A fast look-up method for Bayesian mean-parameterised Conway-Maxwell-Poisson regression models.

Count data that are subject to both under and overdispersion at some hierarchical level cannot be readily accommodated by classic models such as Poisson or negative binomial regression models. The mean-parameterised Conway-Maxwell-Poisson distribution allows for both types of dispersion within the same model, but is doubly intractable with an embedded normalising constant. We propose a look-up method where pre-computing values of the rate parameter dramatically reduces computing times and renders the proposed model a practicable alternative when faced with such bidispersed data. The approach is demonstrated and verified using a simulation study and applied to three datasets: an underdispersed small dataset on takeover bids, a medium dataset on yellow cards issued by referees in the English Premier League prior to and during the Covid-19 pandemic, and a large Test match cricket bowling dataset, the latter two of which each exhibit over and underdispersion at the individual level.

Mid-regional proadrenomedullin (MR-proADM), C-reactive protein (CRP) and other biomarkers in the early identification of disease progression in patients with COVID-19 in the acute NHS setting.

AIMS: There is a lack of biomarkers validated for assessing clinical deterioration in patients with COVID-19 on presentation to secondary or tertiary care. This evaluation looked at the potential clinical application of C reactive protein (CRP), procalcitonin, mid-regional proadrenomedullin (MR-proADM) and white cell count to support prediction of clinical outcomes. METHODS: 135 patients presenting to Hampshire Hospitals NHS Foundation Trust between April and June 2020 confirmed to have COVID-19 via reverse-transcription-qPCR were included. Biomarkers from within 24 hours of presentation were used to predict disease progression by Cox regression and area under the receiver operating characteristic curves. The endpoints assessed were 30-day all-cause mortality, intubation and ventilation, critical care admission and non-invasive ventilation (NIV) use. RESULTS: Elevated MR-proADM was shown to have the greatest ability to predict 30-day mortality adjusting for age, cardiovascular disease, renal disease and neurological disease. A significant association was also noted between raised MR-proADM and CRP concentrations and the requirement for critical care admission and NIV. CONCLUSIONS: The measurement of MR-proADM and CRP in patients with confirmed COVID-19 infection on admission shows significant potential to support clinicians in identifying those at increased risk of disease progression and need for higher level care, subsequently enabling prompt escalation in clinical interventions.

Risk factors associated with readmission within 30 days following stoma surgery: Development of a 'traffic light' prediction model.

AIM: Patients undergoing stoma surgery have a higher risk for early readmission. Some patients may benefit from closer postdischarge surveillance to provide early detection of complications and timely intervention. However, there is a paucity of validated tools to identify those at higher risk of readmission. Here, we aim to determine the independent risk factors associated with readmission within 30 days of discharge following stoma surgery, attempt to validate previous predictive models and develop a novel prediction tool. METHOD: A retrospective review of 423 patients who underwent ileostomy or colostomy stoma formation at a UK tertiary colorectal centre between 2019 and 2021. Univariate, multivariate and logistic regression analyses were used to analyse a large number of demographics and risk factors and the association with readmission. RESULTS: This study cohort included 220 ileostomy and 203 colostomy patients. Of these, 87 (20.6%) were readmitted within 30 days of discharge following index surgery. A large number of demographics were evaluated for association with readmission. Readmission was associated with chronic heart failure (p < 0.05), postoperative stoma-specific complications (bleeding, p = 0.02; high-output stoma, p = 0.01) and those with a loop ileostomy (34.0% vs. 18.6%; p = 0.01). A previous predictive model was ineffective in this cohort, therefore a simplified 'traffic light' risk scoring system was developed and found to have improved discrimination. CONCLUSION: Readmission following stoma formation is associated with key variables that could provide the means to triage, risk score and potentially predict readmissions. We found that a novel and simplified scoring system may provide improved prediction.

Exposing the impact of intensive advice services on health: A realist evaluation.

