Screening of normal endoscopic large bowel biopsies with interpretable graph learning: a retrospective study.

OBJECTIVE: To develop an interpretable artificial intelligence algorithm to rule out normal large bowel endoscopic biopsies, saving pathologist resources and helping with early diagnosis. DESIGN: A graph neural network was developed incorporating pathologist domain knowledge to classify 6591 whole-slides images (WSIs) of endoscopic large bowel biopsies from 3291 patients (approximately 54% female, 46% male) as normal or abnormal (non-neoplastic and neoplastic) using clinically driven interpretable features. One UK National Health Service (NHS) site was used for model training and internal validation. External validation was conducted on data from two other NHS sites and one Portuguese site. RESULTS: Model training and internal validation were performed on 5054 WSIs of 2080 patients resulting in an area under the curve-receiver operating characteristic (AUC-ROC) of 0.98 (SD=0.004) and AUC-precision-recall (PR) of 0.98 (SD=0.003). The performance of the model, named Interpretable Gland-Graphs using a Neural Aggregator (IGUANA), was consistent in testing over 1537 WSIs of 1211 patients from three independent external datasets with mean AUC-ROC=0.97 (SD=0.007) and AUC-PR=0.97 (SD=0.005). At a high sensitivity threshold of 99%, the proposed model can reduce the number of normal slides to be reviewed by a pathologist by approximately 55%. IGUANA also provides an explainable output highlighting potential abnormalities in a WSI in the form of a heatmap as well as numerical values associating the model prediction with various histological features. CONCLUSION: The model achieved consistently high accuracy showing its potential in optimising increasingly scarce pathologist resources. Explainable predictions can guide pathologists in their diagnostic decision-making and help boost their confidence in the algorithm, paving the way for its future clinical adoption.

Standardized Clinical Annotation of Digital Histopathology Slides at the Point of Diagnosis.

As digital pathology replaces conventional glass slide microscopy as a means of reporting cellular pathology samples, the annotation of digital pathology whole slide images is rapidly becoming part of a pathologist's regular practice. Currently, there is no recognizable organization of these annotations, and as a result, pathologists adopt an arbitrary approach to defining regions of interest, leading to irregularity and inconsistency and limiting the downstream efficient use of this valuable effort. In this study, we propose a Standardized Annotation Reporting Style for digital whole slide images. We formed a list of 167 commonly annotated entities (under 12 specialty subcategories) based on review of Royal College of Pathologists and College of American Pathologists documents, feedback from reporting pathologists in our NHS department, and experience in developing annotation dictionaries for PathLAKE research projects. Each entity was assigned a suitable annotation shape, SNOMED CT (SNOMED International) code, and unique color. Additionally, as an example of how the approach could be expanded to specific tumor types, all lung tumors in the fifth World Health Organization of thoracic tumors 2021 were included. The proposed standardization of annotations increases their utility, making them identifiable at low power and searchable across and between cases. This would aid pathologists reporting and reviewing cases and enable annotations to be used for research. This structured approach could serve as the basis for an industry standard and be easily adopted to ensure maximum functionality and efficiency in the use of annotations made during routine clinical examination of digital slides.

Nitrous oxide-induced myeloneuropathy: a case series.

BACKGROUND: Nitrous oxide (N2O) is the second most common recreational drug used by 16- to 24-year-olds in the UK. Neurological symptoms can occur in some people that use N2O recreationally, but most information comes from small case series. METHODS: We describe 119 patients with N2O-myeloneuropathy seen at NHS teaching hospitals in three of the UK's largest cities: London, Birmingham and Manchester. This work summarises the clinical and investigative findings in the largest case series to date. RESULTS: Paraesthesia was the presenting complaint in 85% of cases, with the lower limbs more commonly affected than the upper limbs. Gait ataxia was common, and bladder and bowel disturbance were frequent additional symptoms. The mid-cervical region of the spinal cord (C3-C5) was most often affected on MRI T2-weighted imaging. The number of N2O canisters consumed per week correlated with methylmalonic acid levels in the blood as a measure of functional B12 deficiency (rho (ρ)=0.44, p=0.04). CONCLUSIONS: Preventable neurological harm from N2O abuse is increasingly seen worldwide. Ease of access to canisters and larger cylinders of N2O has led to an apparent rise in cases of N2O-myeloneuropathy in several areas of the UK. Our results highlight the range of clinical manifestations in a large group of patients to improve awareness of risk, aid early recognition, and promote timely treatment.

