Patient navigator's role in latent tuberculosis infection at a New York City Health Department Chest Clinic

Background

Philippines is one of the top ten countries of birth among individuals with tuberculosis in New York City (NYC). The NYC Health Department (HD) screened Filipino-born New Yorkers for latent TB infection (LTBI), but few of those tested positive completed evaluation and treatment.

Objective

To increase the proportion of Filipinos with a positive QuantiFeron-TB Gold Plus (QFT-Plus) complete LTBI evaluation and treatment.

Methods

Nine community-based LTBI screening events were conducted during September-December 2021. Patients with positive QFT-Plus results were offered no-cost LTBI evaluation and treatment at HD Chest Clinic. The HD engaged culturally- and linguistically-competent Filipino patient navigators (PN) to facilitate LTBI evaluation and treatment.

Results

Of 77 Filipinos screened, 17 (22%) tested positive. Fourteen (82%) were evaluated for LTBI; eight of the 14 (57%) completed LTBI treatment.

Conclusions

Pairing patients with culturally- and linguistically- competent Filipino PNs contributed to an increase in the proportion of Filipinos with a positive QFT-Plus who completed LTBI evaluation and treatment. TB prevention programs may wish to consider PNs in LTBI patient care.

Vesical Imaging-Reporting and Data System (VI-RADS) as a grouping imaging biomarker combined with a decision-tree mode to preoperatively predict the pathological grade of bladder cancer

AIM

To investigate whether the Vesical Imaging-Reporting and Data System (VI-RADS) could be used to develop a new non-invasive preoperative grade-prediction system to partially predict high-grade bladder cancer (HG-BC).

MATERIALS AND METHODS

The present study enrolled 89 primary BC patients prospectively from March 2022 to June 2023. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of VI-RADS for predicting HG-BC and muscle-invasive bladder cancer (MIBC) in the entire group. In the low VI-RADS (≤2) group, the decision tree-based method was used to obtain significant predictors and construct the decision-tree model (DT model). The performance of the DT model and low VI-RADS scores for predicting HG-BC was determined using ROC, calibration, and decision curve analyses.

RESULTS

At a cut-off of ≥3, the specificity and positive predictive value of VI-RADS for predicting HG-BC in the entire group was 100%, and the area under the ROC curve (AUC) was 0.697. Among 65 patients with low VI-RADS scores, the DT model showed an AUC of 0.884 in predicting HG-BC compared to 0.506 for low VI-RADS scores. Calibration and decision curve analyses showed that the DT model performed better than the low VI-RADS scores.

CONCLUSION

Most VI-RADS scores ≥3 correspond to HG-BCs. VI-RADS could be used as a grouping imaging biomarker for a pathological grade-prediction procedure, which in combination with the DT model for low VI-RADS (≤2) populations, would provide a potential preoperative non-invasive method of predicting HG-BC.

Phase II trial of domatinostat (4SC-202) in combination with avelumab in patients with previously treated advanced mismatch repair proficient oesophagogastric and colorectal adenocarcinoma: EMERGE

BACKGROUND

Most oesophagogastric adenocarcinomas (OGAs) and colorectal cancers (CRCs) are mismatch repair proficient (MMRp), responding poorly to immune checkpoint inhibition. We evaluated the safety and efficacy of domatinostat (histone deacetylase inhibitor) plus avelumab (anti-PD-L1 antibody) in patients with previously treated inoperable, advanced/metastatic MMRp OGA and CRC.

PATIENTS AND METHODS

Eligible patients were evaluated in a multicentre, open-label dose escalation/dose expansion phase II trial. In the escalation phase, patients received escalating doses of domatinostat [100 mg once daily (OD), 200 mg OD, 200 mg twice daily (BD)] orally for 14 days followed by continuous dosing plus avelumab 10 mg/kg administered intravenously 2-weekly (2qw) to determine the recommended phase II dose (RP2D). The trial expansion phase evaluated the best objective response rate (ORR) during 6 months by RECIST version 1.1 using a Simon two-stage optimal design with 2/9 and 1/10 responses required to proceed to stage 2 in the OGA and CRC cohorts, respectively.

RESULTS

Patients (n = 40) were registered between February 2019 and October 2021. Patients in the dose escalation phase (n = 12) were evaluated to confirm the RP2D of domatinostat 200 mg BD plus avelumab 10 mg/kg. No dose-limiting toxicities were observed. Twenty-one patients were treated at the RP2D, 19 (9 OGA and 10 CRC) were assessable for the best ORR; 2 patients with CRC did not receive combination treatment and were not assessable for the primary endpoint analysis. Six patients were evaluated in the dose escalation and expansion phases. In the OGA cohort, the best ORR was 22.2% (95% one-sided confidence interval lower bound 4.1) and the median duration of disease control was 11.3 months (range 9.9-12.7 months). No responses were observed in the CRC cohort. No treatment-related grade 3-4 adverse events were reported at the RP2D.

CONCLUSIONS

Responses in the OGA cohort met the criteria to expand to stage 2 of recruitment with an acceptable safety profile. There was insufficient signal in the CRC cohort to progress to stage 2.

TRIAL REGISTRATION

NCT03812796 (registered 23rd January 2019).

Targeted-BEHRT: Deep Learning for Observational Causal Inference on Longitudinal Electronic Health Records

Observational causal inference is useful for decision-making in medicine when randomized clinical trials (RCTs) are infeasible or nongeneralizable. However, traditional approaches do not always deliver unconfounded causal conclusions in practice. The rise of "doubly robust" nonparametric tools coupled with the growth of deep learning for capturing rich representations of multimodal data offers a unique opportunity to develop and test such models for causal inference on comprehensive electronic health records (EHRs). In this article, we investigate causal modeling of an RCT-established causal association: the effect of classes of antihypertensive on incident cancer risk. We develop a transformer-based model, targeted bidirectional EHR transformer (T-BEHRT) coupled with doubly robust estimation to estimate average risk ratio (RR). We compare our model to benchmark statistical and deep learning models for causal inference in multiple experiments on semi-synthetic derivations of our dataset with various types and intensities of confounding. In order to further test the reliability of our approach, we test our model on situations of limited data. We find that our model provides more accurate estimates of relative risk [least sum absolute error (SAE) from ground truth] compared with benchmark estimations. Finally, our model provides an estimate of class-wise antihypertensive effect on cancer risk that is consistent with results derived from RCTs.

