A novel method to estimate the response of habitat types to nitrogen deposition

Increasing nitrogen depositions adversely affect European landscapes, including habitats within the Natura2000 network. Critical loads for nitrogen deposition have been established to quantify the loss of habitat quality. When the nitrogen deposition rises above a habitat-specific critical load, the quality of the focal habitat is expected to be negatively influenced. Here, we investigate how the quality of habitat types is affected beyond the critical load. We calculated response curves for 60 terrestrial habitat types in the Netherlands to the estimated nitrogen deposition (EMEP-data). The curves for habitat types are based on the occurrence of their characteristic plant species in North-Western Europe (plot data from the European Vegetation Archive). The estimated response curves were corrected for soil type, mean annual temperature and annual precipitation. Evaluation was carried out by expert judgement, and by comparison with gradient deposition field studies. For 39 habitats the response to nitrogen deposition was judged to be reliable by five experts, while out of the 41 habitat types for which field studies were available, 25 showed a good agreement. Some of the curves showed a steep decline in quality and some a more gradual decline with increasing nitrogen deposition. We compared the response curves with both the empirical and modelled critical loads. For 41 curves, we found a decline already starting below the critical load.

Optimal allocation strategies in platform trials with continuous endpoints

Platform trials are randomized clinical trials that allow simultaneous comparison of multiple interventions, usually against a common control. Arms to test experimental interventions may enter and leave the platform over time. This implies that the number of experimental intervention arms in the trial may change as the trial progresses. Determining optimal allocation rates to allocate patients to the treatment and control arms in platform trials is challenging because the optimal allocation depends on the number of arms in the platform and the latter typically varies over time. In addition, the optimal allocation depends on the analysis strategy used and the optimality criteria considered. In this article, we derive optimal treatment allocation rates for platform trials with shared controls, assuming that a stratified estimation and a testing procedure based on a regression model are used to adjust for time trends. We consider both, analysis using concurrent controls only as well as analysis methods using concurrent and non-concurrent controls and assume that the total sample size is fixed. The objective function to be minimized is the maximum of the variances of the effect estimators. We show that the optimal solution depends on the entry time of the arms in the trial and, in general, does not correspond to the square root of k allocation rule used in classical multi-arm trials. We illustrate the optimal allocation and evaluate the power and type 1 error rate compared to trials using one-to-one and square root of k allocations by means of a case study.

Methods for non-proportional hazards in clinical trials: A systematic review

For the analysis of time-to-event data, frequently used methods such as the log-rank test or the Cox proportional hazards model are based on the proportional hazards assumption, which is often debatable. Although a wide range of parametric and non-parametric methods for non-proportional hazards has been proposed, there is no consensus on the best approaches. To close this gap, we conducted a systematic literature search to identify statistical methods and software appropriate under non-proportional hazard. Our literature search identified 907 abstracts, out of which we included 211 articles, mostly methodological ones. Review articles and applications were less frequently identified. The articles discuss effect measures, effect estimation and regression approaches, hypothesis tests, and sample size calculation approaches, which are often tailored to specific non-proportional hazard situations. Using a unified notation, we provide an overview of methods available. Furthermore, we derive some guidance from the identified articles.

Simultaneous inference procedures for the comparison of multiple characteristics of two survival functions

Survival time is the primary endpoint of many randomized controlled trials, and a treatment effect is typically quantified by the hazard ratio under the assumption of proportional hazards. Awareness is increasing that in many settings this assumption is a priori violated, for example, due to delayed onset of drug effect. In these cases, interpretation of the hazard ratio estimate is ambiguous and statistical inference for alternative parameters to quantify a treatment effect is warranted. We consider differences or ratios of milestone survival probabilities or quantiles, differences in restricted mean survival times, and an average hazard ratio to be of interest. Typically, more than one such parameter needs to be reported to assess possible treatment benefits, and in confirmatory trials, the according inferential procedures need to be adjusted for multiplicity. A simple Bonferroni adjustment may be too conservative because the different parameters of interest typically show considerable correlation. Hence simultaneous inference procedures that take into account the correlation are warranted. By using the counting process representation of the mentioned parameters, we show that their estimates are asymptotically multivariate normal and we provide an estimate for their covariance matrix. We propose according to the parametric multiple testing procedures and simultaneous confidence intervals. Also, the logrank test may be included in the framework. Finite sample type I error rate and power are studied by simulation. The methods are illustrated with an example from oncology. A software implementation is provided in the R package nph.

