Computer-aided X-ray screening for tuberculosis and HIV testing among adults with cough in Malawi (the PROSPECT study): A randomised trial and cost-effectiveness analysis.

BACKGROUND: Suboptimal tuberculosis (TB) diagnostics and HIV contribute to the high global burden of TB. We investigated costs and yield from systematic HIV-TB screening, including computer-aided digital chest X-ray (DCXR-CAD). METHODS AND FINDINGS: In this open, three-arm randomised trial, adults (≥18 years) with cough attending acute primary services in Malawi were randomised (1:1:1) to standard of care (SOC); oral HIV testing (HIV screening) and linkage to care; or HIV testing and linkage to care plus DCXR-CAD with sputum Xpert for high CAD4TBv5 scores (HIV-TB screening). Participants and study staff were not blinded to intervention allocation, but investigator blinding was maintained until final analysis. The primary outcome was time to TB treatment. Secondary outcomes included proportion with same-day TB treatment; prevalence of undiagnosed/untreated bacteriologically confirmed TB on day 56; and undiagnosed/untreated HIV. Analysis was done on an intention-to-treat basis. Cost-effectiveness analysis used a health-provider perspective. Between 15 November 2018 and 27 November 2019, 8,236 were screened for eligibility, with 473, 492, and 497 randomly allocated to SOC, HIV, and HIV-TB screening arms; 53 (11%), 52 (9%), and 47 (9%) were lost to follow-up, respectively. At 56 days, TB treatment had been started in 5 (1.1%) SOC, 8 (1.6%) HIV screening, and 15 (3.0%) HIV-TB screening participants. Median (IQR) time to TB treatment was 11 (6.5 to 38), 6 (1 to 22), and 1 (0 to 3) days (hazard ratio for HIV-TB versus SOC: 2.86, 1.04 to 7.87), with same-day treatment of 0/5 (0%) SOC, 1/8 (12.5%) HIV, and 6/15 (40.0%) HIV-TB screening arm TB patients (p = 0.03). At day 56, 2 SOC (0.5%), 4 HIV (1.0%), and 2 HIV-TB (0.5%) participants had undiagnosed microbiologically confirmed TB. HIV screening reduced the proportion with undiagnosed or untreated HIV from 10 (2.7%) in the SOC arm to 2 (0.5%) in the HIV screening arm (risk ratio [RR]: 0.18, 0.04 to 0.83), and 1 (0.2%) in the HIV-TB screening arm (RR: 0.09, 0.01 to 0.71). Incremental costs were US$3.58 and US$19.92 per participant screened for HIV and HIV-TB; the probability of cost-effectiveness at a US$1,200/quality-adjusted life year (QALY) threshold was 83.9% and 0%. Main limitations were the lower than anticipated prevalence of TB and short participant follow-up period; cost and quality of life benefits of this screening approach may accrue over a longer time horizon. CONCLUSIONS: DCXR-CAD with universal HIV screening significantly increased the timeliness and completeness of HIV and TB diagnosis. If implemented at scale, this has potential to rapidly and efficiently improve TB and HIV diagnosis and treatment. TRIAL REGISTRATION: clinicaltrials.gov NCT03519425.

Staged reflexive artificial intelligence driven testing algorithms for early diagnosis of pituitary disorders.

