Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records.

Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 24.5 million primary-care health records in over 740,000 individuals in the UK Biobank, Million Veteran Program USA, and Estonian Biobank, to discover and validate the genetic architecture of adiposity trajectories. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI by 14%. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (APOE missense variant). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology of quantitative traits in adulthood.

A large-scale and PCR-referenced vocal audio dataset for COVID-19.

The UK COVID-19 Vocal Audio Dataset is designed for the training and evaluation of machine learning models that classify SARS-CoV-2 infection status or associated respiratory symptoms using vocal audio. The UK Health Security Agency recruited voluntary participants through the national Test and Trace programme and the REACT-1 survey in England from March 2021 to March 2022, during dominant transmission of the Alpha and Delta SARS-CoV-2 variants and some Omicron variant sublineages. Audio recordings of volitional coughs, exhalations, and speech were collected in the 'Speak up and help beat coronavirus' digital survey alongside demographic, symptom and self-reported respiratory condition data. Digital survey submissions were linked to SARS-CoV-2 test results. The UK COVID-19 Vocal Audio Dataset represents the largest collection of SARS-CoV-2 PCR-referenced audio recordings to date. PCR results were linked to 70,565 of 72,999 participants and 24,105 of 25,706 positive cases. Respiratory symptoms were reported by 45.6% of participants. This dataset has additional potential uses for bioacoustics research, with 11.3% participants self-reporting asthma, and 27.2% with linked influenza PCR test results.

Outcomes of Neonates Born with Symptomatic Tetralogy of Fallot and Absent Ductus Arteriosus.

OBJECTIVE: To test the hypothesis that neonates with symptomatic tetralogy of Fallot (TOF) and absent ductus arteriosus (ADA) have worse clinical outcomes compared with those with a ductus arteriosus (DA), and that this difference is driven by those born with ADA and with critically deficient pulmonary blood flow (CDPBF). STUDY DESIGN: We performed a retrospective, multicenter cohort study of neonates who underwent intervention for symptomatic TOF comparing death and reintervention between subjects with and without a DA identified on fetal echocardiogram or on echocardiogram performed in the first postnatal day. Exclusion criteria were as follows: inability to define DA status, collaterals supplying pulmonary blood flow, atrioventricular septal defect, and absent pulmonary valve. We defined CDPBF as undergoing a procedure to augment pulmonary blood flow on the date of birth or extracorporeal membrane oxygenation prior to such a procedure. RESULTS: The study cohort included 519 patients, among whom 11% had ADA. Patients with ADA were more likely to have a genetic syndrome and had smaller branch pulmonary artery size. In analyses adjusting for center, interventional treatment strategy, genetic syndrome, and minimum branch pulmonary artery size, ADA was associated with higher mortality risk (adjusted hazard ratio of 2.37 (95% CI: 1.07,5.27; P = .034). Seven patients had CDPBF (1.3% of the entire cohort and 12% of patients with ADA). CONCLUSIONS: A minority of symptomatic TOF neonates have ADA, which is associated with higher adjusted mortality risk compared with those with a DA. CDPBF appears to be a rare but important entity in this population.

A framework for longitudinal latent factor modelling of treatment response in clinical trials with applications to Psoriatic Arthritis and Rheumatoid Arthritis.

OBJECTIVE: Clinical trials involve the collection of a wealth of data, comprising multiple diverse measurements performed at baseline and follow-up visits over the course of a trial. The most common primary analysis is restricted to a single, potentially composite endpoint at one time point. While such an analytical focus promotes simple and replicable conclusions, it does not necessarily fully capture the multi-faceted effects of a drug in a complex disease setting. Therefore, to complement existing approaches, we set out here to design a longitudinal multivariate analytical framework that accepts as input an entire clinical trial database, comprising all measurements, patients, and time points across multiple trials. METHODS: Our framework composes probabilistic principal component analysis with a longitudinal linear mixed effects model, thereby enabling clinical interpretation of multivariate results, while handling data missing at random, and incorporating covariates and covariance structure in a computationally efficient and principled way. RESULTS: We illustrate our approach by applying it to four phase III clinical trials of secukinumab in Psoriatic Arthritis (PsA) and Rheumatoid Arthritis (RA). We identify three clinically plausible latent factors that collectively explain 74.5% of empirical variation in the longitudinal patient database. We estimate longitudinal trajectories of these factors, thereby enabling joint characterisation of disease progression and drug effect. We perform benchmarking experiments demonstrating our method's competitive performance at estimating average treatment effects compared to existing statistical and machine learning methods, and showing that our modular approach leads to relatively computationally efficient model fitting. CONCLUSION: Our multivariate longitudinal framework has the potential to illuminate the properties of existing composite endpoint methods, and to enable the development of novel clinical endpoints that provide enhanced and complementary perspectives on treatment response.

