuals, communities, clinicians and policy makers to make more informed decisions in relation to active ageing.
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Bhalodiya JM, Palit A, Tiwari MK, Prasad SK, Bhudia SK, Arvanitis TN, Williams MA. A Novel Hierarchical Template Matching Model for Cardiac Motion Estimation. Sci Rep 2018. [PMID: 29540762 PMCID: PMC5852007 DOI: 10.1038/s41598-018-22543-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
Cardiovascular disease diagnosis and prognosis can be improved by measuring patient-specific in-vivo local myocardial strain using Magnetic Resonance Imaging. Local myocardial strain can be determined by tracking the movement of sample muscles points during cardiac cycle using cardiac motion estimation model. The tracking accuracy of the benchmark Free Form Deformation (FFD) model is greatly affected due to its dependency on tunable parameters and regularisation function. Therefore, Hierarchical Template Matching (HTM) model, which is independent of tunable parameters, regularisation function, and image-specific features, is proposed in this article. HTM has dense and uniform points correspondence that provides HTM with the ability to estimate local muscular deformation with a promising accuracy of less than half a millimetre of cardiac wall muscle. As a result, the muscles tracking accuracy has been significantly (p < 0.001) improved (30%) compared to the benchmark model. Such merits of HTM provide reliably calculated clinical measures which can be incorporated into the decision-making process of cardiac disease diagnosis and prognosis.
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Orphanidou-Vlachou E, Kohe SE, Brundler MA, MacPherson L, Sun Y, Davies N, Wilson M, Pan X, Arvanitis TN, Grundy RG, Peet AC. Metabolite Levels in Paediatric Brain Tumours Correlate with Histological Features. Pathobiology 2018; 85:157-168. [PMID: 29428932 DOI: 10.1159/000458423] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2016] [Accepted: 01/27/2017] [Indexed: 11/19/2022] Open
Abstract
AIMS Metabolite levels can be measured non-invasively using in vivo 1H magnetic resonance spectroscopy (MRS). These tumour metabolite profiles are highly characteristic for tumour type in childhood brain tumours; however, the relationship between metabolite values and conventional histopathological characteristics has not yet been fully established. This study systematically tests the relationship between metabolite levels detected by MRS and specific histological features in a range of paediatric brain tumours. METHODS Single-voxel MRS was performed routinely in children with brain tumours along with the clinical imaging prior to treatment. Metabolites were quantified using LCModel. Histological features were assessed semi-quantitatively for 27 children on H&E and immunostained slides, blind to the metabolite values. Statistical analysis included 2-tailed independent-samples t tests and 2-tailed Spearman rank correlation tests. RESULTS Ki67, cellular atypia, and mitosis correlated positively with choline metabolites, and phosphocholine in particular. Apoptosis and necrosis were both associated with lipid levels, with the relationship dependent on the use of long or short echo time MRS acquisitions. Neuronal components correlated negatively and glial components positively with N-acetyl-aspartate. Glial components correlated positively with myoinositol. CONCLUSION Metabolite levels in children's brain tumours measured by MRS are closely associated with key histological features routinely assessed by histopathologists in the diagnostic process. This further elucidates our understanding of this important non-invasive diagnostic tool and strengthens our understanding of the relationship between metabolites and histological features.
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Despotou G, Korkontzelos I, Matragkas N, Bilici E, Arvanitis TN. Structuring Clinical Decision Support Rules for Drug Safety Using Natural Language Processing. Stud Health Technol Inform 2018; 251:89-92. [PMID: 29968609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Drug safety is an important aspect in healthcare, resulting in a number of inadvertent events, which may harm the patients. IT based Clinical Decision Support (CDS), integrated in electronic-prescription or Electronic Health Records (EHR) systems, can provide a means for checking prescriptions for errors. This requires expressing prescription guidelines in a way that can be interpreted by IT systems. The paper uses Natural Language Processing (NLP), to interpret drug guidelines by the UK NICE BNF offered in free text. The employed NLP component, MetaMap, identifies the concepts in the instructions and interprets their semantic meaning. The UMLS semantic types that correspond to these concepts are then processed, in order to understand the concepts that are needed to be implemented in software engineering for a CDS engine.