BACKGROUND: Sellar masses (SM) frequently present with insidious hormonal dysfunction. We previously showed that, by utilizing a combined reflex/reflecting approach involving a laboratory clinician (LC) on common endocrine test results requested by non-specialists, and subsequently adding further warranted tests, previously undiagnosed pituitary disorders can be identified. However, manually employing these strategies by an LC is not feasible for wider screening of pituitary disorders. OBJECTIVE: The aim of this study was to compare the accuracy and financial impact of an Artificial Intelligence (AI) based, fully computerized reflex protocol with manual reflex/reflective intervention protocol led by an LC. METHODS: We developed a proof-of-concept AI-based framework to fully computerize multi-stage reflex testing protocols for pituitary dysfunction using automated reasoning methods. We compared the efficacy of this AI-based protocol with a reflex/reflective protocol based on manually curated retrospective data in identifying pituitary dysfunction based on 12 months of laboratory testing. RESULTS: The AI-based reflex protocol, as compared with the manual protocol, would have identified laboratory tests for add-on that either directly matched or included all manual add-on tests in 92% of cases, and recommended a similar specialist referral in 90% of the cases. The AI-based protocol would have issued 2.8 times the total number of manual add-on laboratory tests at an 85% lower operation cost than the manual protocol when considering marginal test costs, technical staff and specialist salary. CONCLUSION/DISCUSSION: Our AI-based reflex protocol can successfully identify patients with pituitary dysfunction, with lower estimated laboratory cost. Future research will focus on enhancing the protocol's accuracy and incorporating the AI-based reflex protocol into institutional laboratory and hospital information systems for the detection of undiagnosed pituitary disorders.

Wide Area Transepithelial Sampling with Computer-Assisted Analysis (WATS3D) Is Cost-Effective in Barrett's Esophagus Screening.

BACKGROUND: Wide area transepithelial sampling with three-dimensional computer-assisted analysis (WATS3D) is an adjunct to the standard random 4-quadrant forceps biopsies (FB, "Seattle protocol") that significantly increases the detection of Barrett's esophagus (BE) and associated neoplasia in patients undergoing screening or surveillance. AIMS: To examine the cost-effectiveness of adding WATS3D to the Seattle protocol in screening patients for BE. METHODS: A decision analytic model was used to compare the effectiveness and cost-effectiveness of two alternative BE screening strategies in chronic gastroesophageal reflux disease patients: FB with and without WATS3D. The reference case was a 60-year-old white male with gastroesophageal reflux disease (GERD). Effectiveness was measured by the number needed to screen to avert one cancer and one cancer-related death, and quality-adjusted life years (QALYs). Cost was measured in 2019 US$, and the incremental cost-effectiveness ratio (ICER) was measured in $/QALY using thresholds for cost-effectiveness of $100,000/QALY and $150,000/QALY. Cost was measured in 2019 US$. Cost and QALYs were discounted at 3% per year. RESULTS: Between 320 and 337 people would need to be screened with WATS3D in addition to FB to avert one additional cancer, and 328-367 people to avert one cancer-related death. Screening with WATS3D costs an additional $1219 and produced an additional 0.017 QALYs, for an ICER of $71,395/QALY. All one-way sensitivity analyses resulted in ICERs under $84,000/QALY. CONCLUSIONS: Screening for BE in 60-year-old white male GERD patients is more cost-effective when WATS3D is used adjunctively to the Seattle protocol than with the Seattle protocol alone.

Assessment of Acute Pulmonary Embolism by Computer-Aided Technique: A Reliability Study.

BACKGROUND Acute pulmonary embolism is one of the most common cardiovascular diseases. Computer-aided technique is widely used in chest imaging, especially for assessing pulmonary embolism. The reliability and quantitative analyses of computer-aided technique are necessary. This study aimed to evaluate the reliability of geometry-based computer-aided detection and quantification for emboli morphology and severity of acute pulmonary embolism. MATERIAL AND METHODS Thirty patients suspected of acute pulmonary embolism were analyzed by both manual and computer-aided interpretation of vascular obstruction index and computer-aided measurements of emboli quantitative parameters. The reliability of Qanadli and Mastora scores was analyzed using computer-aided and manual interpretation. RESULTS The time costs of manual and computer-aided interpretation were statistically different (374.90±150.16 versus 121.07±51.76, P<0.001). The difference between the computer-aided and manual interpretation of Qanadli score was 1.83±2.19, and 96.7% (29 out of 30) of the measurements were within 95% confidence interval (intraclass correlation coefficient, ICC=0.998). The difference between the computer-aided and manual interpretation of Mastora score was 1.46±1.62, and 96.7% (29 out of 30) of the measurements were within 95% confidence interval (ICC=0.997). The emboli quantitative parameters were moderately correlated with the Qanadli and Mastora scores (all P<0.001). CONCLUSIONS Computer-aided technique could reduce the time costs, improve the and reliability of vascular obstruction index and provided additional quantitative parameters for disease assessment.