Development and validation of a telephone classification interview for common chronic headache disorders.

BACKGROUND: For a trial of supportive self-management for people with chronic headache we needed to develop and validate a telephone classification interview that can be used by a non-headache specialist to classify common chronic headache types in primary care. We aimed to specifically: exclude secondary headaches other than medication overuse, exclude primary headache disorders other than migraine and tension type headache (TTH), distinguish between chronic migraine and chronic TTH, and identify medication overuse headache. METHODS: We held a headache classification consensus conference to draw on evidence and expertise to inform the content of a logic model underpinning the classification interview. Nurses trained to use the logic model did telephone classification interviews with participants recruited from primary care. Doctors specialising in headache did a second validation interview. RESULTS: Twenty-six delegates attended the headache classification conference including headache specialist doctors, nurses and lay representatives (with chronic headache). We trained six nurses to do the classification interviews and completed 107 paired interviews, median days between interviews was 32 days (interquartile range 21-48 days). We measured level of agreement between the nurse and doctor interviews using proportion of concordance, simple kappa and prevalence-adjusted bias-adjusted kappa (PABAK). Proportion of concordance of agreement between nurse and doctor interviews was 0.76, simple kappa coefficient κ 0.31 (95% CI, 0.09 to 0.52), and PABAK 0.51 (95% CI, 0.35 to 0.68), a moderate agreement. In a sensitivity test following review of headache characteristics recorded, concordance was 0.91, κ = 0.53 (95% CI, 0.28 to 0.79), and PABAK = 0.81 (95% CI, 0.70 to 0.92), a very good agreement. CONCLUSION: We developed and validated a new evidence-based telephone classification interview that can be used by a non-headache specialist to classify common chronic headache types in primary care.

The Use and Indication of Ivabradine in Heart Failure.

Heart failure affects more than 6 million people in the United States each year and the prognosis is poor. The elevated heart rate in heart failure patents is problematic, because it increases myocardial oxygen demand, decreases myocardial perfusion, and has been associated with increased rates of hospitalization and mortality. For these reasons, heart rate reduction has long been a therapeutic target in heart failure. Ivabradine is a selective inhibitor of the sinoatrial pacemaker modulating "f-current" (If) and provides heart rate reduction that can be beneficial in patients with heart failure with reduced ejection fraction.

Periprocedural antithrombotic management for lumbar puncture: Association of British Neurologists clinical guideline.

Lumbar puncture (LP) is an important and frequently performed invasive procedure for the diagnosis and management of neurological conditions. There is little in the neurological literature on the topic of periprocedural management of antithrombotics in patients undergoing LP. Current practice is therefore largely extrapolated from guidelines produced by anaesthetic bodies on neuraxial anaesthesia, haematology groups advising on periprocedural management of antiplatelet agents and anticoagulants, and by neuroradiology on imaging-guided spinal procedures. This paper summarises the existing literature on the topic and offers recommendations to guide periprocedural antithrombotic management for LP, based on the consolidation of the best available evidence. ​.

Mycophenolate and methotrexate are better tolerated than azathioprine in myasthenia gravis.