Regulatory Issues of Platform Trials: Learnings from EU-PEARL

Although platform trials have many benefits, the complexity of these designs may result not only in increased methodological but also regulatory and ethical challenges. These aspects were addressed as part of the IMI project EU Patient-Centric Clinical Trial Platforms (EU-PEARL). We reviewed the available guidelines on platform trials in the European Union and the United States. This is supported and complemented by feedback received from regulatory interactions with the European Medicines Agency and the US Food and Drug Administration. Throughout the project we collected the needs of all relevant stakeholders including ethics committees, regulators, and health technology assessment bodies through active dialog and dedicated stakeholder workshops. Furthermore, we focused on methodological aspects and where applicable identified the corresponding guidance. Learnings from the guideline review, regulatory interactions, and workshops are provided. Based on these, a master protocol template was developed. Issues that still need harmonization or clarification in guidelines or where further methodological research is needed are also presented. These include questions around clinical trial submissions in Europe, the need for multiplicity control across the whole master protocol, the use of non-concurrent controls, and the impact of different randomization schemes. Master protocols are an efficient and patient-centered clinical trial design that can expedite drug development. However, they can also introduce additional operational and regulatory complexities. It is important to understand the different requirements of stakeholders upfront and address them in the trial. While relevant guidance is increasing, early dialog with relevant stakeholders can help to further support such designs.

Red blood cell transfusion-related dynamics of extracellular vesicles in intensive care patients: a prospective subanalysis

Extracellular vesicles (EVs) accumulate during packed red blood cell (PRBC) storage. To date, the involvement of EVs in transfusion-related immunomodulation (TRIM) has not been prospectively evaluated in intensive care unit (ICU) patients. This was a prospective subanalysis of a recent observational feasibility study in postoperative ICU patients after: (1) open aortic surgery (Aorta), (2) bilateral lung transplantation (LuTx), and (3) other types of surgery (Comparison). Patient plasma was collected three times each before and after leukoreduced PRBC transfusion at 30-min intervals. The total number of EVs and EVs derived from erythrocytes (EryEVs), total platelets (total PEVs), activated platelets, granulocytes (GEVs), monocytes, and myeloid cells in PRBC samples and patient plasma were analyzed by flow cytometry. Statistical analysis was performed by Spearman's correlation test, linear mixed models and pairwise comparisons by Wilcoxon matched-pairs test. Twenty-three patients (Aorta n = 5, LuTx n = 9, Comparison n = 9) were included in the final analysis. All EV subgroups analyzed were detectable in all PRBCs samples (n = 23), but concentrations did not correlate with storage time. Moreover, all EVs analyzed were detectable in all plasma samples (n = 138), and EV counts were consistent before transfusion. Concentrations of total EVs, EryEVs, total PEVs, and GEVs increased after transfusion compared with baseline in the entire cohort but not in specific study groups. Furthermore, the change in plasma EV counts (total EVs and EryEVs) after transfusion correlated with PRBC storage time in the entire cohort. Extracellular vesicles were detectable in all PRBC and plasma samples. Individual EV subtypes increased after transfusion in the entire cohort, and in part correlated with storage duration. Future clinical studies to investigate the role of EVs in TRIM are warranted and should anticipate a larger sample size.Trial registration: Clinicaltrials.gov: NCT03782623.