Cost-effectiveness of electronic- and clinician-delivered screening, brief intervention and referral to treatment for women in reproductive health centers.

AIMS: To determine the cost-effectiveness of electronic- and clinician-delivered SBIRT (Screening, Brief Intervention and Referral to Treatment) for reducing primary substance use among women treated in reproductive health centers. DESIGN: Cost-effectiveness analysis based on a randomized controlled trial. SETTING: New Haven, CT, USA. PARTICIPANTS: A convenience sample of 439 women seeking routine care in reproductive health centers who used cigarettes, risky amounts of alcohol, illicit drugs or misused prescription medication. INTERVENTIONS: Participants were randomized to enhanced usual care (EUC, n = 151), electronic-delivered SBIRT (e-SBIRT, n = 143) or clinician-delivered SBIRT (SBIRT, n = 145). MEASUREMENTS: The primary outcome was days of primary substance abstinence during the 6-month follow-up period. To account for the possibility that patients might substitute a different drug for their primary substance during the 6-month follow-up period, we also considered the number of days of abstinence from all substances. Incremental cost-effectiveness ratios and cost-effectiveness acceptability curves determined the relative cost-effectiveness of the three conditions from both the clinic and patient perspectives. FINDINGS: From a health-care provider perspective, e-SBIRT is likely (with probability greater than 0.5) to be cost-effective for any willingness-to-pay value for an additional day of primary-substance abstinence and an additional day of all-substance abstinence. From a patient perspective, EUC is most likely to be the cost-effective intervention when the willingness to pay for an additional day of abstinence (both primary-substance and all-substance) is less than $0.18 and e-SBIRT is most likely to be the cost-effective intervention when the willingness to pay for an additional day of abstinence (both primary-substance and all-substance) is greater than $0.18. CONCLUSIONS: e-SBIRT could be a cost-effective approach, from both health-care provider and patient perspectives, for use in reproductive health centers to help women reduce substance misuse.

Recent advancement in the early detection of melanoma using computerized tools: An image analysis perspective.

BACKGROUND: The paper reviews the advancement of tools and current technologies for the detection of melanoma. We discussed several computational strategies from pre- to postprocessing image operations, descriptors, and popular classifiers to diagnose a suspected skin lesion based on its virtual similarity to the malignant lesion with known histopathology. We reviewed the current state of smart phone-based apps as diagnostic tools for screening. METHODS: A literature survey was conducted using a combination of keywords in the bibliographic databases: PubMed, AJCC, PH2, EDRA, and ISIC melanoma project. A number of melanoma detection apps were downloaded for two major mobile operating systems, iOS and Android; their important uses, key challenges, and various expert opinions were evaluated and also discussed. RESULTS: We have provided an overview of research on the computer-aided diagnosis methods to estimate melanoma risk and early screening. Dermoscopic images are the most viable option for the advent of new image processing technologies based on which many of the skin cancer detection apps are being developed recently. We have categorized and explored their potential uses, evaluation criteria, limitations, and other details. CONCLUSION: Such advancements are helpful in the sense they are raising awareness. Diagnostic accuracy is the major issue of smart phone-based apps and it cannot replace an adequate clinical experience and biopsy procedures.

Cost-effectiveness of digital surveillance clinics with optical coherence tomography versus hospital eye service follow-up for patients with screen-positive maculopathy.