Azathioprine is recommended as the first-line steroid-sparing immunosuppressive agent for myasthenia gravis. Mycophenolate and methotrexate are often considered as second-line choices despite widespread consensus on their efficacy. We aimed to gather real-world data comparing the tolerability and reasons for discontinuation for these agents, by performing a national United Kingdom survey of side effects and reasons for discontinuation of immunosuppressants in myasthenia gravis. Of 235 patients, 166 had taken azathioprine, 102 mycophenolate, and 40 methotrexate. The most common side effects for each agent were liver dysfunction for azathioprine (23 %), diarrhoea for mycophenolate (14 %), and fatigue for methotrexate (18 %). Women were generally more likely to experience side effects of immunosuppressants. Azathioprine was significantly more likely to be discontinued than mycophenolate and methotrexate due to side effects. There was no significant difference in treatment cessation due to lack of efficacy. This study highlights the significant side-effect burden of treatment for myasthenia gravis. Mechanisms to reduce azathioprine toxicity should be utilised, however mycophenolate and methotrexate appear to be good treatment choices if teratogenicity is not a concern. Women are disadvantaged due to higher frequency of side effects and considerations around pregnancy and breastfeeding. Treatments with improved tolerability are needed.

Utilising accessible and reproducible neurological assessments in clinical studies: Insights from use of the Neurological Impairment Scale in the multi-centre COVID-CNS study.

Reproducible and standardised neurological assessment scales are important in quantifying research outcomes. These scales are often performed by non-neurologists and/or non-clinicians and must be robust, quantifiable, reproducible and comparable to a neurologist's assessment. COVID-CNS is a multi-centre study which utilised the Neurological Impairment Scale (NIS) as a core assessment tool in studying neurological outcomes following COVID-19 infection. We investigated the strengths and weaknesses of the NIS when used by non-neurology clinicians and non-clinicians, and compared performance to a structured neurological examination performed by a neurology clinician. Through our findings, we provide practical advice on how non-clinicians can be readily trained in conducting reproducible and standardised neurological assessments in a multi-centre study, as well as illustrating potential pitfalls of these tools.

Addressing ethnic disparities in neurological research in the United Kingdom: An example from the prospective multicentre COVID-19 Clinical Neuroscience Study.

BACKGROUND: Minority ethnic groups have often been underrepresented in research, posing a problem in relation to external validity and extrapolation of findings. Here, we aimed to assess recruitment and retainment strategies in a large observational study assessing neurological complications following SARS-CoV-2 infection. METHODS: Participants were recruited following confirmed infection with SARS-CoV-2 and hospitalisation. Self-reported ethnicity was recorded alongside other demographic data to identify potential barriers to recruitment. RESULTS: 807 participants were recruited to COVID-CNS, and ethnicity data were available for 93.2%. We identified a proportionate representation of self-reported ethnicity categories, and distribution of broad ethnicity categories mirrored individual centres' catchment areas. White ethnicity within individual centres ranged between 44.5% and 89.1%, with highest percentage of participants with non-White ethnicity in London-based centres. Examples are provided how to reach potentially underrepresented minority ethnic groups. CONCLUSIONS: Recruitment barriers in relation to potentially underrepresented ethnic groups may be overcome with strategies identified here.

Development and validation of artificial intelligence-based prescreening of large-bowel biopsies taken in the UK and Portugal: a retrospective cohort study.