Current state-of-the-art and gaps in platform trials: 10 things you should know, insights from EU-PEARL

Platform trials bring the promise of making clinical research more efficient and more patient centric. While their use has become more widespread, including their prominent role during the COVID-19 pandemic response, broader adoption of platform trials has been limited by the lack of experience and tools to navigate the critical upfront planning required to launch such collaborative studies. The European Union-Patient-cEntric clinicAl tRial pLatform (EU-PEARL) initiative has produced new methodologies to expand the use of platform trials with an overarching infrastructure and services embedded into Integrated Research Platforms (IRPs), in collaboration with patient representatives and through consultation with U.S. Food and Drug Administration and European Medicines Agency stakeholders. In this narrative review, we discuss the outlook for platform trials in Europe, including challenges related to infrastructure, design, adaptations, data sharing and regulation. Documents derived from the EU-PEARL project, alongside a literature search including PubMed and relevant grey literature (e.g., guidance from regulatory agencies and health technology agencies) were used as sources for a multi-stage collaborative process through which the 10 more important points based on lessons drawn from the EU-PEARL project were developed and summarised as guidance for the setup of platform trials. We conclude that early involvement of critical stakeholder such as regulatory agencies or patients are critical steps in the implementation and later acceptance of platform trials. Addressing these gaps will be critical for attaining the full potential of platform trials for patients.

Funding

Innovative Medicines Initiative 2 Joint Undertaking with support from the European Union's Horizon 2020 research and innovation programme and EFPIA.

Adaptive clinical trial designs with blinded selection of binary composite endpoints and sample size reassessment

For randomized clinical trials where a single, primary, binary endpoint would require unfeasibly large sample sizes, composite endpoints (CEs) are widely chosen as the primary endpoint. Despite being commonly used, CEs entail challenges in designing and interpreting results. Given that the components may be of different relevance and have different effect sizes, the choice of components must be made carefully. Especially, sample size calculations for composite binary endpoints depend not only on the anticipated effect sizes and event probabilities of the composite components but also on the correlation between them. However, information on the correlation between endpoints is usually not reported in the literature which can be an obstacle for designing future sound trials. We consider two-arm randomized controlled trials with a primary composite binary endpoint and an endpoint that consists only of the clinically more important component of the CE. We propose a trial design that allows an adaptive modification of the primary endpoint based on blinded information obtained at an interim analysis. Especially, we consider a decision rule to select between a CE and its most relevant component as primary endpoint. The decision rule chooses the endpoint with the lower estimated required sample size. Additionally, the sample size is reassessed using the estimated event probabilities and correlation, and the expected effect sizes of the composite components. We investigate the statistical power and significance level under the proposed design through simulations. We show that the adaptive design is equally or more powerful than designs without adaptive modification on the primary endpoint. Besides, the targeted power is achieved even if the correlation is misspecified at the planning stage while maintaining the type 1 error. All the computations are implemented in R and illustrated by means of a peritoneal dialysis trial.

Immunogenicity and reactogenicity of a first booster with BNT162b2 or full-dose mRNA-1273: A randomised VACCELERATE trial in adults ≥75 years (EU-COVAT-1)

BACKGROUND

Vaccination remains crucial for protection against severe SARS-CoV-2 infection, especially for people of advanced age, however, optimal dosing regimens are as yet lacking.

METHODS

EU-COVAT-1-AGED Part A is a randomised controlled, adaptive, multicentre phase II trial evaluating safety and immunogenicity of a 3rd vaccination (1st booster) in individuals ≥75 years. Fifty-three participants were randomised to full-doses of either mRNA-1273 (Spikevax®, 100 µg) or BNT162b2 (Comirnaty®, 30 µg). The primary endpoint was the rate of 2-fold circulating antibody titre increase 14 days post-vaccination measured by quantitative electrochemiluminescence (ECL) immunoassay, targeting RBD region of Wuhan wild-type SARS-CoV-2. Secondary endpoints included the changes in neutralising capacity against wild-type and 25 variants of concern at 14 days and up to 12 months. Safety was assessed by monitoring of solicited adverse events (AEs) for seven days after on-study vaccination. Unsolicited AEs were collected until the end of follow-up at 12 months, SAEs were pursued for a further 30 days.

