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Background: Tuberculosis (TB) incidence in South Africa is among the highest globally. Initial loss to follow-up (ILFU), defined as not starting on TB treatment within 28 days of testing positive, is undermining control efforts. We assessed the feasibility, acceptability, and potential of a mHealth application to reduce ILFU. Methods: An mHealth application was developed to capture patients TB investigation data, provide results and monitor treatment initiation. This was implemented in two primary health clinics (PHC) in inner-city Johannesburg. Feasibility was assessed by comparing documentation of personal details, specimen results for same individuals during implementation period (paper register and Mhealth application). Effectiveness was assessed by comparing proportion of patients with results within 48 hours, and proportion started on treatment within 28 days of testing TB positive during pre- implementation (paper register) and implementation (mHealth application) periods. In-depth interviews with patients and providers were conducted to assess acceptability of application. Results: Pre-implementation, 457 patients were recorded in paper registers [195 (42.7%) male, median age 34 years (interquartile range IQR (28–40), 45 (10.5%) sputum Xpert positive]. During implementation, 319 patients were recorded in paper register and the mHealth application [131 (41.1%) male, median age 32 years (IQR 27–38), 33 (10.3%) sputum Xpert positive]. The proportion with complete personal details: [mHealth 95.0% versus paper register 94.0%, (p = 0.54)] and proportion with documented results: [mHealth 97.4% versus paper register 97.8%, (p = 0.79)] were not different in the two methods. The proportion of results available within 48 hours: [mHealth 96.8% versus paper register 68.6%), (p <0.001)], and the proportion on treatment within 28 days [mHealth 28/33 (84.8%) versus paper register 30/44 (68.2%), (p = 0.08)] increased during implementation but was not statistically significant. In-depth interviews showed that providers easily integrated the mHealth application into routine TB investigation and patients positively received the delivery of results via text message. Time from sputum collection to TB treatment initiation decreased from 4 days (pre-implementation) to 3 days but was not statistically significant. Conclusions: We demonstrated that implementation of the mHealth application was feasible, acceptable to health care providers and patients, and has potential to reduce the time to TB treatment initiation and ILFU in PHC settings. [ABSTRACT FROM AUTHOR]

Objective: Gestural interfaces allow accessing and manipulating Electronic Medical Records (EMR) in hospitals while keeping a complete sterile environment. Particularly, in the Operating Room (OR), these interfaces enable surgeons to browse Picture Archiving and Communication System (PACS) without the need of delegating functions to the surgical staff. Existing gesture based medical interfaces rely on a suboptimal and an arbitrary small set of gestures that are mapped to a few commands available in PACS software. The objective of this work is to discuss a method to determine the most suitable set of gestures based on surgeon’s acceptability. To achieve this goal, the paper introduces two key innovations: (a) a novel methodology to incorporate gestures’ semantic properties into the agreement analysis, and (b) a new agreement metric to determine the most suitable gesture set for a PACS. Materials and methods: Three neurosurgical diagnostic tasks were conducted by nine neurosurgeons. The set of commands and gesture lexicons were determined using a Wizard of Oz paradigm. The gestures were decomposed into a set of 55 semantic properties based on the motion trajectory, orientation and pose of the surgeons’ hands and their ground truth values were manually annotated. Finally, a new agreement metric was developed, using the known Jaccard similarity to measure consensus between users over a gesture set. Results: A set of 34 PACS commands were found to be a sufficient number of actions for PACS manipulation. In addition, it was found that there is a level of agreement of 0.29 among the surgeons over the gestures found. Two statistical tests including paired t-test and Mann Whitney Wilcoxon test were conducted between the proposed metric and the traditional agreement metric. It was found that the agreement values computed using the former metric are significantly higher (p < 0.001) for both tests. Conclusions: This study reveals that the level of agreement among surgeons over the best gestures for PACS operation is higher than the previously reported metric (0.29 vs 0.13). This observation is based on the fact that the agreement focuses on main features of the gestures rather than the gestures themselves. The level of agreement is not very high, yet indicates a majority preference, and is better than using gestures based on authoritarian or arbitrary approaches. The methods described in this paper provide a guiding framework for the design of future gesture based PACS systems for the OR. [ABSTRACT FROM AUTHOR]