BACKGROUND: Histopathological examination is a crucial step in the diagnosis and treatment of many major diseases. Aiming to facilitate diagnostic decision making and improve the workload of pathologists, we developed an artificial intelligence (AI)-based prescreening tool that analyses whole-slide images (WSIs) of large-bowel biopsies to identify typical, non-neoplastic, and neoplastic biopsies. METHODS: This retrospective cohort study was conducted with an internal development cohort of slides acquired from a hospital in the UK and three external validation cohorts of WSIs acquired from two hospitals in the UK and one clinical laboratory in Portugal. To learn the differential histological patterns from digitised WSIs of large-bowel biopsy slides, our proposed weakly supervised deep-learning model (Colorectal AI Model for Abnormality Detection [CAIMAN]) used slide-level diagnostic labels and no detailed cell or region-level annotations. The method was developed with an internal development cohort of 5054 biopsy slides from 2080 patients that were labelled with corresponding diagnostic categories assigned by pathologists. The three external validation cohorts, with a total of 1536 slides, were used for independent validation of CAIMAN. Each WSI was classified into one of three classes (ie, typical, atypical non-neoplastic, and atypical neoplastic). Prediction scores of image tiles were aggregated into three prediction scores for the whole slide, one for its likelihood of being typical, one for its likelihood of being non-neoplastic, and one for its likelihood of being neoplastic. The assessment of the external validation cohorts was conducted by the trained and frozen CAIMAN model. To evaluate model performance, we calculated area under the convex hull of the receiver operating characteristic curve (AUROC), area under the precision-recall curve, and specificity compared with our previously published iterative draw and rank sampling (IDaRS) algorithm. We also generated heat maps and saliency maps to analyse and visualise the relationship between the WSI diagnostic labels and spatial features of the tissue microenvironment. The main outcome of this study was the ability of CAIMAN to accurately identify typical and atypical WSIs of colon biopsies, which could potentially facilitate automatic removing of typical biopsies from the diagnostic workload in clinics. FINDINGS: A randomly selected subset of all large bowel biopsies was obtained between Jan 1, 2012, and Dec 31, 2017. The AI training, validation, and assessments were done between Jan 1, 2021, and Sept 30, 2022. WSIs with diagnostic labels were collected between Jan 1 and Sept 30, 2022. Our analysis showed no statistically significant differences across prediction scores from CAIMAN for typical and atypical classes based on anatomical sites of the biopsy. At 0·99 sensitivity, CAIMAN (specificity 0·5592) was more accurate than an IDaRS-based weakly supervised WSI-classification pipeline (0·4629) in identifying typical and atypical biopsies on cross-validation in the internal development cohort (p<0·0001). At 0·99 sensitivity, CAIMAN was also more accurate than IDaRS for two external validation cohorts (p<0·0001), but not for a third external validation cohort (p=0·10). CAIMAN provided higher specificity than IDaRS at some high-sensitivity thresholds (0·7763 vs 0·6222 for 0·95 sensitivity, 0·7126 vs 0·5407 for 0·97 sensitivity, and 0·5615 vs 0·3970 for 0·99 sensitivity on one of the external validation cohorts) and showed high classification performance in distinguishing between neoplastic biopsies (AUROC 0·9928, 95% CI 0·9927-0·9929), inflammatory biopsies (0·9658, 0·9655-0·9661), and atypical biopsies (0·9789, 0·9786-0·9792). On the three external validation cohorts, CAIMAN had AUROC values of 0·9431 (95% CI 0·9165-0·9697), 0·9576 (0·9568-0·9584), and 0·9636 (0·9615-0·9657) for the detection of atypical biopsies. Saliency maps supported the representation of disease heterogeneity in model predictions and its association with relevant histological features. INTERPRETATION: CAIMAN, with its high sensitivity in detecting atypical large-bowel biopsies, might be a promising improvement in clinical workflow efficiency and diagnostic decision making in prescreening of typical colorectal biopsies. FUNDING: The Pathology Image Data Lake for Analytics, Knowledge and Education Centre of Excellence; the UK Government's Industrial Strategy Challenge Fund; and Innovate UK on behalf of UK Research and Innovation.

A systematic review of validated methods for identifying cerebrovascular accident or transient ischemic attack using administrative data.

PURPOSE: To perform a systematic review of the validity of algorithms for identifying cerebrovascular accidents (CVAs) or transient ischemic attacks (TIAs) using administrative and claims data. METHODS: PubMed and Iowa Drug Information Service searches of the English language literature were performed to identify studies published between 1990 and 2010 that evaluated the validity of algorithms for identifying CVAs (ischemic and hemorrhagic strokes, intracranial hemorrhage, and subarachnoid hemorrhage) and/or TIAs in administrative data. Two study investigators independently reviewed the abstracts and articles to determine relevant studies according to pre-specified criteria. RESULTS: A total of 35 articles met the criteria for evaluation. Of these, 26 articles provided data to evaluate the validity of stroke, seven reported the validity of TIA, five reported the validity of intracranial bleeds (intracerebral hemorrhage and subarachnoid hemorrhage), and 10 studies reported the validity of algorithms to identify the composite endpoints of stroke/TIA or cerebrovascular disease. Positive predictive values (PPVs) varied depending on the specific outcomes and algorithms evaluated. Specific algorithms to evaluate the presence of stroke and intracranial bleeds were found to have high PPVs (80% or greater). Algorithms to evaluate TIAs in adult populations were generally found to have PPVs of 70% or greater. CONCLUSIONS: The algorithms and definitions to identify CVAs and TIAs using administrative and claims data differ greatly in the published literature. The choice of the algorithm employed should be determined by the stroke subtype of interest.