Gout and incidence of 12 cardiovascular diseases: a case-control study including 152 663 individuals with gout and 709 981 matched controls

BACKGROUND

Gout, a common crystal arthropathy, is associated with increased risk of cardiovascular disease. We aimed to identify how this risk varies by individual cardiovascular disease across a broad spectrum of conditions.

METHODS

In this matched case-control study, we used linked primary and secondary electronic health records from the UK Clinical Practice Research Datalink to assemble a cohort of individuals with a first-time diagnosis of gout between Jan 1, 2000 and Dec 31, 2017, who were aged 80 years or younger at diagnosis, and free of cardiovascular diseases up to 12 months after diagnosis. The control cohort comprised up to five control individuals per patient with gout, matched on age, sex, socioeconomic status, geographical region, and calendar time, randomly selected among individuals free of gout at any time before and during the study period. The cohorts were followed up until June 30, 2019. We investigated the incidence of 12 cardiovascular diseases and used Cox proportional hazards models to examine differences in people with and without gout, overall and by subgroups of sex, age, socioeconomic status, and year of study inclusion. We further adjusted models for known cardiovascular risk factors (blood pressure, BMI, smoking status, cholesterol, type 2 diabetes, chronic kidney disease, and history of hypertension).

FINDINGS

We identified 152 663 individuals with gout (mean age 56·2 years [SD 13·3]; 120 324 [78·8%] men and 32 339 [21·2%] women) and 709 981 matched controls (mean age 56·5 years [13·2]; 561 002 [79·0%] men and 148 979 [21·0%] women). Of these individuals, 31 479 (20·6%) with gout and 106 520 (15·0%) without gout developed cardiovascular disease during a median follow-up of 6·5 years (IQR 3·1-10·5). Patients with gout had higher risk of cardiovascular diseases than matched controls (hazard ratio [HR] 1·58 [95% CI 1·52-1·63]). Excess risk of cardiovascular disease in gout was greater in women than men (women: HR 1·88 [1·75-2·02]; men: HR 1·49 [1·43-1·56]), and, among all age groups, was highest in younger individuals (HR in people aged <45 years: 2·22 [1·92-2·57]). Excess risk was observed across all 12 cardiovascular diseases investigated. Patients with gout had higher BMI than matched controls (mean difference 2·90 kg/m2 [95% CI 2·87-2·93]) and higher prevalence of chronic kidney disease, dyslipidaemia, history of hypertension, obesity, and type 2 diabetes. Adjusting for known cardiovascular risk factors attenuated but did not eliminate the excess risk of cardiovascular disease related to gout (adjusted HR 1·31 [1·27-1·36]).

INTERPRETATION

Patients with gout had an excess risk of developing a broad range of cardiovascular diseases that extend beyond atherosclerotic diseases and include heart failure, arrhythmias, valve disease, and thromboembolic diseases. Excess risk was highest in women and younger individuals. These findings suggest that strategies to reduce cardiovascular risk in patients with gout need to evolve and be implemented in clinical practice.

FUNDING

Research Foundation Flanders.

Efficacy of decentralised home-based antihypertensive treatment in older adults with multimorbidity and polypharmacy (ATEMPT): an open-label randomised controlled pilot trial

BACKGROUND

Older patients with multimorbidity and polypharmacy have been under-represented in clinical trials. We aimed to assess the effect of different intensities of antihypertensive treatment on changes in blood pressure, major safety outcomes, and patient-reported outcomes in this population.

METHODS

ATEMPT was a decentralised, two-armed, parallel-group, open-label randomised controlled pilot trial conducted in the Thames Valley area, South East England. Individuals aged 65 years or older with multimorbidity (three or more chronic conditions) or polypharmacy (five or more types of medications) and a systolic blood pressure of 115-165 mm Hg were eligible for inclusion. Participants were identified through a search of national hospital discharge databases, identification of patients registered with an online pharmacy, and via targeted advertising on social media platforms. Participants were randomly assigned to receive up to two more classes versus up to two fewer classes of antihypertensive medications. Apart from routine home visits for conducting the baseline assessment, all communication, monitoring, and management of participants by the trial team was conducted remotely. The primary outcome was change in home-measured blood pressure.

FINDINGS

Between Dec 15, 2020, and Aug 31, 2022, 230 participants were randomly assigned (n=126 to more vs n=104 to fewer antihypertensive medications). The frequency of serious adverse events was similar across both groups; no cardiovascular events occurred in the more antihypertensive drugs group, compared with six in the fewer antihypertensive drugs group, of which two were fatal. Over a 13-month follow-up period, the mean systolic blood pressure in the group allocated to receive more antihypertensive medications decreased from 134·5 mm Hg (SD 10·7) at baseline to 122·1 mm Hg (10·5). By contrast, in the group allocated to receive fewer antihypertensive medications, it remained relatively unchanged, moving from 134·8 mm Hg (SD 11·2) at baseline to 132·9 mm Hg (15·3); this corresponded to a mean difference of -10·7 mm Hg (95% CI -17·5 to -4·0).

INTERPRETATION

Remotely delivered antihypertensive treatment substantially reduced systolic blood pressure in older adults who are often less represented in trials, with no increase in the risk of serious adverse events. The results of this trial will inform a larger clinical trial focusing on assessing major cardiovascular events, safety, physical functioning, and cognitive function that is currently in the planning stages. These results also underscore the efficiency of decentralised trial designs, which might be of broader interest in other settings.

FUNDING

National Institute for Health Research Oxford Biomedical Research Centre and the Oxford Martin School.

Sodium-based paracetamol: impact on blood pressure, cardiovascular events, and all-cause mortality

BACKGROUND AND AIMS

Effervescent formulations of paracetamol containing sodium bicarbonate have been reported to associate with increased blood pressure and a higher risk of cardiovascular diseases and all-cause mortality. Given the major implications of these findings, the reported associations were re-examined.

