The effectiveness of revaccination with pneumococcal polysaccharide vaccine for preventing pneumococcal disease in older adults in England: A population-based cohort study.

BACKGROUND: Pneumococcal disease in older adults in the United Kingdom is rising despite immunisation. A key gap in the literature is the clinical effectiveness of revaccination with the pneumococcal polysaccharide vaccine (PPV23). METHODS: A cohort study was performed in England, using electronic medical records in the Clinical Practice Research Datalink. Individuals aged ≥64 years and vaccinated with PPV23 were included. Rates of hospitalised pneumonia (HP) and invasive pneumococcal disease (IPD) were compared between individuals receiving a single PPV23 dose versus those receiving two doses using multi-level Cox proportional hazards models. Propensity score weighting was performed to minimise the effect of confounding covariates across the comparison groups. RESULTS: Between 2006 and 2019, there were 462 505 eligible participants. Of those, 6747 (1·5 %) received revaccination. Two doses compared to one dose was associated with an increased risk of HP (adjusted Hazard Ratio [aHR] 1·95; 95 %CI 1·74-2·20) and IPD (aHR 1·44; 95 %CI 1·41-1·46). In participants aged 64-74 years PPV23 revaccination was associated with more IPD (aHR 2·02; 95 %CI 1·75-2·33) and HP (aHR 1·46; 95 %CI 1·42-1.49). In those aged ≥75 years PPV23 revaccination was associated with more HP (aHR 1·12; 95 %CI 1·08-1·16) with no statistically significant difference detected in risk of IPD (aHR 1·20; 95 %CI 0·94-1·52). CONCLUSIONS: No clear benefit of PPV23 revaccination was measured in older adults in this observational study. The small proportion of revaccinated subjects limits the strength of the conclusions. Further research evaluating the clinical effectiveness of PPV23 revaccination is required.

Clinical prediction models for treatment outcomes in newly diagnosed epilepsy: A systematic review.

Up to 35% of individuals diagnosed with epilepsy continue to have seizures despite treatment, commonly referred to as drug-resistant epilepsy. Uncontrolled seizures can directly, or indirectly, negatively impact an individual's quality of life. To inform clinical management and life decisions, it is important to be able to predict the likelihood of seizure control. Those likely to achieve seizure control will be able to return sooner to their usual work and leisure activities and require less follow-up, whereas those with a poor prognosis will need more frequent clinical attendance and earlier consideration of epilepsy surgery. This is a systematic review aimed at identifying demographic, clinical, physiological (e.g., electroencephalographic), and imaging (e.g., magnetic resonance imaging) factors that may be predictive of treatment outcomes in patients with newly diagnosed epilepsy (NDE). MEDLINE and Embase were searched for prediction models of treatment outcomes in patients with NDE. Study characteristics were extracted and subjected to assessment of risk of bias (and applicability concerns) using the PROBAST (Prediction Model Risk of Bias Assessment Tool) tool. Baseline variables associated with treatment outcomes are reported as prognostic factors. After screening, 48 models were identified in 32 studies, which generally scored low for concerns of applicability, but universally scored high for susceptibility to bias. Outcomes reported fit broadly into four categories: drug resistance, short-term treatment response, seizure remission, and mortality. Prognostic factors were also heterogenous, but the predictors that were commonly significantly associated with outcomes were those related to seizure characteristics/types, epilepsy history, and age at onset. Antiseizure medication response was often included as a baseline variable, potentially obscuring other factor relationships at baseline. Currently, outcome prediction models for NDE demonstrate a high risk of bias. Model development could be improved with a stronger adherence to recommended TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) practices. Furthermore, we outline actionable changes to common practices that are intended to improve the overall quality of prediction model development in NDE.

'Knowledge exchange' workshops to optimise development of a risk prediction tool to assist conveyance decisions for suspected seizures - Part of the Risk of ADverse Outcomes after a Suspected Seizure (RADOSS) project.

PURPOSE: Suspected seizures present challenges for ambulance services, with paramedics reporting uncertainty over whether or not to convey individuals to emergency departments. The Risk of ADverse Outcomes after a Suspected Seizure (RADOSS) project aims to address this by developing a risk assessment tool utilizing structured patient care record and dispatch data. It proposes a tool that would provide estimates of an individual's likelihood of death and/or recontact with emergency care within 3 days if conveyed compared to not conveyed, and the likelihood of an 'avoidable attendance' occurring if conveyed. Knowledge Exchange workshops engaged stakeholders to resolve key design uncertainties before model derivation. METHOD: Six workshops involved 26 service users and their significant others (epilepsy or nonepileptic attack disorder), and 25 urgent and emergency care clinicians from different English ambulance regions. Utilizing Nominal Group Techniques, participants shared views of the proposed tool, benefits and concerns, suggested predictors, critiqued outcome measures, and expressed functionality preferences. Data were analysed using Hamilton's Rapid Analysis. RESULTS: Stakeholders supported tool development, proposing 10 structured variables for predictive testing. Emphasis was placed on the tool supporting, not dictating, care decisions. Participants highlighted some reasons why RADOSS might struggle to derive a predictive model based on structured data alone and suggested some non-structured variables for future testing. Feedback on prediction timeframes for service recontact was received, along with advice on amending the 'avoidable attendance' definition to prevent the tool's predictions being undermined by potential overuse of certain investigations in hospital. CONCLUSION: Collaborative stakeholder engagement provided crucial insights that can guide RADOSS to develop a user-aligned, optimized tool.

