Large language models encode clinical knowledge.

Large language models (LLMs) have demonstrated impressive capabilities, but the bar for clinical applications is high. Attempts to assess the clinical knowledge of models typically rely on automated evaluations based on limited benchmarks. Here, to address these limitations, we present MultiMedQA, a benchmark combining six existing medical question answering datasets spanning professional medicine, research and consumer queries and a new dataset of medical questions searched online, HealthSearchQA. We propose a human evaluation framework for model answers along multiple axes including factuality, comprehension, reasoning, possible harm and bias. In addition, we evaluate Pathways Language Model1 (PaLM, a 540-billion parameter LLM) and its instruction-tuned variant, Flan-PaLM2 on MultiMedQA. Using a combination of prompting strategies, Flan-PaLM achieves state-of-the-art accuracy on every MultiMedQA multiple-choice dataset (MedQA3, MedMCQA4, PubMedQA5 and Measuring Massive Multitask Language Understanding (MMLU) clinical topics6), including 67.6% accuracy on MedQA (US Medical Licensing Exam-style questions), surpassing the prior state of the art by more than 17%. However, human evaluation reveals key gaps. To resolve this, we introduce instruction prompt tuning, a parameter-efficient approach for aligning LLMs to new domains using a few exemplars. The resulting model, Med-PaLM, performs encouragingly, but remains inferior to clinicians. We show that comprehension, knowledge recall and reasoning improve with model scale and instruction prompt tuning, suggesting the potential utility of LLMs in medicine. Our human evaluations reveal limitations of today's models, reinforcing the importance of both evaluation frameworks and method development in creating safe, helpful LLMs for clinical applications.

Metrics reloaded: recommendations for image analysis validation.

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. In biomedical image analysis, chosen performance metrics often do not reflect the domain interest, and thus fail to adequately measure scientific progress and hinder translation of ML techniques into practice. To overcome this, we created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. Developed by a large international consortium in a multistage Delphi process, it is based on the novel concept of a problem fingerprint-a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), dataset and algorithm output. On the basis of the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as classification tasks at image, object or pixel level, namely image-level classification, object detection, semantic segmentation and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. Its applicability is demonstrated for various biomedical use cases.

International evaluation of an AI system for breast cancer screening.

Screening mammography aims to identify breast cancer at earlier stages of the disease, when treatment can be more successful1. Despite the existence of screening programmes worldwide, the interpretation of mammograms is affected by high rates of false positives and false negatives2. Here we present an artificial intelligence (AI) system that is capable of surpassing human experts in breast cancer prediction. To assess its performance in the clinical setting, we curated a large representative dataset from the UK and a large enriched dataset from the USA. We show an absolute reduction of 5.7% and 1.2% (USA and UK) in false positives and 9.4% and 2.7% in false negatives. We provide evidence of the ability of the system to generalize from the UK to the USA. In an independent study of six radiologists, the AI system outperformed all of the human readers: the area under the receiver operating characteristic curve (AUC-ROC) for the AI system was greater than the AUC-ROC for the average radiologist by an absolute margin of 11.5%. We ran a simulation in which the AI system participated in the double-reading process that is used in the UK, and found that the AI system maintained non-inferior performance and reduced the workload of the second reader by 88%. This robust assessment of the AI system paves the way for clinical trials to improve the accuracy and efficiency of breast cancer screening.

A clinically applicable approach to continuous prediction of future acute kidney injury.

The early prediction of deterioration could have an important role in supporting healthcare professionals, as an estimated 11% of deaths in hospital follow a failure to promptly recognize and treat deteriorating patients1. To achieve this goal requires predictions of patient risk that are continuously updated and accurate, and delivered at an individual level with sufficient context and enough time to act. Here we develop a deep learning approach for the continuous risk prediction of future deterioration in patients, building on recent work that models adverse events from electronic health records2-17 and using acute kidney injury-a common and potentially life-threatening condition18-as an exemplar. Our model was developed on a large, longitudinal dataset of electronic health records that cover diverse clinical environments, comprising 703,782 adult patients across 172 inpatient and 1,062 outpatient sites. Our model predicts 55.8% of all inpatient episodes of acute kidney injury, and 90.2% of all acute kidney injuries that required subsequent administration of dialysis, with a lead time of up to 48 h and a ratio of 2 false alerts for every true alert. In addition to predicting future acute kidney injury, our model provides confidence assessments and a list of the clinical features that are most salient to each prediction, alongside predicted future trajectories for clinically relevant blood tests9. Although the recognition and prompt treatment of acute kidney injury is known to be challenging, our approach may offer opportunities for identifying patients at risk within a time window that enables early treatment.