A systematic review of validated methods for identifying heart failure using administrative data.

PURPOSE: To identify and describe the validity of algorithms used to detect heart failure (HF) using administrative and claims data sources. METHODS: A systematic review of PubMed and Iowa Drug Information Service searches of the English language was performed to identify studies published between 1990 and 2010 that evaluated the validity of algorithms for the identification of patients with HF using and claims data. Abstracts and articles were reviewed by two study investigators to determine their relevance on the basis of predetermined criteria. RESULTS: The initial search strategy identified 887 abstracts. Of these, 499 full articles were reviewed and 35 studies included data to evaluate the validity of identifying patients with HF. Positive predictive values (PPVs) were in the acceptable to high range, with most being very high (>90%). Studies that included patients with a primary hospital discharge diagnosis of International Classification of Diseases, Ninth Revision, code 428.X had the highest PPV and specificity for HF. PPVs for this algorithm ranged from 84% to 100%. This algorithm, however, may compromise sensitivity because many HF patients are managed on an outpatient basis. The most common 'gold standard' for the validation of HF was the Framingham Heart Study criteria. CONCLUSIONS: The algorithms and definitions used to identify HF using administrative and claims data perform well, particularly when using a primary hospital discharge diagnosis. Attention should be paid to whether patients who are managed on an outpatient basis are included in the study sample. Including outpatient codes in the described algorithms would increase the sensitivity for identifying new cases of HF.

Sex bias in lymphocytes: Implications for autoimmune diseases.

Autoimmune diseases are characterized by a significant sex dimorphism, with women showing increased susceptibility to disease. This is, at least in part, due to sex-dependent differences in the immune system that are influenced by the complex interplay between sex hormones and sex chromosomes, with contribution from sociological factors, diet and gut microbiota. Sex differences are evident in the number and function of lymphocyte populations. Women mount a stronger pro-inflammatory response than males, with increased lymphocyte proliferation, activation and pro-inflammatory cytokine production, whereas men display expanded regulatory cell subsets. Ageing alters the immune landscape of men and women in differing ways, resulting in changes in autoimmune disease susceptibility. Here we review the current literature on sex differences in lymphocyte function, the factors that influence this, and the implications for autoimmune disease. We propose that improved understanding of sex bias in lymphocyte function can provide sex-specific tailoring of treatment strategies for better management of autoimmune diseases.

Heart failure with recovered ejection fraction and the utility of defibrillator therapy: a review.

Heart failure with recovered ejection fraction (HFrecEF) involves those who have previously had reduced cardiac function that has subsequently improved. However, there is not a single definition of this phenomenon and recovery of cardiac function in terms of left ventricular ejection fraction (LVEF) itself does not necessarily correlate with remission from the detrimental physiology of heart failure (HF) and its consequences. There is also the question of the utility of defibrillators in these patients, and whether they should be replaced at the time of battery depletion. To address this, several studies have shown specific predictors of ensuing LVEF recovery, including patient demographics, co-morbidities, and medication use, as well as predictors of ventricular arrhythmias (VA) following LVEF recovery. Recent studies have also shown novel imaging parameters that may aid in predicting which patients would have a higher risk of these arrhythmias. Additional data describe a small, yet appreciable risk of VA, in addition to appropriate shocks as well. In this review, we describe predictors of LVEF recovery, carefully analyse and characterize the continued risk for VA and appropriate shocks following LVEF recovery, and explore additional novel modalities that may aid in decision-making.