Background: There have been growing recommendations to include education in multi-disciplinary interventions targeting chronic pain management. However, effects of this strategy on short- and long-term self-management of chronic pain, remain largely unexplored. Objectives: 1. To provide an updated overview of studies that report on the impact of patient education in multi-disciplinary interventions, on self-management of chronic pain; 2. To explore associations between education and chronic pain self-management techniques; and 3. To identify the format and duration of suitable chronic pain interventions targeted at patient self-management. Methods: Design: Narrative systematic literature review of randomised or controlled study designs. Data Sources: PubMed, CINAHL, EMBASE, PsycINFO. Participants: Adult patients with chronic pain of any aetiology participating in multi-disciplinary programs that included education. Main outcome measures: Assessments of level of pain, function, quality of life, self-efficacy, self-management, and any other relevant assessments. Study Appraisal and Synthesis Methods: PRISMA guidelines, Cochrane Risk of Bias tool, and TIDieR model. Results: Database searching identified 485 potential papers. After removal of duplicates, and irrelevant articles by title and abstract, 120 full-text articles were reviewed and 27 studies were included in this systematic review. Studies were predominantly from the United States (n = 8; 29.6%). Over one hundred outcome measures were identified across all studies, with significant variation also observed in terms of how chronic pain duration was defined, and how education was delivered to participants. Overall, positive benefits of education were reported. Conclusions: Education, as part of multi-disciplinary programs, is likely to improve self-management and self-efficacy in people with chronic pain of any aetiology. Heterogeneity in terms of: chronic pain duration; educational resources; healthcare professionals; and outcome measures, were identified as limitations. Further research, in the form of Randomised Controlled Trials addressing these limitations, is recommended. [ABSTRACT FROM AUTHOR]

Background: Detection of ossification areas of hand bones in X-ray images is an important task, e.g. as a preprocessing step in automated bone age estimation. Deep neural networks have emerged recently as de facto standard detection methods, but their drawback is the need of large annotated datasets. Finetuning pre-trained networks is a viable alternative, but it is not clear a priori if training with small annotated datasets will be successful, as it depends on the problem at hand. In this paper, we show that pre-trained networks can be utilized to produce an effective detector of ossification areas in pediatric X-ray images of hands. Methods and findings: A publicly available Faster R-CNN network, pre-trained on the COCO dataset, was utilized and finetuned with 240 manually annotated radiographs from the RSNA Pediatric Bone Age Challenge, which comprises over 14.000 pediatric radiographs. The validation is done on another 89 radiographs from the dataset and the performance is measured by Intersection-over-Union (IoU). To understand the effect of the data size on the pre-trained network, subsampling was applied to the training data and the training was repeated. Additionally, the network was trained from scratch without any pre-trained weights. Finally, to understand whether the trained model could be useful, we compared the inference of the network to an annotation of an expert radiologist. The finetuned network was able to achieve an average precision (mAP@0.5IoU) of 92.92 ± 1.93. Apart from the wrist region, all ossification areas were able to benefit from more data. In contrast, the network trained from scratch was not able to produce any correct results. When compared to the annotations of the expert radiologist, the network was able to localize the regions quite well, as the F1-Score was on average 91.85 ± 1.06. Conclusions: By finetuning a pre-trained deep neural network, with 240 annotated radiographs, we were able to successfully detect ossification areas in prediatric hand radiographs. [ABSTRACT FROM AUTHOR]