Hybrid Stenting of Pulmonary Venous Baffle Stenosis: Subxiphoid Approach in Transposition of the Great Arteries.

A 31-year-old woman with transposition of the great arteries status post-Senning operation presents with severe pulmonary venous baffle obstruction. Both standards of care (percutaneous stenting or open repair) were deemed suboptimal and/or high risk. A multidisciplinary, hybrid approach via subxiphoid incision, guided by 3-dimensional modeling, provided a lower risk and minimally invasive intervention.

Catheterization for Congenital Heart Disease Adjustment for Risk Method II.

BACKGROUND: Current metrics used to adjust for case mix complexity in congenital cardiac catheterization are becoming outdated due to the introduction of novel procedures, innovative technologies, and expanding patient subgroups. This study aims to develop a risk adjustment methodology introducing a novel, clinically meaningful adverse event outcome and incorporating a modern understanding of risk. METHODS: Data from diagnostic only and interventional cases with defined case types were collected for patients ≤18 years of age and ≥2.5 kg at all Congenital Cardiac Catheterization Project on Outcomes participating centers. The derivation data set consisted of cases performed from 2014 to 2017, and the validation data set consisted of cases performed from 2019 to 2020. Severity level 3 adverse events were stratified into 3 tiers by clinical impact (3a/b/c); the study outcome was clinically meaningful adverse events, severity level ≥3b (3bc/4/5). RESULTS: The derivation data set contained 15 224 cases, and the validation data set included 9462 cases. Clinically meaningful adverse event rates were 4.5% and 4.2% in the derivation and validation cohorts, respectively. The final risk adjustment model included age <30 days, Procedural Risk in Congenital Cardiac Catheterization risk category, and hemodynamic vulnerability score (C statistic, 0.70; Hosmer-Lemeshow P value, 0.83; Brier score, 0.042). CONCLUSIONS: CHARM II (Congenital Heart Disease Adjustment for Risk Method II) risk adjustment methodology allows for equitable comparison of clinically meaningful adverse events among institutions and operators with varying patient populations and case mix complexity performing pediatric cardiac catheterization.

Wastewater-based surveillance models for COVID-19: A focused review on spatio-temporal models.

The evident shedding of the SARS-CoV-2 RNA particles from infected individuals into the wastewater opened up a tantalizing array of possibilities for prediction of COVID-19 prevalence prior to symptomatic case identification through community testing. Many countries have therefore explored the use of wastewater metrics as a surveillance tool, replacing traditional direct measurement of prevalence with cost-effective approaches based on SARS-CoV-2 RNA concentrations in wastewater samples. Two important aspects in building prediction models are: time over which the prediction occurs and space for which the predicted case numbers is shown. In this review, our main focus was on finding mathematical models which take into the account both the time-varying and spatial nature of wastewater-based metrics into account. We used six main characteristics as our assessment criteria: i) modelling approach; ii) temporal coverage; iii) spatial coverage; iv) sample size; v) wastewater sampling method; and vi) covariates included in the modelling. The majority of studies in the early phases of the pandemic recognized the temporal association of SARS-CoV-2 RNA concentration level in wastewater with the number of COVID-19 cases, ignoring their spatial context. We examined 15 studies up to April 2023, focusing on models considering both temporal and spatial aspects of wastewater metrics. Most early studies correlated temporal SARS-CoV-2 RNA levels with COVID-19 cases but overlooked spatial factors. Linear regression and SEIR models were commonly used (n = 10, 66.6 % of studies), along with machine learning (n = 1, 6.6 %) and Bayesian approaches (n = 1, 6.6 %) in some cases. Three studies employed spatio-temporal modelling approach (n = 3, 20.0 %). We conclude that the development, validation and calibration of further spatio-temporally explicit models should be done in parallel with the advancement of wastewater metrics before the potential of wastewater as a surveillance tool can be fully realised.