Variation in seizure risk increases from antiseizure medication withdrawal among patients with well-controlled epilepsy: A pooled analysis.

OBJECTIVE: Guidelines suggest considering antiseizure medication (ASM) discontinuation in seizure-free patients with epilepsy. Past work has poorly explored how discontinuation effects vary between patients. We evaluated (1) what factors modify the influence of discontinuation on seizure risk; and (2) the range of seizure risk increase due to discontinuation across low- versus high-risk patients. METHODS: We pooled three datasets including seizure-free patients who did and did not discontinue ASMs. We conducted time-to-first-seizure analyses. First, we evaluated what individual patient factors modified the relative effect of ASM discontinuation on seizure risk via interaction terms. Then, we assessed the distribution of 2-year risk increase as predicted by our adjusted logistic regressions. RESULTS: We included 1626 patients, of whom 678 (42%) planned to discontinue all ASMs. The mean predicted 2-year seizure risk was 43% [95% confidence interval (CI) 39%-46%] for discontinuation versus 21% (95% CI 19%-24%) for continuation. The mean 2-year absolute seizure risk increase was 21% (95% CI 18%-26%). No individual interaction term was significant after correcting for multiple comparisons. The median [interquartile range (IQR)] risk increase across patients was 19% (IQR 14%-24%; range 7%-37%). Results were unchanged when restricting analyses to only the two RCTs. SIGNIFICANCE: No single patient factor significantly modified the influence of discontinuation on seizure risk, although we captured how absolute risk increases change for patients that are at low versus high risk. Patients should likely continue ASMs if even a 7% 2-year increase in the chance of any more seizures would be too much and should likely discontinue ASMs if even a 37% risk increase would be too little. In between these extremes, individualized risk calculation and a careful understanding of patient preferences are critical. Future work will further develop a two-armed individualized seizure risk calculator and contextualize seizure risk thresholds below which to consider discontinuation. PLAIN LANGUAGE SUMMARY: Understanding how much antiseizure medications (ASMs) decrease seizure risk is an important part of determining which patients with epilepsy should be treated, especially for patients who have not had a seizure in a while. We found that there was a wide range in the amount that ASM discontinuation increases seizure risk-between 7% and 37%. We found that no single patient factor modified that amount. Understanding what a patient's seizure risk might be if they discontinued versus continued ASM treatment is critical to making informed decisions about whether the benefit of treatment outweighs the downsides.

Growth differentiation factor-15 in patients with or at risk of heart failure but before first hospitalisation.

OBJECTIVE: Identification of patients at risk of adverse outcome from heart failure (HF) at an early stage is a priority. Growth differentiation factor (GDF)-15 has emerged as a potentially useful biomarker. This study sought to identify determinants of circulating GDF-15 and evaluate its prognostic value, in patients at risk of HF or with HF but before first hospitalisation. METHODS: Prospective, longitudinal cohort study of 2166 consecutive patients in stage A-C HF undergoing cardiovascular magnetic resonance and measurement of GDF-15. Multivariable linear regression investigated determinants of GDF-15. Cox proportional hazards modelling, Net Reclassification Improvement and decision curve analysis examined its incremental prognostic value. Primary outcome was a composite of first hospitalisation for HF or all-cause mortality. Median follow-up was 1093 (939-1231) days. RESULTS: Major determinants of GDF-15 were age, diabetes and N-terminal pro-B-type natriuretic peptide, although despite extensive phenotyping, only around half of the variability of GDF-15 could be explained (R2 0.51). Log-transformed GDF-15 was the strongest predictor of outcome (HR 2.12, 95% CI 1.71 to 2.63) and resulted in a risk prediction model with higher predictive accuracy (continuous Net Reclassification Improvement 0.26; 95% CI 0.13 to 0.39) and with greater clinical net benefit across the entire range of threshold probabilities. CONCLUSION: In patients at risk of HF, or with HF but before first hospitalisation, GDF-15 provides unique information and is highly predictive of hospitalisation for HF or all-cause mortality, leading to more accurate risk stratification that can improve clinical decision making. TRIAL REGISTRATION NUMBER: NCT02326324.