An International Comparison of the Management of Gastrointestinal Surgical Emergencies in Octogenarians-England Versus United States: A National Population-based Cohort Study.

OBJECTIVE: To compare the United States and England for the utilization of surgical intervention and in-hospital mortality from 5 gastrointestinal emergencies in octogenarians. BACKGROUND: The proportion of older adults is growing and will represent a substantial challenge to clinicians in the next decade. METHODS: Between 2006 and 2012, the rate of surgical intervention and in-hospital mortality for 5 index conditions for octogenarians were compared between the United States and England: appendicitis, incarcerated/strangulated abdominal hernia, perforation of esophagus, small or large bowel, and peptic ulcer. Univariate and multivariate analyses were performed to adjust for underlying differences in patient demographics. RESULTS: Thirty-two thousand one hundred fifty-one admissions of octogenarians in England for 5 index surgical emergencies were compared with 162,142 admissions in the USA.Surgical intervention was significantly more common in the USA than in England for all 5 conditions: appendicitis [odds ratio (OR) 4.63, 95% confidence interval (95% CI) 4.21-5.09], abdominal hernia (OR 2.06, 95% CI 1.97-2.15), perforated esophagus (OR 1.71, 95% CI 1.31-2.24), small and large bowel perforation (OR 4.33, 95% CI 4.12-4.56), and peptic ulcer perforation (OR 4.63, 95% CI 4.27-5.02). In-hospital mortality was significantly more common in England than in the USA for all 5 conditions: appendicitis (OR 3.22, 95% CI 2.73-3.78), abdominal hernia (OR 3.49, 95% CI 3.29-3.70), perforated esophagus (OR 4.06, 95% CI 3.03-5.44), small and large bowel perforation (OR 6.97, 95% CI 6.60-7.37), and peptic ulcer perforation (OR 3.67, 95% CI 3.40-3.96). CONCLUSION: Surgery is used less commonly in England for emergency gastrointestinal conditions in octogenarians, which may be associated with a high rate of in-hospital mortality from these conditions compared with the USA.

Clinically Applicable Segmentation of Head and Neck Anatomy for Radiotherapy: Deep Learning Algorithm Development and Validation Study.

BACKGROUND: Over half a million individuals are diagnosed with head and neck cancer each year globally. Radiotherapy is an important curative treatment for this disease, but it requires manual time to delineate radiosensitive organs at risk. This planning process can delay treatment while also introducing interoperator variability, resulting in downstream radiation dose differences. Although auto-segmentation algorithms offer a potentially time-saving solution, the challenges in defining, quantifying, and achieving expert performance remain. OBJECTIVE: Adopting a deep learning approach, we aim to demonstrate a 3D U-Net architecture that achieves expert-level performance in delineating 21 distinct head and neck organs at risk commonly segmented in clinical practice. METHODS: The model was trained on a data set of 663 deidentified computed tomography scans acquired in routine clinical practice and with both segmentations taken from clinical practice and segmentations created by experienced radiographers as part of this research, all in accordance with consensus organ at risk definitions. RESULTS: We demonstrated the model's clinical applicability by assessing its performance on a test set of 21 computed tomography scans from clinical practice, each with 21 organs at risk segmented by 2 independent experts. We also introduced surface Dice similarity coefficient, a new metric for the comparison of organ delineation, to quantify the deviation between organ at risk surface contours rather than volumes, better reflecting the clinical task of correcting errors in automated organ segmentations. The model's generalizability was then demonstrated on 2 distinct open-source data sets, reflecting different centers and countries to model training. CONCLUSIONS: Deep learning is an effective and clinically applicable technique for the segmentation of the head and neck anatomy for radiotherapy. With appropriate validation studies and regulatory approvals, this system could improve the efficiency, consistency, and safety of radiotherapy pathways.

Reintervention After Antireflux Surgery for Gastroesophageal Reflux Disease in England.

