Heart rate dependency of JT interval sections.

BACKGROUND: Little experience exists with the heart rate correction of J-Tpeak and Tpeak-Tend intervals. METHODS: In a population of 176 female and 176 male healthy subjects aged 32.3±9.8 and 33.1±8.4years, respectively, curve-linear and linear relationship to heart rate was investigated for different sections of the JT interval defined by the proportions of the area under the vector magnitude of the reconstructed 3D vectorcardiographic loop. RESULTS: The duration of the JT sub-section between approximately just before the T peak and almost the T end was found heart rate independent. Most of the JT heart rate dependency relates to the beginning of the interval. The duration of the terminal T wave tail is only weakly heart rate dependent. CONCLUSIONS: The Tpeak-Tend is only minimally heart rate dependent and in studies not showing substantial heart rate changes does not need to be heart rate corrected. For any correction formula that has linear additive properties, heart rate correction of JT and JTpeak intervals is practically the same as of the QT interval. However, this does not apply to the formulas in the form of Int/RR(a) since they do not have linear additive properties

Detection of T wave peak for serial comparisons of JTp interval

Electrocardiogram (ECG) studies of drug-induced prolongation of the interval between the J point and the peak of the T wave (JTp interval) distinguished QT prolonging drugs that predominantly block the delayed potassium rectifier current from those affecting multiple cardiac repolarisation ion channel currents. Since the peak of the T wave depends on ECG lead, a “global” T peak requires to combine ECG leads into one-dimensional signal in which the T wave peak can be measured. This study aimed at finding the optimum one-dimensional representation of 12-lead ECGs for the most stable JTp measurements. Seven different one-dimensional representations were investigated including the vector magnitude of the orthogonal XYZ transformation, root mean square of all 12 ECG leads, and the vector magnitude of the 3 dominant orthogonal leads derived by singular value decomposition. All representations were applied to the representative waveforms of 660,657 separate 10-second 12-lead ECGs taken from repeated day-time Holter recordings in 523 healthy subjects aged 33.5±8.4 years (254 women). The JTp measurements were compared with the QT intervals and with the intervals between the J point and the median point of the area under the T wave one-dimensional representation (JT50 intervals) by means of calculating the residuals of the subject-specific curvilinear regression models relating the measured interval to the hysteresis-corrected RR interval of the underlying heart rate. The residuals of the regression models (equal to the intra-subject standard deviations of individually heart rate corrected intervals) expressed intra-subject stability of interval measurements. For both the JTp intervals and the JT50 intervals, the curvilinear regression residuals of measurements derived from the orthogonal XYZ representation were marginally but statistically significantly lower compared to the other representations. Using the XYZ representation, the residuals of the QT/RR, JTp/RR and JT50/RR regressions were 5.6±1.1 ms, 7.2±2.2 ms, and 4.9±1.2 ms, respectively (all statistically significantly different; p<0.0001). The study concludes that the orthogonal XYZ ECG representation might be proposed for future investigations of JTp and JT50 intervals. If the ability of classifying QT prolonging drugs is further confirmed for the JT50 interval, it might be appropriate to replace the JTp interval since it appears more stable

Diets of the Barents Sea cod (Gadus morhua) from the 1930s to 2018

A new dataset on the diet of Atlantic cod in the Barents Sea from the 1930s to the present day has been compiled to produce one of the largest fish diet datasets available globally. Atlantic cod is one of the most ecologically and commercially important fish species in the North Atlantic. The stock in the Barents Sea is by far the largest, as a result of both successful management and favourable environmental conditions since the early 2000s. As a top predator, cod plays a key role in the Barents Sea ecosystem. The species has a broad diet consisting mainly of crustaceans and teleost fish, and both the amount and type of prey vary in space and time. The data – from Russia, Norway and the United Kingdom – represent quantitative stomach content records from more than 400 000 fish and qualitative data from 2.5 million fish. Many of the data are from joint collaborative surveys between Norway and Russia. The sampling was conducted throughout each year, allowing for seasonal, annual and decadal comparisons to be made. Visual analysis shows cod diets have changed considerably from the start of the dataset in the 1930s to the present day. There was a large proportion of herring in the diets in the 1930s, whereas in more recent decades capelin, invertebrates and other fish dominate. There are also significant interannual asynchronous fluctuations in prey, particularly capelin and euphausiids. Combining these datasets can help us understand how the environment and ecosystems are responding to climatic changes, and what influences the diet and prey switching of cod. Trends in temperature and variability indices can be tested against the occurrence of different prey items, and the effects of fishing pressure on cod and prey stocks on diet composition could be investigated. The dataset will also enable us to improve parametrization of food web models and to forecast how Barents Sea fisheries may respond in the future to management and to climate change. The Russian data are available through joint projects with the Polar Branch of the Russian Federal Research Institute of Fisheries and Oceanography (VNIRO).publishedVersio

A Common Genetic Variant Risk Score is Associated with Drug-Induced QT Prolongation and Torsade de Pointes Risk: A Pilot Study.