METHODS

Using linked electronic health records data, a cohort of 475 442 UK individuals with at least one prescription of paracetamol, aged between 60 and 90 years, was identified. Outcomes in patients taking sodium-based paracetamol were compared with those taking non-sodium-based formulations of the same. Using a deep learning approach, associations with systolic blood pressure (SBP), major cardiovascular events (myocardial infarction, heart failure, and stroke), and all-cause mortality within 1 year after baseline were investigated.

RESULTS

A total of 460 980 and 14 462 patients were identified for the non-sodium-based and sodium-based paracetamol exposure groups, respectively (mean age: 74 years; 64% women). Analysis revealed no difference in SBP [mean difference -0.04 mmHg (95% confidence interval -0.51, 0.43)] and no association with major cardiovascular events [relative risk (RR) 1.03 (0.91, 1.16)]. Sodium-based paracetamol showed a positive association with all-cause mortality [RR 1.46 (1.40, 1.52)]. However, after further accounting of other sources of residual confounding, the observed association attenuated towards the null [RR 1.08 (1.01, 1.16)]. Exploratory analyses revealed dysphagia and related conditions as major sources of uncontrolled confounding by indication for this association.

CONCLUSIONS

This study does not support previous suggestions of increased SBP and an elevated risk of cardiovascular events from short-term use of sodium bicarbonate paracetamol in routine clinical practice.

Benefits of routine probiotic supplementation in preterm infants

AIM

We introduced routine probiotic supplementation (RPS) of preterm infants in June 2012. We previously reported that RPS reduced the incidence of necrotising enterocolitis (NEC) and mortality in such infants. In this study, we assessed if the benefits of RPS were sustained for infants in the current era.

METHOD

We compared the outcomes of preterm infants in recent epoch 3 (RPS, 1st June 2014 to 31st December 2019) versus epoch 2 (RPS, 1st June 2012 to 31st May 2014) and epoch 1 (no RPS, 1st December 2008 to 30th November 2010). Multiple logistic and Cox regression models were used to compare the outcomes.

RESULTS

There were 645 infants in epoch 1, 712 in epoch 2 and 1715 in epoch 3. Age at full feeds was significantly lower in epoch 3 vs. 2 and epoch 3 vs. 1 in infants <28 weeks of gestation. NEC and late-onset sepsis (LOS) were significantly lower in epoch 3 vs. 1 in infants <28 weeks. LOS and age at full feeds were significantly lower in epoch 3 vs. 2 and epoch 3 vs. 1 in infants with gestation 28 to 32 weeks.

CONCLUSION

The benefits associated with RPS were sustained during epoch 3.

Metabolism-based category formation for the prioritisation of genotoxicity hazard assessment for plant protection product residues (part 3): Strobilurins

In dietary risk assessment of plant protection products, residues of active ingredients and their metabolites need to be evaluated for their genotoxic potential. The European Food Safety Authority recommend a tiered approach focussing assessment and testing on classes of similar chemicals. To characterise similarity, in terms of metabolism, a metabolic similarity profiling scheme has been developed from an analysis of 46 chemicals of strobilurin fungicides and their metabolites for which either Ames, chromosomal aberration or micronucleus test results are publicly available. This profiling scheme consists of a set of ten sub-structures, each linked to a key metabolic transformation present in the strobilurin metabolic space. This metabolic similarity profiling scheme was combined with covalent chemistry profiling and physico-chemistry properties to develop chemical categories suitable for chemical prioritisation via read-across. The method is a robust and reproducible approach to such read-across predictions, with the potential to reduce unnecessary testing. The key challenge in the approach was identified as being the need for metabolism data and individual groups of plant protection products as the basis for the development of such profiling schemes.

A Phase 1 Trial of the Safety, Tolerability, and Biological Effects of Intravenous Enadenotucirev (EnAd), a Novel Oncolytic Virus, in Combination with Chemoradiotherapy in Locally Advanced Rectal Cancer (CEDAR)

PURPOSE/OBJECTIVE(S)

Novel treatment combinations are required to increase response rates in rectal cancer. EnAd is an intravenous, tumor selective, oncolytic adenovirus with high affinity for malignant colorectal epithelial cells. Pre-clinical evidence of synergy with radiation warranted further clinical evaluation and assessment of safety in combination with chemoradiation (CRT), 25 × 2Gy and concurrent capecitabine.

MATERIALS/METHODS

EnAd was escalated using 2 dose levels of viral particles (1 × 1012, 3 × 1012), given Monday, Wednesday, Friday over 3 schedules (pre-CRT, pre & post CRT). Toxicity and efficacy were used as dual end points in escalation decisions. A 2-parameter and 3-parameter logistic Time to Event Continual Reassessment Method (TiTE-CRM) were used estimate the dose-toxicity and dose-efficacy relationship, respectively. Results are shown as probability and 95% credible interval (Cr.I). The dose limiting toxicity (DLT) window was 13 weeks. Patients who had not completed their DLT window at the time of a dose decision were included in the safety analysis but down-weighted according to their follow-up time and amount of IMP received. Efficacy was assessed at 13 weeks using MRI Tumor Regression Grade (mrTRG), where mrTRG 1-2 equals response. The trial (NCT03916510) was conducted in 4 UK centers.

RESULTS

A total of 13 patients were enrolled, 12 of whom were evaluable. Median age was 57 (range 31-84), and 10/13 were male. One patient had two G3 adverse events (AE); diarrhea, acute kidney injury. All other adverse events (AEs) were G1 or 2, with no G4/5 events. The most common AE by organ system was gastrointestinal (20.8%, G1). There were two observed DLTs on Dose schedule 3; leg swelling and acute kidney injury. Responses and toxicities increased with escalating schedules of EnAd (Table 1).

CONCLUSION

CEDAR is the first trial to successfully combine an intravenous oncolytic adenovirus with radiation, demonstrating the feasibility and acceptability of this approach, and a new paradigm in radiosensitization in rectal cancer. Within this small Phase I study, EnAd demonstrated an acceptable safety profile with evidence of a higher-than-expected rate of response by mrTRG. Translation analysis of tissue, blood and microbiome for biological correlates of radiation synergy is underway.

FUNDING

PsiOxus, CRUK (A24474).