Deriving and validating an asthma diagnosis prediction model for children and young people in primary care.

Introduction: Accurately diagnosing asthma can be challenging. We aimed to derive and validate a prediction model to support primary care clinicians assess the probability of an asthma diagnosis in children and young people. Methods: The derivation dataset was created from the Avon Longitudinal Study of Parents and Children (ALSPAC) linked to electronic health records. Participants with at least three inhaled corticosteroid prescriptions in 12-months and a coded asthma diagnosis were designated as having asthma. Demographics, symptoms, past medical/family history, exposures, investigations, and prescriptions were considered as candidate predictors. Potential candidate predictors were included if data were available in ≥60% of participants. Multiple imputation was used to handle remaining missing data. The prediction model was derived using logistic regression. Internal validation was completed using bootstrap re-sampling. External validation was conducted using health records from the Optimum Patient Care Research Database (OPCRD). Results: Predictors included in the final model were wheeze, cough, breathlessness, hay-fever, eczema, food allergy, social class, maternal asthma, childhood exposure to cigarette smoke, prescription of a short acting beta agonist and the past recording of lung function/reversibility testing. In the derivation dataset, which comprised 11,972 participants aged <25 years (49% female, 8% asthma), model performance as indicated by the C-statistic and calibration slope was 0.86, 95% confidence interval (CI) 0.85-0.87 and 1.00, 95% CI 0.95-1.05 respectively. In the external validation dataset, which included 2,670 participants aged <25 years (50% female, 10% asthma), the C-statistic was 0.85, 95% CI 0.83-0.88, and calibration slope 1.22, 95% CI 1.09-1.35. Conclusions: We derived and validated a prediction model for clinicians to calculate the probability of asthma diagnosis for a child or young person up to 25 years of age presenting to primary care. Following further evaluation of clinical effectiveness, the prediction model could be implemented as a decision support software.

Prognosis of adults and children following a first unprovoked seizure.

