Objective dysphonia quantification in vocal fold paralysis: comparing nonlinear with classical measures

Clinical acoustic voice recording analysis is usually performed using classical perturbation measures including jitter, shimmer and noise-to-harmonic ratios. However, restrictive mathematical limitations of these measures prevent analysis for severely dysphonic voices. Previous studies of alternative nonlinear random measures addressed wide varieties of vocal pathologies. Here, we analyze a single vocal pathology cohort, testing the performance of these alternative measures alongside classical measures.

We present voice analysis pre- and post-operatively in unilateral vocal fold paralysis (UVFP) patients and healthy controls, patients undergoing standard medialisation thyroplasty surgery, using jitter, shimmer and noise-to-harmonic ratio (NHR), and nonlinear recurrence period density entropy (RPDE), detrended fluctuation analysis (DFA) and correlation dimension. Systematizing the preparative editing of the recordings, we found that the novel measures were more stable and hence reliable, than the classical measures, on healthy controls.

RPDE and jitter are sensitive to improvements pre- to post-operation. Shimmer, NHR and DFA showed no significant change (p > 0.05). All measures detect statistically significant and clinically important differences between controls and patients, both treated and untreated (p < 0.001, AUC > 0.7). Pre- to post-operation, GRBAS ratings show statistically significant and clinically important improvement in overall dysphonia grade (G) (AUC = 0.946, p < 0.001).

Re-calculating AUCs from other study data, we compare these results in terms of clinical importance. We conclude that, when preparative editing is systematized, nonlinear random measures may be useful UVFP treatment effectiveness monitoring tools, and there may be applications for other forms of dysphonia.
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Exploiting Nonlinear Recurrence and Fractal Scaling Properties for Voice Disorder Detection

Background: Voice disorders affect patients profoundly, and acoustic tools can potentially measure voice function objectively. Disordered sustained vowels exhibit wide-ranging phenomena, from nearly periodic to highly complex, aperiodic vibrations, and increased "breathiness". Modelling and surrogate data studies have shown significant nonlinear and non-Gaussian random properties in these sounds. Nonetheless, existing tools are limited to analysing voices displaying near periodicity, and do not account for this inherent biophysical nonlinearity and non-Gaussian randomness, often using linear signal processing methods insensitive to these properties. They do not directly measure the two main biophysical symptoms of disorder: complex nonlinear aperiodicity, and turbulent, aeroacoustic, non-Gaussian randomness. Often these tools cannot be applied to more severe disordered voices, limiting their clinical usefulness.

Methods: This paper introduces two new tools to speech analysis: recurrence and fractal scaling, which overcome the range limitations of existing tools by addressing directly these two symptoms of disorder, together reproducing a "hoarseness" diagram. A simple bootstrapped classifier then uses these two features to distinguish normal from disordered voices.

Results: On a large database of subjects with a wide variety of voice disorders, these new techniques can distinguish normal from disordered cases, using quadratic discriminant analysis, to overall correct classification performance of 91.8% plus or minus 2.0%. The true positive classification performance is 95.4% plus or minus 3.2%, and the true negative performance is 91.5% plus or minus 2.3% (95% confidence). This is shown to outperform all combinations of the most popular classical tools.

Conclusions: Given the very large number of arbitrary parameters and computational complexity of existing techniques, these new techniques are far simpler and yet achieve clinically useful classification performance using only a basic classification technique. They do so by exploiting the inherent nonlinearity and turbulent randomness in disordered voice signals. They are widely applicable to the whole range of disordered voice phenomena by design. These new measures could therefore be used for a variety of practical clinical purposes.
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Data quality and patient characteristics in European ANCA-associated vasculitis registries: data retrieval by federated querying

Objectives This study aims to describe the data structure and harmonisation process, explore data quality and define characteristics, treatment, and outcomes of patients across six federated antineutrophil cytoplasmic antibody-associated vasculitis (AAV) registries.Methods Through creation of the vasculitis-specific Findable, Accessible, Interoperable, Reusable, VASCulitis ontology, we harmonised the registries and enabled semantic interoperability. We assessed data quality across the domains of uniqueness, consistency, completeness and correctness. Aggregated data were retrieved using the semantic query language SPARQL Protocol and Resource Description Framework Query Language (SPARQL) and outcome rates were assessed through random effects meta-analysis.Results A total of 5282 cases of AAV were identified. Uniqueness and data-type consistency were 100% across all assessed variables. Completeness and correctness varied from 49%–100% to 60%–100%, respectively. There were 2754 (52.1%) cases classified as granulomatosis with polyangiitis (GPA), 1580 (29.9%) as microscopic polyangiitis and 937 (17.7%) as eosinophilic GPA. The pattern of organ involvement included: lung in 3281 (65.1%), ear-nose-throat in 2860 (56.7%) and kidney in 2534 (50.2%). Intravenous cyclophosphamide was used as remission induction therapy in 982 (50.7%), rituximab in 505 (17.7%) and pulsed intravenous glucocorticoid use was highly variable (11%–91%). Overall mortality and incidence rates of end-stage kidney disease were 28.8 (95% CI 19.7 to 42.2) and 24.8 (95% CI 19.7 to 31.1) per 1000 patient-years, respectively.Conclusions In the largest reported AAV cohort-study, we federated patient registries using semantic web technologies and highlighted concerns about data quality. The comparison of patient characteristics, treatment and outcomes was hampered by heterogeneous recruitment settings