Background: The accessibility of services within community pharmacies provides an ideal opportunity to manage minor ailments, yet over £1.1 billion is spent by the National Health Service (NHS) in the United Kingdom (UK) in managing minor ailments in high cost settings. There is a need to review the evidence base around clinical effectiveness of pharmacy-based management of minor ailments since the absence of such may lead to under-utilisation of pharmacy services and non-implementation of available pharmacy service models. This study aimed to systematically review the methodological approaches used to assess clinical outcomes of pharmacy-based management of minor ailments in the research literature. Methods: A systematic review was conducted to identify relevant literature using the following databases: Medline, EMBASE, CINAHL, IPA, CRD, CDSR, and Google Scholar from publication year 2000 onwards. Studies were included if they evaluated clinical outcomes of pharmacy-based management of any minor ailments, with or without a comparator setting such as Emergency Departments (EDs) or general practices. Screening and selection of titles, abstracts and full texts followed by data extraction and quality assessment (QA) was conducted. Paired researchers, from the team, reviewed papers using a protocol based on the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P). QA was undertaken using the Critical Appraisal Skills Programme (CASP). Reporting was conducted in accordance with PRISMA checklist and statements. Results: A total of 19 studies were included. The majority of studies were observational, conducted in community pharmacies, and did not use a comparator participant group nor a comparator setting. Interventions included counselling, medicines supply and provision of advice on the management of minor ailments. One study used the randomised controlled trial (RCT) design with majority of the study utilising observational design. A range of clinical outcomes including symptom severity, pattern, resolution, and quality of life were reported. Methods used for the assessment of clinical outcomes were, overall, poorly reported. This included a lack of information on the development and validation of the data collection tools and the timing of baseline and follow-up data collection. Adverse clinical outcomes data were collected by only seven studies. Conclusions: Currently, there are methodological limitations in the studies that have sought to assess clinical outcomes of pharmacy-based management of minor ailments. Such lack of high quality evidence may contribute to failings to shift care from high cost settings, such as EDs and general practices. Generation of high quality evidence is likely to influence public choices when seeking care for minor ailments. There is scope for development of a core outcomes set specific to minor ailments management and development of a validated methodology for measuring such outcomes in a research study. [ABSTRACT FROM AUTHOR]

The Prenatal Assessment of Genome and Exomes (PAGE) project is a UK-wide study aiming to gain a better understanding of genetic variants causing developmental problems during pregnancy. A further aim of the study is to provide an evidence-base for the introduction of prenatal whole genome and exome sequencing (PWGES) into prenatal diagnostics provided by the NHS, which is expected in 2018. This paper presents the findings of a qualitative interview study undertaken with 20 health professionals and researchers involved in the PAGE project, and explores their implications for understandings of ‘good practice’ in the uses of prenatal genomics clinically. A number of critical issues are identified that will need to be addressed in the development of a model of good ethical practice for prenatal genomics: consent, management of expectations, return of results, and professional duties in the context of PWGES. The analysis presented identifies and illustrates a great deal of complexity and qualitative richness in these issues as they arise in the day-to-day work of genomics professionals. Inclusive, critical discussion of these findings, together with the findings from other empirical studies, normative analysis and scientific discoveries resulting from PAGE, will be required to inform the development of appropriate guidelines of good ethical practice that address the needs and concerns to be encountered in daily clinical practice. [ABSTRACT FROM AUTHOR]

Background: Complementary and alternative medicine (CAM) is very popular with patients frequently combining it with orthodox health care. The high prevalence of CAM use and satisfaction with CAM reported by patients directly challenges an orthodox system that can only approve such use if it results from the application of biomedical concepts and science. Studies highlighting this as a cultural, sociological and historical phenomenon emphasise the value of choice for consumers of health care. Musculoskeletal conditions typify common problems for which the effectiveness of orthodox care is often unclear. We postulated that the reasons people give for using or not using CAM for musculoskeletal conditions, would therefore indicate the full range of expectations that people have of health care. Furthermore, these reasons would indicate how much people feel orthodox health care is or is not meeting their expectations. Therefore, this study aims to investigate people’s reasons for choosing or avoiding CAM for non-traumatic musculoskeletal conditions. Methods: A systematic search and narrative synthesis was conducted of published qualitative and quantitative studies related to CAM and non-traumatic musculoskeletal conditions. Results: We identified 169 relevant papers detailing 152 separate studies, from which 1486 justifications were extracted concerning CAM use. Content analysis resulted in 11 distinct categories across four themes: practical aspects of care, clinical effectiveness, non-clinical outcomes of care, and a person’s philosophy of illness and care. People provided similar rationales for both using and avoiding CAM, emphasising that, whilst CAM is perceived by many patients with musculoskeletal conditions to fill gaps in care (such as practitioner time or quality of the therapeutic relationship), orthodox care also seeks to deliver these aspects of care. However, people who used CAM also highlighted its alignment with their general philosophy and ideas about illness and health care, and often emphasised CAM’s capacity to give them control over their condition and its treatment. Conclusion: Currently, CAM appears to have a significant role for patients with common painful long-term conditions in providing choices to enable individual needs to be met. [ABSTRACT FROM AUTHOR]