Semantic annotation for computational pathology: multidisciplinary experience and best practice recommendations.

Recent advances in whole-slide imaging (WSI) technology have led to the development of a myriad of computer vision and artificial intelligence-based diagnostic, prognostic, and predictive algorithms. Computational Pathology (CPath) offers an integrated solution to utilise information embedded in pathology WSIs beyond what can be obtained through visual assessment. For automated analysis of WSIs and validation of machine learning (ML) models, annotations at the slide, tissue, and cellular levels are required. The annotation of important visual constructs in pathology images is an important component of CPath projects. Improper annotations can result in algorithms that are hard to interpret and can potentially produce inaccurate and inconsistent results. Despite the crucial role of annotations in CPath projects, there are no well-defined guidelines or best practices on how annotations should be carried out. In this paper, we address this shortcoming by presenting the experience and best practices acquired during the execution of a large-scale annotation exercise involving a multidisciplinary team of pathologists, ML experts, and researchers as part of the Pathology image data Lake for Analytics, Knowledge and Education (PathLAKE) consortium. We present a real-world case study along with examples of different types of annotations, diagnostic algorithm, annotation data dictionary, and annotation constructs. The analyses reported in this work highlight best practice recommendations that can be used as annotation guidelines over the lifecycle of a CPath project.

Heart failure in pregnancy: what is the long-term impact of pregnancy on cardiac function? A tertiary care centre experience and systematic review.

BACKGROUND: Women with cardiomyopathy (CM) are often advised against pregnancy due to risk for major adverse cardiovascular events (MACE). However, the impact of CM subtype on maternal MACE is not understood, and so we sought to evaluate the influence of CM phenotype on maternal outcomes, as well as the effect on immediate and late left ventricular function. METHODS: We evaluated all pregnant women in our high-risk maternal cardiovascular programme (2009-2019). Composite maternal MACE included: death, inotrope use, left ventricular assist device, orthotopic heart transplant and/or escalation in transplant listing status, acute decompensated heart failure and sustained ventricular arrhythmia. RESULTS: Among 875 women followed, 32 had CM (29±7 years old, left ventricular ejection fraction (LVEF) 41%±12%): 3 ischaemic CM (ICM), 10 peripartum CM (PPCM) and 19 non-ICM (NICM). MACE events occurred in 6 (18%) women (PPCM: 2 (33%), NICM: 4 (67%)). There was no difference in LVEF at baseline, however, women with MACE had significantly lower LVEF both early (LVEF: 27±5% vs . 41±2%, p<0.05) and late post partum (LVEF: 28±5% vs . 44±2%, p<0.01). CONCLUSIONS: In this contemporary cohort of women with CM, maternal MACE rates were lower than previously reported, and were less common in PPCM as compared with ICM and NICM. Heart function in women with MACE was negatively impacted immediately after delivery and in late postpartum follow-up, suggesting that pregnancy itself likely has influence on future left ventricular function in women with underlying CM.

Coronavirus disease 2019 in heart transplant recipients: Risk factors, immunosuppression, and outcomes.

BACKGROUND: COVID-19 continues to inflict significant morbidity and mortality, particularly on patients with preexisting health conditions. The clinical course, outcomes, and significance of immunosuppression regimen in heart transplant recipients with COVID-19 remains unclear. METHODS: We included the first 99 heart transplant recipients at participating centers with COVID-19 and followed patients until resolution. We collected baseline information, symptoms, laboratory studies, vital signs, and outcomes for included patients. The association of immunosuppression regimens at baseline with severe disease were compared using logistic regression, adjusting for age and time since transplant. RESULTS: The median age was 60 years, 25% were female, and 44% were white. The median time post-transplant to infection was 5.6 years. Overall, 15% died, 64% required hospital admission, and 7% remained asymptomatic. During the course of illness, only 57% of patients had a fever, and gastrointestinal symptoms were common. Tachypnea, oxygen requirement, elevated creatinine and inflammatory markers were predictive of severe course. Age ≥ 60 was associated with higher risk of death and the use of the combination of calcineurin inhibitor, antimetabolite, and prednisone was associated with more severe disease compared to the combination of calcineurin inhibitor and antimetabolite alone (adjusted OR = 7.3, 95% CI 1.8-36.2). Among hospitalized patients, 30% were treated for secondary infection, acute kidney injury was common and 17% required new renal replacement therapy. CONCLUSIONS: We present the largest study to date of heart transplant patients with COVID-19 showing common atypical presentations and a high case fatality rate of 24% among hospitalized patients and 16% among symptomatic patients.

