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Right Ventricular Strain Improves Cardiac MRI-based Prognostication in Heart Failure with Preserved Ejection Fraction.
Background Right ventricular (RV) function is an independent predictor of clinical status and prognosis in multiple cardiovascular diseases; however, the prognostic value of RV strain in patients with heart failure with preserved ejection fraction (HFpEF) remains largely unknown. Purpose To determine the associations between RV strain variables derived from cardiac MRI feature tracking and adverse outcomes in patients with HFpEF. Materials and Methods This retrospective study included patients with HFpEF who underwent cardiac MRI from January 2010 to December 2018. The primary end point was all-cause mortality. The results were validated in a cohort of patients with HFpEF enrolled from January 2019 to June 2021. Cox regression analysis was performed to assess the associations between variables and clinical outcomes. Results The development cohort comprised 1019 patients (mean age, 56.9 years ± 12.3 [SD]; 710 men), and the validation cohort comprised 273 patients (mean age, 55.3 years ± 14.0; 191 men). During a median follow-up of 7.8 and 3.9 years, respectively, 103 patients in the development cohort and nine in the validation cohort died. Multivariable Cox regression analysis showed that RV global longitudinal and circumferential strain were independent predictors of all-cause mortality (adjusted hazard ratio per 1% increase, 1.07 [95% CI: 1.02, 1.12; P = .005] and 1.13 [95% CI: 1.05, 1.21; P < .001], respectively). The full model based on clinical, conventional imaging, and RV strain variables demonstrated the best discrimination performance in the development (C index = 0.794) and validation (C index = 0.782) cohorts. In a subgroup with T1 mapping data, RV global longitudinal and circumferential strain remained independent predictors after separate adjustment for native T1 value and extracellular volume fraction (all models, P < .05). Conclusion RV global longitudinal and circumferential strain derived from cardiac MRI were independent predictors of adverse outcomes in patients with HFpEF, providing greater prognostic value than traditional clinical and imaging-derived risk markers. © RSNA, 2025 Supplemental material is available for this article. See also the editorial by Murphy and Quinn in this issue.
Is it time to revisit the scoring of Slow Wave (N3) Sleep?
The use of a fixed electroencephalogram (EEG) amplitude threshold of 75 µV for labelling slow waves is a subject of ongoing discussion given EEG amplitude is known to vary with age and sex. This paper investigates the impact of this amplitude threshold on age- and sex-related trends in visually-annotated SWS. Automated methods for labelling SWS using data-driven thresholds and amplitude- or frequency-based inputs are developed. Age- and sex-related trends in SWS derived from visual annotation and automated labelling are then compared across a cohort of 2,913 participants from the Sleep Heart Health Study. In the selected cohort, males exhibit an age-related decrease in visually-annotated SWS, which is preserved when using automated labelling. In contrast, females exhibit a mild age-related increase in visually-annotated and amplitude-labelled SWS, but an age-related decrease in frequency-labelled SWS. Further, using frequency-labelled SWS results in a reduction in SWS in females to a level comparable to that of males. Overall, the consistency of age-related trends in SWS in males between visual annotation and automated labelling, as well as the lack of consistency in these trends in females, is striking. Given that the 75 µV amplitude threshold was established using data acquired primarily from young males, these results suggest that observed sex-based differences in visually-annotated SWS may be artefactual rather than physiological, and a result of the 75 µV amplitude criterion. This sex-related disparity highlights the need for the AASM guidelines for scoring SWS to be reviewed and updated to provide equivalent performance for males and females.
Continuous Indexing of Fibrosis (CIF): improving the assessment and classification of MPN patients.