BACKGROUND: After antireflux surgery, highly variable rates of recurrent gastroesophageal reflux disease (GERD) have been reported. OBJECTIVE: To identify the occurrence and risk factors of recurrent GERD requiring surgical reintervention or medication. METHODS: The Hospital Episode Statistics database was used to identify adults in England receiving primary antireflux surgery for GERD in 2000 to 2012 with follow-up through 2014, and the outcome was surgical reintervention. In a subset of participants, the Clinical Practice Research Datalink was additionally used to assess proton pump inhibitor therapy for at least 6 months (medical reintervention). Risk factors were assessed using multivariable Cox regression providing adjusted hazard ratios (HRs) with 95% confidence intervals (95% CIs). RESULTS: Among 22,377 patients who underwent primary antireflux surgery in the Hospital Episode Statistics dataset, 811 (3.6%) had surgical reintervention, with risk factors being age 41 to 60 years (HR = 1.22, 95% CI 1.03-1.44), female sex (HR = 1.5; 95% CI 1.3-1.74), white ethnicity (HR = 1.71, 95% CI 1.06-2.77), and low hospital annual volume of antireflux surgery (HR = 1.32, 95% CI 1.04-1.67). Among 2005 patients who underwent primary antireflux surgery in the Clinical Practice Research Datalink dataset, 189 (9.4%) had surgical reintervention and 1192 (59.5%) used proton pump inhibitor therapy, with risk factors for the combined outcome being age >60 years (HR = 2.38, 95% CI 1.81-3.13) and preoperative psychiatric morbidity (HR = 1.58, 95% CI 1.25-1.99). CONCLUSION: At least 3.6% of patients may require surgical reintervention and 59.5% medical therapy following antireflux surgery in England. The influence of patient characteristics and hospital volume highlights the need for patient selection and surgical experience in successful antireflux surgery.

Editor's Choice - Assessment of Correlation Between Mean Size of Infrarenal Abdominal Aortic Aneurysm at Time of Intact Repair Against Repair and Rupture Rate in Nine Countries.

OBJECTIVE: This study aimed to analyse the mean abdominal aortic aneurysm (AAA) diameter for repair in nine countries, and to determine variation in mean AAA diameter for elective AAA repair and its relationship to rupture AAA repair rates and aneurysm related mortality in corresponding populations. METHODS: Data on intact (iAAA) and ruptured infrarenal AAA (rAAA) repair for the years 2010-2012 were collected from Denmark, England, Finland, Germany, Hungary, New Zealand, Norway, Sweden, and the USA. The rate of iAAA repair and rAAA per 100 000 inhabitants above 59 years old, mean AAA diameter for iAAA repair and rAAA repair, and the national rates of rAAA were assessed. National cause of death statistics were used to estimate aneurysm related mortality. Direct standardisation methods were applied to the national mortality data. Logistic regression and analysis of variance model adjustments were made for age groups, sex, and year. RESULTS: There was a variation in the mean diameter of iAAA repair (n = 34 566; range Germany = 57 mm, Denmark = 68 mm). The standardised iAAA repair rate per 100000 inhabitants varied from 10.4 (Hungary) to 66.5 (Norway), p<.01, and the standardised rAAA repair rate per 100 000 from 5.8 (USA) to 16.9 (England), p<.01. Overall, there was no significant correlation between mean diameter of iAAA repair and standardised iAAA rate (r2 = 0.04, p = .3). There was no significant correlation between rAAA repair rate (n = 12 628) with mean diameter of iAAA repair (r2 = 0.2, p = .1). CONCLUSION: Despite recommendations from learned society guidelines, data indicate variations in mean diameter for AAA repair. There was no significant correlation between mean diameter of AAA repair and rates of iAAA repair and rAAA repair. These analyses are subject to differences in disease prevalence, uncertainties in rupture rates, validations of vascular registries, causes of death and registrations.

Comparison of Surgical Intervention and Mortality for Seven Surgical Emergencies in England and the United States.