RESULTS

Between 08th of November 2021 and 04th of January 2022, 53 participants ≥75 years received a COVID-19 vaccine as 1st booster. Fifty subjects (BNT162b2 n = 25/mRNA-1273 n = 25) were included in the analyses for immunogenicity at day 14. The primary endpoint of a 2-fold anti-RBD IgG titre increase 14 days after vaccination was reached for all subjects. A 3rd vaccination of full-dose mRNA-1273 provided higher anti-RBD IgG titres (Geometric mean titre) D14 mRNA-127310711 IU/mL (95 %-CI: 8003;14336) vs. BNT162b2: 7090 IU/mL (95 %-CI: 5688;8837). We detected a pattern showing higher neutralising capacity of full-dose mRNA-1273 against wild-type as well as for 23 out of 25 tested variants.

INTERPRETATION

Third doses of either BNT162b2 or mRNA-1273 provide substantial circulating antibody increase 14 days after vaccination. Full-dose mRNA-1273 provides higher antibody levels with an overall similar safety profile for people ≥75 years.

FUNDING

This trial was funded by the European Commission (Framework Program HORIZON 2020).

The impact of religion on changes in end-of-life practices in European intensive care units: a comparative analysis over 16 years

PURPOSE

Religious beliefs affect end-of-life practices in intensive care units (ICUs). Changes over time in end-of-life practices were not investigated regarding religions.

METHODS

Twenty-two European ICUs (3 regions: Northern, Central, and Southern Europe) participated in both Ethicus-1 (years 1999-2000) and Ethicus-2 studies (years 2015-2016). Data of ICU patients who died or had limitations of life-sustaining therapy were analysed regarding changes in end-of-life practices and patient/physician religious affiliations. Frequencies, timing of decision-making, and religious affiliations of physicians/patients were compared using the same definitions.

RESULTS

In total, 4592 adult ICU patients (n = 2807 Ethicus-1, n = 1785 Ethicus-2) were analysed. In both studies, patient and physician religious affiliations were mostly Catholic, Greek Orthodox, Jewish, Protestant, or unknown. Treating physicians (but not patients) commonly reported no religious affiliation (18%). Distribution of end-of-life practices with respect to religion and geographical regions were comparable between the two studies. Withholding [n = 1143 (40.7%) Ethicus-1 and n = 892 (50%) Ethicus-2] and withdrawing [n = 695 (24.8%) Ethicus-1 and n = 692 (38.8%) Ethicus-2] were most commonly decided. No significant changes in end-of-life practices were observed for any religion over 16 years. The number of end-of-life discussions with patients/ families/ physicians increased, while mortality and time until first decision decreased.

CONCLUSIONS

Changes in end-of-life practices observed over 16 years appear unrelated to religious affiliations of ICU patients or their treating physicians, but the effects of religiosity and/or culture could not be assessed. Shorter time until decision in the ICU and increased numbers of patient and family discussions may indicate increased awareness of the importance of end-of-life decision-making in the ICU.

Are early post-discharge physician contacts associated with 30-day psychiatric re-hospitalisation? A nationwide claims data based retrospective cohort study in Austria free of immortal time bias

OBJECTIVES

Cost containment and quality of care considerations have increased research interest in the potential preventability of early re-hospitalisations. Various registry-based retrospective cohort studies on psychiatric re-hospitalisation have focused on the role of early post-discharge service contacts, but either did not consider their time-dependent nature ('immortal time bias') or evaded the issue by analysing late re-hospitalisations. The present study takes care of the immortal time bias in studying early psychiatric re-hospitalisations.

METHODS

In a retrospective cohort study using nationwide electronic claims data in Austria, 10,689 adults discharged from acute psychiatric inpatient wards were followed up for 30 days. Cox regression analyses were performed with post-discharge psychiatric and general practitioner contacts as time-dependent covariates and time to first psychiatric re-hospitalisation as outcome.