The grading of fibrosis in myeloproliferative neoplasms (MPN) is an important component of disease classification, prognostication and monitoring. However, current fibrosis grading systems are only semi-quantitative and fail to fully capture sample heterogeneity. To improve the quantitation of reticulin fibrosis, we developed a machine learning approach using bone marrow trephine (BMT) samples (n = 107) from patients diagnosed with MPN or a reactive marrow. The resulting Continuous Indexing of Fibrosis (CIF) enhances the detection and monitoring of fibrosis within BMTs, and aids MPN subtyping. When combined with megakaryocyte feature analysis, CIF discriminates between the frequently challenging differential diagnosis of essential thrombocythemia (ET) and pre-fibrotic myelofibrosis with high predictive accuracy [area under the curve = 0.94]. CIF also shows promise in the identification of MPN patients at risk of disease progression; analysis of samples from 35 patients diagnosed with ET and enrolled in the Primary Thrombocythemia-1 trial identified features predictive of post-ET myelofibrosis (area under the curve = 0.77). In addition to these clinical applications, automated analysis of fibrosis has clear potential to further refine disease classification boundaries and inform future studies of the micro-environmental factors driving disease initiation and progression in MPN and other stem cell disorders.
Vascular and inflammatory biomarkers of cardiovascular events in non-steroidal anti-inflammatory drug users.
AimsThe Standard care vs. Celecoxib Outcome Trial (SCOT) found similar risk of cardiovascular events with traditional non-steroidal anti-inflammatory drugs (NSAIDs) and the cyclooxygenase-2-selective drug celecoxib. While pre-clinical work has suggested roles for vascular and renal dysfunction in NSAID cardiovascular toxicity, our understanding of these mechanisms remains incomplete. A post hoc analysis of the SCOT cohort was performed to identify clinical risk factors and circulating biomarkers of cardiovascular events in NSAID users.Methods and resultsWithin SCOT (7295 NSAID users with osteoarthritis or rheumatoid arthritis), clinical risk factors associated with cardiovascular events were identified using least absolute shrinkage and selection operator regression. A nested case-control study of serum biomarkers including targeted proteomics was performed in individuals who experienced a cardiovascular event within 1 year (n = 49), matched 2:1 with controls who did not (n = 97). Risk factors significantly associated with cardiovascular events included increasing age, male sex, smoking, total cholesterol:HDL ratio ≥5, and aspirin use. Statin use was cardioprotective [odds ratio (OR) 0.68; 95% confidence interval (CI) 0.46-0.98]. There was significantly higher immunoglobulin (Ig)G anti-malondialdehyde-modified LDL (MDA-LDL), asymmetric dimethylarginine (ADMA), and lower arginine/ADMA. Targeted proteomic analysis identified serum growth differentiation factor 15 (GDF-15) as a candidate biomarker [area under the curve of 0.715 (95% CI 0.63-0.81)].ConclusionGrowth differentiation factor 15 has been identified as a candidate biomarker and should be explored for its mechanistic contribution to NSAID cardiovascular toxicity, particularly given the remarkable providence that GDF-15 was originally described as NSAID-activated gene-1.
Lung development genes, adult lung function and cognitive traits.
Lower lung function is associated with lower cognitive function and an increased risk of dementia. This has not been adequately explained and may partly reflect shared developmental pathways. In UK Biobank participants of European ancestry, we tested the association between lung function measures (forced vital capacity and forced expiratory volume in 1 s to forced vital capacity ratio; n = 306 476) and cognitive traits including nine cognitive function test scores (n = 32 321-428 609), all-cause dementia, Alzheimer's disease and vascular dementia (6805, 2859 and 1544 cases, respectively, and ∼421 241 controls). In the same population, we derived summary statistics for associations between common genetic variants in 55 lung development genes and lung function measures and cognitive traits using adjusted linear/logistic regression models. Using a hypothesis-driven Bayesian co-localization analysis, we finally investigated the presence of shared genetic signals between lung function measures and cognitive traits at each of these 55 genes. Higher lung function measures were generally associated with higher scores of cognitive function tests as well as lower risk of dementia. The strongest association was between forced vital capacity and vascular dementia (adjusted hazard ratio 0.74 per standard deviation increase, 95% confidence interval 0.67-0.83). Of the 55 genes of interest, we found shared variants in four genes, namely: CSNK2B rs9267531 (forced vital capacity and forced expiratory volume in 1 s to forced vital capacity ratio with fluid intelligence and pairs matching), NFATC3 rs548092276 & rs11275011 (forced expiratory volume in 1 s to forced vital capacity ratio with fluid intelligence), PTCH1 rs2297086 & rs539078574 (forced expiratory volume in 1 s to forced vital capacity ratio with reaction time) and KAT8 rs138259061 (forced vital capacity with pairs matching). However, the direction of effects was not in keeping with our hypothesis, i.e. variants associated with lower lung function were associated with better cognitive function or vice versa. We also found distinct variants associated with lung function and cognitive function in KAT8 (forced vital capacity and Alzheimer's disease) and PTCH1 (forced vital capacity and forced expiratory volume in 1 s to forced vital capacity ratio with fluid intelligence and reaction time). The links between CSNK2B and NFATC3 and cognitive traits have not been previously reported by genome-wide association studies. Despite shared genes and variants, our findings do not support the hypothesis that shared developmental signalling pathways explain the association of lower adult lung function with poorer cognitive function.