Pulmonary Artery Hypoplasia in Neonates With Tetralogy of Fallot.

BACKGROUND: Neonates with symptomatic tetralogy of Fallot (sTOF) with hypoplastic pulmonary arteries (hPA) are considered high risk. Data are needed to inform the impact of hPA on outcomes, and the ideal management strategy. OBJECTIVES: The objectives of this study were to quantify the impact of hPA on outcomes in neonates with sTOF and measure the impact of strategy on pulmonary artery (PA) growth in this population. METHODS: Neonates with sTOF from 2005 to 2017 were reviewed from the Congenital Cardiac Research Collaborative. Criteria for hPA included a unilateral PA z score <-2.0 and contralateral PA z score <0. Primary outcome was mortality. Secondary outcomes included reintervention and PA growth. RESULTS: We included 542 neonates with sTOF, including 188 (35%) with hPA and 354 (65%) with normal PA, with median follow-up of 4.1 years. Median right and left hPA z scores were -2.19 (25th-75th percentile: -2.55 to -1.94) and -2.23 (25th-75th percentile: -2.64 to -1.91), respectively. Staged repair (vs primary TOF repair) was less common in the hPA cohort (36 vs 44%; P = 0.07). Survival was similar between groups (unadjusted P = 0.16; adjusted P = 0.25). Reintervention was more common in the hPA group (HR: 1.28; 95% CI: 1.01-1.63; P = 0.044); there was no difference after definitive repair (HR: 1.21; 95% CI: 0.93-1.58; P = 0.16). PA growth at 1 year was greater in the hPA cohort, particularly for the right PA (P < 0.001). CONCLUSIONS: Despite perception, the presence of hPA in neonates with sTOF conferred no increase in overall hazard of mortality or reintervention after definitive repair. PA growth was superior in the hPA cohort. These findings suggest that the presence of hPA does not adversely impact outcomes in sTOF.

Comparison of treatment strategies for neonates with tetralogy of Fallot and pulmonary atresia.

OBJECTIVE: Neonates with tetralogy of Fallot and pulmonary atresia (TOF/PA) but no major aorta-pulmonary collaterals are dependent on the arterial duct for pulmonary blood flow and require early intervention, either by primary (PR) or staged repair (SR) with initial palliation (IP) followed by complete repair (CR). The optimal approach has not been established. METHODS: Neonates with TOF/PA who underwent PR or SR were retrospectively reviewed from the Congenital Cardiac Research Collaborative. Outcomes were compared between PR and SR (IP + CR) strategies. Propensity scoring was used to adjust for baseline differences. The primary outcome was mortality. Secondary outcomes included complications, length of stay, cardiopulmonary bypass and anesthesia times, reintervention (RI), and pulmonary artery (PA) growth. RESULTS: Of 282 neonates, 106 underwent PR and 176 underwent SR (IP: 144 surgical, 32 transcatheter). Patients who underwent SR were more likely to have DiGeorge syndrome and greater rates of mechanical ventilation before the initial intervention. Mortality was not significantly different. Duration of mechanical ventilation, inotrope use, and complication rates were similar. Cumulative length of stay, cardiopulmonary bypass, and anesthesia times favored PR (P ≤ .001). Early RI was more common in patients who underwent SR (rate ratio, 1.42; P = .003) but was similar after CR (P = .837). Conduit size at the time of CR was larger with SR. Right PA growth was greater with PR. CONCLUSIONS: In neonates with TOF/PA, SR is more common in greater-risk patients. Accounting for this, SR and PR strategies have similar mortality. Perioperative morbidities, RI, and right PA growth generally favor PR, whereas SR allows for larger initial conduit implantation.

A spatio-temporal framework for modelling wastewater concentration during the COVID-19 pandemic.