Progressive improvement in short-, medium- and long-term graft survival in kidney transplantation patients in Ireland - a retrospective study

It is often quoted that while short-term graft survival in kidney transplantation has improved in recent years, it has not translated into a commensurate improvement in long-term graft survival. We considered whether this was true of the entire experience of the national kidney transplant program in Ireland. A retrospective analysis of the National Kidney Transplant Service (NKTS) database was undertaken to investigate patient and graft survival for all adult first deceased donor kidney transplant recipients in Ireland, 1971-2015. Three thousand two hundred and sixty recipients were included in this study. Kaplan-Meier methods were used to estimate survival at each time period post transplant for the various eras of transplantation. Uncensored graft survival has improved over the course of the program in Ireland at various time points despite risk factors for graft failure progressively increasing over successive eras. For example the graft survival at 15 years post transplant has increased from 10% in 1971-1975 to 45% by 1996-2000. Ireland has experienced a progressive improvement in long-term graft survival following kidney transplantation. Whether these trends are attributable to biological or nonbiological factors is unclear but likely involves a combination of both

PESFOR-W: Improving the design and environmental effectiveness of woodlands for water Payments for Ecosystem Services

ABSTRACT: The EU Water Framework Directive aims to ensure restoration of Europe?s water bodies to ?good ecological status? by 2027. Many Member States will struggle to meet this target, with around half of EU river catchments currently reporting below standard water quality. Diffuse pollution from agriculture represents a major pressure, affecting over 90% of river basins. Accumulating evidence shows that recent improvements to agricultural practices are benefiting water quality but in many cases will be insufficient to achieve WFD objectives. There is growing support for land use change to help bridge the gap, with a particular focus on targeted tree planting to intercept and reduce the delivery of diffuse pollutants to water. This form of integrated catchment management offers multiple benefits to society but a significant cost to landowners and managers. New economic instruments, in combination with spatial targeting, need to be developed to ensure cost effective solutions - including tree planting for water benefits - are realised. Payments for Ecosystem Services (PES) are flexible, incentive-based mechanisms that could play an important role in promoting land use change to deliver water quality targets. The PESFOR-W COST Action will consolidate learning from existing woodlands for water PES schemes in Europe and help standardize approaches to evaluating the environmental effectiveness and cost-effectiveness of woodland measures. It will also create a European network through which PES schemes can be facilitated, extended and improved, for example by incorporating other ecosystem services linking with aims of the wider forestscarbon policy nexus

Data linkage in medical science using the resource description framework: the AVERT model

There is an ongoing challenge as to how best manage and understand ?big data? in precision medicine settings. This paper describes the potential for a Linked Data approach, using a Resource Description Framework (RDF) model, to combine multiple datasets with temporal and spatial elements of varying dimensionality. This ?AVERT model? provides a framework for converting multiple standalone files of various formats, from both clinical and environmental settings, into a single data source. This data source can thereafter be queried effectively, shared with outside parties, more easily understood by multiple stakeholders using standardized vocabularies, incorporating provenance metadata and supporting temporo-spatial reasoning. The approach has further advantages in terms of data sharing, security and subsequent analysis. We use a case study relating to anti-Glomerular Basement Membrane (GBM) disease, a rare autoimmune condition, to illustrate a technical proof of concept for the AVERT model

