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The burden of an epidemic is often characterized by death counts, but this can be misleading as it fails to acknowledge the age of the deceased patients. Years of life lost is therefore widely used as a more relevant metric, however, such calculations in the context of COVID-19 are all biased upwards: patients dying from COVID-19 are typically multimorbid, having far worse life expectation than the general population. These questions are quantitatively investigated using a unique Hungarian dataset that contains individual patient level data on comorbidities for all COVID-19 deaths in the country. To account for the comorbidities of the patients, a parametric survival model using 11 important long-term conditions was used to estimate a more realistic years of life lost. As of 12 May, 2021, Hungary reported a total of 27,837 deaths from COVID-19 in patients above 50 years of age. The usual calculation indicates 10.5 years of life lost for each death, which decreases to 9.2 years per death after adjusting for 11 comorbidities. The expected number of years lost implied by the life table, reflecting the mortality of a developed country just before the pandemic is 11.1 years. The years of life lost due to COVID-19 in Hungary is therefore 12% or 1.3 years per death lower when accounting for the comorbidities and is below its expected value, but how this should be interpreted is still a matter of debate. Further research is warranted on how to optimally integrate this information into epidemiologic risk assessments during a pandemic.

Background The World Health Organization (WHO)’s excess mortality estimates presented in May 2022 stirred controversy, due in part to the high estimate provided for Germany, which was later attributed to the spline model used. This paper aims to reproduce the problem using synthetic datasets, thus allowing the investigation of its sensitivity to parameters, both of the mortality curve and of the used method, thereby shedding light on the conditions that gave rise to this error and identifying possible remedies. Methods A negative binomial model was used accounting for long-term change, seasonality, flu seasons, and heat waves. Simulated mortality curves from this model were then analysed using simple methods (mean, linear trend), the WHO method, and the method of Acosta and Irizarry. Results The performance of the WHO’s method with its original parametrization was indeed very poor, however it can be profoundly improved by a better choice of parameters. The Acosta–Irizarry method outperformed the WHO method despite being also based on splines, but it was also dependent on its parameters. Linear extrapolation could produce very good results, but was highly dependent on the choice of the starting year, while the average was the worst in almost all cases. Conclusions Splines are not inherently unsuitable for predicting baseline mortality, but caution should be taken. In particular, the results suggest that the key issue is that the splines should not be too flexible to avoid overfitting. Even after having investigated a limited number of scenarios, the results suggest that there is not a single method that outperforms the others in all situations. As the WHO method on the German data illustrates, whatever method is chosen, it remains important to visualize the data, the fit, and the predictions before trusting any result. It will be interesting to see whether further research including other scenarios will come to similar conclusions.

Context:In recent years, the focus on sustainable meat production in large-scale pig farming has increased. An essential element is acquiring and evaluating digital data on ecological, outdoor pig housing environments and individuals.Objective:Some of the precision farming Internet of Things (IoT) tools that can be used in pasture-based, extensive pig production include those that have been proven in pasture-based ruminants and have been used in confined pig production for many years. These include Radio Frequency IDentification (RFID) technology, in which passive RFID tags attached to pigs’ ears capture signals from a reader equipped with an antenna. The reader can also be used to collect weather parameters.Methods:In our on-farm research, which lasted 7 months and covered three seasons, we used RFID technology to investigate the effects of ambient temperature, humidity, air pressure, and hour of day on the appearance of breeding sows kept on pasture at the wallowing site.Results and conclusion:We found that all three weather parameters and hour-of-day had a significant effect (p < 0.001) on the appearance of sows at the wallow. We calculated the THI (Temperature Humidity Index) and found days in summer and early autumn when there was a risk of heat stress. This is essential information for the pig farmer because heat stress has a strong negative effect on sow fertility. Our on-farm study found that RFID technology is suitable for detecting the presence of pigs in the pasture. However, the limitations of the technology, both in terms of the housing environment and the species specificity of the pigs, need to be taken into account.Significance:In pasture-based pig production systems, the meat production process is performed under extensive conditions of natural animal-environment interaction. The negative impact on the natural environment is much lower, but animal welfare is higher than in intensive pig farming. It is also a profit-oriented activity, where the production of traceable and reliable animal products is a social and economic requirement. Collecting information from trusted sources using precision livestock farming (PLF) techniques is also feasible in this type of farming, providing significant added value for pig farmers and consumers.