Attention has turned to welfare advice as a potential health and social care intervention. However, establishing direct evidence of health impact has proven difficult. This is compounded by the need to understand both the facilitative contexts and mechanisms through which this impact occurs. This study investigated if, how and in which circumstances an intensive advice service had an impact on stress and well-being (as precursors to health impacts), for clients attending a branch of Citizens Advice, located in the North East of England. A mixed methods realist evaluation of three intensive advice services offered by Citizens Advice (CA) was operationalised in five phases: (a) Building programme theories, (b) refining programme theories, (c) Development of a data recording tool, (d) Testing programme theories with empirical data, (e) Impact interviews. This paper focuses on phase 4. The Warwick Edinburgh Mental Wellbeing Scale (WEMWBS) and Perceived Stress Scale (PSS) were completed by 191 clients, with a 91% follow-up rate (data collected: February 2016 to March 2017). Twenty-two CA clients participated in interviews (data collected: October 2015 to November 2016). The PSS indicated a significant decrease in stress from initial consultation to approximately 4-6 weeks post advice from 31.4 to 10.3 (p < 0.001) and the WEMWBS indicated a significant increase in client well-being from a mean of 26.9 to 46.5 (p < 0.001). Nine refined programme theories are presented which combine the qualitative and quantitative analysis; they are underpinned by three abstract theories: Capabilities model, The Decision to Trust Model, and Third Space. An explanatory framework is presented covering the micro, meso, and macro levels of CA. Use of a stress and well-being lens has allowed insight into the precursors of health in those receiving intensive advice. Using these measures whilst explaining contextual and mechanistic properties, begins to build a complex and real picture of how advice services impact on health.

joineRML: a joint model and software package for time-to-event and multivariate longitudinal outcomes.

BACKGROUND: Joint modelling of longitudinal and time-to-event outcomes has received considerable attention over recent years. Commensurate with this has been a rise in statistical software options for fitting these models. However, these tools have generally been limited to a single longitudinal outcome. Here, we describe the classical joint model to the case of multiple longitudinal outcomes, propose a practical algorithm for fitting the models, and demonstrate how to fit the models using a new package for the statistical software platform R, joineRML. RESULTS: A multivariate linear mixed sub-model is specified for the longitudinal outcomes, and a Cox proportional hazards regression model with time-varying covariates is specified for the event time sub-model. The association between models is captured through a zero-mean multivariate latent Gaussian process. The models are fitted using a Monte Carlo Expectation-Maximisation algorithm, and inferences are based on approximate standard errors from the empirical profile information matrix, which are contrasted to an alternative bootstrap estimation approach. We illustrate the model and software on a real data example for patients with primary biliary cirrhosis with three repeatedly measured biomarkers. CONCLUSIONS: An open-source software package capable of fitting multivariate joint models is available. The underlying algorithm and source code makes use of several methods to increase computational speed.

Joint Models of Longitudinal and Time-to-Event Data with More Than One Event Time Outcome: A Review.

Methodological development and clinical application of joint models of longitudinal and time-to-event outcomes have grown substantially over the past two decades. However, much of this research has concentrated on a single longitudinal outcome and a single event time outcome. In clinical and public health research, patients who are followed up over time may often experience multiple, recurrent, or a succession of clinical events. Models that utilise such multivariate event time outcomes are quite valuable in clinical decision-making. We comprehensively review the literature for implementation of joint models involving more than a single event time per subject. We consider the distributional and modelling assumptions, including the association structure, estimation approaches, software implementations, and clinical applications. Research into this area is proving highly promising, but to-date remains in its infancy.

Joint modelling of time-to-event and multivariate longitudinal outcomes: recent developments and issues.

BACKGROUND: Available methods for the joint modelling of longitudinal and time-to-event outcomes have typically only allowed for a single longitudinal outcome and a solitary event time. In practice, clinical studies are likely to record multiple longitudinal outcomes. Incorporating all sources of data will improve the predictive capability of any model and lead to more informative inferences for the purpose of medical decision-making. METHODS: We reviewed current methodologies of joint modelling for time-to-event data and multivariate longitudinal data including the distributional and modelling assumptions, the association structures, estimation approaches, software tools for implementation and clinical applications of the methodologies. RESULTS: We found that a large number of different models have recently been proposed. Most considered jointly modelling linear mixed models with proportional hazard models, with correlation between multiple longitudinal outcomes accounted for through multivariate normally distributed random effects. So-called current value and random effects parameterisations are commonly used to link the models. Despite developments, software is still lacking, which has translated into limited uptake by medical researchers. CONCLUSION: Although, in an era of personalized medicine, the value of multivariate joint modelling has been established, researchers are currently limited in their ability to fit these models routinely. We make a series of recommendations for future research needs.

Measuring the Impact of Research: Lessons from the UK's Research Excellence Framework 2014.