RESULTS

Post-discharge ambulatory physician contacts were significantly associated with a decreased psychiatric re-hospitalisation rate (hazard ratio 0.77 [95% CI 0.69; 0.87], p < 0.0001), with similarly strong contributions to this association by general practitioners and psychiatrists.

CONCLUSIONS

Despite avoiding the immortal time bias and controlling for several confounders, we suggest to be cautious with a causal interpretation of the identified association, since potentially relevant confounders, such as disease severity, were unavailable in our claims data base.

Comparing maximum diameter and volume when assessing the growth of small abdominal aortic aneurysms using longitudinal CTA data: cohort study

BACKGROUND

Monitoring of abdominal aortic aneurysms (AAAs) is currently based on serial measurements of maximum aortic diameter. Additional assessment of aneurysm volume has previously been proposed to possibly improve growth prediction and treatment decisions. To evaluate the use of supplementing volume measurements, the authors aimed to characterise the growth distribution of AAA volume and to compare the growth rates of the maximum diameter and volume at the patient level.

METHODS

Maximum diameter and volume were monitored every 6 months in 84 patients with small AAAs, with a total of 331 computed tomographic angiographies (with initial maximum diameters of 30-68 mm). A previously developed statistical growth model for AAAs was applied to assess the growth distribution of volume and to compare individual growth rates for volume and for maximum diameter.

RESULTS

The median (25-75% quantile) expansion in volume was 13.4 (6.5-24.7) % per year. Cube root transformed volume and maximum diameter showed a closely linear association with a within-subject correlation of 0.77. At the surgery threshold maximum diameter of 55 mm, the median (25-75% quantile) volume was 132 (103-167) ml. In 39% of subjects, growth rates for volume and maximum diameter were equivalent, in 33% growth was faster in volume and in 27% growth was faster in maximum diameter.

CONCLUSION

At the population level, volume and maximum diameter show a substantial association such that the average volume is approximately proportional to the average maximum diameter raised to a power of three. At the individual level, however, in the majority of patient's AAAs grow at different pace in different dimensions. Hence, closer monitoring of aneurysms with sub-critical diameter but suspicious morphology may benefit from complementing maximum diameter by volume or related measurements.

Online error rate control for platform trials

Platform trials evaluate multiple experimental treatments under a single master protocol, where new treatment arms are added to the trial over time. Given the multiple treatment comparisons, there is the potential for inflation of the overall type I error rate, which is complicated by the fact that the hypotheses are tested at different times and are not necessarily pre-specified. Online error rate control methodology provides a possible solution to the problem of multiplicity for platform trials where a relatively large number of hypotheses are expected to be tested over time. In the online multiple hypothesis testing framework, hypotheses are tested one-by-one over time, where at each time-step an analyst decides whether to reject the current null hypothesis without knowledge of future tests but based solely on past decisions. Methodology has recently been developed for online control of the false discovery rate as well as the familywise error rate (FWER). In this article, we describe how to apply online error rate control to the platform trial setting, present extensive simulation results, and give some recommendations for the use of this new methodology in practice. We show that the algorithms for online error rate control can have a substantially lower FWER than uncorrected testing, while still achieving noticeable gains in power when compared with the use of a Bonferroni correction. We also illustrate how online error rate control would have impacted a currently ongoing platform trial.

On the use of non-concurrent controls in platform trials: a scoping review

BACKGROUND

Platform trials gained popularity during the last few years as they increase flexibility compared to multi-arm trials by allowing new experimental arms entering when the trial already started. Using a shared control group in platform trials increases the trial efficiency compared to separate trials. Because of the later entry of some of the experimental treatment arms, the shared control group includes concurrent and non-concurrent control data. For a given experimental arm, non-concurrent controls refer to patients allocated to the control arm before the arm enters the trial, while concurrent controls refer to control patients that are randomised concurrently to the experimental arm. Using non-concurrent controls can result in bias in the estimate in case of time trends if the appropriate methodology is not used and the assumptions are not met.