SPONSOR

University of Oxford.

Long-Term Exposure to Road Traffic Noise and Incident Heart Failure: Evidence From UK Biobank

BACKGROUND

Evidence on road traffic noise and heart failure (HF) is limited, and little is known on the potential mediation roles of acute myocardial infarction (AMI), hypertension, or diabetes.

OBJECTIVES

The purpose of this study was to evaluate the impacts of long-term road traffic noise exposure on the risk of incident HF considering air pollution, and explore the mediations of the previously mentioned diseases.

METHODS

This prospective study included 424,767 participants without HF at baseline in UK Biobank. The residential-level noise and air pollution exposure was estimated, and the incident HF was identified through linkages with medical records. Cox proportional hazard models were used to estimate HRs. Furthermore, time-dependent mediation was performed.

RESULTS

During a median 12.5 years of follow-up, 12,817 incident HF were ascertained. The HRs were 1.08 (95% CI: 1.00-1.16) per 10 dB[A] increase in weighted average 24-hour road traffic noise level (Lden), and 1.15 (95% CI: 1.02-1.31) for exposure to Lden >65 dB[A] compared with the reference category (Lden ≤55 dB[A]), respectively. Furthermore, the strongest combined effects were found in those with both high exposures to road traffic noise and air pollution including fine particles and nitrogen dioxide. Prior AMI before HF within 2 years' time interval mediated 12.5% of the association of road traffic noise with HF.

CONCLUSIONS

More attention should be paid and a preventive strategy should be considered to alleviate the disease burden of HF related to road traffic noise exposure, especially in participants who survived AMI and developed HF within 2 years.

A comparative study of model-centric and data-centric approaches in the development of cardiovascular disease risk prediction models in the UK Biobank

Aims

A diverse set of factors influence cardiovascular diseases (CVDs), but a systematic investigation of the interplay between these determinants and the contribution of each to CVD incidence prediction is largely missing from the literature. In this study, we leverage one of the most comprehensive biobanks worldwide, the UK Biobank, to investigate the contribution of different risk factor categories to more accurate incidence predictions in the overall population, by sex, different age groups, and ethnicity.

Methods and results

The investigated categories include the history of medical events, behavioural factors, socioeconomic factors, environmental factors, and measurements. We included data from a cohort of 405 257 participants aged 37-73 years and trained various machine learning and deep learning models on different subsets of risk factors to predict CVD incidence. Each of the models was trained on the complete set of predictors and subsets where each category was excluded. The results were benchmarked against QRISK3. The findings highlight that (i) leveraging a more comprehensive medical history substantially improves model performance. Relative to QRISK3, the best performing models improved the discrimination by 3.78% and improved precision by 1.80%. (ii) Both model- and data-centric approaches are necessary to improve predictive performance. The benefits of using a comprehensive history of diseases were far more pronounced when a neural sequence model, BEHRT, was used. This highlights the importance of the temporality of medical events that existing clinical risk models fail to capture. (iii) Besides the history of diseases, socioeconomic factors and measurements had small but significant independent contributions to the predictive performance.

Conclusion

These findings emphasize the need for considering broad determinants and novel modelling approaches to enhance CVD incidence prediction.

Systolic blood pressure, chronic obstructive pulmonary disease and cardiovascular risk

OBJECTIVE

In individuals with complex underlying health problems, the association between systolic blood pressure (SBP) and cardiovascular disease is less well recognised. The association between SBP and risk of cardiovascular events in patients with chronic obstructive pulmonary disease (COPD) was investigated.

METHODS AND ANALYSIS

In this cohort study, 39 602 individuals with a diagnosis of COPD aged 55-90 years between 1990 and 2009 were identified from validated electronic health records (EHR) in the UK. The association between SBP and risk of cardiovascular end points (composite of ischaemic heart disease, heart failure, stroke and cardiovascular death) was analysed using a deep learning approach.

RESULTS

In the selected cohort (46.5% women, median age 69 years), 10 987 cardiovascular events were observed over a median follow-up period of 3.9 years. The association between SBP and risk of cardiovascular end points was found to be monotonic; the lowest SBP exposure group of <120 mm Hg presented nadir of risk. With respect to reference SBP (between 120 and 129 mm Hg), adjusted risk ratios for the primary outcome were 0.99 (95% CI 0.93 to 1.05) for SBP of <120 mm Hg, 1.02 (0.97 to 1.07) for SBP between 130 and 139 mm Hg, 1.07 (1.01 to 1.12) for SBP between 140 and 149 mm Hg, 1.11 (1.05 to 1.17) for SBP between 150 and 159 mm Hg and 1.16 (1.10 to 1.22) for SBP ≥160 mm Hg.

CONCLUSION

Using deep learning for modelling EHR, we identified a monotonic association between SBP and risk of cardiovascular events in patients with COPD.

Stratification of diabetes in the context of comorbidities, using representation learning and topological data analysis

Diabetes is a heterogenous, multimorbid disorder with a large variation in manifestations, trajectories, and outcomes. The aim of this study is to validate a novel machine learning method for the phenotyping of diabetes in the context of comorbidities. Data from 9967 multimorbid patients with a new diagnosis of diabetes were extracted from Clinical Practice Research Datalink. First, using BEHRT (a transformer-based deep learning architecture), the embeddings corresponding to diabetes were learned. Next, topological data analysis (TDA) was carried out to test how different areas in high-dimensional manifold correspond to different risk profiles. The following endpoints were considered when profiling risk trajectories: major adverse cardiovascular events (MACE), coronary artery disease (CAD), stroke (CVA), heart failure (HF), renal failure (RF), diabetic neuropathy, peripheral arterial disease, reduced visual acuity and all-cause mortality. Kaplan Meier curves were plotted for each derived phenotype. Finally, we tested the performance of an established risk prediction model (QRISK) by adding TDA-derived features. We identified four subgroups of patients with diabetes and divergent comorbidity patterns differing in their risk of future cardiovascular, renal, and other microvascular outcomes. Phenotype 1 (young with chronic inflammatory conditions) and phenotype 2 (young with CAD) included relatively younger patients with diabetes compared to phenotypes 3 (older with hypertension and renal disease) and 4 (older with previous CVA), and those subgroups had a higher frequency of pre-existing cardio-renal diseases. Within ten years of follow-up, 2592 patients (26%) experienced MACE, 2515 patients (25%) died, and 2020 patients (20%) suffered RF. QRISK3 model's AUC was augmented from 67.26% (CI 67.25-67.28%) to 67.67% (CI 67.66-67.69%) by adding specific TDA-derived phenotype and the distances to both extremities of the TDA graph improving its performance in the prediction of CV outcomes. We confirmed the importance of accounting for multimorbidity when risk stratifying heterogenous cohort of patients with new diagnosis of diabetes. Our unsupervised machine learning method improved the prediction of clinical outcomes.