Impactful academic research plays a stellar role in society, pressing to ask the question of how one measures the impact created by different areas of academic research. Measuring the societal, cultural, economic and scientific impact of research is currently the priority of the National Science Foundation, European Commission and several research funding agencies. The recently concluded United Kingdom's national research quality exercise, the Research Excellence Framework (REF) 2014, which piloted impact assessment as part of the overall evaluation offers a lens to view how impact of research in different disciplines can be measured. Overall research quality was assessed through quality of outputs, 'impact' and research environment. We performed two studies using the REF 2014 as a case study. The first study on 363 Impact Case Studies (ICSs) submitted in 5 research areas (UoAs) reveals that, in general, the impact scores were constructed upon a combination of factors i.e. quantity of quartile-one (Q1) publications, quantity and value of grants/income, number of researchers stated in the ICSs, spin-offs created, discoveries/patents and presentation of esteem data, informing researchers/ academics of the factors to consider in order to achieve a better impact score in research impact assessments. However, there were differences among disciplines in terms of the role played by the factors in achieving their overall scores for the ICSs. The outcome of this study is thus a set of impact indicators, and their relationship with the overall score of impact of research in different disciplines as determined in REF2014, which would in the first instance provide some answers to impact measures that would be useful for researchers in different disciplines. The second study extracts the general themes of impact reported by universities by performing a word frequency analysis in all the ICSs submitted in the five chosen research areas, which were substantially varied owing to their fields.

Reducing inequalities in care for patients with non-malignant diseases: Insights from a realist evaluation of an integrated palliative care pathway.

BACKGROUND: The need for palliative care is growing internationally with an increasing prevalence of non-malignant diseases. The integrated care pathway was implemented in primary care by multidisciplinary teams from 2009 in a locality in the North East of England. Fourteen general practitioner practices provided data for the study. AIM: To find whether, how, and under what circumstances palliative care registrations are made for patients with non-malignant diseases in primary care. DESIGN: General practitioner practice data were analysed statistically and qualitative data were collected from health care professionals and members of relevant organisations. FINDINGS: A mixed-effects logistic model indicated a significant difference beyond the 0.1% level (p < 0.001) in registrations between the malignant and non-malignant groups in 2011, with an odds ratio of 0.09 (=exp(-2.4266)), indicating that patients in the non-malignant group are around 11 times (1/0.09) less likely to be registered than patients in the malignant group. However, patients with non-malignant diseases were significantly more likely to be registered in 2012 than in 2011 with an odds ratio of 1.46, significant beyond the 1% level. Qualitative analyses indicate that health care professionals find registering patients with non-malignant diseases stressful, yet feel that their confidence in treating this population is increasing. CONCLUSION: The integrated care pathway began to enable the reduction in inequalities in care by identifying, registering and managing an increasing number of palliative patients with non-malignant diseases. Consensual and inclusive definitions of palliative care were developed in order to legitimise the registration of such patients.

South Asians and coronary disease: is there discordance between effects on incidence and prognosis?

OBJECTIVE: To determine whether the effect of South Asian ethnicity differs between studies of incidence and prognosis of coronary disease. DESIGN: Systematic literature review and meta-analysis, and cohort analysis from a national acute coronary syndrome (ACS) registry linked to mortality (National Institute of Cardiovascular Outcomes Research/Myocardial Infarction National Audit Project). SETTING: International for the review, and England and Wales for the cohort analysis. PATIENTS: The numbers of South Asians included in the meta-analysis were 111 555 (incidence) and 14 531 (prognosis) of whom 8251 were from the ACS cohort. MAIN OUTCOME MEASURES: Incidence studies: non-fatal myocardial infarction or fatal coronary heart disease; prognostic studies: mortality; HRs for 1-year all-cause death in ACS cohort. RESULTS: South Asians had higher incidence of coronary disease compared with white subjects (HR 1.35 95% CI 1.30 to 1.40) based on meta-analysis of nine studies. Among 10 studies on prognosis, South Asians had better prognosis compared with white subjects (HR 0.78 95% CI 0.74 to 0.82). In the ACS cohort, the impact of diabetes (42.4% of South Asians, 16.9% of white subjects) on 1-year mortality was stronger in South Asians than white subjects (age-adjusted HR 1.83 95% CI 1.59 to 2.11 vs 1.53 95% CI 1.49 to 1.57). However, prognosis was better in South Asians even among diabetics, older people and those living in areas of the highest social deprivation. CONCLUSIONS: South Asian ethnicity is associated with higher incidence of coronary disease, but lower mortality once coronary disease is manifest. The dissociation between effects on incidence and prognosis suggests that public health initiatives to reduce inequalities in mortality between South Asian and white populations should focus on primary prevention. This is a CALIBER study with ClinicalTrials.gov Identifier: NCT01163513.