METHODS

We conducted two reviews on the use of non-concurrent controls in platform trials: one on statistical methodology and one on regulatory guidance. We broadened our searches to the use of external and historical control data. We conducted our review on the statistical methodology in 43 articles identified through a systematic search in PubMed and performed a review on regulatory guidance on the use of non-concurrent controls in 37 guidelines published on the EMA and FDA websites.

RESULTS

Only 7/43 of the methodological articles and 4/37 guidelines focused on platform trials. With respect to the statistical methodology, in 28/43 articles, a Bayesian approach was used to incorporate external/non-concurrent controls while 7/43 used a frequentist approach and 8/43 considered both. The majority of the articles considered a method that downweights the non-concurrent control in favour of concurrent control data (34/43), using for instance meta-analytic or propensity score approaches, and 11/43 considered a modelling-based approach, using regression models to incorporate non-concurrent control data. In regulatory guidelines, the use of non-concurrent control data was considered critical but was deemed acceptable for rare diseases in 12/37 guidelines or was accepted in specific indications (12/37). Non-comparability (30/37) and bias (16/37) were raised most often as the general concerns with non-concurrent controls. Indication specific guidelines were found to be most instructive.

CONCLUSIONS

Statistical methods for incorporating non-concurrent controls are available in the literature, either by means of methods originally proposed for the incorporation of external controls or non-concurrent controls in platform trials. Methods mainly differ with respect to how the concurrent and non-concurrent data are combined and temporary changes handled. Regulatory guidance for non-concurrent controls in platform trials are currently still limited.

Nationwide analysis of hospital admissions and outcomes of patients with SARS-CoV-2 infection in Austria in 2020 and 2021

This retrospective study evaluated temporal and regional trends of patient admissions to hospitals, intensive care units (ICU), and intermediate care units (IMCU) as well as outcomes during the COVID-19 pandemic in Austria. We analysed anonymous data from patients admitted to Austrian hospitals with COVID-19 between January 1st, 2020 and December 31st, 2021. We performed descriptive analyses and logistic regression analyses for in-hospital mortality, IMCU or ICU admission, and in-hospital mortality following ICU admission. 68,193 patients were included, 8304 (12.3%) were primarily admitted to ICU, 3592 (5.3%) to IMCU. Hospital mortality was 17.3%; risk factors were male sex (OR 1.67, 95% CI 1.60-1.75, p < 0.001) and high age (OR 7.86, 95% CI 7.07-8.74, p < 0.001 for 90+ vs. 60-64 years). Mortality was higher in the first half of 2020 (OR 1.15, 95% CI 1.04-1.27, p = 0.01) and the second half of 2021 (OR 1.11, 95% CI 1.05-1.17, p < 0.001) compared to the second half of 2020 and differed regionally. ICU or IMCU admission was most likely between 55 and 74 years, and less likely in younger and older age groups. We find mortality in Austrian COVID-19-patients to be almost linearly associated with age, ICU admission to be less likely in older individuals, and outcomes to differ between regions and over time.

Red blood cell transfusion-related eicosanoid profiles in intensive care patients—A prospective, observational feasibility study

Introduction: Eicosanoids are bioactive lipids present in packed red blood cells (PRBCs), and might play a role in transfusion-related immunomodulation (TRIM). We tested the feasibility of analyzing eicosanoid profiles in PRBC supernatant and in plasma samples of postoperative intensive care unit (ICU) patients transfused with one unit of PRBCs.

Methods: We conducted a prospective, observational feasibility study enrolling postoperative ICU patients: 1) patients treated with acetylsalicylic acid following abdominal aortic surgery (Aorta); 2) patients on immunosuppressants after bilateral lung transplantation (LuTx); and 3) patients undergoing other types of major surgery (Comparison). Abundances of arachidonic acid (AA) and seven pre-defined eicosanoids were assessed by liquid chromatography and tandem mass spectrometry. PRBC supernatant was sampled directly from the unit immediately prior to transfusion. Spearman’s correlations between eicosanoid abundance in PRBCs and storage duration were assessed. Patient plasma was collected at 30-min intervals: Three times each before and after transfusion. To investigate temporal changes in eicosanoid abundances, we fitted linear mixed models.