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Fetit AE, Novak J, Rodriguez D, Auer DP, Clark CA, Grundy RG, Peet AC, Arvanitis TN. Radiomics in paediatric neuro-oncology: A multicentre study on MRI texture analysis. NMR IN BIOMEDICINE 2018; 31:e3781. [PMID: 29073725 DOI: 10.1002/nbm.3781] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Revised: 07/08/2017] [Accepted: 07/10/2017] [Indexed: 06/07/2023]
Abstract
Brain tumours are the most common solid cancers in children in the UK and are the most common cause of cancer deaths in this age group. Despite current advances in MRI, non-invasive diagnosis of paediatric brain tumours has yet to find its way into routine clinical practice. Radiomics, the high-throughput extraction and analysis of quantitative image features (e.g. texture), offers potential solutions for tumour characterization and decision support. In the search for diagnostic oncological markers, the primary aim of this work was to study the application of MRI texture analysis (TA) for the classification of paediatric brain tumours. A multicentre study was carried out, within a supervised classification framework, on clinical MR images, and a support vector machine (SVM) was trained with 3D textural attributes obtained from conventional MRI. To determine the cross-centre transferability of TA, an assessment of how SVM performs on unseen datasets was carried out through rigorous pairwise testing. The study also investigated the nature of features that are most likely to train classifiers that can generalize well with the data. Finally, the issue of class imbalance, which arises due to some tumour types being more common than others, was explored. For each of the tests carried out through pairwise testing, the optimal area under the receiver operating characteristic curve ranged between 76% and 86%, suggesting that the model was able to capture transferable tumour information. Feature selection results suggest that similar aspects of tumour texture are enhanced by MR images obtained at different hospitals. Our results also suggest that the availability of equally represented classes has enabled SVM to better characterize the data points. The findings of the study presented here support the use of 3D TA on conventional MR images to aid diagnostic classification of paediatric brain tumours.
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Bilici E, Despotou G, Arvanitis TN. The use of computer-interpretable clinical guidelines to manage care complexities of patients with multimorbid conditions: A review. Digit Health 2018; 4:2055207618804927. [PMID: 30302270 PMCID: PMC6172935 DOI: 10.1177/2055207618804927] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Accepted: 09/05/2018] [Indexed: 01/25/2023] Open
Abstract
Clinical practice guidelines (CPGs) document evidence-based information and recommendations on treatment and management of conditions. CPGs usually focus on management of a single condition; however, in many cases a patient will be at the centre of multiple health conditions (multimorbidity). Multiple CPGs need to be followed in parallel, each managing a separate condition, which often results in instructions that may interact with each other, such as conflicts in medication. Furthermore, the impetus to deliver customised care based on patient-specific information, results in the need to be able to offer guidelines in an integrated manner, identifying and managing their interactions. In recent years, CPGs have been formatted as computer-interpretable guidelines (CIGs). This enables developing CIG-driven clinical decision support systems (CDSSs), which allow the development of IT applications that contribute to the systematic and reliable management of multiple guidelines. This study focuses on understanding the use of CIG-based CDSSs, in order to manage care complexities of patients with multimorbidity. The literature between 2011 and 2017 is reviewed, which covers: (a) the challenges and barriers in the care of multimorbid patients, (b) the role of CIGs in CDSS augmented delivery of care, and (c) the approaches to alleviating care complexities of multimorbid patients. Generating integrated care plans, detecting and resolving adverse interactions between treatments and medications, dealing with temporal constraints in care steps, supporting patient-caregiver shared decision making and maintaining the continuity of care are some of the approaches that are enabled using a CIG-based CDSS.
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Laleci Erturkmen GB, Yuksel M, Sarigul B, Lilja M, Chen R, Arvanitis TN. Personalised Care Plan Management Utilizing Guideline-Driven Clinical Decision Support Systems. Stud Health Technol Inform 2018; 247:750-754. [PMID: 29678061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Older age is associated with an increased accumulation of multiple chronic conditions. The clinical management of patients suffering from multiple chronic conditions is very complex, disconnected and time-consuming with the traditional care settings. Integrated care is a means to address the growing demand for improved patient experience and health outcomes of multimorbid and long-term care patients. Care planning is a prevalent approach of integrated care, where the aim is to deliver more personalized and targeted care creating shared care plans by clearly articulating the role of each provider and patient in the care process. In this paper, we present a method and corresponding implementation of a semi-automatic care plan management tool, integrated with clinical decision support services which can seamlessly access and assess the electronic health records (EHRs) of the patient in comparison with evidence based clinical guidelines to suggest personalized recommendations for goals and interventions to be added to the individualized care plans.