Background Limited information is available on the effectiveness of the BBIBP-CorV (Sinopharm, Beijing CNBG) vaccine, especially in the elderly, despite the fact that it is approved in more than 50 countries. Methods RBD-specific antibody titres, as a rapidly available and highly predictive surrogate marker, were measured after two doses of the BBIBP-CorV vaccine in 450 subjects. Results were analyzed in a multivariable model accounting for age, sex and time since the administration of the second dose of the vaccine. Results Sex and time since the second dose had little association with the antibody titres. Age, however, was highly relevant: measurable antibody levels were present in about 90% of individuals below the age of 50, but antibody production after BBIBP-CorV vaccination was strongly reduced with increasing age. A large number of elderly subjects, reaching 25% at 60 years, and up to 50% at ages over 80, were found not to produce any protective antibody. Conclusions RBD-specific antibody titre, as a correlate of protection for COVID-19 disease susceptibility, should help to evaluate the effectiveness of the BBIBP-CorV vaccine. Results suggest that proper measures should be undertaken to prevent a potential outbreak of COVID-19 in BBIBP-CorV vaccinated but eventually unprotected elderly individuals.

Background/Objectives: Randomized studies of patients with unprotected left main coronary artery (ULMCA) disease involve highly selected populations. Therefore, we sought to investigate the 60-month event-free survival of consecutive patients undergoing ULMCA percutaneous coronary intervention (PCI) and determine the best risk score system and independent predictors of event-free survival. Methods: All patients who underwent ULMCA PCI at our center between 1 January 2007 and 31 December 2014 were included. The primary endpoint was the time to cardiac death, target lesion myocardial infarction, or target lesion revascularization (whichever came first) with a follow-up of 60 months. Results: A total of 513 patients (mean age 68 ± 12 years, 64% male, 157 elective, 356 acute) underwent ULMCA PCI. The 60-month incidence of events was 16.8% and 38.0% in elective and acute patients, respectively. There were significantly more events in the acute group during the first 6.5 months. Of the risk scores, the ACEF (AUC = 0.786) and SYNTAX II (AUC = 0.716) scores had the best predictive power in elective and acute patients, respectively. The SYNTAX score proved to be the least predictive in both groups (AUC = 0.638 and 0.614 in the elective and acute groups, respectively). Left ventricular function (hazard ratio (HR) for +10% 0.53 [95% CI, 0.38–0.75] and 0.81 [95% CI, 0.71–0.92] in elective and acute patients, respectively) and, in acute patients, access site (femoral vs. radial HR 1.76 [95% CI, 1.11–2.80]), hyperlipidemia (HR 0.58 [95% CI, 0.39–0.86]), and renal function (HR for +10 mL/min/1.73 m2 higher GFR: 0.87 [95% CI, 0.78–0.97]) were independent predictors of event-free survival. Conclusions: Acute ULMCA PCI patients have worse prognosis than elective patients, having more events during the first 6.5 months. Besides anatomical complexity, clinical and procedural parameters determine the prognosis.

This randomized study aims to compare the left atrial (LA) lesion size, function, and tissue damage following pulmonary vein isolation (PVI) by high-power short-duration (HPSD) radiofrequency (RF) and second-generation cryoballoon (CB2) ablation. We enrolled 40 patients with paroxysmal atrial fibrillation who underwent PVI by HPSD RF (n = 21) or CB2 (n = 19). Every patient underwent LA CT angiography and transthoracic echocardiography (TTE) to assess the LA anatomy and function. Biomarker levels (hs-cTnT, hs-CRP, LDH) were compared pre- and post-procedurally. Pre- and post-ablation high-density mapping (HDM) was performed. The isolation area was defined under 0.2 mV bipolar voltage (low voltage area, LVA). We calculated the post-PVI LVA/LA surface ratio using LA CT-HDM merge images. At 3-month follow-up, TTE was performed to assess the changes in LA function. Post-ablation hs-cTnT level was significantly higher in the RF group (RF: 1249 ± 469 ng/L, CB2: 995 ± 280 ng/L, p = 0.024). Post-PVI hs-CRP (RF: 9.53 ± 10.30 mg/L, CB2: 12.36 ± 5.76 mg/L, p = 0.034) and LDH levels (RF: 349.9 ± 65.6 U/L, CB2: 451.6 ± 91.3 U/L, p < 0.001) were significantly higher following CB2 ablation. Post-PVI LVA/LA surface ratios were 8.37 ± 6.42% in the RF group and 13.58 ± 8.92% in the CB2 group (p = 0.022). LA function did not change significantly after the PVI procedure. Our data indicate that second-generation cryoballoon ablation produces a significantly larger LA lesion size compared to “point-by-point” HPSD radiofrequency. Both techniques preserve LA function. The myocardial component of tissue loss appears to be higher using HPSD radiofrequency ablation, with less collateral damage.