Results: Of 128 patients screened, 21 were included in the final analysis (Aorta n = 4, LuTx n = 8, Comparison n = 9). In total, 21 PRBC and 125 plasma samples were analyzed. Except for 20-hydroxyeicosatetraenoic acid (HETE), all analyzed eicosanoids were detectable in PRBCs, and their abundance positively correlated with storage duration of PRBCs. While 5-HETE, 12-HETE/8-HETE, 15-HETE, 20-HETE, and AA were detectable in virtually all plasma samples, 9-HETE and 11-HETE were detectable in only 57% and 23% of plasma samples, respectively.

Conclusions: Recruitment of ICU patients into this transfusion study was challenging but feasible. Eicosanoid abundances increased in PRBC supernatants during storage. In plasma of ICU patients, eicosanoid abundances were ubiquitously detectable and showed limited fluctuations over time prior to transfusion. Taken together, larger clinical studies seem warranted and feasible to further investigate the role of PRBC-derived eicosanoids in TRIM.

Association of immediate versus delayed extubation of patients admitted to intensive care units postoperatively and outcomes: A retrospective study

AIM OF THIS STUDY

This study seeks to investigate, whether extubation of tracheally intubated patients admitted to intensive care units (ICU) postoperatively either immediately at the day of admission (day 1) or delayed at the first postoperative day (day 2) is associated with differences in outcomes.

MATERIALS AND METHODS

We performed a retrospective analysis of data from an Austrian ICU registry. Adult patients admitted between January 1st, 2012 and December 31st, 2019 following elective and emergency surgery, who were intubated at the day 1 and were extubated at day 1 or day 2, were included. We performed logistic regression analyses for in-hospital mortality and over-sedation or agitation following extubation.

RESULTS

52 982 patients constituted the main study population. 1 231 (3.3%) patients extubated at day 1 and 958 (5.9%) at day 2 died in hospital, 464 (1.3%) patients extubated at day 1 and 613 (3.8%) at day 2 demonstrated agitation or over-sedation after extubation during ICU stay; OR (95% CI) for in-hospital mortality were OR 1.17 (1.01-1.35, p = 0.031) and OR 2.15 (1.75-2.65, p<0.001) for agitation or over-sedation.

CONCLUSIONS

We conclude that immediate extubation as soon as deemed feasible by clinicians is associated with favourable outcomes and may thus be considered preferable in tracheally intubated patients admitted to ICU postoperatively.

Online control of the False Discovery Rate in group-sequential platform trials

When testing multiple hypotheses, a suitable error rate should be controlled even in exploratory trials. Conventional methods to control the False Discovery Rate assume that all p-values are available at the time point of test decision. In platform trials, however, treatment arms enter and leave the trial at different times during its conduct. Therefore, the actual number of treatments and hypothesis tests is not fixed in advance and hypotheses are not tested at once, but sequentially. Recently, for such a setting the concept of online control of the False Discovery Rate was introduced. We propose several heuristic variations of the LOND procedure (significance Levels based On Number of Discoveries) that incorporate interim analyses for platform trials, and study their online False Discovery Rate via simulations. To adjust for the interim looks spending functions are applied with O'Brien-Fleming or Pocock type group-sequential boundaries. The power depends on the prior distribution of effect sizes, for example, whether true alternatives are uniformly distributed over time or not. We consider the choice of design parameters for the LOND procedure to maximize the overall power and investigate the impact on the False Discovery Rate by including both concurrent and non-concurrent control data.