As an important way to help express the preference relation between alternatives, distributed preference relation (DPR) can represent the preferred, non-preferred, indifferent, and uncertain degrees of one alternative over another simultaneously. DPR, however, is unavailable in some situations where a decision maker cannot provide the precise degrees of one alternative over another due to lack of knowledge, experience, and data. In this paper, to address this issue, we propose interval-valued DPR (IDPR) and present its properties of validity and normalization. Through constructing two optimization models, an IDPR matrix is transformed into a score matrix to facilitate the comparison between any two alternatives. The properties of the score matrix are analyzed. To guarantee the rationality of the comparisons between alternatives derived from the score matrix, the additive consistency of the score matrix is developed. In terms of these, IDPR is applied to model and solve multiple criteria group decision making (MCGDM) problem. Particularly, the relationship between the parameters for the consistency of the score matrix associated with each decision maker and those for the consistency of the score matrix associated with the group of decision makers is analyzed. A manager selection problem is investigated to demonstrate the application of IDPRs to MCGDM problems. [ABSTRACT FROM AUTHOR]

Introduction: Health Care Workers (HCWs) are among the highest risk groups for contracting tuberculosis (TB), which is ranked the third most common occupational health disease in South Africa. Little is known about the true extent of the burden of TB among South African HCWs and current surveillance approaches are inadequate. The study aimed to determine the feasibility of using postal and web-based surveys accessed through registries of registered professionals to estimate the prevalence of TB among HCWs in South Africa. Materials and methods: We conducted a cross sectional survey on a sample of professional nurses and doctors (general practitioners) registered on the Medpages database platform; a subscription based registry for practising health care professionals. The survey included professionals who were actively involved in the clinical management of patients, either in public or private health care facilities. The paper based survey, including pre-paid return envelopes, was distributed via the post office and web-based surveys were distributed via e-mail through a hyperlink. Descriptive statistics were used to summarize the data and the Chi-square test to determine associations between categorical variables. Active TB was defined as any history of TB Results: Out of a total of 3,400 health care professionals contacted, 596 (18%) responses were received: 401 (67%) web-based and 195 (33%) postal. A significantly higher percentage of complete forms were from postal compared to web-based (97% [189/195] versus 87% [348/401], p<0.001). Younger (<60 years) professionals were more likely to use the web-based compared to postal (87% [236/270] versus 71% [134/189], p<0.001). Overall, the prevalence of active TB infection was 8.7%, (95%CI: 6.3%–11.7%) and there was no difference observed between doctors and nurses (10.8% [18/167] versus 7.5% [22/292], p = 0.236). Conclusion: This novel approach demonstrated the feasibility of using an existing registry of professionals to conduct surveys to estimate the prevalence of TB. Our findings showed a high TB prevalence; however the estimate might have been biased by the low response rate. Further research to optimise our approach could lead to a viable option in improving surveillance among health care professionals. [ABSTRACT FROM AUTHOR]

The 3D convolutional neural network (CNN) is able to make full use of the spatial 3D context information of lung nodules, and the multi-view strategy has been shown to be useful for improving the performance of 2D CNN in classifying lung nodules. In this paper, we explore the classification of lung nodules using the 3D multi-view convolutional neural networks (MV-CNN) with both chain architecture and directed acyclic graph architecture, including 3D Inception and 3D Inception-ResNet. All networks employ the multi-view-one-network strategy. We conduct a binary classification (benign and malignant) and a ternary classification (benign, primary malignant and metastatic malignant) on Computed Tomography (CT) images from and Image Database Resource Initiative database (LIDC-IDRI). All results are obtained via 10-fold cross validation. As regards the MV-CNN with chain architecture, results show that the performance of 3D MV-CNN surpasses that of 2D MV-CNN by a significant margin. Finally, a 3D Inception network achieved an error rate of 4.59% for the binary classification and 7.70% for the ternary classification, both of which represent superior results for the corresponding task. We compare the multi-view-one-network strategy with the one-view-one-network strategy. The results reveal that the multi-view-one-network strategy can achieve a lower error rate than the one-view-one-network strategy. [ABSTRACT FROM AUTHOR]

