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Background Giant cell arteritis (GCA) is a relatively common form of primary systemic vasculitis, which, if left untreated, can lead to permanent sight loss. We compared ultrasound as an alternative diagnostic test with temporal artery biopsy, which may be negative in 9–61% of true cases. Objective To compare the clinical effectiveness and cost-effectiveness of ultrasound with biopsy in diagnosing patients with suspected GCA. Design Prospective multicentre cohort study. Setting Secondary care. Participants A total of 381 patients referred with newly suspected GCA. Main outcome measures Sensitivity, specificity and cost-effectiveness of ultrasound compared with biopsy or ultrasound combined with biopsy for diagnosing GCA and interobserver reliability in interpreting scan or biopsy findings. Results We developed and implemented an ultrasound training programme for diagnosing suspected GCA. We recruited 430 patients with suspected GCA. We analysed 381 patients who underwent both ultrasound and biopsy within 10 days of starting treatment for suspected GCA and who attended a follow-up assessment (median age 71.1 years; 72% female). The sensitivity of biopsy was 39% [95% confidence interval (CI) 33% to 46%], which was significantly lower than previously reported and inferior to ultrasound (54%, 95% CI 48% to 60%); the specificity of biopsy (100%, 95% CI 97% to 100%) was superior to ultrasound (81%, 95% CI 73% to 88%). If we scanned all suspected patients and performed biopsies only on negative cases, sensitivity increased to 65% and specificity was maintained at 81%, reducing the need for biopsies by 43%. Strategies combining clinical judgement (clinician’s assessment at 2 weeks) with the tests showed sensitivity and specificity of 91% and 81%, respectively, for biopsy and 93% and 77%, respectively, for ultrasound; cost-effectiveness (incremental net monetary benefit) was £485 per patient in favour of ultrasound with both cost savings and a small health gain. Inter-rater analysis revealed moderate agreement among sonographers (intraclass correlation coefficient 0.61, 95% CI 0.48 to 0.75), similar to pathologists (0.62, 95% CI 0.49 to 0.76). Limitations There is no independent gold standard diagnosis for GCA. The reference diagnosis used to determine accuracy was based on classification criteria for GCA that include clinical features at presentation and biopsy results. Conclusion We have demonstrated the feasibility of providing training in ultrasound for the diagnosis of GCA. Our results indicate better sensitivity but poorer specificity of ultrasound compared with biopsy and suggest some scope for reducing the role of biopsy. The moderate interobserver agreement for both ultrasound and biopsy indicates scope for improving assessment and reporting of test results and challenges the assumption that a positive biopsy always represents GCA. Future work Further research should address the issue of an independent reference diagnosis, standards for interpreting and reporting test results and the evaluation of ultrasound training, and should also explore the acceptability of these new diagnostic strategies in GCA. Funding The National Institute for Health Research Health Technology Assessment programme.

Our purpose was to conduct a new analysis to update and extend previously published trends of fructose availability and estimated fructose intake and food sources of dietary fructose from the 1977-1978 Nationwide Food Consumption Survey (NFCS) data. We estimated fructose usual intake with data from NHANES 1999-2004 for 25,165 individuals (1 y and older, excluding pregnant and lactating women and breast-fed infants) using the Iowa State C-SIDE software. We applied food group-specific conversion factors to individual measures of sugar intakes following the earlier study. Sweetener availability in the United States increased from 1978, peaked in 1999, and declined through 2005. The high-fructose corn syrup percentage of sweeteners increased from 16% in 1978 to 42% in 1998 and then stabilized. Since 1978, mean daily intakes of added and total fructose increased in all gender and age groups, whereas naturally occurring (N) fructose intake decreased or remained constant. Total fructose intake as percentage of energy and as percentage of carbohydrate increased 1 and 1.2%, whereas daily energy and carbohydrate intakes increased 18 and 41%, respectively. Similar to 1978 results, nonalcoholic beverages and grain products were the principal food sources of added fructose. Fruits and fruit products were the main dietary sources of N fructose in 2004; in 1978, grain products and vegetables were more predominant food sources. Although comparison of estimates of fructose intakes between data from the 1977-1978 NFCS and the NHANES 1999-2004 showed an increase, this increase was dwarfed by greater increases in total daily energy and carbohydrate intakes.

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Purpose of Review Artificial intelligence (AI) technology holds both great promise to transform mental healthcare and potential pitfalls. This article provides an overview of AI and current applications in healthcare, a review of recent original research on AI specific to mental health, and a discussion of how AI can supplement clinical practice while considering its current limitations, areas needing additional research, and ethical implications regarding AI technology. Recent Findings We reviewed 28 studies of AI and mental health that used electronic health records (EHRs), mood rating scales, brain imaging data, novel monitoring systems (e.g., smartphone, video), and social media platforms to predict, classify, or subgroup mental health illnesses including depression, schizophrenia or other psychiatric illnesses, and suicide ideation and attempts. Collectively, these studies revealed high accuracies and provided excellent examples of AI's potential in mental healthcare, but most should be considered early proof-of-concept works demonstrating the potential of using machine learning (ML) algorithms to address mental health questions, and which types of algorithms yield the best performance. Summary As AI techniques continue to be refined and improved, it will be possible to help mental health practitioners re-define mental illnesses more objectively than currently done in the DSM-5, identify these illnesses at an earlier or prodromal stage when interventions may be more effective, and personalize treatments based on an individual's unique characteristics. However, caution is necessary in order to avoid over-interpreting preliminary results, and more work is required to bridge the gap between AI in mental health research and clinical care.