BACKGROUND: Epilepsy is clinically defined as two or more unprovoked epileptic seizures more than 24 hours apart. Given that, a diagnosis of epilepsy can be associated with significant morbidity and mortality, it is imperative that clinicians (and people with seizures and their relatives) have access to accurate and reliable prognostic estimates, to guide clinical practice on the risks of developing further unprovoked seizures (and by definition, a diagnosis of epilepsy) following single unprovoked epileptic seizure. OBJECTIVES: 1. To provide an accurate estimate of the proportion of individuals going on to have further unprovoked seizures at subsequent time points following a single unprovoked epileptic seizure (or cluster of epileptic seizures within a 24-hour period, or a first episode of status epilepticus), of any seizure type (overall prognosis). 2. To evaluate the mortality rate following a first unprovoked epileptic seizure. SEARCH METHODS: We searched the following databases on 19 September 2019 and again on 30 March 2021, with no language restrictions. The Cochrane Register of Studies (CRS Web), MEDLINE Ovid (1946 to March 29, 2021), SCOPUS (1823 onwards), ClinicalTrials.gov, the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP). CRS Web includes randomized or quasi-randomized, controlled trials from PubMed, Embase, ClinicalTrials.gov, the World Health Organization International Clinical Trials Registry Platform (ICTRP), the Cochrane Central Register of Controlled Trials (CENTRAL), and the Specialized Registers of Cochrane Review Groups including Epilepsy. In MEDLINE (Ovid) the coverage end date always lags a few days behind the search date. SELECTION CRITERIA: We included studies, both retrospective and prospective, of all age groups (except those in the neonatal period (< 1 month of age)), of people with a single unprovoked seizure, followed up for a minimum of six months, with no upper limit of follow-up, with the study end point being seizure recurrence, death, or loss to follow-up. To be included, studies must have included at least 30 participants. We excluded studies that involved people with seizures that occur as a result of an acute precipitant or provoking factor, or in close temporal proximity to an acute neurological insult, since these are not considered epileptic in aetiology (acute symptomatic seizures). We also excluded people with situational seizures, such as febrile convulsions. DATA COLLECTION AND ANALYSIS: Two review authors conducted the initial screening of titles and abstracts identified through the electronic searches, and removed non-relevant articles. We obtained the full-text articles of all remaining potentially relevant studies, or those whose relevance could not be determined from the abstract alone and two authors independently assessed for eligibility. All disagreements were resolved through discussion with no need to defer to a third review author. We extracted data from included studies using a data extraction form based on the checklist for critical appraisal and data extraction for systematicreviews of prediction modelling studies (CHARMS). Two review authors then appraised the included studies, using a standardised approach based on the quality in prognostic studies (QUIPS) tool, which was adapted for overall prognosis (seizure recurrence). We conducted a meta-analysis using Review Manager 2014, with a random-effects generic inverse variance meta-analysis model, which accounted for any between-study heterogeneity in the prognostic effect. We then summarised the meta-analysis by the pooled estimate (the average prognostic factor effect), its 95% confidence interval (CI), the estimates of I² and Tau² (heterogeneity), and a 95% prediction interval for the prognostic effect in a single population at three various time points, 6 months, 12 months and 24 months. Subgroup analysis was performed according to the ages of the cohorts included; studies involving all ages, studies that recruited adult only and those that were purely paediatric. MAIN RESULTS: Fifty-eight studies (involving 54 cohorts), with a total of 12,160 participants (median 147, range 31 to 1443), met the inclusion criteria for the review. Of the 58 studies, 26 studies were paediatric studies, 16 were adult and the remaining 16 studies were a combination of paediatric and adult populations. Most included studies had a cohort study design with two case-control studies and one nested case-control study. Thirty-two studies (29 cohorts) reported a prospective longitudinal design whilst 15 studies had a retrospective design whilst the remaining studies were randomised controlled trials. Nine of the studies included presented mortality data following a first unprovoked seizure. For a mortality study to be included, a proportional mortality ratio (PMR) or a standardised mortality ratio (SMR) had to be given at a specific time point following a first unprovoked seizure. To be included in the meta-analysis a study had to present clear seizure recurrence data at 6 months, 12 months or 24 months. Forty-six studies were included in the meta-analysis, of which 23 were paediatric, 13 were adult, and 10 were a combination of paediatric and adult populations. A meta-analysis was performed at three time points; six months, one year and two years for all ages combined, paediatric and adult studies, respectively. We found an estimated overall seizure recurrence of all included studies at six months of 27% (95% CI 24% to 31%), 36% (95% CI 33% to 40%) at one year and 43% (95% CI 37% to 44%) at two years, with slightly lower estimates for adult subgroup analysis and slightly higher estimates for paediatric subgroup analysis. It was not possible to provide a summary estimate of the risk of seizure recurrence beyond these time points as most of the included studies were of short follow-up and too few studies presented recurrence rates at a single time point beyond two years. The evidence presented was found to be of moderate certainty. AUTHORS' CONCLUSIONS: Despite the limitations of the data (moderate-certainty of evidence), mainly relating to clinical and methodological heterogeneity we have provided summary estimates for the likely risk of seizure recurrence at six months, one year and two years for both children and adults. This provides information that is likely to be useful for the clinician counselling patients (or their parents) on the probable risk of further seizures in the short-term whilst acknowledging the paucity of long-term recurrence data, particularly beyond 10 years.

Protocol for an observational cohort study investigating biomarkers predicting seizure recurrence following a first unprovoked seizure in adults.

INTRODUCTION: A first unprovoked seizure is a common presentation, reliably identifying those that will have recurrent seizures is a challenge. This study will be the first to explore the combined utility of serum biomarkers, quantitative electroencephalogram (EEG) and quantitative MRI to predict seizure recurrence. This will inform patient stratification for counselling and the inclusion of high-risk patients in clinical trials of disease-modifying agents in early epilepsy. METHODS AND ANALYSIS: 100 patients with first unprovoked seizure will be recruited from a tertiary neuroscience centre and baseline assessments will include structural MRI, EEG and a blood sample. As part of a nested pilot study, a subset of 40 patients will have advanced MRI sequences performed that are usually reserved for patients with refractory chronic epilepsy. The remaining 60 patients will have standard clinical MRI sequences. Patients will be followed up every 6 months for a 24-month period to assess seizure recurrence. Connectivity and network-based analyses of EEG and MRI data will be carried out and examined in relation to seizure recurrence. Patient outcomes will also be investigated with respect to analysis of high-mobility group box-1 from blood serum samples. ETHICS AND DISSEMINATION: This study was approved by North East-Tyne & Wear South Research Ethics Committee (20/NE/0078) and funded by an Association of British Neurologists and Guarantors of Brain clinical research training fellowship. Findings will be presented at national and international meetings published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NIHR Clinical Research Network's (CRN) Central Portfolio Management System (CPMS)-44976.

Supporting the ambulance service to safely convey fewer patients to hospital by developing a risk prediction tool: Risk of Adverse Outcomes after a Suspected Seizure (RADOSS)-protocol for the mixed-methods observational RADOSS project.