The potential utility of wastewater-based epidemiology as an early warning tool has been explored widely across the globe during the current COVID-19 pandemic. Methods to detect the presence of SARS-CoV-2 RNA in wastewater were developed early in the pandemic, and extensive work has been conducted to evaluate the relationship between viral concentration and COVID-19 case numbers at the catchment areas of sewage treatment works (STWs) over time. However, no attempt has been made to develop a model that predicts wastewater concentration at fine spatio-temporal resolutions covering an entire country, a necessary step towards using wastewater monitoring for the early detection of local outbreaks. We consider weekly averages of flow-normalised viral concentration, reported as the number of SARS-CoV-2N1 gene copies per litre (gc/L) of wastewater available at 303 STWs over the period between 1 June 2021 and 30 March 2022. We specify a spatially continuous statistical model that quantifies the relationship between weekly viral concentration and a collection of covariates covering socio-demographics, land cover and virus associated genomic characteristics at STW catchment areas while accounting for spatial and temporal correlation. We evaluate the model's predictive performance at the catchment level through 10-fold cross-validation. We predict the weekly viral concentration at the population-weighted centroid of the 32,844 lower super output areas (LSOAs) in England, then aggregate these LSOA predictions to the Lower Tier Local Authority level (LTLA), a geography that is more relevant to public health policy-making. We also use the model outputs to quantify the probability of local changes of direction (increases or decreases) in viral concentration over short periods (e.g. two consecutive weeks). The proposed statistical framework can predict SARS-CoV-2 viral concentration in wastewater at high spatio-temporal resolution across England. Additionally, the probabilistic quantification of local changes can be used as an early warning tool for public health surveillance.

The genetic architecture of changes in adiposity during adulthood.

Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 1.5 million primary-care health records in over 177,000 individuals in UK Biobank to study the genetic architecture of weight-change. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (a missense variant in APOE). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI, and higher in women than in men. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology driving quantitative trait values in adulthood.

Early Postoperative Congenital Cardiac Catheterization Outcomes: A Multicenter Study.

BACKGROUND: Early postoperative catheterizations (EPOCs) within 6 weeks after a congenital heart surgical procedure can treat residual lesions and provide important clinical information. However, EPOCs are often assumed to impose additional risk on a vulnerable patient population. This study aimed to describe the EPOC population, evaluate procedural safety, compare EPOC patients with procedure-matched non-EPOC patients, and determine risk factors for poor outcomes using data from the Congenital Cardiac Catheterization Project on Outcomes registry. METHODS: In a retrospective cohort, demographic, clinical, and procedural characteristics were analyzed for diagnostic and interventional catheterizations performed in 13 participating institutions from January 2014 to December 2017, excluding patients after heart transplant. The primary outcome was a high-severity adverse event (AE). Three distinct analyses included (1) describing the full cohort and EPOC patients, (2) comparing EPOC patients with and without a high-severity AE, and (3) comparing EPOC patients with controls matched on case type. RESULTS: This study included 17,776 catheterizations, with 1399 EPOCs. The high-severity AE rate was 6.4% overall, 8.9% in the EPOC cohort, and 8.4% in matched controls (P = .74). The association between EPOC status and high-severity AE was not significant in a multivariable model (P = .17). In EPOCs with a high-severity AE, median procedure duration was 30 minutes longer (P < .001), and median time from surgical procedure to catheterization was 3 days longer (P = .05). CONCLUSIONS: EPOC was not associated with additional risk. Individual patient characteristics of size and hemodynamic vulnerability may serve as informative predictors. Timely catheterization may preempt further clinical deterioration, and intraprocedure duration optimization may correlate with improved outcomes.

Severe aortopulmonary collaterals are associated with lower transplant-free survival in patients undergoing staged single ventricle palliation.

Objective: To identify risk factors for aortopulmonary collateral (APC) development and assess the impact of severe APCs in children undergoing staged single ventricle palliation. Methods: Children undergoing a bidirectional Glenn operation between January 1, 2016, and March 31, 2021, at our center were included. All underwent angiography prior to Glenn and Fontan; APC flow was graded on a scale of 0 (no appreciable collateral flow) to 4 (severe burden). Demographic data, congenital diagnosis, clinical history, and outcomes were stratified by Glenn assessment; Fontan outcomes were stratified by pre-Fontan grade. Results: Sixty patients met the inclusion criteria, all of whom had angiographic evidence of APCs. There were 7 transplants and 9 deaths in the cohort. There were no significant differences in demographics among the patients. Right ventricular morphology was more common in patients with severe pre-Glenn collaterals (24 of 44 vs 2 of 6 vs 7 of 8; P = .014). Longer stage 1 aortic cross-clamp duration was associated with greater severity pre-Glenn (44 minutes vs 34 minutes vs 66 minutes; P = .023). Patients with grade 3 pre-Glenn collaterals more commonly required transplantation than those with grade 1 collaterals (P < .001) and had lower overall transplant-free survival than those with grade 1 (P = .005) or grade 2 (P = .04) collaterals. Conclusions: The ubiquity of APCs in this study demonstrates their prevalence in single ventricle disease. Right ventricular morphology and prolonged aortic cross-clamp duration are associated with higher burden. Greater severity was associated with decreased transplant-free survival. These data emphasize the negative long-term impact of these collaterals.