COVID-19 epidemic has been suppressed in Hungary due to timely non-pharmaceutical interventions, prompting a considerable reduction in the number of contacts and transmission of the virus. This strategy was effective in preventing epidemic growth and reducing the incidence of COVID-19 to low levels. In this report, we present the first epidemiological and statistical analysis of the early phase of the COVID-19 outbreak in Hungary. Then, we establish an age-structured compartmental model to explore alternative post-lockdown scenarios. We incorporate various factors, such as age-specific measures, seasonal effects, and spatial heterogeneity to project the possible peak size and disease burden of a COVID-19 epidemic wave after the current measures are relaxed.

IntroductionPrehospital emergency care (PEC) requires rapid evidence-based decisions to maximise the effectiveness of care and to improve clinical outcomes. There are multiple challenges related to clinical research performed in the PEC setting. The aim of our study is to systematically review and assess the characteristics, quality of reporting, risk of bias and pragmatism in recent PEC trials, thereby identifying potential gaps and strengths that can guide the design of future prehospital studies.Methods and analysisWe will systematically search databases MEDLINE, Embase and Cochrane CENTRAL to identify all randomised controlled trials conducted in the field of PEC and published in English language between 2010 and 2024. No restrictions will be made to the participants, interventions and outcomes. Risk of bias will be evaluated using the Cochrane Risk of Bias 2 tool. The level of pragmatism will be assessed using the Pragmatic-Explanatory Continuum Indicator Summary-2 score. Exploratory data analysis will be used to investigate and summarise main patterns. Differences in characteristics between PEC fields, study designs, publication year and associations between pragmatism levels, risk of bias and quality of reporting will be the primary focus.Ethics and disseminationThere are no ethical concerns directly relevant to this review. This study has been previously registered with the Open Science Framework (osf.io/rzn9j). The manuscript will be submitted for publication to a relevant, peer-reviewed journal.

This study examines the likelihood and evolution of overall and hypoglycemia-inducing variability of insulin sensitivity in ICU patients based on diagnosis and day of stay. An analysis of model-based insulin sensitivity for n=390 patients in a medical ICU (Christchurch, New Zealand). Two metrics are defined to measure the variability of a patient's insulin sensitivity relative to predictions of a stochastic model created from the same data for all patients over all days of stay. The first selectively captures large increases related to the risk of hypoglycemia. The second captures overall variability. Distributions of per-patient variability scores were evaluated over different ICU days of stay and for different diagnosis groups based on APACHE III: operative and non-operative cardiac, gastric, all other. Linear and generalized linear mixed effects models assess the statistical significance of differences between groups and over days. Variability defined by the two metrics was not substantially different. Variability was highest on day 1, and decreased over time (p<0.0001) in every diagnosis group. There were significant differences between some diagnosis groups: non-operative gastric patients were the least variable, while cardiac (operative and non-operative) patients exhibited the highest variability. This study characterizes the variability and evolution of insulin sensitivity in critically ill patients, and may help inform the clinical management of metabolic dysfunction in critical care.

AbstractPurposeThe purpose of the present study was to find the independent predictors of Fractional Flow Reserve (FFR) measured immediately after percutaneous coronary intervention with drug-eluting stent implantation (post-PCI FFR) and investigate if applying vessel-specific post-PCI FFR cut-off values to predict target vessel failure (TVF), a composite of cardiac death (CD), non-fatal myocardial infarction (MI) and target vessel revascularization (TVR), or a composite of CD and MI ameliorated its predictive power.MethodsConsecutive patients with post-PCI FFR measurement at our center between 2009 and 2021 were included in this analysis.ResultsA total of 434 patients with 500 vessels were included. Median pre-PCI FFR was 0.72 with no difference between LAD and non-LAD vessels. Median post-PCI FFR was 0.87. LAD location, male gender, smaller stent diameter, and lower pre-PCI FFR proved to be significant predictors of a lower post-PCI FFR. On a vessel-level, post-PCI FFR, stent length, and diabetes mellitus proved to be significant predictors of TVF and the composite of CD and MI. The best post-PCI FFR cut-off to predict TVF or a composite of CD and MI was 0.83 in the LAD and 0.91 in non-LAD vessels.ConclusionLAD location is a predictor of a lower post-PCI FFR. Post-PCI FFR is an independent predictor of TVF as well as of the composite of CD and MI. No uniform target post-PCI FFR value exists; different cut-off values may have to be applied in LAD as opposed to non-LAD vessels.