INTRODUCTION: Ambulances services are asked to further reduce avoidable conveyances to emergency departments (EDs). Risk of Adverse Outcomes after a Suspected Seizure seeks to support this by: (1) clarifying the risks of conveyance and non-conveyance, and (2) developing a risk prediction tool for clinicians to use 'on scene' to estimate the benefits an individual would receive if conveyed to ED and risks if not. METHODS AND ANALYSIS: Mixed-methods, multi-work package (WP) project. For WP1 and WP2 we shall use an existing linked data set that tracks urgent and emergency care (UEC) use of persons served by one English regional ambulance service. Risk tools are specific to clinical scenarios. We shall use suspected seizures in adults as an exemplar.WP1: Form a cohort of patients cared for a seizure by the service during 2019/2020. It, and nested Knowledge Exchange workshops with clinicians and service users, will allow us to: determine the proportions following conveyance and non-conveyance that die and/or recontact UEC system within 3 (/30) days; quantify the proportion of conveyed incidents resulting in 'avoidable ED attendances' (AA); optimise risk tool development; and develop statistical models that, using information available 'on scene', predict the risk of death/recontact with the UEC system within 3 (/30) days and the likelihood of an attendance at ED resulting in an AA.WP2: Form a cohort of patients cared for a seizure during 2021/2022 to 'temporally' validate the WP1 predictive models.WP3: Complete the 'next steps' workshops with stakeholders. Using nominal group techniques, finalise plans to develop the risk tool for clinical use and its evaluation. ETHICS AND DISSEMINATION: WP1a and WP2 will be conducted under database ethical approval (IRAS 307353) and Confidentiality Advisory Group (22/CAG/0019) approval. WP1b and WP3 have approval from the University of Liverpool Central Research Ethics Committee (11450). We shall engage in proactive dissemination and knowledge mobilisation to share findings with stakeholders and maximise evidence usage.

Clinical prediction models assessing response to radiotherapy for rectal cancer: protocol for a systematic review.

BACKGROUND: Rectal cancer has a high prevalence. The standard of care for management of localised disease involves major surgery and/or chemoradiotherapy, but these modalities are sometimes associated with mortality and morbidity. The notion of 'watch and wait' has therefore emerged and offers an organ-sparing approach to patients after administering a less invasive initial treatment, such as X-ray brachytherapy (Papillon technique). It is thus important to evaluate how likely patients are to respond to such therapies, to develop patient-tailored treatment pathways. We propose a systematic review to identify published clinical prediction models of the response of rectal cancer to treatment that includes radiotherapy and here present our protocol. METHODS: Included studies will develop multivariable clinical prediction models which assess response to treatment and overall survival of adult patients who have been diagnosed with any stage of rectal cancer and have received radiotherapy treatment with curative intent. Cohort studies and randomised controlled trials will be included. The primary outcome will be the occurrence of salvage surgery at 1 year after treatment. Secondary outcomes include salavage surgery at at any reported time point, the predictive accuracy of models, the quality of the developed models and the feasibility of using the model in clinical practice. Ovid MEDLINE, PubMed, Cochrane Library, EMBASE and CINAHL will be searched from inception to 24 February 2022. Keywords and phrases related to rectal cancer, radiotherapy and prediction models will be used. Studies will be selected once the deduplication, title, abstract and full-text screening process have been completed by two independent reviewers. The PRISMA-P checklist will be followed. A third reviewer will resolve any disagreement. The data extraction form will be pilot-tested using a representative 5% sample of the studies reviewed. The CHARMS checklist will be implemented. Risk of bias in each study will be assessed using the PROBAST tool. A narrative synthesis will be performed and if sufficient data are identified, meta-analysis will be undertaken as described in Debray et al. DISCUSSION: This systematic review will identify factors that predict response to the treatment protocol. Any gaps for potential development of new clinical prediction models will be highlighted. TRIAL REGISTRATION: CRD42022277704.

Validated Model for Prediction of Adverse Cardiac Outcome in Patients With Fabry Disease.

BACKGROUND: The cardiac manifestations of Fabry disease are the leading cause of death, but risk stratification remains inadequate. Identifying patients who are at risk of adverse cardiac outcome may facilitate more evidence-based treatment guidance. Contemporary cardiovascular cardiac magnetic resonance biomarkers have become widely adopted, but their prognostic value remains unclear. OBJECTIVES: The objective of this study was to develop, internally validate, and evaluate the performance of, a prognostic model, including contemporary deep phenotyping, which can be used to generate individual risk estimates for adverse cardiac outcome in patients with Fabry disease. METHODS: This longitudinal prospective cohort study consisted of 200 consecutive patients with Fabry disease undergoing clinical cardiac magnetic resonance. Median follow-up was 4.5 years (IQR: 2.7-6.3 years). Prognostic models were developed using Cox proportional hazards modeling. Outcome was a composite of adverse cardiac events. Model performance was evaluated. A risk calculator, which provides 5-year estimated risk of adverse cardiac outcome for individual patients, including men and women, was generated. RESULTS: The highest performing, internally validated, parsimonious multivariable model included age, native myocardial T1 dispersion (SD of per voxel myocardial T1 relaxation times), and indexed left ventricular mass. Median optimism-adjusted c-statistic across 5 imputed model development data sets was 0.77 (95% CI: 0.70-0.84). Model calibration was excellent across the full risk profile. CONCLUSIONS: This study developed and internally validated a risk prediction model that accurately predicts 5-year risk of adverse cardiac outcome for individual patients with Fabry disease, including men and women, which could easily be integrated into clinical care. External validation is warranted.