BACKGROUND: Annually 2.7 million individuals are offered screening for diabetic retinopathy (DR) in England. Spectral-Domain Optical Coherence Tomography (SD-OCT) has the potential to relieve pressure on NHS services by correctly identifying patients who are screen positive for maculopathy on two-dimensional photography without evidence of clinically significant macular oedema (CSMO), limiting the number of referrals to hospitals. We aim to assess whether the addition of SDOCT imaging in digital surveillance clinics is a cost-effective intervention relative to hospital eye service (HES) follow-up. METHODS: We used patient-level data from the Gloucestershire Diabetic Eye Screening Service linked to the local digital surveillance programme and HES between 2012 and 2015. A model was used to simulate the progression of individuals with background diabetic retinopathy (R1) and diabetic maculopathy (M1) following DR screening across the clinic pathways over 12 months. RESULTS: Between January 2012 and December 2014, 696 people undergoing DR screening were found to have screen-positive maculopathy in at least one eye for the first time, with a total of 766 eyes identified as having R1M1. The mean annual cost of assessing and surveillance through the SD-OCT clinic pathway was £101 (95% CI: 91-139) as compared with £177 (95%CI: 164-219) under the HES pathway. Surveillance under an SD-OCT clinic generated cost savings of £76 (95% CI: 70-81) per patient. CONCLUSIONS: Our analysis shows that SD-OCT surveillance of patients diagnosed as R1M1 at DR screening is not only cost-effective but generates considerable cost savings.

Learning-based classification of informative laryngoscopic frames.

BACKGROUND AND OBJECTIVE: Early-stage diagnosis of laryngeal cancer is of primary importance to reduce patient morbidity. Narrow-band imaging (NBI) endoscopy is commonly used for screening purposes, reducing the risks linked to a biopsy but at the cost of some drawbacks, such as large amount of data to review to make the diagnosis. The purpose of this paper is to present a strategy to perform automatic selection of informative endoscopic video frames, which can reduce the amount of data to process and potentially increase diagnosis performance. METHODS: A new method to classify NBI endoscopic frames based on intensity, keypoint and image spatial content features is proposed. Support vector machines with the radial basis function and the one-versus-one scheme are used to classify frames as informative, blurred, with saliva or specular reflections, or underexposed. RESULTS: When tested on a balanced set of 720 images from 18 different laryngoscopic videos, a classification recall of 91% was achieved for informative frames, significantly overcoming three state of the art methods (Wilcoxon rank-signed test, significance level = 0.05). CONCLUSIONS: Due to the high performance in identifying informative frames, the approach is a valuable tool to perform informative frame selection, which can be potentially applied in different fields, such us computer-assisted diagnosis and endoscopic view expansion.

Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network.

BACKGROUND: Ocular images play an essential role in ophthalmological diagnoses. Having an imbalanced dataset is an inevitable issue in automated ocular diseases diagnosis; the scarcity of positive samples always tends to result in the misdiagnosis of severe patients during the classification task. Exploring an effective computer-aided diagnostic method to deal with imbalanced ophthalmological dataset is crucial. METHODS: In this paper, we develop an effective cost-sensitive deep residual convolutional neural network (CS-ResCNN) classifier to diagnose ophthalmic diseases using retro-illumination images. First, the regions of interest (crystalline lens) are automatically identified via twice-applied Canny detection and Hough transformation. Then, the localized zones are fed into the CS-ResCNN to extract high-level features for subsequent use in automatic diagnosis. Second, the impacts of cost factors on the CS-ResCNN are further analyzed using a grid-search procedure to verify that our proposed system is robust and efficient. RESULTS: Qualitative analyses and quantitative experimental results demonstrate that our proposed method outperforms other conventional approaches and offers exceptional mean accuracy (92.24%), specificity (93.19%), sensitivity (89.66%) and AUC (97.11%) results. Moreover, the sensitivity of the CS-ResCNN is enhanced by over 13.6% compared to the native CNN method. CONCLUSION: Our study provides a practical strategy for addressing imbalanced ophthalmological datasets and has the potential to be applied to other medical images. The developed and deployed CS-ResCNN could serve as computer-aided diagnosis software for ophthalmologists in clinical application.

[Evaluating the maturity of IT-supported clinical imaging and diagnosis using the Digital Imaging Adoption Model : Are your clinical imaging processes ready for the digital era?] / Bestimmung des Reifegrades der IT-gestützten klinischen Bildgebung und Befundung mit dem Digital Imaging Adoption Model : Ist Ihre klinische Bildgebung bereit für das digitale Zeitalter?