OBJECTIVE: To examine differences between England and the USA in the rate of surgical intervention and in-hospital mortality for 7 index surgical emergencies. BACKGROUND: Considerable international variation exists in the configuration, provision, and outcomes of emergency healthcare. METHODS: Patients aged <80 years hospitalized with 1 of 7 surgical emergencies (ruptured abdominal aortic aneurysm, aortic dissection, appendicitis, perforated esophagus, peptic ulcer, small bowel or large bowel, and incarcerated or strangulated hernias) were identified from English Hospital Episode Statistics and the USA Nationwide Inpatient Sample (2006-2012) and classified by whether they received a corrective surgical intervention. The rates of surgical intervention and population mortality were compared between England and the USA after adjustment for patient demographic factors. RESULTS: From 2006 to 2012, there were 136,047 admissions in English hospitals and 1,863,626 admissions in US hospitals due to the index surgical emergencies.Proportion of patients receiving no surgical intervention, for all 7 conditions was greater in the England (OR 4.25, 1.55, 8.53, 1.92, 2.06, 2.42, 1.75) and population in-hospital mortality was greater in England (OR 1.34, 1.67, 2.22, 1.65, 2.7, 4.46, 3.22) for ruptured abdominal aortic aneurysm, aortic dissection, appendicitis, perforated esophagus, peptic ulcer, small bowel or large bowel, and incarcerated or strangulated hernias respectively.In England (where follow-up was available), lack of utilization of surgery was also associated with increased in-hospital and long-term mortality for all conditions. CONCLUSION: England and US hospitals differ in the threshold for surgical intervention, which may be associated with increases in mortality in England for these 7 general surgical emergencies.

Thresholds for Abdominal Aortic Aneurysm Repair in England and the United States.

BACKGROUND: Thresholds for repair of abdominal aortic aneurysms vary considerably among countries. METHODS: We examined differences between England and the United States in the frequency of aneurysm repair, the mean aneurysm diameter at the time of the procedure, and rates of aneurysm rupture and aneurysm-related death. Data on the frequency of repair of intact (nonruptured) abdominal aortic aneurysms, in-hospital mortality among patients who had undergone aneurysm repair, and rates of aneurysm rupture during the period from 2005 through 2012 were extracted from the Hospital Episode Statistics database in England and the U.S. Nationwide Inpatient Sample. Data on the aneurysm diameter at the time of repair were extracted from the U.K. National Vascular Registry (2014 data) and from the U.S. National Surgical Quality Improvement Program (2013 data). Aneurysm-related mortality during the period from 2005 through 2012 was determined from data obtained from the Centers for Disease Control and Prevention and the U.K. Office of National Statistics. Data were adjusted with the use of direct standardization or conditional logistic regression for differences between England and the United States with respect to population age and sex. RESULTS: During the period from 2005 through 2012, a total of 29,300 patients in England and 278,921 patients in the United States underwent repair of intact abdominal aortic aneurysms. Aneurysm repair was less common in England than in the United States (odds ratio, 0.49; 95% confidence interval [CI], 0.48 to 0.49; P<0.001), and aneurysm-related death was more common in England than in the United States (odds ratio, 3.60; 95% CI, 3.55 to 3.64; P<0.001). Hospitalization due to an aneurysm rupture occurred more frequently in England than in the United States (odds ratio, 2.23; 95% CI, 2.19 to 2.27; P<0.001), and the mean aneurysm diameter at the time of repair was larger in England (63.7 mm vs. 58.3 mm, P<0.001). CONCLUSIONS: We found a lower rate of repair of abdominal aortic aneurysms and a larger mean aneurysm diameter at the time of repair in England than in the United States and lower rates of aneurysm rupture and aneurysm-related death in the United States than in England. (Funded by the Circulation Foundation and others.).

Key challenges for delivering clinical impact with artificial intelligence.