IVIg-exposure and thromboembolic event risk: findings from the UK Biobank.

BACKGROUND: Arterial and venous thromboembolic events (TEEs) have been associated with intravenous Ig use, but the risk has been poorly quantified. We aimed to calculate the risk of TEEs associated with exposure to intravenous Ig. METHODS: We included participants from UK Biobank recruited over 3 years, data extracted September 2020.The study endpoints were incidence of myocardial infarction, other acute ischaemic heart disease, stroke, pulmonary embolism and other venous embolism and thrombosis.Predictors included known TEE risk factors: age, sex, hypertension, smoking status, type 2 diabetes mellitus, hypercholesterolaemia, cancer and past history of TEE. Intravenous Ig and six other predictors were added in the sensitivity analysis.Information from participants was collected prospectively, while data from linked resources, including death, cancer, hospital admissions and primary care records were collected retrospectively and prospectively.  FINDINGS: 14 794 of 502 492 individuals had an incident TEE during the study period. The rate of incident events was threefold higher in those with prior history of TEE (8 .7%) than those without previous history of TEE (3.0%).In the prior TEE category, intravenous Ig exposure was independently associated with increased risk of incident TEE (OR=3.69 (95% CI 1.15 to 11.92), p=0.03) on multivariate analysis. The number needed to harm by exposure to intravenous Ig in those with a history of TEE was 5.8 (95% CI 2.3 to 88.3).Intravenous Ig exposure did not increase risk of TEE in those with no previous history of TEE. INTERPRETATION: Intravenous Ig is associated with increased risk of further TEE in individuals with prior history of an event with one further TEE for every six people exposed. In practice, this will influence how clinicians consent for and manage overall TEE risk on intravenous Ig exposure.

Predicting hospitalisation for heart failure and death in patients with, or at risk of, heart failure before first hospitalisation: a retrospective model development and external validation study.

BACKGROUND: Identifying people who are at risk of being admitted to hospital (hospitalised) for heart failure and death, and particularly those who have not previously been hospitalised for heart failure, is a priority. We aimed to develop and externally validate a prognostic model involving contemporary deep phenotyping that can be used to generate individual risk estimates of hospitalisation for heart failure or all-cause mortality in patients with, or at risk of, heart failure, but who have not previously been hospitalised for heart failure. METHODS: Between June 1, 2016, and May 31, 2018, 3019 consecutive adult patients (aged ≥16 years) undergoing cardiac magnetic resonance (CMR) at Manchester University National Health Service Foundation Trust, Manchester, UK, were prospectively recruited into a model development cohort. Candidate predictor variables were selected according to clinical practice and literature review. Cox proportional hazards modelling was used to develop a prognostic model. The final model was validated in an external cohort of 1242 consecutive adult patients undergoing CMR at the University of Pittsburgh Medical Center Cardiovascular Magnetic Resonance Center, Pittsburgh, PA, USA, between June 1, 2010, and March 25, 2016. Exclusion criteria for both cohorts included previous hospitalisation for heart failure. Our study outcome was a composite of first hospitalisation for heart failure or all-cause mortality after CMR. Model performance was evaluated in both cohorts by discrimination (Harrell's C-index) and calibration (assessed graphically). FINDINGS: Median follow-up durations were 1118 days (IQR 950-1324) for the development cohort and 2117 days (1685-2446) for the validation cohort. The composite outcome occurred in 225 (7·5%) of 3019 patients in the development cohort and in 219 (17·6%) of 1242 patients in the validation cohort. The final, externally validated, parsimonious, multivariable model comprised the predictors: age, diabetes, chronic obstructive pulmonary disease, N-terminal pro-B-type natriuretic peptide, and the CMR variables, global longitudinal strain, myocardial infarction, and myocardial extracellular volume. The median optimism-adjusted C-index for the externally validated model across 20 imputed model development datasets was 0·805 (95% CI 0·793-0·829) in the development cohort and 0·793 (0·766-0·820) in the external validation cohort. Model calibration was excellent across the full risk profile. A risk calculator that provides an estimated risk of hospitalisation for heart failure or all-cause mortality at 3 years after CMR for individual patients was generated. INTERPRETATION: We developed and externally validated a risk prediction model that provides accurate, individualised estimates of the risk of hospitalisation for heart failure and all-cause mortality in patients with, or at risk of, heart failure, before first hospitalisation. It could be used to direct intensified therapy and closer follow-up to those at increased risk. FUNDING: The UK National Institute for Health Research, Guerbet Laboratories, and Roche Diagnostics International.