FAIRVASC: A semantic web approach to rare disease registry integration

Rare disease data is often fragmented within multiple heterogeneous siloed regional disease registries, each containing a small number of cases. These data are particularly sensitive, as low subject counts make the identification of patients more likely, meaning registries are not inclined to share subject level data outside their registries. At the same time access to multiple rare disease datasets is important as it will lead to new research opportunities and analysis over larger cohorts. To enable this, two major challenges must therefore be overcome. The first is to integrate data at a semantic level, so that it is possible to query over registries and return results which are comparable. The second is to enable queries which do not take subject level data from the registries. To meet the first challenge, this paper presents the FAIRVASC ontology to manage data related to the rare disease anti-neutrophil cytoplasmic antibody (ANCA) associated vasculitis (AAV), which is based on the harmonisation of terms in seven European data registries. It has been built upon a set of key clinical questions developed by a team of experts in vasculitis selected from the registry sites and makes use of several standard classifications, such as Systematized Nomenclature of Medicine - Clinical Terms (SNOMED-CT) and Orphacode. It also presents the method for adding semantic meaning to AAV data across the registries using the declarative Relational to Resource Description Framework Mapping Language (R2RML). To meet the second challenge a federated querying approach is presented for accessing aggregated and pseudonymized data, and which supports analysis of AAV data in a manner which protects patient privacy. For additional security the federated querying approach is augmented with a method for auditing queries (and the uplift process) using the provenance ontology (PROV-O) to track when queries and changes occur and by whom. The main contribution of this work is the successful application of semantic web technologies and federated queries to provide a novel infrastructure that can readily incorporate additional registries, thus providing access to harmonised data relating to unprecedented numbers of patients with rare disease, while also meeting data privacy and security concerns

FAIRVASC: A semantic web approach to rare disease registry integration

Rare disease data is often fragmented within multiple heterogeneous siloed regional disease registries, each containing a small number of cases. These data are particularly sensitive, as low subject counts make the identification of patients more likely, meaning registries are not inclined to share subject level data outside their registries. At the same time access to multiple rare disease datasets is important as it will lead to new research opportunities and analysis over larger cohorts. To enable this, two major challenges must therefore be overcome. The first is to integrate data at a semantic level, so that it is possible to query over registries and return results which are comparable. The second is to enable queries which do not take subject level data from the registries. To meet the first challenge, this paper presents the FAIRVASC ontology to manage data related to the rare disease anti-neutrophil cytoplasmic antibody (ANCA) associated vasculitis (AAV), which is based on the harmonisation of terms in seven European data registries. It has been built upon a set of key clinical questions developed by a team of experts in vasculitis selected from the registry sites and makes use of several standard classifications, such as Systematized Nomenclature of Medicine - Clinical Terms (SNOMED-CT) and Orphacode. It also presents the method for adding semantic meaning to AAV data across the registries using the declarative Relational to Resource Description Framework Mapping Language (R2RML). To meet the second challenge a federated querying approach is presented for accessing aggregated and pseudonymized data, and which supports analysis of AAV data in a manner which protects patient privacy. For additional security the federated querying approach is augmented with a method for auditing queries (and the uplift process) using the provenance ontology (PROV-O) to track when queries and changes occur and by whom. The main contribution of this work is the successful application of semantic web technologies and federated queries to provide a novel infrastructure that can readily incorporate additional registries, thus providing access to harmonised data relating to unprecedented numbers of patients with rare disease, while also meeting data privacy and security concerns

COSUTI: a protocol for the development of a core outcome set (COS) for interventions for the treatment of uncomplicated urinary tract infection (UTI) in adults

Background: Urinary tract infections (UTIs) are the second most common infection presenting in the community. Clinical guidelines and decision aids assist health practitioners to treat a UTI; however, treatment practices vary due to patient needs and context of presentation. Numerous trials have evaluated the effectiveness of treatment interventions for UTI; however, it is difficult to compare the results between trials due to inconsistencies between reported outcomes. Poor choice of outcome measures can lead to impairment of evidence synthesis due to the inability to compare outcomes between trials with similar aims. Transparency in selecting and reporting outcomes can be mitigated through the development of an agreed minimum set of outcomes that should be reported in clinical trials, referred to as a core outcome set (COS). This paper presents the protocol for the development of a COS for interventions in the treatment of uncomplicated UTI in adults. Methods: This COS development consists of three phases. Phase 1 is a systematic review, which aims to identify the core outcomes that have been reported in trials and systematic reviews of interventions treating uncomplicated UTI in adults. Phase 2 consists of a three-round online Delphi survey with stakeholders in the area of treatment interventions for UTI. The aim of this online Delphi survey is to achieve consensus on the importance of the outcomes emerging from Phase 1 of this research. Phase 3 is a consensus meeting to finalise the COS that should be reported in trials evaluating the effectiveness of interventions for the treatment of UTI. Discussion: It is hoped that the development of a COS for interventions for the treatment of uncomplicated UTI in adults will be adopted as a minimum set of outcomes that should be reported and measured within this context. If the findings from clinical trials related to treatment interventions for UTI are to impact on policy and practice, it is important that the findings from different treatment interventions are comparable across trials.</p