BACKGROUND: Artificial intelligence (AI) research in healthcare is accelerating rapidly, with potential applications being demonstrated across various domains of medicine. However, there are currently limited examples of such techniques being successfully deployed into clinical practice. This article explores the main challenges and limitations of AI in healthcare, and considers the steps required to translate these potentially transformative technologies from research to clinical practice. MAIN BODY: Key challenges for the translation of AI systems in healthcare include those intrinsic to the science of machine learning, logistical difficulties in implementation, and consideration of the barriers to adoption as well as of the necessary sociocultural or pathway changes. Robust peer-reviewed clinical evaluation as part of randomised controlled trials should be viewed as the gold standard for evidence generation, but conducting these in practice may not always be appropriate or feasible. Performance metrics should aim to capture real clinical applicability and be understandable to intended users. Regulation that balances the pace of innovation with the potential for harm, alongside thoughtful post-market surveillance, is required to ensure that patients are not exposed to dangerous interventions nor deprived of access to beneficial innovations. Mechanisms to enable direct comparisons of AI systems must be developed, including the use of independent, local and representative test sets. Developers of AI algorithms must be vigilant to potential dangers, including dataset shift, accidental fitting of confounders, unintended discriminatory bias, the challenges of generalisation to new populations, and the unintended negative consequences of new algorithms on health outcomes. CONCLUSION: The safe and timely translation of AI research into clinically validated and appropriately regulated systems that can benefit everyone is challenging. Robust clinical evaluation, using metrics that are intuitive to clinicians and ideally go beyond measures of technical accuracy to include quality of care and patient outcomes, is essential. Further work is required (1) to identify themes of algorithmic bias and unfairness while developing mitigations to address these, (2) to reduce brittleness and improve generalisability, and (3) to develop methods for improved interpretability of machine learning predictions. If these goals can be achieved, the benefits for patients are likely to be transformational.

A population-based cohort study examining the risk of abdominal cancer after endovascular abdominal aortic aneurysm repair.

OBJECTIVE: Endovascular aneurysm repair (EVAR) has increasingly been used as the primary treatment approach for abdominal aortic aneurysm (AAA). This study examined the hypothesis that EVAR leads to an increased risk of abdominal cancer within the radiation field compared with open AAA repair. METHODS: The nationwide English Hospital Episode Statistics database was used to identify all patients older than 50 years who received an AAA repair in 2005 to 2013. EVAR and open AAA repair groups were compared for the incidence of postoperative cancer using inverse probability weights and G-computation formula to adjust for selection bias and confounding. RESULTS: Among 14,150 patients who underwent EVAR and 24,645 patients who underwent open AAA repair, follow-up was up to 7 years. EVAR was associated with an increased risk of postoperative abdominal cancer (hazard ratio [HR], 1.14; 95% confidence interval [CI], 1.03-1.27) and all cancers (HR, 1.09; 95% CI, 1.02-1.17). However, there was no difference between the groups in the risk of lung cancer (HR, 1.04; 95% CI, 0.92-1.18) or obesity-related nonabdominal cancer (HR, 1.12; 95% CI, 0.69-1.83). Within the EVAR group, use of computed tomography surveillance was not associated with any increased risk of abdominal cancer (HR, 0.94; 95% CI, 0.71-1.23) or all cancers (HR, 0.97; 95% CI, 0.81-1.17). CONCLUSIONS: This study suggests an increased risk of abdominal cancer after EVAR compared with open AAA repair. The differential cancer risk should be further explored in alternative national populations, and radiation exposure during EVAR should be measured as a quality metric in the assessment of EVAR centers.

Multicentre Post-EVAR Surveillance Evaluation Study (EVAR-SCREEN).

OBJECTIVE: Surveillance imaging is considered mandatory after endovascular aneurysm repair (EVAR), but many patients are lost to follow up and the impact of this is poorly understood. This study aimed to examine compliance with post-operative surveillance in the UK and the impact of mal-/non-compliance on endograft re-interventions and survival. METHODS: EVAR-SCREEN centres reported EVAR for intact infrarenal abdominal aortic aneurysms (AAA) from 1 January 2007 to 31 December 2010, with follow up included up to 31 July 2014. Non-compliance was defined by the presence of a single 18 month period in which no surveillance imaging was performed. The outcomes were reported in compliant and non-compliant groups with survival analysis. RESULTS: EVAR was performed in 1414 patients in 10 UK centres. At the end of the study period there were 378 patients with five years of follow up available for analysis. Compliance with surveillance was 66% (61-68%). Compliance varied widely, from 9% to 88% between centres. Age (hazard ratio [HR] 1.03, 95% confidence interval [CI] 1.01-1.05; p = .02) and distance from hospital (HR 1.01, 95% CI 1.00-1.01; p < .001) were independent predictors of non-compliance. Non-compliant patients had lower all cause mortality in the first three years after EVAR, whereas compliant patients had lower all cause mortality 4-5 years after EVAR (p < .001). No significant difference in re-intervention rates was found between compliant and non-compliant patients. CONCLUSION: A substantial proportion of patients were non-compliant with surveillance after EVAR in the UK with considerable variation between centres. The survival benefit for EVAR after three years appeared to be related to compliance with surveillance which has implications for the future delivery of EVAR.