The Digital Imaging Adoption Model (DIAM) has been jointly developed by HIMSS Analytics and the European Society of Radiology (ESR). It helps evaluate the maturity of IT-supported processes in medical imaging, particularly in radiology. This eight-stage maturity model drives your organisational, strategic and tactical alignment towards imaging-IT planning. The key audience for the model comprises hospitals with imaging centers, as well as external imaging centers that collaborate with hospitals. The assessment focuses on different dimensions relevant to digital imaging, such as software infrastructure and usage, workflow security, clinical documentation and decision support, data exchange and analytical capabilities. With its standardised approach, it enables regional, national and international benchmarking. All DIAM participants receive a structured report that can be used as a basis for presenting, e.g. budget planning and investment decisions at management level.

Modeling the patient and health system impacts of alternative xpert® MTB/RIF algorithms for the diagnosis of pulmonary tuberculosis in Addis Ababa, Ethiopia.

BACKGROUND: To reduce global tuberculosis (TB) burden, the active disease must be diagnosed quickly and accurately and patients should be treated and cured. In Ethiopia, TB diagnosis mainly relies on spot-morning-spot (SMS) sputum sample smear analysis using Ziehl-Neelsen staining techniques (ZN). Since 2014 targeted use of xpert has been implemented. New diagnostic techniques have higher sensitivity and are likely to detect more cases if routinely implemented. The objective of our study was to project the effects of alternative diagnostic algorithms on the patient, health system, and costs, and identify cost-effective algorithms that increase TB case detection in Addis Ababa, Ethiopia. METHODS: An observational quantitative modeling framework was applied using the Virtual Implementation approach. The model was designed to represent the operational and epidemiological context of Addis Ababa, the capital city of Ethiopia. We compared eight diagnostic algorithm with ZN microscopy, light emitting diode (LED) fluorescence microscopy and Xpert MTB/RIF. Interventions with an annualized cost per averted disability adjusted life year (DALY) of less than the Gross Domestic Product (GDP) per capita are considered cost-effective interventions. RESULTS: With a cost lower than the average per-capita GDP (US$690 for Ethiopia) for each averted disability adjusted life year (DALY), three of the modeled algorithms are cost-effective. Implementing them would have important patient, health system, and population-level effects in the context of Addis Ababa ❖ The full roll-out of Xpert MTB/RIF as the primary test for all presumptive TB cases would avert 91170 DALYs (95% credible interval [CrI] 54888 - 127448) with an additional health system cost of US$ 11.6 million over the next 10 years. The incremental cost-effectiveness ratio (ICER) is $370 per DALY averted. ❖ Same day LED fluorescence microscopy for all presumptive TB cases combined with Xpert MTB/RIF targeted to HIV-positive and High multidrug resistant (MDR) risk groups would avert 73600 DALYs( 95% CrI 48373 - 99214) with an additional cost of US$5.1 million over the next 10 years. The ICER is $169per DALY averted. ❖ Same-day LED fluorescence microscopy for all presumptive TB cases (and no Xpert MTB/RIF) would avert 43580 DALYs with a reduction cost of US$ 0.2 million over the next 10years. The ICER is $13 per DALY averted. CONCLUSIONS: The full roll-out of Xpert MTB/RIF is predicted to be the best option to substantially reduce the TB burden in Addis Ababa and is considered cost effective. However, the investment cost to implement this is far beyond the budget of the national TB control program. Targeted use of Xpert MTB/RIF for HIV positive and high MDR risk groups with same-day LED fluorescence microscopy for all other presumptive TB cases is an affordable alternative.

Fast retrieval of calcification from sequential intravascular ultrasound gray-scale images.