Changes in Practice/Outcomes of Pediatric/Congenital Catheterization in Response to the First Wave of COVID.

Background: The COVID-19 pandemic has posed tremendous stress on the health care system. Its effects on pediatric/congenital catheterization program practice and performance have not been described. Objectives: The purpose of this study was to evaluate how case volumes, risk-profile, and outcomes of pediatric/congenital catheterization procedures changed in response to the first wave of COVID-19 and after that wave. Methods: A multicenter retrospective observational study was performed using Congenital Cardiac Catheterization Project on Outcomes Registry (C3PO) data to study changes in volume, case mix, and outcomes (high-severity adverse events [HSAEs]) during the first wave of COVID (March 1, 2020, to May 31, 2020) in comparison to the period prior to (January 1, 2019, to February 28, 2020) and after (June 1, 2020, to December 31, 2020) the first wave. Multivariable analyses adjusting for case type, hemodynamic vulnerability, and age group were performed. Hospital responses to the first wave were captured with an electronic study instrument. Results: During the study period, 12,557 cases were performed at 14 C3PO hospitals (with 8% performed during the first wave of COVID and 32% in the postperiod). Center case volumes decreased from a median 32.1 cases/month (IQR: 20.7-49.0 cases/month) before COVID to 22 cases/month (IQR: 13-31 cases/month) during the first wave (P = 0.001). The proportion of cases with risk factors for HSAE increased during the first wave, specifically proportions of infants and neonates (P < 0.001) and subjects with renal insufficiency (P = 0.02), recent cardiac surgery (P < 0.001), and a higher hemodynamic vulnerability score (P = 0.02). The observed HSAE risk did not change significantly (P = 0.13). In multivariable analyses, odds of HSAE during the first wave of COVID (odds ratio: 0.75) appeared to be lower than that before COVID, but the difference was not significant (P = 0.09). Conclusions: Despite increased case-mix complexity, C3PO programs maintained, if not improved, their performance in terms of HSAE. Exploratory analyses of practice changes may inform future harm-reduction efforts.

Multivariate phenotype analysis enables genome-wide inference of mammalian gene function.

The function of the majority of genes in the human and mouse genomes is unknown. Investigating and illuminating this dark genome is a major challenge for the biomedical sciences. The International Mouse Phenotyping Consortium (IMPC) is addressing this through the generation and broad-based phenotyping of a knockout (KO) mouse line for every protein-coding gene, producing a multidimensional data set that underlies a genome-wide annotation map from genes to phenotypes. Here, we develop a multivariate (MV) statistical approach and apply it to IMPC data comprising 148 phenotypes measured across 4,548 KO lines. There are 4,256 (1.4% of 302,997 observed data measurements) hits called by the univariate (UV) model analysing each phenotype separately, compared to 31,843 (10.5%) hits in the observed data results of the MV model, corresponding to an estimated 7.5-fold increase in power of the MV model relative to the UV model. One key property of the data set is its 55.0% rate of missingness, resulting from quality control filters and incomplete measurement of some KO lines. This raises the question of whether it is possible to infer perturbations at phenotype-gene pairs at which data are not available, i.e., to infer some in vivo effects using statistical analysis rather than experimentation. We demonstrate that, even at missing phenotypes, the MV model can detect perturbations with power comparable to the single-phenotype analysis, thereby filling in the complete gene-phenotype map with good sensitivity. A factor analysis of the MV model's fitted covariance structure identifies 20 clusters of phenotypes, with each cluster tending to be perturbed collectively. These factors cumulatively explain 75% of the KO-induced variation in the data and facilitate biological interpretation of perturbations. We also demonstrate that the MV approach strengthens the correspondence between IMPC phenotypes and existing gene annotation databases. Analysis of a subset of KO lines measured in replicate across multiple laboratories confirms that the MV model increases power with high replicability.

Interoperability of statistical models in pandemic preparedness: principles and reality.