Background -Drug-induced QT interval prolongation, a risk factor for life-threatening ventricular arrhythmias, is a potential side effect of many marketed and withdrawn medications. The contribution of common genetic variants previously associated with baseline QT interval to drug-induced QT prolongation and arrhythmias is not known. Methods -We tested the hypothesis that a weighted combination of common genetic variants contributing to QT interval at baseline, identified through genome-wide association studies, can predict individual response to multiple QT-prolonging drugs. Genetic analysis of 22 subjects was performed in a secondary analysis of a randomized, double-blind, placebo-controlled, cross-over trial of 3 QT-prolonging drugs with 15 time-matched QT and plasma drug concentration measurements. Subjects received single doses of dofetilide, quinidine, ranolazine and placebo. The outcome was the correlation between a genetic QT score comprising 61 common genetic variants and the slope of an individual subject's drug-induced increase in heart rate corrected QT (QTc) vs. drug concentration. Results -The genetic QT score was correlated with drug-induced QTc prolongation. Among white subjects, genetic QT score explained 30% of the variability in response to dofetilide (r = 0.55 [95% CI, 0.09-0.81], P = 0.02), 23% in response to quinidine (r = 0.48 [95% CI, -0.03 to 0.79], P = 0.06) and 27% in response to ranolazine (r = 0.52 [95% CI, 0.05 to 0.80], P = 0.03). Furthermore, the genetic QT score was a significant predictor of drug-induced torsade de pointes in an independent sample of 216 cases compared to 771 controls (r(2) = 12%, P = 1x10(-7)). Conclusions -We demonstrate that a genetic QT score comprising 61 common genetic variants explains a significant proportion of the variability in drug-induced QT prolongation and is a significant predictor of drug-induced torsade de pointes. These findings highlight an opportunity for recent genetic discoveries to improve individualized risk-benefit assessment for pharmacologic therapies. Replication of these findings in larger samples is needed to more precisely estimate variance explained and to establish the individual variants that drive these effects. Clinical Trial Registration - http://clinicaltrials.gov Unique identifier: NCT01873950

Use of Advanced Flexible Modeling Approaches for Survival Extrapolation from Early Follow-up Data in two Nivolumab Trials in Advanced NSCLC with Extended Follow-up

Objectives: Immuno-oncology (IO) therapies are often associated with delayed responses that are deep and durable, manifesting as long-term survival benefits in patients with metastatic cancer. Complex hazard functions arising from IO treatments may limit the accuracy of extrapolations from standard parametric models (SPMs). We evaluated the ability of flexible parametric models (FPMs) to improve survival extrapolations using data from 2 trials involving patients with non–small-cell lung cancer (NSCLC). Methods: Our analyses used consecutive database locks (DBLs) at 2-, 3-, and 5-y minimum follow-up from trials evaluating nivolumab versus docetaxel in patients with pretreated metastatic squamous (CheckMate-017) and nonsquamous (CheckMate-057) NSCLC. For each DBL, SPMs, as well as 3 FPMs—landmark response models (LRMs), mixture cure models (MCMs), and Bayesian multiparameter evidence synthesis (B-MPES)—were estimated on nivolumab overall survival (OS). The performance of each parametric model was assessed by comparing milestone restricted mean survival times (RMSTs) and survival probabilities with results obtained from externally validated SPMs. Results: For the 2- and 3-y DBLs of both trials, all models tended to underestimate 5-y OS. Predictions from nonvalidated SPMs fitted to the 2-y DBLs were highly unreliable, whereas extrapolations from FPMs were much more consistent between models fitted to successive DBLs. For CheckMate-017, in which an apparent survival plateau emerges in the 3-y DBL, MCMs fitted to this DBL estimated 5-y OS most accurately (11.6% v. 12.3% observed), and long-term predictions were similar to those from the 5-y validated SPM (20-y RMST: 30.2 v. 30.5 mo). For CheckMate-057, where there is no clear evidence of a survival plateau in the early DBLs, only B-MPES was able to accurately predict 5-y OS (14.1% v. 14.0% observed [3-y DBL]). Conclusions: We demonstrate that the use of FPMs for modeling OS in NSCLC patients from early follow-up data can yield accurate estimates for RMST observed with longer follow-up and provide similar long-term extrapolations to externally validated SPMs based on later data cuts. B-MPES generated reasonable predictions even when fitted to the 2-y DBLs of the studies, whereas MCMs were more reliant on longer-term data to estimate a plateau and therefore performed better from 3 y. Generally, LRM extrapolations were less reliable than those from alternative FPMs and validated SPMs but remained superior to nonvalidated SPMs. Our work demonstrates the potential benefits of using advanced parametric models that incorporate external data sources, such as B-MPES and MCMs, to allow for accurate evaluation of treatment clinical and cost-effectiveness from trial data with limited follow-up. Flexible advanced parametric modeling methods can provide improved survival extrapolations for immuno-oncology cost-effectiveness in health technology assessments from early clinical trial data that better anticipate extended follow-up. Advantages include leveraging additional observable trial data, the systematic integration of external data, and more detailed modeling of underlying processes. Bayesian multiparameter evidence synthesis performed particularly well, with well-matched external data. Mixture cure models also performed well but may require relatively longer follow-up to identify an emergent plateau, depending on the specific setting. Landmark response models offered marginal benefits in this scenario and may require greater numbers in each response group and/or increased follow-up to support improved extrapolation within each subgroup