Mediation of metabolic syndrome in the association between long-term co-exposure to road traffic noise, air pollution and incident type 2 diabetes

OBJECTIVES

Recent studies have linked exposure to road traffic noise or air pollution with incident type 2 diabetes (T2D), but investigation on their co-exposure was limited and underlying mechanisms remain unclear. We hypothesized that long-term co-exposure to road traffic noise and air pollution increases the risk of incident T2D via the development of metabolic syndrome (MetS).

METHODS

This prospective study included 390,834 participants in UK Biobank. Cumulative risk index (CRI), the health-based weighted levels of multiple exposures, was applied to characterize the co-exposure to 24-hour road traffic noise (L_den), particulate matter with aerodynamic diameter ≤ 2.5 µm (PM_2.5), and nitrogen dioxide (NO₂). L_den was modeled by the Common Noise Assessment Methods in Europe and air pollutant levels were measured by the Land Use Regression model at participants' residential addresses. Incident T2D was ascertained through linkages to inpatient hospital records. MetS was defined by five (central obesity, triglycerides, HDL cholesterol, glucose, and blood pressure) or six factors (C-reactive protein additionally). Cox proportional hazard models were used to assess the association between environmental exposures and incident T2D, and mediation analyses were applied to investigate the role of MetS.

RESULTS

After a median of 10.9 years of follow-up, 13,214 (3.4%) incident T2D cases were ascertained. The exposure to L_den, PM_2.5, and NO₂, as well as their co-exposure, were significantly associated with an elevated risk of incident T2D, with HRs of 1.03 (95%CI: 1.00, 1.05) per 3.5 dB(A) increase in L_den, 1.05 (95%CI: 1.01, 1.10) per 1.3 μg/m³ increase in PM_2.5, 1.07 (95%CI: 1.02, 1.11) per 9.8 μg/m³ increase in NO₂, and 1.06 (95%CI: 1.02, 1.09) per interquartile range increase in CRI. MetS significantly mediated 43.5%- 54.7% of the CRI-T2D relationship.

CONCLUSIONS

Long-term co-exposure to road traffic noise and air pollution is associated with an elevated risk of incident T2D, which may partly be mediated by MetS.

Development of a novel immobilisation protocol for black-faced impala (Aepyceros melampus ssp. petersi) in Etosha National Park

Black-faced impala (Aepyceros melampus ssp. petersi) are endemic to Namibia where conservation management involves immobilisation and translocation, and mortality with current protocols is common. Critically evaluated field immobilisation protocols are needed to maximise animal safety. This prospective study was done in two phases: the first compared etorphine- and thiafentanil-based combinations, the second evaluated the influence of oxygen in impala receiving the thiafentanil-based combination. Animals (10 per group) received 50 mg ketamine (K) and 10 mg butorphanol (B), with either 2.0 mg etorphine (E) or 2.0 mg thiafentanil (T). A third group of ten impala were anaesthetised using TKB with supplemental nasal oxygen (O) at a rate of 5 L/minute. Behavioural, metabolic and physiological variables were assessed within five minutes of recumbency and at 10, 15, and 20 minutes post-recumbency. Statistical analyses for non-parametric data were performed to compare the treatment groups as well as time points; p ≤ 0.05 considered significant. Following darting, 7/10 EKB animals were standing when approached, compared to 2/20 in the thiafentanil treatment groups. Time to first effect was significantly higher for EKB (155 ± 105.7 seconds) compared to TKBO (61.5 ± 21.4 seconds). Time to sternal after darting was significantly higher with EKB (411.6 ± 174 seconds) compared to TKB (160.5 ± 85.4 seconds) and TKBO (166 ± 77.3 seconds). This study builds on previous work investigating the effects of potent opioids on impala and is the first evaluating their use in a field setting. The thiafentanil combination had a faster onset and resulted in a smoother induction than the etorphine combination. Additionally, oxygenation improved in animals receiving oxygen supplementation.

Radiation dose during interventional cardiology procedures: portable C-arm vs. a new generation fluoroscopy system

INTRODUCTION

Occupational exposure to ionizing radiation poses health risks for veterinary interventionalists. There are limited veterinary studies evaluating radiation dose in the cardiac catheterization laboratory. The purpose of this study was to report direct radiation dose exposure to patients during common interventional cardiology procedures and compare these doses between two fluoroscopy units.

ANIMALS

One hundred and fifty-four client-owned dogs.

MATERIALS AND METHODS

Patient dose during procedures using a portable C-arm were retrospectively analyzed and compared to those performed in a contemporary interventional suite. Fluoroscopy equipment, procedure type, operator, patient weight, fluoroscopy time, dose area product, and air kerma were recorded and statistically modeled using univariable and multivariable linear regression to evaluate the effect of each factor.

RESULTS

Patient dose population (154 dogs), comprised 61 patent ductus arteriosus occlusions, 60 balloon pulmonary valvuloplasties, and 33 pacemaker implantations. Patient dose was significantly lower in the group utilizing a newer generation fluoroscopy unit vs. the group utilizing an older portable C-arm, positively correlated with patient weight, and highest during balloon pulmonary valvuloplasties compared to patent ductus arteriosus occlusions or pacemaker implantations (all p<0.010).

DISCUSSION

Newer fluoroscopy systems can be equipped with technologies that improve image quality while reducing patient dose and radiation exposure to interventional personnel.

CONCLUSIONS

We documented a significant reduction in patient radiation dose using a newer fluoroscopy system as compared to an older portable C-arm for interventional cardiology procedures in animals. Improved knowledge of patient radiation dose factors may promote better radiation safety protocols in veterinary interventional cardiology.