Cluster randomized trials to study the comparative effectiveness of therapeutics: stakeholders' concerns and recommendations.

PURPOSE: To describe the concerns raised by health plan members, providers and purchasers related to studying the comparative effectiveness of therapeutics using cluster randomized trials (CRTs) within health plans. An additional goal was to develop recommendations for increasing acceptability. METHODS: Eighty-four qualitative in-depth telephone interviews were conducted; 50 with health plan members, 21 with providers, and 13 with purchasers. Interviews focused on stakeholders' concerns about and recommendations for conducting CRTs in health plans. RESULTS: Members expressed concerns that CRTs might compromise their healthcare. Providers and purchasers recognized the value of and the need for comparative effectiveness research. Providers expressed concerns that they would not have sufficient time to discuss a CRT with patients, and that participation in such a study could negatively impact their relationships with patients. Purchasers would want assurances that study participation would not result in members receiving lesser care, and that benefits would remain equitable for all members. CONCLUSIONS: This study provides insight into how health plan members, providers and purchasers might react to a CRT being conducted in their health plan. The recommendations reported here provide guidance for researchers and policy makers considering this methodological approach and suggest that with sufficient preparation and planning CRTs can be an acceptable and efficient methodology for studying the comparative effectiveness of therapeutics in real world settings.

Communicating hospital infection data to the public: a study of consumer responses and preferences.

There is growing interest in public reporting of health care performance data relating to healthcare-associated infections (HAIs). This study evaluated different approaches for reporting hospital-level comparative data on HAIs and the extent to which such data might influence hospital choice. Eight versions of a report were developed, varying whether data were consistent across indicators, whether data were presented in text or graphs, and whether confidence intervals were included. A report and a questionnaire were mailed to a randomly selected sample of local residents. Findings provide no evidence that consistency of indicators, data presentation, report format, or inclusion of confidence intervals significantly impacted consumers' understanding. More educated consumers reported greater understanding of the reports. Responses suggested that public reporting of comparative data on HAIs could influence hospital choice, but other factors including prior experience, reputation, physicians' recommendations, and insurance coverage are also influential. Most consumers understand information on HAIs when it is presented in a short, simple report, and most correctly select the best or worst hospital. Consumers may be influenced by such data, but other factors are likely to be as or more important.

FUS-ALS presenting with myoclonic jerks in a 17-year-old man.

Fused in sarcoma-related amyotrophic lateral sclerosis (FUS-ALS) accounts for 4% of all familial motor neurone disease, but has a much higher incidence in juvenile ALS. We present a case of a 17-year-old British man with rapidly progressive bulbar and respiratory failure. On examination he had weak periocular muscles, neck flexion weakness, and a wasted, fasciculating and weak tongue. There were no sensory, cerebellar, or extrapyramidal features but he had frequent myoclonic jerks of the limbs. Routine bloods were normal and an MRI of the neuroaxis as well as CT chest, abdomen and pelvis were unremarkable. NCS/EMG was consistent with anterior horn cell disorder and EEG showed multiple paroxysmal generalized spike-wave discharges. DNA sequencing demonstrated that he was heterozygous for the c.1483C>T pathogenic nonsense mutation in exon 14 of the FUS gene, consistent with ALS6. This is the first reported case of FUS-ALS presenting with prominent myoclonus.