Intravascular ultrasound (IVUS)-based tissue characterization is invaluable for the computer-aided diagnosis and interventional treatment of cardiac vessel diseases. Although the analysis of raw backscattered signals allows more accurate plaque characterization than gray-scale images, its applications are limited due to its nature of electrocardiogram-gated acquisition. Images acquired by IVUS devices that do not allow the acquisition of raw signals cannot be characterized. To address these limitations, we developed a method for fast frame-by-frame retrieval and location of calcification according to the jump features of radial gray-level variation curves from sequential IVUS gray-scale images. The proposed method consists of three main steps: (1) radial gray-level variation curves are extracted from each filtered polar view, (2) sequential images are preliminarily queried according to the maximal slopes of radial gray-level variation curves, and finally, (3) key frames that include calcification are selected through checking the gray-level features of successive pixel columns in the preliminary results. Experimental results with clinically acquired in vivo data sets indicate key frames that include calcification can be retrieved with the advantages of simplicity, high efficiency, and accuracy. Recognition results correlate well with manual characterization results obtained by experienced physicians and through virtual histology.

Validation of a substance and alcohol use assessment instrument among orphans and vulnerable children in Zambia using Audio Computer Assisted Self-Interviewing (ACASI).

BACKGROUND: Substance and alcohol misuse is a global problem that increases the risk of HIV infection. This is a concern among orphans and vulnerable children (OVC) in sub-Saharan Africa who may have elevated substance use rates. The Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) is a reliable and valid instrument of substance use among adults in primary care high-income settings. This study examined psychometric properties of the ASSIST among OVC in Zambia using Audio Computer Assisted Self-Interviewing (ACASI). METHODS: Baseline data from an ongoing randomized trial of interventions to reduce HIV risk behaviors were analyzed. The analysis included 502 OVC ages 13-17 living in low-income, high-density neighborhoods in Lusaka, Zambia. Internal consistency of the ASSIST was assessed and discriminant validity was measured using items from the Youth Self Report as criterion variables. RESULTS: Internal reliability was strong with a Cronbach's alpha of ≥0.80 for each of the specific substance scales and total substance involvement. For all substances except tobacco and sedatives, discriminant validity was demonstrated in distinguishing between low risk use and moderate use. Sensitivity and specificity analysis indicated adequate area under the curve across substance types (AUC range: 0.68-0.80). Discrimination between moderate and high risk was demonstrated for alcohol and total substance involvement. CONCLUSIONS: ASSIST administered via ACASI is a reliable instrument and an appropriate tool for distinguishing between low and hazardous substance use among adolescent OVC populations in sub-Saharan Africa. Additional examination is warranted to determine its ability to measure gradations of severity within hazardous use.

Evaluating a computer aid for assessing stomach symptoms (ECASS): study protocol for a randomised controlled trial.

BACKGROUND: For most cancers, only a minority of patients have symptoms meeting the National Institute for Health and Clinical Excellence guidance for urgent referral. For gastro-oesophageal cancers, the 'alarm' symptoms of dysphagia and weight loss are reported by only 32 and 8 % of patients, respectively, and their presence correlates with advanced-stage disease. Electronic clinical decision-support tools that integrate with clinical computer systems have been developed for general practice, although uncertainty remains concerning their effectiveness. The objectives of this trial are to optimise the intervention and establish the acceptability of both the intervention and randomisation, confirm the suitability and selection of outcome measures, finalise the design for the phase III definitive trial, and obtain preliminary estimates of the intervention effect. METHODS/DESIGN: This is a two-arm, multi-centre, cluster-randomised, controlled phase II trial design, which will extend over a 16-month period, across 60 general practices within the North East and North Cumbria and the Eastern Local Clinical Research Network areas. Practices will be randomised to receive either the intervention (the electronic clinical decision-support tool) or to act as a control (usual care). From these practices, we will recruit 3000 adults who meet the trial eligibility criteria and present to their GP with symptoms suggestive of gastro-oesophageal cancer. The main measures are the process data, which include the practitioner outcomes, service outcomes, diagnostic intervals, health economic outcomes, and patient outcomes. One-on-one interviews in a sub-sample of 30 patient-GP dyads will be undertaken to understand the impact of the use or non-use of the electronic clinical decision-support tool in the consultation. A further 10-15 GPs will be interviewed to identify and gain an understanding of the facilitators and constraints influencing implementation of the electronic clinical decision-support tool in practice. DISCUSSION: We aim to generate new knowledge on the process measures regarding the use of electronic clinical decision-support tools in primary care in general and to inform a subsequent definitive phase III trial. Preliminary data on the impact of the support tool on resource utilisation and health care costs will also be collected. TRIAL REGISTRATION: ISRCTN Registry, ISRCTN12595588 .