Effectiveness of Preparedness Training Delivered to Pre-final and Final Year Nursing Undergraduates to Combat COVID-19: A Need-based Initiative

A major concern during the COVID-19 pandemic has been the shortage of manpower for patient care. The recommendation of various authorised bodies encouraged the training of students from medical, nursing, and allied fields to manage COVID-19 cases by tele-consultation and monitoring of mild cases under the supervision of faculty. Anticipating a further shortage of human resources, leading to dire consequences, preparedness training for the final year and pre-final nursing undergraduates was initiated. The current study was conducted to evaluate the effectiveness of and feedback on COVID-19 preparedness training delivered to final-and pre-final-year undergraduate nursing students. A 3-day training was given to pre-final and final year nursing undergraduates on ECG, COVID-19 management protocols, personal protective equipment "donning and doffing", "hand hygiene", "biomedical waste management", "contact tracing" and cleaning and disinfection and simulation-based skills. Scores before and after training were conducted and mean scores were compared using a paired t-test. In total, 154 nursing students participated in the training program. Mean pre-test and post-test scores included: general instructions (21.69±2.5 and 25.09±3.29); skill procedures (5.4±1.21 and 6.3±1.2) and COVID management (22.84±3.26 and 26.48±2.06). There was a statistically significant improvement in knowledge and skills in all training sessions (p=0.0001). The mean post-test scores obtained at the OSCE stations for cardiac monitoring, prone positioning, compression-only CPR, airway, ECG and ABG ranged from 97.0% to 100.0% and all participants scored >70.0%. About 92.8% of the students felt that hands-on training enhanced their learning experiences. A need-based initiative of training final-and pre-final-year nursing students in COVID-19 support care effectively and efficiently created a skilled workforce.

Systolic Blood Pressure and Cardiovascular Risk in Patients With Diabetes: A Prospective Cohort Study

BACKGROUND

Whether the association between systolic blood pressure (SBP) and risk of cardiovascular disease is monotonic or whether there is a nadir of optimal blood pressure remains controversial. We investigated the association between SBP and cardiovascular events in patients with diabetes across the full spectrum of SBP.

METHODS

A cohort of 49 000 individuals with diabetes aged 50 to 90 years between 1990 and 2005 was identified from linked electronic health records in the United Kingdom. Associations between SBP and cardiovascular outcomes (ischemic heart disease, heart failure, stroke, and cardiovascular death) were analyzed using a deep learning approach.

RESULTS

Over a median follow-up of 7.3 years, 16 378 cardiovascular events were observed. The relationship between SBP and cardiovascular events followed a monotonic pattern, with the group with the lowest baseline SBP of <120 mm Hg exhibiting the lowest risk of cardiovascular events. In comparison to the reference group with the lowest SBP (<120 mm Hg), the adjusted risk ratio for cardiovascular disease was 1.03 (95% CI, 0.97-1.10) for SBP between 120 and 129 mm Hg, 1.05 (0.99-1.11) for SBP between 130 and 139 mm Hg, 1.08 (1.01-1.15) for SBP between 140 and 149 mm Hg, 1.12 (1.03-1.20) for SBP between 150 and 159 mm Hg, and 1.19 (1.09-1.28) for SBP ≥160 mm Hg.

CONCLUSIONS

Using deep learning modeling, we found a monotonic relationship between SBP and risk of cardiovascular outcomes in patients with diabetes, without evidence of a J-shaped relationship.

Hi-BEHRT: Hierarchical Transformer-Based Model for Accurate Prediction of Clinical Events Using Multimodal Longitudinal Electronic Health Records

Electronic health records (EHR) represent a holistic overview of patients' trajectories. Their increasing availability has fueled new hopes to leverage them and develop accurate risk prediction models for a wide range of diseases. Given the complex interrelationships of medical records and patient outcomes, deep learning models have shown clear merits in achieving this goal. However, a key limitation of current study remains their capacity in processing long sequences, and long sequence modelling and its application in the context of healthcare and EHR remains unexplored. Capturing the whole history of medical encounters is expected to lead to more accurate predictions, but the inclusion of records collected for decades and from multiple resources can inevitably exceed the receptive field of the most existing deep learning architectures. This can result in missing crucial, long-term dependencies. To address this gap, we present Hi-BEHRT, a hierarchical Transformer-based model that can significantly expand the receptive field of Transformers and extract associations from much longer sequences. Using a multimodal large-scale linked longitudinal EHR, the Hi-BEHRT exceeds the state-of-the-art deep learning models 1% to 5% for area under the receiver operating characteristic (AUROC) curve and 1% to 8% for area under the precision recall (AUPRC) curve on average, and 2% to 8% (AUROC) and 2% to 11% (AUPRC) for patients with long medical history for 5-year heart failure, diabetes, chronic kidney disease, and stroke risk prediction. Additionally, because pretraining for hierarchical Transformer is not well-established, we provide an effective end-to-end contrastive pre-training strategy for Hi-BEHRT using EHR, improving its transferability on predicting clinical events with relatively small training dataset.

Validation of risk prediction models applied to longitudinal electronic health record data for the prediction of major cardiovascular events in the presence of data shifts

Aims

Deep learning has dominated predictive modelling across different fields, but in medicine it has been met with mixed reception. In clinical practice, simple, statistical models and risk scores continue to inform cardiovascular disease risk predictions. This is due in part to the knowledge gap about how deep learning models perform in practice when they are subject to dynamic data shifts; a key criterion that common internal validation procedures do not address. We evaluated the performance of a novel deep learning model, BEHRT, under data shifts and compared it with several ML-based and established risk models.

Methods and results

Using linked electronic health records of 1.1 million patients across England aged at least 35 years between 1985 and 2015, we replicated three established statistical models for predicting 5-year risk of incident heart failure, stroke, and coronary heart disease. The results were compared with a widely accepted machine learning model (random forests), and a novel deep learning model (BEHRT). In addition to internal validation, we investigated how data shifts affect model discrimination and calibration. To this end, we tested the models on cohorts from (i) distinct geographical regions; (ii) different periods. Using internal validation, the deep learning models substantially outperformed the best statistical models by 6%, 8%, and 11% in heart failure, stroke, and coronary heart disease, respectively, in terms of the area under the receiver operating characteristic curve.