Background: Myomectomy has potential risks of complications. To reduce these risks, medical pre-treatment can be applied to reduce fibroid size and thereby potentially decrease intra-operative blood loss, the need for blood transfusion and emergency hysterectomy. The aim of this systematic review and meta-analysis is to study the effectiveness of medical pre-treatment with Gonadotropin-releasing hormone agonists (GnRHa) or ulipristal acetate prior to laparoscopic or laparotomic myomectomy on intra-operative and post-operative outcomes. Methods: We performed an extensive search in Embase.com, Wiley/Cochrane Library and PubMed in accordance with the Prisma guidelines. All studies published as full papers in peer reviewed journals using GnRHa or ulipristal acetate as medical pre-treatment independent of route of administration or dosage before laparotomic or laparoscopic myomectomy were included. The primary outcome was duration of surgery. Secondary outcomes were duration of enucleation, blood loss, degree of difficulty of surgery, identification of cleavage planes, proportion of vertical incisions, conversion rate, frequency of blood transfusions, post-operative complications, duration of hospital stay, frequency of recurrence of fibroids, frequency of uterine adhesions, recovery time and quality of life. No language restrictions were applied. Meta-analysis were performed where possible. Findings: Twenty-three studies were included. In laparotomic myomectomy, pre-treatment with GnRHa decreases intra-operative blood loss with 97.39ml (95% CI -111.80 to -82.97) compared to no pre-treatment or placebo. Pre-treatment with GnRHa before laparoscopic myomectomies also shows a reduction in intra-operative blood loss by 23.03ml (95% CI -40.79 to -5.27) and in the frequency of blood transfusions (OR 0.17, 95% CI 0.05 to 0.55) compared to no pre-treatment. Only two retrospective cohort studies reported on pre-treatment with ulipristal acetate compared to no pre-treatment before laparoscopic myomectomy showing a statistically significant reduction in intra-operative blood loss, duration of surgery and frequency of blood transfusions after pre-treatment with ulipristal acetate. Conclusion: Administration of GnRHa prior to laparotomic myomectomy reduces blood loss and might decrease uterine adhesion formation. Pre-treatment with GnRHa before laparoscopic myomectomy reduces blood loss, the frequency of blood transfusions and might increase recurrence rate of fibroids, however it should be taken into account that some results are mainly based on cohort studies. Other pre-treatment agent ulipristal acetate has not been investigated sufficiently for relevant surgical outcomes. [ABSTRACT FROM AUTHOR]

In this paper we address the problem of automated grading of invasive breast carcinoma through the encoding of histological images as VLAD (Vector of Locally Aggregated Descriptors) representations on the Grassmann manifold. The proposed method considers each image as a set of multidimensional spatially-evolving signals that can be efficiently modeled through a higher-order linear dynamical systems analysis. Subsequently, each H&E (Hematoxylin and Eosin) stained breast cancer histological image is represented as a cloud of points on the Grassmann manifold, while a vector representation approach is applied aiming to aggregate the Grassmannian points based on a locality criterion on the manifold. To evaluate the efficiency of the proposed methodology, two datasets with different characteristics were used. More specifically, we created a new medium-sized dataset consisting of 300 annotated images (collected from 21 patients) of grades 1, 2 and 3, while we also provide experimental results using a large dataset, namely BreaKHis, containing 7,909 breast cancer histological images, collected from 82 patients, of both benign and malignant cases. Experimental results have shown that the proposed method outperforms a number of state of the art approaches providing average classification rates of 95.8% and 91.38% with our dataset and the BreaKHis dataset, respectively. [ABSTRACT FROM AUTHOR]