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Smith CM, Lim Choi Keung SN, Khan MO, Arvanitis TN, Fothergill R, Hartley-Sharpe C, Wilson MH, Perkins GD. Barriers and facilitators to public access defibrillation in out-of-hospital cardiac arrest: a systematic review. EUROPEAN HEART JOURNAL. QUALITY OF CARE & CLINICAL OUTCOMES 2017; 3:264-273. [PMID: 29044399 DOI: 10.1093/ehjqcco/qcx023] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Accepted: 07/12/2017] [Indexed: 11/14/2022]
Abstract
Public access defibrillation initiatives make automated external defibrillators available to the public. This facilitates earlier defibrillation of out-of-hospital cardiac arrest victims and could save many lives. It is currently only used for a minority of cases. The aim of this systematic review was to identify barriers and facilitators to public access defibrillation. A comprehensive literature review was undertaken defining formal search terms for a systematic review of the literature in March 2017. Studies were included if they considered reasons affecting the likelihood of public access defibrillation and presented original data. An electronic search strategy was devised searching MEDLINE and EMBASE, supplemented by bibliography and related-article searches. Given the low-quality and observational nature of the majority of articles, a narrative review was performed. Sixty-four articles were identified in the initial literature search. An additional four unique articles were identified from the electronic search strategies. The following themes were identified related to public access defibrillation: knowledge and awareness; willingness to use; acquisition and maintenance; availability and accessibility; training issues; registration and regulation; medicolegal issues; emergency medical services dispatch-assisted use of automated external defibrillators; automated external defibrillator-locator systems; demographic factors; other behavioural factors. In conclusion, several barriers and facilitators to public access defibrillation deployment were identified. However, the evidence is of very low quality and there is not enough information to inform changes in practice. This is an area in urgent need of further high-quality research if public access defibrillation is to be increased and more lives saved. PROSPERO registration number CRD42016035543.
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Zarinabad N, Abernethy LJ, Avula S, Davies NP, Rodriguez Gutierrez D, Jaspan T, MacPherson L, Mitra D, Rose HEL, Wilson M, Morgan PS, Bailey S, Pizer B, Arvanitis TN, Grundy RG, Auer DP, Peet A. Application of pattern recognition techniques for classification of pediatric brain tumors by in vivo 3T 1 H-MR spectroscopy-A multi-center study. Magn Reson Med 2017; 79:2359-2366. [PMID: 28786132 PMCID: PMC5850456 DOI: 10.1002/mrm.26837] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2017] [Revised: 06/22/2017] [Accepted: 06/23/2017] [Indexed: 11/30/2022]
Abstract
Purpose 3T magnetic resonance scanners have boosted clinical application of 1H‐MR spectroscopy (MRS) by offering an improved signal‐to‐noise ratio and increased spectral resolution, thereby identifying more metabolites and extending the range of metabolic information. Spectroscopic data from clinical 1.5T MR scanners has been shown to discriminate between pediatric brain tumors by applying machine learning techniques to further aid diagnosis. The purpose of this multi‐center study was to investigate the discriminative potential of metabolite profiles obtained from 3T scanners in classifying pediatric brain tumors. Methods A total of 41 pediatric patients with brain tumors (17 medulloblastomas, 20 pilocytic astrocytomas, and 4 ependymomas) were scanned across four different hospitals. Raw spectroscopy data were processed using TARQUIN. Borderline synthetic minority oversampling technique was used to correct for the data skewness. Different classifiers were trained using linear discriminative analysis, support vector machine, and random forest techniques. Results Support vector machine had the highest balanced accuracy for discriminating the three tumor types. The balanced accuracy achieved was higher than the balanced accuracy previously reported for similar multi‐center dataset from 1.5T magnets with echo time 20 to 32 ms alone. Conclusion This study showed that 3T MRS can detect key differences in metabolite profiles for the main types of childhood tumors. Magn Reson Med 79:2359–2366, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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