Conclusion

The performance of all models declined as a result of data shifts; despite this, the deep learning models maintained the best performance in all risk prediction tasks. Updating the model with the latest information can improve discrimination but if the prior distribution changes, the model may remain miscalibrated.

Effects of distal radial access vs conventional radial access in patients undergoing coronary angiography and/or intervention: a meta-analysis of randomised trials

Background

Recently the distal radial access (DRA) technique has been introduced for coronary angiography and intervention as an alternative to the conventional radial access (RA).

Purpose

The aim of this study was to provide a quantitative appraisal of the effects of DRA vs conventional RA for coronary angiography with or without intervention.

Methods

The PubMed, Embase, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov databases were searched for randomised clinical trials (RCT) comparing DRA versus RA for coronary angiography and/or intervention. Data were pooled by meta-analysis using a random-effects model. The number of patients needed to treat for an additional beneficial outcome (NNTB) and the number needed to treat for an additional harmful outcome (NNTH) were calculated. The primary endpoint was radial artery occlusion (RAO) at the longest available follow-up. Additional secondary outcomes were assessed.

Results

A total of 13 RCT including 4,901 patients were identified and included in the final analysis. Coronary angiography alone was performed in 3 studies, percutaneous coronary intervention was performed in a variable proportion of patients ranging from 24% to 100% across studies. Study population included patients with chronic coronary syndrome in the large majority, and the proportion of acute coronary syndrome ranged from to 31% to 100% across studies. Compared with RA, DRA was associated with a significant lower risk of RAO, either detected at the longest follow-up (risk ratio [RR]: 0.36; 95% CI: 0.23 to 0.58; p&lt;0.001, NNTB = 24.5), or in-hospital (RR: 0.32; 95% CI: 0.18 to 0.57; p&lt;0.001, NNTB = 21.5), as well as Early discharge after transradial stenting of coronary arteries (EASY) Scale ≥ II hematoma (RR: 0.46; 95% CI: 0.22 to 0.97; p=0.04, NNTB = 66). By contrast, DRA was associated with a higher risk of access site crossover (RR: 3.43; 95% CI: 1.88 to 6.25, p&lt;0.001, NNTH = 10), a longer time for radial artery puncture (standardized mean difference [SMD]: 3.56; 95% CI: 0.96 to 6.16; p&lt;0.001), and sheath insertion (SMD: 0.38; 95% CI: 0.11 to 0.65, p=0.006), and a higher number of puncture attempts (SMD: 0.59, 95% CI: 0.48 to 0.69, p&lt;0.001). A meta-regression analysis showed that increasing age in the RA group was associated with a reduced effect of DRA, compared with RA, on the risk of RAO. No significant effect of other variables such as the prevalence of female sex, diabetes, smoking status, acute coronary syndrome, and percutaneous coronary intervention was found.

Conclusions

Compared with RA, DRA is associated with lower risks of RAO and EASY ≥ II hematoma, but requires longer time for radial artery puncture and sheath insertion, more puncture attempts and a higher access site crossover.

Funding Acknowledgement

Type of funding sources: None.

Advances in physiological mechanisms of selenium to improve heavy metal stress tolerance in plants

Selenium (Se) is a metalloid mineral nutrient for human and animal health. Plants are the main foodstuff source of the Se intake of humans. For plants, the addition of an appropriate amount of Se could promotes growth and development, and improves the tolerance to environmental stress, especially stress from some of heavy metals (HM) stress, such as cadmium (Cd) and mercury (Hg). This paper mainly reviews and summarizes the physiological mechanism of Se in enhancing HM stress tolerance in plants. The antagonistic effect of Se on HM is a comprehensive effect that includes many physiological mechanisms. Se can promote the removal of excessive reactive oxygen species and reduce the oxidative damage of plant cells under HM elements stress. Se participates in the regulation of the transportation and distribution of HM ions in plants, and alleviates the damage caused by of HM stress. Moreover, Se combine with HM elements to form Se-HM complexes and promote the production of phytochelatins (PCs), thereby reducing the accumulation of HM ions in plants. Overall, Se plays an important role in plant response to HM stress, but current studies mainly focus on physiological mechanism, and further in-depth study on the molecular mechanism is essential to confirm the participation of Se in plant response to environmental stress. This review helps to comprehensively understand the physiological mechanism of Se in plant tolerance against to HM stress of plants, and provides important theoretical support for the practical application of Se in environmental remediation and agricultural development.

Effect of a 2-step probiotic program on digestive health and performance of Holstein heifer calves

Managing the composition of the bacterial communities in the digestive tract with the use of probiotics that enhance protective microflora could result in positive effects on health and performance of calves. The objective of this study was to evaluate a 2-step probiotic program (added to colostrum and milk) on the digestive health and growth of preweaning Holstein heifers. A randomized clinical trial was conducted from July to October 2020 in a calf rearing facility in Colorado. Calves were housed in pairs sharing the same treatment in 2 polyethylene hutches within a common area of 4.50 m². A total of 232 calves were enrolled at birth and randomly allocated into 2 treatment groups [control (CTR) = 116; treatment (PB) = 116] and followed until weaning (64 ± 3 d). Treatment consisted of 2 formulations of a multistrain bacterial-based probiotic added in colostrum (PBF1) and milk (PBF2). Treatment calves received 2 g of PBF1 added to each colostrum feeding, and 1 g of PBF2 added to the milk at the morning feeding 3 times per week up to weaning. Calf weight was collected at birth, at 30 d of age, and at weaning. Serum total protein was determined at age 3 ± 1 d and a health assessment was completed 3 times per week. Statistical analyses were performed using SAS, with calf considered the experimental unit clustered by housing pair. Cox proportional hazard analysis and time to event analysis were used to compare time to the first diarrhea event and time to recovery between treatment groups. The total number of diarrhea events and culling were assessed by Poisson regression and logistic regression analysis, respectively. Linear regression was performed to evaluate differences in average daily gain by treatment group. Overall, the mean (± standard error) temperature humidity index (THI) was 75 (± 0.44) units during the study period, which resulted in continuous exposure to heat stress in the day hours. No difference between treatment groups was observed in serum total protein. The overall incidence of diarrhea was 96.6% (CTR = 99%, PB = 95%); no differences were determined in the hazard of a first diarrhea episode or in the median time to the first diarrhea event (11 d in both groups). Similarly, no differences were found in the likelihood of recovery or in the median time to recovery from diarrhea (7 d in both groups). Likewise, treatment group was not associated with the number of diarrhea events, mean (± standard error, g/d) average daily gain from birth to weaning [CTR = 562.5 (13.9); PB = 570.8 (13.5)], or with the odds of culling. The most prevalent pathogen isolated from feces was Clostridium, which tended to be more frequent in CTR calves than PB calves. In conclusion, the probiotic program did not affect the incidence of enteric disease or the growth of preweaning heifer calves.