Implementation of a Digitally Enabled Care Pathway (Part 2): Qualitative Analysis of Experiences of Health Care Professionals.

BACKGROUND: One reason for the introduction of digital technologies into health care has been to try to improve safety and patient outcomes by providing real-time access to patient data and enhancing communication among health care professionals. However, the adoption of such technologies into clinical pathways has been less examined, and the impacts on users and the broader health system are poorly understood. We sought to address this by studying the impacts of introducing a digitally enabled care pathway for patients with acute kidney injury (AKI) at a tertiary referral hospital in the United Kingdom. A dedicated clinical response team-comprising existing nephrology and patient-at-risk and resuscitation teams-received AKI alerts in real time via Streams, a mobile app. Here, we present a qualitative evaluation of the experiences of users and other health care professionals whose work was affected by the implementation of the care pathway. OBJECTIVE: The aim of this study was to qualitatively evaluate the impact of mobile results viewing and automated alerting as part of a digitally enabled care pathway on the working practices of users and their interprofessional relationships. METHODS: A total of 19 semistructured interviews were conducted with members of the AKI response team and clinicians with whom they interacted across the hospital. Interviews were analyzed using inductive and deductive thematic analysis. RESULTS: The digitally enabled care pathway improved access to patient information and expedited early specialist care. Opportunities were identified for more constructive planning of end-of-life care due to the earlier detection and alerting of deterioration. However, the shift toward early detection also highlighted resource constraints and some clinical uncertainty about the value of intervening at this stage. The real-time availability of information altered communication flows within and between clinical teams and across professional groups. CONCLUSIONS: Digital technologies allow early detection of adverse events and of patients at risk of deterioration, with the potential to improve outcomes. They may also increase the efficiency of health care professionals' working practices. However, when planning and implementing digital information innovations in health care, the following factors should also be considered: the provision of clinical training to effectively manage early detection, resources to cope with additional workload, support to manage perceived information overload, and the optimization of algorithms to minimize unnecessary alerts.

Implementation of a Digitally Enabled Care Pathway (Part 1): Impact on Clinical Outcomes and Associated Health Care Costs.

BACKGROUND: The development of acute kidney injury (AKI) in hospitalized patients is associated with adverse outcomes and increased health care costs. Simple automated e-alerts indicating its presence do not appear to improve outcomes, perhaps because of a lack of explicitly defined integration with a clinical response. OBJECTIVE: We sought to test this hypothesis by evaluating the impact of a digitally enabled intervention on clinical outcomes and health care costs associated with AKI in hospitalized patients. METHODS: We developed a care pathway comprising automated AKI detection, mobile clinician notification, in-app triage, and a protocolized specialist clinical response. We evaluated its impact by comparing data from pre- and postimplementation phases (May 2016 to January 2017 and May to September 2017, respectively) at the intervention site and another site not receiving the intervention. Clinical outcomes were analyzed using segmented regression analysis. The primary outcome was recovery of renal function to ≤120% of baseline by hospital discharge. Secondary clinical outcomes were mortality within 30 days of alert, progression of AKI stage, transfer to renal/intensive care units, hospital re-admission within 30 days of discharge, dependence on renal replacement therapy 30 days after discharge, and hospital-wide cardiac arrest rate. Time taken for specialist review of AKI alerts was measured. Impact on health care costs as defined by Patient-Level Information and Costing System data was evaluated using difference-in-differences (DID) analysis. RESULTS: The median time to AKI alert review by a specialist was 14.0 min (interquartile range 1.0-60.0 min). There was no impact on the primary outcome (estimated odds ratio [OR] 1.00, 95% CI 0.58-1.71; P=.99). Although the hospital-wide cardiac arrest rate fell significantly at the intervention site (OR 0.55, 95% CI 0.38-0.76; P<.001), DID analysis with the comparator site was not significant (OR 1.13, 95% CI 0.63-1.99; P=.69). There was no impact on other secondary clinical outcomes. Mean health care costs per patient were reduced by £2123 (95% CI -£4024 to -£222; P=.03), not including costs of providing the technology. CONCLUSIONS: The digitally enabled clinical intervention to detect and treat AKI in hospitalized patients reduced health care costs and possibly reduced cardiac arrest rates. Its impact on other clinical outcomes and identification of the active components of the pathway requires clarification through evaluation across multiple sites.