A comparison of IIR and wavelet filtering for noise reduction of the ECG

Abstrac

Burden of Respiratory Syncytial Virus in the European Union:estimation of RSV-associated hospitalizations in children under 5 years

Background No overall estimate of respiratory syncytial virus (RSV)-associated hospitalizations in children aged under 5 years has been published for the European Union (EU). We aimed to estimate the RSV hospitalization burden in children aged under 5 years in EU countries and Norway, by age group. Methods We collated national RSV-associated hospitalization estimates calculated using linear regression models via the RESCEU project for Denmark, England, Finland, Norway, the Netherlands, and Scotland, 2006-2018. Additional estimates were obtained from a systematic review. Using multiple imputation and nearest neighbor matching methods, we estimated overall RSV-associated hospitalizations and rates in the EU. Results Additional estimates for 2 countries (France and Spain) were found in the literature. In the EU, an average of 245 244 (95% confidence interval [CI], 224 688-265 799) yearly hospital admissions with a respiratory infection per year were associated with RSV in children aged under 5 years, with most cases occurring among children aged under 1 year (75%). Infants aged under 2 months represented the most affected group (71.6 per 1000 children; 95% CI, 66.6-76.6). Conclusions Our findings will help support decisions regarding prevention efforts and represent an important benchmark to understand changes in the RSV burden following the introduction of RSV immunization programs in Europe.The study estimated that an average of 245 244 children aged under 5 years are hospitalized annually due to RSV in the EU, with the highest hospitalization rates in children aged less than 2 months (71.6 per 1000 children)

Changing rates but persisting seasons: patterns of enterovirus infections in hospitalizations and outpatient visits in Denmark 2015-2022

BackgroundEnteroviruses (EV) constitute a diverse group of viruses manifesting a broad spectrum of clinical presentations in humans ranging from mild skin manifestations to more severe central nervous system (CNS) infection. Severe infections are reported with increased frequency globally, albeit the burden of diseases and the evolution of circulating viruses is largely unknown. We aimed to systematically explore contemporary trends in hospitalizations attributed to EV infections using national hospitalization discharge data.MethodsWe utilized the Danish National Patient Register which holds information on all contacts to Danish hospitals. We covered eight full years (2015-2022). Length-of-stay and administrative procedure codes were used to distinguish hospital admissions from outpatient visits. We utilized burden of disease estimates and distribution statistics.ResultsWe identified 1029 hospitalizations and 1970 outpatient visits due to EV infections. The hospital admissions were primarily associated with CNS-infections (n=570, 55.4%) and skin (n=252, 24.5%), with variation over the studied period. The admitted patients were predominately children (43.8%) though patients were identified in all ages. The clinical manifestation was associated with age, with CNS infections dominating in the neonates and adults, and skin infections dominating in children 1-2 years (17.2%). Outpatient visits were predominantly observed among children 1-2 years (55.0%), presenting with skin symptoms (77.9%). We show a seasonal pattern of EV infections with summer/fall peaks and markedly impact on the EV hospitalization burden related to COVID-19 mitigation measures including national lockdown periods. 25% of hospital admissions occurred during 2020-2022.ConclusionEV infections caused both hospital admissions and outpatient visits in the period studied, predominately among children aged 1-2 years. Overall, skin infections dominated the outpatient visits, while the majority of hospital admissions were due to CNS infections. The pandemic period did not change the seasonal pattern of EV infections but notably lowered the number of admissions to hospital with CNS infection and raised the number of outpatient admissions with skin infection

Treatment challenges in and outside a specialist network setting: Pancreatic neuroendocrine tumours

Pancreatic Neuroendocrine Neoplasms comprise a group of rare tumours with special biology, an often indolent behaviour and particular diagnostic and therapeutic requirements. The specialized biochemical tests and radiological investigations, the complexity of surgical options and the variety of medical treatments that require individual tailoring, mandate a multidisciplinary approach that can be optimally achieved through an organized network. The present study describes currents concepts in the management of these tumours as well as an insight into the challenges of delivering the pathway in and outside a Network