A phase II study of retifanlimab (INCMGA00012) in patients with squamous carcinoma of the anal canal who have progressed following platinum-based chemotherapy (POD1UM-202)

Background

Locally advanced or metastatic squamous carcinoma of the anal canal (SCAC) has poor prognosis following platinum-based chemotherapy. Retifanlimab (INCMGA00012), a humanized monoclonal antibody targeting programmed death protein-1 (PD-1), demonstrated clinical activity across a range of solid tumors in clinical trials. We present results from POD1UM-202 (NCT03597295), an open-label, single-arm, multicenter, phase II study evaluating retifanlimab in patients with previously treated advanced or metastatic SCAC.

Patients and methods

Patients ≥18 years of age had measurable disease and had progressed following, or were ineligible for, platinum-based therapy. Retifanlimab 500 mg was administered intravenously every 4 weeks. The primary endpoint was overall response rate (ORR) by independent central review. Secondary endpoints were duration of response (DOR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and safety.

Results

Overall, 94 patients were enrolled. At a median follow-up of 7.1 months (range, 0.9-19.4 months), ORR was 13.8% [95% confidence interval (CI) 7.6% to 22.5%], with one complete response (1.1%) and 12 partial responses (12.8%). Responses were observed regardless of human immunodeficiency virus or human papillomavirus status, programmed death ligand 1 (PD-L1) expression, or liver metastases. Stable disease was observed in 33 patients (35.1%) for a DCR of 48.9% (95% CI 38.5% to 59.5%). Median DOR was 9.5 months (range, 5.6 months-not estimable). Median (95% CI) PFS and OS were 2.3 (1.9-3.6) and 10.1 (7.9-not estimable) months, respectively. Retifanlimab safety in this population was consistent with previous experience for the PD-(L)1 inhibitor class.

Conclusions

Retifanlimab demonstrated clinically meaningful and durable antitumor activity, and an acceptable safety profile in patients with previously treated locally advanced or metastatic SCAC who have progressed on or are intolerant to platinum-based chemotherapy.

•

Retifanlimab (PD-1 inhibitor) monotherapy demonstrated encouraging results in patients with platinum-refractory SCAC.

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Clinically meaningful antitumor activity was reported with ORR of 13.8% and stable disease in 35.1%, for a DCR of 48.9%.

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Observed responses in advanced SCAC were durable (median 9.5 months).

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Acceptable safety profile consistent with that reported for the PD-(L)1 inhibitor class.

•

Promising results warrant further investigation of retifanlimab in advanced SCAC as well as earlier stages of disease.

An Explainable Transformer-Based Deep Learning Model for the Prediction of Incident Heart Failure

Predicting the incidence of complex chronic conditions such as heart failure is challenging. Deep learning models applied to rich electronic health records may improve prediction but remain unexplainable hampering their wider use in medical practice. We aimed to develop a deep-learning framework for accurate and yet explainable prediction of 6-month incident heart failure (HF). Using 100,071 patients from longitudinal linked electronic health records across the U.K., we applied a novel Transformer-based risk model using all community and hospital diagnoses and medications contextualized within the age and calendar year for each patient's clinical encounter. Feature importance was investigated with an ablation analysis to compare model performance when alternatively removing features and by comparing the variability of temporal representations. A post-hoc perturbation technique was conducted to propagate the changes in the input to the outcome for feature contribution analyses. Our model achieved 0.93 area under the receiver operator curve and 0.69 area under the precision-recall curve on internal 5-fold cross validation and outperformed existing deep learning models. Ablation analysis indicated medication is important for predicting HF risk, calendar year is more important than chronological age, which was further reinforced by temporal variability analysis. Contribution analyses identified risk factors that are closely related to HF. Many of them were consistent with existing knowledge from clinical and epidemiological research but several new associations were revealed which had not been considered in expert-driven risk prediction models. In conclusion, the results highlight that our deep learning model, in addition high predictive performance, can inform data-driven risk factor identification.

CT volumetry helps predict prognosis of large hepatocellular carcinoma after resection

AIM

To determine whether the tumour volume measurement on preoperative contrast-enhanced computed tomography (CT) could be used to predict the overall survival patients with large hepatocellular carcinoma (>5 cm) after resection.

MATERIALS AND METHODS

This study included 171 patients with surgically confirmed hepatocellular carcinoma who underwent preoperative CT. The largest diameter, the product of the axial dimension, tumour volume, and tumour-to-liver volume ratio (TTLVR) on CT images were measured and calculated. The univariate and multivariate Cox proportional hazard ratio regression models were used to identify the impact of the tumour burden-related risk factors on overall survival.

RESULTS

In multivariate analysis, TTLVR (p=0.042) and major vascular invasion (p=0.006) were independently associated with overall survival of patients with hepatocellular carcinoma after the resection. The group in which the patients had a low TTLVR showed higher cumulative survival rates than patients with a TTLVR (p=0.004). Patients with a low TTLVR (≤26.23%) and absence of major vascular invasion had significantly higher cumulative survival rates compared to those patients with hepatocellular carcinoma with either or both the risk factors (p=0.001).

CONCLUSION

A higher TTLVR in combination with the presence of major vascular invasion was associated with poorer overall survival in patients with large hepatocellular carcinoma after resection.