Pneumonia is the leading cause of infectious disease mortality in children. Currently, health care providers (HCPs) are trained to use World Health Organization Integrated Management of Childhood Illness (IMCI) paper-based protocols and manually assess respiratory rate to diagnose pneumonia in low-resource settings (LRS). However, this approach of relying on clinical signs alone has proven problematic. Hypoxemia, a diagnostic indicator of pneumonia severity associated with an increased risk of death, is not assessed because pulse oximetry is often not available in LRS. To improve HCPs’ ability to diagnose, classify, and manage pneumonia and other childhood illnesses, “mPneumonia” was developed. mPneumonia is a mobile health application that integrates a digital version of the IMCI algorithm with a software-based breath counter and a pulse oximeter. A design-stage qualitative pilot study was conducted to assess feasibility, usability, and acceptability of mPneumonia in six health centers and five community-based health planning and services centers in Ghana. Nine health administrators, 30 HCPs, and 30 caregivers were interviewed. Transcribed interview audio recordings were coded and analyzed for common themes. Health administrators reported mPneumonia would be feasible to implement with approval and buy-in from national and regional decision makers. HCPs felt using the mPneumonia application would be feasible to integrate into their work with the potential to improve accurate patient care. They reported it was “easy to use” and provided confidence in diagnosis and treatment recommendations. HCPs and caregivers viewed the pulse oximeter and breath counter favorably. Challenges included electricity requirements for charging and the time needed to complete the application. Some caregivers saw mPneumonia as a sign of modernity, increasing their trust in the care received. Other caregivers were hesitant or confused about the new technology. Overall, this technology was valued by users and is a promising innovation for improving quality of care in frontline health facilities. [ABSTRACT FROM AUTHOR]

Background: Prognostic accuracy in palliative care is valued by patients, carers, and healthcare professionals. Previous reviews suggest clinicians are inaccurate at survival estimates, but have only reported the accuracy of estimates on patients with a cancer diagnosis. Objectives: To examine the accuracy of clinicians’ estimates of survival and to determine if any clinical profession is better at doing so than another. Data Sources: MEDLINE, Embase, CINAHL, and the Cochrane Database of Systematic Reviews and Trials. All databases were searched from the start of the database up to June 2015. Reference lists of eligible articles were also checked. Eligibility Criteria: Inclusion criteria: patients over 18, palliative population and setting, quantifiable estimate based on real patients, full publication written in English. Exclusion criteria: if the estimate was following an intervention, such as surgery, or the patient was artificially ventilated or in intensive care. Study Appraisal and Synthesis Methods: A quality assessment was completed with the QUIPS tool. Data on the reported accuracy of estimates and information about the clinicians were extracted. Studies were grouped by type of estimate: categorical (the clinician had a predetermined list of outcomes to choose from), continuous (open-ended estimate), or probabilistic (likelihood of surviving a particular time frame). Results: 4,642 records were identified; 42 studies fully met the review criteria. Wide variation was shown with categorical estimates (range 23% to 78%) and continuous estimates ranged between an underestimate of 86 days to an overestimate of 93 days. The four papers which used probabilistic estimates tended to show greater accuracy (c-statistics of 0.74–0.78). Information available about the clinicians providing the estimates was limited. Overall, there was no clear “expert” subgroup of clinicians identified. Limitations: High heterogeneity limited the analyses possible and prevented an overall accuracy being reported. Data were extracted using a standardised tool, by one reviewer, which could have introduced bias. Devising search terms for prognostic studies is challenging. Every attempt was made to devise search terms that were sufficiently sensitive to detect all prognostic studies; however, it remains possible that some studies were not identified. Conclusion: Studies of prognostic accuracy in palliative care are heterogeneous, but the evidence suggests that clinicians’ predictions are frequently inaccurate. No sub-group of clinicians was consistently shown to be more accurate than any other. Implications of Key Findings: Further research is needed to understand how clinical predictions are formulated and how their accuracy can be improved. [ABSTRACT FROM AUTHOR]