Asthma and incident coronary heart disease: an observational and Mendelian randomisation study.
BackgroundObservational studies suggest asthma is a risk factor for coronary heart disease (CHD) and sex modifies the risk, but they may suffer from methodological limitations. To overcome these, we applied a "triangulation approach", where different methodologies, with different potential biases, were leveraged to enhance confidence in findings.MethodsFirst, we conducted an observational study using UK medical records to match asthma patients 1:1, by age, sex and general practitioner (GP) practice, to the general population. We measured the association between asthma and incident CHD (myocardial infarction: hospitalisation/death) by applying minimal sufficient adjustment: model 1, smoking, body mass index, oral corticosteroids, atopy and deprivation; model 2, additionally adjusting for healthcare behaviour (GP consultation frequency). Second, we conducted a Mendelian randomisation (MR) study using data from the UK Biobank, Trans-National Asthma Genetic Consortium (TAGC) and Coronary Artery Disease Genome-wide Replication and Meta-analysis consortium (CARDIoGRAM). Using 64 asthma single nucleotide polymorphisms, the effect of asthma on CHD was estimated with inverse variance-weighted meta-analysis and methods that adjust for pleiotropy.ResultsIn our observational study (n=1 522 910), we found asthma was associated with 6% increased risk of CHD (model 1: HR 1.06, 95% CI 1.01-1.13); after accounting for healthcare behaviour, we found no association (model 2: HR 0.99, 95% CI 0.94-1.05). Asthma severity did not modify the association, but sex did (females: HR 1.11, 95% CI 1.01-1.21; males: HR 0.91, 95% CI 0.84-0.98). Our MR study (n=589 875) found no association between asthma and CHD (OR 1.01, 95% CI 0.98-1.04) and no modification by sex.ConclusionsOur findings suggest that asthma is not a risk factor for CHD. Previous studies may have suffered from detection bias or residual confounding.
Association of Daily Steps with Incident Non-Alcoholic Fatty Liver Disease: Evidence from the UK Biobank Cohort.
PurposeLow physical activity has been shown to be associated with higher risk of non-alcoholic fatty liver disease (NAFLD). However, the strength and shape of this association are currently uncertain due to a reliance on self-reported physical activity measures. This report aims to investigate the relationship of median daily step count with NAFLD using accelerometer-derived step count from a large prospective cohort study.MethodsThe wrist-worn accelerometer sub-study of the UK Biobank (N = ~100,000) was used to characterise median daily step count over a seven-day period. NAFLD cases were ascertained via record linkage with hospital inpatient data and death registers or by using a measure of liver fat from imaging. Cox proportional hazards models were employed to assess the association between step count and NAFLD, adjusting for age, sociodemographic, and lifestyle factors. Mediation analyses were conducted.ResultsAmong 91,031 participants (709,440 person-years of follow-up), there were 762 incident NAFLD cases. Higher step count was log-linearly and inversely associated with risk of NAFLD. A 1000-step increase (representing 10 minutes of walking) was associated with a 12% (95% CI: 10%-14%) lower hazard of NAFLD. When using imaging to identify NAFLD, a 1,000-step increase was associated with a 6% (95% CI: 6%-7%) lower risk. There was evidence for mediation by adiposity, accounting for 39% of the observed association.ConclusionsDaily step count, a modifiable risk factor, is log-linearly and inversely associated with NAFLD. This association was only partially explained by adiposity. These findings from a large cohort study may have important implications for strategies to lower NAFLD risk.