Telemedicine and M-Health in Hypertension Management: Technologies, Applications and Clinical Evidence.

Electronic processes and communication technologies are more and more often employed to provide healthcare services to caregivers and their patients. Such solutions are currently referred as e-health, the most popular and widely distributed being those based on telemedicine and mobile health (m-health). A specific application of telemedicine for hypertension management is blood pressure telemonitoring (BPT), which allows remote data transmission of BP and additional information on patients' health status from their living site or from a community setting to the doctor's office or the hospital. Several randomized studies have documented a significant BP reduction with regular BPT compared to usual care, particularly in high risk hypertensive patients. Additional benefits are observed when BPT is offered under the supervision of a team of healthcare professionals, including a community pharmacist. BPT may also be provided in the context of m-health solutions, which commonly include wireless diagnostic and clinical decision support tools. M-health has the potential to promote patient's self-management, as a complement to the doctor's intervention, and encourage greater participation in medical decision making. Current statistics show that half of smartphone owners gather health information through their phone and 19 % use a health app. In case of hypertensive patients the most popular apps are those with tracking function, including BPT. Thus, e-health, and in particular BPT and m-health, are progressively gaining a key role in the management of hypertensive patients, having the potential to improve the quality of the delivered care and to more effectively prevent cardiovascular consequences of high BP.

A prediction model based on artificial neural networks for the diagnosis of obstructive sleep apnea.

BACKGROUND: Recently, artificial neural networks (ANNs) have been widely applied in science, engineering, and medicine. In the present study, we evaluated the ability of artificial neural networks to be used as a computer program and assistant tool in the diagnosis of obstructive sleep apnea (OSA). Our hypothesis was that ANNs could use clinical information to precisely predict cases of OSA. METHOD: The study population in this clinical trial consisted of 201 patients with suspected OSA (140 with a positive diagnosis of OSA and 61 with a negative diagnosis of OSA). The artificial neural network was trained by assessing five clinical variables from 201 patients; efficiency was then estimated in this group of 201 patients. The patients were classified using a five-element input vector. ANN classifiers were assessed with the multilayer perceptron (MLP) networks. RESULTS: Use of the MLP classifiers resulted in a diagnostic accuracy of 86.6 %, which in clinical practice is high enough to reduce the number of patients evaluated by polysomnography (PSG), an expensive and limited diagnostic resource. CONCLUSIONS: By establishing a pattern that allows the recognition of OSA, ANNs can be used to identify patients requiring PSG.

Retrospective analysis supports algorithm as efficient diagnostic approach to treatable intellectual developmental disabilities.