Reappraisal of the Medical Research Council Antiepileptic Drug Withdrawal Study: Contamination-adjusted and dose-response re-analysis.

OBJECTIVE: The 1991 Medical Research Council (MRC) Study compared seizure relapse for seizure-free patients randomized to withdraw vs continue of antiseizure medications (ASMs). We re-analyzed this trial to account for crossover between arms using contamination-adjusted intention to treat (CA ITT) methods, to explore dose-response curves, and to validate predictions against external data. ITT assesses the effect of being randomized to withdraw, as-treated analysis assesses the confounded effect of withdrawing, but CA ITT assesses the unconfounded effect of actually withdrawing. METHODS: CA ITT involves two stages. First, we used randomized arm to predict whether patients withdrew their ASM (logistic) or total daily ASM dose (linear). Second, we used those values to predict seizure occurrence (logistic). RESULTS: The trial randomized 503 patients to withdraw and 501 patients to continue ASMs. We found that 316 of 376 patients (88%) who were randomized to withdraw decreased their dose at every pre-seizure visit, compared with 35 of 424 (8%) who were randomized to continue (p < .01). Adjusted odds ratios of a 2-year seizure for those who withdrew vs those who did not was 1.3 (95% confidence interval [CI] 0.9-1.9) in the as-treated analysis, 2.5 (95% CI 1.9-3.4) comparing those randomized to withdraw vs continue for ITT, and 3.1 (95% CI 2.1-4.5) for CA ITT. Probabilities (withdrawal vs continue) were 28% vs 24% (as-treated), 40% vs 22% (ITT), and 43% vs 21% (CA ITT). Differences between ITT and CA ITT were greater when varying the predictor (reaching zero ASMs) or outcome (1-year seizures). As-treated dose-response curves demonstrated little to no effects, but larger effects in CA ITT analysis. MRC data overpredicted risk in Lossius data, with moderate discrimination (areas under the curve ~0.70). SIGNIFICANCE: CA ITT results (the effect of actually withdrawing ASMs on seizures) were slightly greater than ITT effects (the effect of recommend withdrawing ASMs on seizures). How these findings affect clinical practice must be individualized.

A systematic review of interventions to increase physical activity and reduce sedentary behaviour following bariatric surgery.

BACKGROUND: Bariatric surgery promotes weight loss and improves co-morbid conditions, with patients who are more physically active having better outcomes. However, levels of physical activity and sedentary behaviour often remain unchanged following surgery. OBJECTIVES: To identify interventions and components thereof that are able to facilitate changes in physical activity and sedentary behaviour. ELIGIBILITY: Physical activity and/or sedentary behaviour must have been measured, pre and post intervention, in patients who have undergone bariatric surgery. STUDY APPRAISAL AND SYNTHESIS METHODS: Four databases were searched with key-words. Two researchers conducted paper screening, data extraction and risk-of-bias assessment. RESULTS: Twelve studies were included; eleven were randomised. Two were delivered presurgery and ten postsurgery; five found positive effect. Moderate to vigorous physical activity increased in three studies, two of which also found a significant increase in step count. The fourth found a significant increase in strenuous activity and the fifth a significant increase in metabolic equivalent of task/day and reduced time spent watching television. LIMITATIONS: Meta-analysis could not be conducted due to heterogeneity of outcomes and the tools used. CONCLUSION AND IMPLICATIONS OF KEY FINDINGS: This review has identified interventions and components thereof that were able to provoke positive effect. However, intervention and control conditions were not always well described particularly in terms of behaviour change techniques and the rationale for their use. SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO (CRD42019121372).

Complication rates following ventricular tachycardia ablation in ischaemic and non-ischaemic cardiomyopathies: a systematic review.