The Influence of Antireflux Surgery on Esophageal Cancer Risk in England: National Population-based Cohort Study.

OBJECTIVE: To evaluate how antireflux surgery influences the risk of esophageal cancer in patients with gastroesophageal reflux disease (GERD) and Barrett esophagus. BACKGROUND: GERD is a major risk factor for esophageal adenocarcinoma, and the United Kingdom has the highest incidence of esophageal adenocarcinoma globally. METHODS: Hospital Episode Statistics database was used to identify all patients in England aged over 18 years diagnosed with GERD with or without Barrett Esophagus from 2000 to 2012, with antireflux surgery being the exposure investigated. The Clinical Practice Research Datalink (CPRD) was used to provide a sensitivity analysis comparing proton pump inhibitor therapy and antireflux surgery. Hazard ratios (HR) with 95% confidence intervals (CI) were calculated using Cox proportional hazards model with inverse probability weights based on the probability of having surgery to adjust for selection bias and confounding factors. RESULTS: (i) Hospital Episode Statistics analysis; among 838,755 included patients with GERD and 28,372 with Barrett esophagus, 22,231 and 737 underwent antireflux surgery, respectively. In GERD patients, antireflux surgery reduced the risk of esophageal cancer (HR = 0.64; 95% CI 0.52-0.78). In Barrett esophagus patients, the corresponding HR was (HR = 0.47; 95% CI 0.12-1.90).(ii) CPRD analysis; antireflux surgery was associated with decreased point estimates of esophageal adenocarcinoma in patients with GERD (0% vs. 0.2%; P = 0.16) and Barrett esophagus (HR = 0.75; 95% CI 0.21-2.63), but these were not statistically significant. CONCLUSION: Antireflux surgery may be associated with a reduced risk of esophageal cancer risk, however it remains primarily an operation for symptomatic relief.

Editor's Choice - The Implications of Non-compliance to Endovascular Aneurysm Repair Surveillance: A Systematic Review and Meta-analysis.

OBJECTIVE/BACKGROUND: Increasingly, reports show that compliance rates with endovascular aneurysm repair (EVAR) surveillance are often suboptimal. The aim of this study was to determine the safety implications of non-compliance with surveillance. METHODS: The study was carried out according to the Preferred Items for Reporting of Systematic Reviews and Meta-Analyses (PRISMA) guidelines. An electronic search was undertaken by two independent authors using Embase, MEDLINE, Cochrane, and Web of Science databases from 1990 to July 2017. Only studies that analysed infrarenal EVAR and had a definition of non-compliance described as weeks or months without imaging surveillance were analysed. Meta-analysis was carried out using the random-effects model and restricted maximum likelihood estimation. RESULTS: Thirteen articles (40,730 patients) were eligible for systematic review; of these, seven studies (14,311 patients) were appropriate for comparative meta-analyses of mortality rates. Three studies (8316 patients) were eligible for the comparative meta-analyses of re-intervention rates after EVAR and four studies (12,995 patients) eligible for meta-analysis for abdominal aortic aneurysm related mortality (ARM). The estimated average non-compliance rate was 42.0% (95% confidence interval [CI] 28-56%). Although there is some evidence that non-compliant patients have better survival rates, there was no statistically significant difference in all cause mortality rates (year 1: odds ratio [OR] 5.77, 95% CI 0.74-45.14; year 3: OR 2.28, 95% CI 0.92-5.66; year 5: OR 1.81, 95% CI 0.88-3.74) and ARM (OR 1.47, 95% CI 0.99-2.19) between compliant and non-compliant patients in the first 5 years after EVAR. The re-intervention rate was statistically significantly higher in compliant patients from 3 to 5 years after EVAR (year 1: OR 6.36, 95% CI 0.23-172.73; year 3: OR 3.94, 85% CI 1.46-10.69; year 5: OR 5.34, 95% CI 1.87-15.29). CONCLUSION: This systematic review and meta-analysis suggests that patients compliant with EVAR surveillance programmes may have an increased re-intervention rate but do not appear to have better survival rates than non-compliant patients.