BACKGROUND: Intellectual developmental disorders (IDD(1)), characterized by a significant impairment in cognitive function and behavior, affect 2.5% of the population and are associated with considerable morbidity and healthcare costs. Inborn errors of metabolism (IEM) currently constitute the largest group of genetic defects presenting with IDD, which are amenable to causal therapy. Recently, we created an evidence-based 2-tiered diagnostic protocol (TIDE protocol); the first tier is a 'screening step' applied in all patients, comprising routinely performed, wide available metabolic tests in blood and urine, while second-tier tests are more specific and based on the patient's phenotype. The protocol is supported by an app (www.treatable-ID.org). OBJECTIVE: To retrospectively examine the cost- and time-effectiveness of the TIDE protocol in patients identified with a treatable IEM at the British Columbia Children's Hospital. METHODS: We searched the database for all IDD patients diagnosed with a treatable IEM, during the period 2000-2009 in our academic institution. Data regarding the patient's clinical phenotype, IEM, diagnostic tests and interval were collected. Total costs and time intervals associated with all testing and physician consultations actually performed were calculated and compared to the model of the TIDE protocol. RESULTS: Thirty-one patients (16 males) were diagnosed with treatable IDD during the period 2000-2009. For those identifiable via the 1st tier (n=20), the average cost savings would have been $311.17 CAD, and for those diagnosed via a second-tier test (n=11) $340.14 CAD. Significant diagnostic delay (mean 9 months; range 1-29 months) could have been avoided in 9 patients with first-tier diagnoses, had the TIDE protocol been used. For those with second-tier treatable IDD, diagnoses could have been more rapidly achieved with the use of the Treatable IDD app allowing for specific searches based on signs and symptoms. CONCLUSION: The TIDE protocol for treatable forms of IDD appears effective reducing diagnostic delay and unnecessary costs. Larger prospective studies, currently underway, are needed to prove that standard screening for treatable conditions in patients with IDD is time- and cost-effective, and most importantly will preserve brain function by timely diagnosis enabling initiation of causal therapy.

Assessing diagnostic complexity: An image feature-based strategy to reduce annotation costs.

Computer-aided diagnosis systems can play an important role in lowering the workload of clinical radiologists and reducing costs by automatically analyzing vast amounts of image data and providing meaningful and timely insights during the decision making process. In this paper, we present strategies on how to better manage the limited time of clinical radiologists in conjunction with predictive model diagnosis. We first introduce a metric for discriminating between the different categories of diagnostic complexity (such as easy versus hard) encountered when interpreting CT scans. Second, we propose to learn the diagnostic complexity using a classification approach based on low-level image features automatically extracted from pixel data. We then show how this classification can be used to decide how to best allocate additional radiologists to interpret a case based on its diagnosis category. Using a lung nodule image dataset, we determined that, by a simple division of cases into hard and easy to diagnose, the number of interpretations can be distributed to significantly lower the cost with limited loss in prediction accuracy. Furthermore, we show that with just a few low-level image features (18% of the original set) we are able to determine the easy from hard cases for a significant subset (66%) of the lung nodule image data.

Effectiveness and cost-effectiveness of telehealthcare for chronic obstructive pulmonary disease: study protocol for a cluster randomized controlled trial.

BACKGROUND: Several feasibility studies show promising results of telehealthcare on health outcomes and health-related quality of life for patients suffering from chronic obstructive pulmonary disease, and some of these studies show that telehealthcare may even lower healthcare costs. However, the only large-scale trial we have so far - the Whole System Demonstrator Project in England - has raised doubts about these results since it conclude that telehealthcare as a supplement to usual care is not likely to be cost-effective compared with usual care alone. METHODS/DESIGN: The present study is known as 'TeleCare North' in Denmark. It seeks to address these doubts by implementing a large-scale, pragmatic, cluster-randomized trial with nested economic evaluation. The purpose of the study is to assess the effectiveness and the cost-effectiveness of a telehealth solution for patients suffering from chronic obstructive pulmonary disease compared to usual practice. General practitioners will be responsible for recruiting eligible participants (1,200 participants are expected) for the trial in the geographical area of the North Denmark Region. Twenty-six municipality districts in the region define the randomization clusters. The primary outcomes are changes in health-related quality of life, and the incremental cost-effectiveness ratio measured from baseline to follow-up at 12 months. Secondary outcomes are changes in mortality and physiological indicators (diastolic and systolic blood pressure, pulse, oxygen saturation, and weight). DISCUSSION: There has been a call for large-scale clinical trials with rigorous cost-effectiveness assessments in telehealthcare research. This study is meant to improve the international evidence base for the effectiveness and cost-effectiveness of telehealthcare to patients suffering from chronic obstructive pulmonary disease by implementing a large-scale pragmatic cluster-randomized clinical trial. TRIAL REGISTRATION: Clinicaltrials.gov, http://NCT01984840, November 14, 2013.