BACKGROUND: Catheter ablation of ventricular tachycardia (VT) is associated with potential major complications, including mortality. The risk of acute complications in patients with ischaemic cardiomyopathy (ICM) and non-ischaemic cardiomyopathy (NICM) has not been systematically evaluated. METHODS: PubMed was searched for studies of catheter ablation of VT published between September 2009 and September 2019. Pre-specified primary outcomes were (1) rate of major acute complications, including death, and (2) mortality rate. RESULTS: A total of 7395 references were evaluated for relevance. From this, 50 studies with a total of 3833 patients undergoing 4319 VT ablation procedures fulfilled the inclusion criteria (mean age 59 years; male 82%; 2363 [62%] ICM; 1470 [38%] NICM). The overall major complication rate in ICM cohorts was 9.4% (95% CI, 8.1-10.7) and NICM cohorts was 7.1% (95% CI, 6.0-8.3). Reported complication rates were highly variable between studies (ICM I2 = 90%; NICM I2 = 89%). Vascular complications (ICM 2.5% [95% CI, 1.9-3.1]; NICM 1.2% [95% CI, 0.7-1.7]) and cerebrovascular events (ICM 0.5% [95% CI, 0.2-0.7]; NICM, 0.1% [95% CI, 0-0.2]) were significantly higher in ICM cohorts. Acute mortality rates in the ICM and NICM cohorts were low (ICM 0.9% [95% CI, 0.5-1.3]; NICM 0.6% [95% CI, 0.3-1.0]) with the majority of overall deaths (ICM 75%; NICM 80%) due to either recurrent VT or cardiogenic shock. CONCLUSION: Overall acute complication rates of VT ablation are comparable between ICM and NICM patients. However, the pattern and predictors of complications vary depending on the underlying cardiomyopathy.

Risk of seizure recurrence in people with single seizures and early epilepsy - Model development and external validation.

PURPOSE: Following a single seizure, or recent epilepsy diagnosis, it is difficult to balance risk of medication side effects with the potential to prevent seizure recurrence. A prediction model was developed and validated enabling risk stratification which in turn informs treatment decisions and individualises counselling. METHODS: Data from a randomised controlled trial was used to develop a prediction model for risk of seizure recurrence following a first seizure or diagnosis of epilepsy. Time-to-event data was modelled via Cox's proportional hazards regression. Model validity was assessed via discrimination and calibration using the original dataset and also using three external datasets - National General Practice Survey of Epilepsy (NGPSE), Western Australian first seizure database (WA) and FIRST (Italian dataset of people with first tonic-clonic seizures). RESULTS: People with neurological deficit, focal seizures, abnormal EEG, not indicated for CT/MRI scan, or not immediately treated have a significantly higher risk of seizure recurrence. Discrimination was fair and consistent across the datasets (c-statistics: 0.555 (NGPSE); 0.558 (WA); 0.597 (FIRST)). Calibration plots showed good agreement between observed and predicted probabilities in NGPSE at one and three years. Plots for WA and FIRST showed poorer agreement with the model underpredicting risk in WA, and over-predicting in FIRST. This was resolved following model recalibration. CONCLUSION: The model performs well in independent data especially when recalibrated. It should now be used in clinical practice as it can improve the lives of people with single seizures and early epilepsy by enabling targeted treatment choices and more informed patient counselling.

Protocol for the Addressing the Social Determinants and Consequences of Tuberculosis in Nepal (ASCOT) pilot trial.

BACKGROUND: The World Health Organization's End TB (tuberculosis) Strategy advocates social and economic support for TB-affected households but evidence from low-income settings is scarce. We will evaluate the feasibility and acceptability of a locally-appropriate socioeconomic support intervention for TB-affected households in Nepal. METHODS: We will conduct a pilot randomised-controlled trial with mixed-methods process evaluation in four TB-endemic, impoverished districts of Nepal: Pyuthan, Chitwan, Mahottari, and Morang. We will recruit 128 people with TB notified to the Nepal National TB Program (NTP) and 40 multisectoral stakeholders including NTP staff, civil-society members, policy-makers, and ASCOT (Addressing the Social Determinants and Consequences of Tuberculosis) team members. People with TB will be randomised 1:1:1:1 to four study arms (n=32 each): control; social support; economic support; and combined social and economic (socioeconomic) support. Social support will be TB education and peer-led mutual-support TB Clubs providing TB education and stigma-reduction counselling. Economic support will be monthly unconditional cash transfers during TB treatment with expectations (not conditions) of meeting NTP goals. At 0, 2, and 6 months following TB treatment initiation, participants will be asked to complete a survey detailing the social determinants and consequences of TB and their feedback on ASCOT. Complementary process evaluation will use focus group discussions (FGD), key informant interviews (KII), and a workshop with multi-sectoral stakeholders to consider the challenges to ASCOT's implementation and scale-up. A sample of ~100 people with TB is recommended to estimate TB-related costs. Information power is estimated to be reached with approximately 25 FGD and 15 KII participants. CONCLUSIONS: The ASCOT pilot trial will both generate robust evidence on a locally-appropriate, socioeconomic support intervention for TB-affected households in Nepal and inform a large-scale future ASCOT trial, which will evaluate the intervention's impact on catastrophic costs mitigation and TB outcomes. The trial is registered with the ISRCTN ( ISRCTN17025974).