Sex-specific cardiometabolic multimorbidity, metabolic syndrome and left ventricular function in heart failure with preserved ejection fraction in the UK Biobank.
BackgroundCardiometabolic disturbances play a central role in the pathogenesis of heart failure with preserved ejection fraction (HFpEF). Due to its complexity, HFpEF is a challenging condition to treat, making phenotype-specific disease management a promising approach. However, HFpEF phenotypes are heterogenous and there is a lack of detailed evidence on the different, sex-specific profiles of cardiometabolic multimorbidity and metabolic syndrome present in HFpEF.MethodsWe performed a retrospective, modified cross-sectional study examining a subset of participants in the UK Biobank, an ongoing multi-centre prospective cohort study in the United Kingdom. We defined HFpEF as a record of a heart failure diagnosis using ICD-10 code I50, coupled with a left ventricular ejection fraction (LVEF) ≥ 50% derived from cardiac magnetic resonance (CMR) imaging. We examined sex-specific differences in cardiometabolic comorbidity burden and metabolic syndrome, performed latent class analysis (LCA) to identify distinct clusters of patients based on their cardiometabolic profile, and compared CMR imaging-derived parameters of left ventricular function at rest in the different clusters identified to reflect possible differences in adverse cardiac remodelling.ResultsWe ascertained HFpEF in 445 participants, of which 299 (67%) were men and 146 (33%) women. The median age was 70 years old (interquartile range: [66.0-74.0]). A combination of hypertension and obesity was the most prevalent cardiometabolic pattern both in men and women with HFpEF. Most men had 2-3 clinical cardiometabolic comorbidities while most women had 1-2, despite a similar metabolic syndrome profile (p = 0.05). LCA revealed three distinct, clinically relevant phenogroups, namely (1) a most male and multimorbid group (n = 117); (2) a group with a high prevalence of severe obesity, abnormal waist circumference and with the highest relative proportion of females (n = 116); and finally (3) a group with an apparently lower comorbidity burden aside from hypertension (n = 212). There were significant differences in clinical measurements and medication across the three phenogroups identified. Cardiac output at rest was significantly higher in group 2 vs. group 3 (males: median 5.6 L/min vs. 5.2 L/min, p ConclusionWomen with cardiometabolic HFpEF had a lower comorbidity burden compared to men despite a similar metabolic syndrome profile. Based on patients' cardiometabolic profile, we identified three distinct subgroups which differed in body shape and mass, lipid biomarker and medication profile, as well as in cardiac output at rest both in men and women. These factors may affect disease trajectory, treatment options and outcomes in those subgroups. Subject to further validation, our findings provide a refined characterisation of the cardiometabolic HFpEF phenotype, contributing towards a better understanding of the condition to enable phenotype-specific disease management.
Antidepressant Switching as a Proxy Phenotype for Drug Nonresponse: Investigating Clinical, Demographic, and Genetic Characteristics.