We present interoperability as a guiding framework for statistical modelling to assist policy makers asking multiple questions using diverse datasets in the face of an evolving pandemic response. Interoperability provides an important set of principles for future pandemic preparedness, through the joint design and deployment of adaptable systems of statistical models for disease surveillance using probabilistic reasoning. We illustrate this through case studies for inferring and characterising spatial-temporal prevalence and reproduction numbers of SARS-CoV-2 infections in England.

Impact of Management Strategy on Feeding and Somatic Growth in Neonates with Symptomatic Tetralogy of Fallot: Results from the Congenital Cardiac Research Collaborative.

OBJECTIVE: To evaluate early growth following primary or staged repair of neonatal symptomatic tetralogy of Fallot (sTOF). STUDY DESIGN: We performed a retrospective, multicenter cohort study of consecutive infants with sTOF who underwent initial intervention at age ≤30 days, from 2005 to 2017. Management strategies were either primary repair or staged repair (ie, initial palliation followed by complete repair). The primary outcome was change in weight-for-age z-score (ΔWAZ) from the initial intervention to age 6 ± 2 months. Secondary outcomes included method and mode of feeding, feeding-related medications, and feeding-related readmissions. Propensity score adjustment was used to account for baseline differences between groups. A secondary analysis was performed comparing patients stratified by the presence of adequate growth (6-month ΔWAZ > -0.5) or inadequate growth (6-month ΔWAZ ≤ -0.5), independent of treatment strategy. RESULTS: The study cohort included 143 primary repair subjects and 240 staged repair subjects. Prematurity was more common in the staged repair group. After adjustment, median ΔWAZ did not differ between treatment groups over the first 6 months of life (primary: -0.43 [IQR, -1.17 to 0.50]; staged: -0.31 [IQR, -1.31 to 0.71]; P = .55). For the entire cohort, ΔWAZ was negative (-0.36; IQR, -1.21 to 0.63). There were no between-group differences in the secondary outcomes. Secondary analysis revealed that the subjects with adequate growth were more likely to be orally fed at initial hospital discharge (P = .04). CONCLUSIONS: In neonates with sTOF, growth trajectory over the first 6 months of life was substandard, irrespective of treatment strategy. Those patients with adequate growth were more likely to be discharged from the index procedure on oral feeds.

The COVID-19 Pandemic Is Associated with Reduced Survival after Pancreatic Ductal Adenocarcinoma Diagnosis: A Single-Centre Retrospective Analysis.

The COVID-19 pandemic has hugely disrupted healthcare provision, including oncology services. To evaluate the effects of the pandemic on referral routes leading to diagnosis, treatments, and prognosis in patients with pancreatic ductal adenocarcinoma, we performed a retrospective cohort study at a single tertiary centre in the UK. The patients were identified from the weekly hepatopancreatobiliary multidisciplinary team meetings between February 2018 and March 2021. The demographic, referral, and treatment data for each patient and date of death, where applicable, were extracted from the electronic patient record. The patients (n = 203) were divided into "pre-pandemic" and "pandemic" cohorts based on a referral date cut-off of 23rd March 2020. The median survival was 7.4 months [4.9-9.3] in the "pre-pandemic" cohort (n = 125), halving to 3.3 months [2.2-6.0], (p = 0.015) in the "pandemic" cohort (n = 78). There was no significant difference in patient characteristics between the two cohorts. There was a trend toward increased emergency presentations at diagnosis and reduced use of surgical resection in the "pandemic" cohort. This small-scale study suggested that the COVID-19 pandemic is associated with a halving of median survival in pancreatic ductal adenocarcinoma. Urgent further studies are required to confirm these findings and examine corresponding effects in other cancer types.

Bayesian imputation of COVID-19 positive test counts for nowcasting under reporting lag.

Obtaining up to date information on the number of UK COVID-19 regional infections is hampered by the reporting lag in positive test results for people with COVID-19 symptoms. In the UK, for 'Pillar 2' swab tests for those showing symptoms, it can take up to five days for results to be collated. We make use of the stability of the under reporting process over time to motivate a statistical temporal model that infers the final total count given the partial count information as it arrives. We adopt a Bayesian approach that provides for subjective priors on parameters and a hierarchical structure for an underlying latent intensity process for the infection counts. This results in a smoothed time-series representation nowcasting the expected number of daily counts of positive tests with uncertainty bands that can be used to aid decision making. Inference is performed using sequential Monte Carlo.