BACKGROUND: Selective serotonin reuptake inhibitors (SSRIs) are a first-line pharmacological therapy in major depressive disorder (MDD), but treatment response rates are low. Clinical trials lack the power to study the genetic contribution to SSRI response. Real-world evidence from electronic health records provides larger sample sizes, but novel response definitions are needed to accurately define SSRI nonresponders. METHODS: In the UK Biobank (UKB) (N = 38,813) and Generation Scotland (N = 1777) datasets, SSRI switching was defined using ≤90-day gap between prescriptions for an SSRI and another antidepressant in primary care. Nonswitchers were participants with ≥3 consecutive prescriptions for an SSRI. In the UKB, clinical, demographic, and polygenic score (PGS) associations with switching were determined, and the common-variant heritability was estimated. RESULTS: In the UKB, 5133 (13.2%) SSRI switchers and 33,680 nonswitchers were defined. The mean time to switch was 28 days (interquartile range, 17-49). Switching patterns were consistent across the UKB and Generation Scotland (n = 498 switchers). Higher annual income and educational levels (odds ratio [OR] [95% CI] for a university degree, 0.73 [0.67-0.79] compared with no qualifications) were associated with lower levels of switching. PGSs for nonremission, based on clinical studies, were associated with increased risk of switching (OR, 1.07 [1.02-1.12], p = .007). MDD PGSs and family history of depression were not significantly associated with switching. Using genome-wide complex trait Bayesian, the single nucleotide polymorphism-based heritability was approximately 4% (SE 0.016) on the observed scale. CONCLUSIONS: This study identified SSRI switching as a proxy for nonresponse, scalable across biobanks with electronic health records, capturing demographics and genetics of treatment nonresponse, and independent of MDD genetics.
Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): preliminary results of a randomised, controlled, open-label, platform trial
SUMMARY Background Tocilizumab is a monoclonal antibody that binds to the receptor for interleukin (IL)-6, reducing inflammation, and is commonly used to treat rheumatoid arthritis. We evaluated the safety and efficacy of tocilizumab in adult patients admitted to hospital with COVID-19 with evidence of both hypoxia and systemic inflammation. Methods This randomised, controlled, open-label, platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing several possible treatments in patients hospitalised with COVID-19 in the UK. Those trial participants with hypoxia (oxygen saturation <92% on air or requiring oxygen therapy) and evidence of systemic inflammation (C-reactive protein [CRP] ≥75 mg/L) were eligible for randomisation to usual standard of care alone versus usual standard of care plus tocilizumab at a dose of 400 mg to 800 mg (depending on weight) given intravenously. A second dose could be given 12 to 24 hours later if the patient’s condition had not improved. The primary outcome was 28-day mortality, assessed in the intention-to-treat population. The trial is registered with ISRCTN (50189673) and clinicaltrials.gov ( NCT04381936 ). Findings Between 23 April 2020 and 24 January 2021, 4116 adults were included in the assessment of tocilizumab, including 562 (14%) patients receiving invasive mechanical ventilation, 1686 (41%) receiving non-invasive respiratory support, and 1868 (45%) receiving no respiratory support other than oxygen. Median CRP was 143 [IQR 107-204] mg/L and 3385 (82%) patients were receiving systemic corticosteroids at randomisation. Overall, 596 (29%) of the 2022 patients allocated tocilizumab and 694 (33%) of the 2094 patients allocated to usual care died within 28 days (rate ratio 0·86; 95% confidence interval [CI] 0·77-0·96; p=0·007). Consistent results were seen in all pre-specified subgroups of patients. In particular, a clear mortality benefit was seen in those receiving systemic corticosteroids. Patients allocated to tocilizumab were more likely to be discharged from hospital alive within 28 days (54% vs. 47%; rate ratio 1·22; 95% CI 1·12-1·34; p<0·0001). Among those not receiving invasive mechanical ventilation at baseline, patients allocated tocilizumab were less likely to reach the composite endpoint of invasive mechanical ventilation or death (33% vs. 38%; risk ratio 0·85; 95% CI 0·78-0·93; p=0·0005). Interpretation In hospitalised COVID-19 patients with hypoxia and systemic inflammation, tocilizumab improved survival and other clinical outcomes. These benefits were seen regardless of the level of respiratory support and were additional to the benefits of systemic corticosteroids. Funding UK Research and Innovation (Medical Research Council) and National Institute of Health Research (Grant ref: MC_PC_19056).