Estimands and Complex Innovative Designs

Since the release of the ICH E9(R1) (International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use Addendum on Estimands and Sensitivity Analysis in Clinical Trials to the Guideline on Statistical Principles for Clinical Trials) document in 2019, the estimand framework has become a fundamental part of clinical trial protocols. In parallel, complex innovative designs have gained increased popularity in drug development, in particular in early development phases or in difficult experimental situations. While the estimand framework is relevant to any study in which a treatment effect is estimated, experience is lacking as regards its application to these designs. In a basket trial for example, should a different estimand be specified for each subpopulation of interest, defined, for example, by cancer site? Or can a single estimand focusing on the general population (defined, for example, by the positivity to a certain biomarker) be used? In the case of platform trials, should a different estimand be proposed for each drug investigated? In this work we discuss possible ways of implementing the estimand framework for different types of complex innovative designs. We consider trials that allow adding or selecting experimental treatment arms, modifying the control arm or the standard of care, and selecting or pooling populations. We also address the potentially data-driven, adaptive selection of estimands in an ongoing trial and disentangle certain statistical issues that pertain to estimation rather than to estimands, such as the borrowing of nonconcurrent information. We hope this discussion will facilitate the implementation of the estimand framework and its description in the study protocol when the objectives of the trial require complex innovative designs.

A multinational, phase 2, randomised, adaptive protocol to evaluate immunogenicity and reactogenicity of different COVID-19 vaccines in adults ≥75 already vaccinated against SARS-CoV-2 (EU-COVAT-1-AGED): a trial conducted within the VACCELERATE network

Background

In the ongoing COVID-19 pandemic, advanced age is a risk factor for a severe clinical course of SARS-CoV-2 infection. Thus, older people may benefit in particular from booster doses with potent vaccines and research should focus on optimal vaccination schedules. In addition to each individual’s medical history, immunosenescence warrants further research in this population. This study investigates vaccine-induced immune response over 1 year.

Methods/design

EU-COVAT-1-AGED is a randomised controlled, adaptive, multicentre phase II protocol evaluating different booster strategies in individuals aged ≥75 years (n=600) already vaccinated against SARS-CoV-2. The initial protocol foresaw a 3rd vaccination (1st booster) as study intervention. The present modified Part B of this trial foresees testing of mRNA-1273 (Spikevax®) vs. BNT162b2 (Comirnaty®) as 4th vaccination dose (2nd booster) for comparative assessment of their immunogenicity and safety against SARS-CoV-2 wild-type and variants. The primary endpoint of the trial is to assess the rate of 2-fold antibody titre increase 14 days after vaccination measured by quantitative enzyme-linked immunosorbent assay (Anti-RBD-ELISA) against wild-type virus. Secondary endpoints include the changes in neutralising antibody titres (Virus Neutralisation Assay) against wild-type as well as against Variants of Concern (VOC) at 14 days and up to 12 months. T cell response measured by qPCR will be performed in subgroups at 14 days as exploratory endpoint. Biobanking samples are being collected for neutralising antibody titres against potential future VOC. Furthermore, potential correlates between humoral immune response, T cell response and neutralising capacity will be assessed.

The primary endpoint analysis will be triggered as soon as for all patients the primary endpoint (14 days after the 4th vaccination dose) has been observed.

Discussion

The EU-COVAT-1-AGED trial Part B compares immunogenicity and safety of mRNA-1273 (Spikevax®) and BNT162b2 (Comirnaty®) as 4th SARS-CoV-2 vaccine dose in adults ≥75 years of age. The findings of this trial have the potential to optimise the COVID-19 vaccination strategy for this at-risk population.

Trial registration

ClinicalTrials.govNCT05160766. Registered on 16 December 2021.

Protocol version: V06_0: 27 July 2022

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06791-y.

Impact of adaptive filtering on power and false discovery rate in RNA-seq experiments

Background

In RNA-sequencing studies a large number of hypothesis tests are performed to compare the differential expression of genes between several conditions. Filtering has been proposed to remove candidate genes with a low expression level which may not be relevant and have little or no chance of showing a difference between conditions. This step may reduce the multiple testing burden and increase power.

Results

We show in a simulation study that filtering can lead to some increase in power for RNA-sequencing data, too aggressive filtering, however, can lead to a decline. No uniformly optimal filter in terms of power exists. Depending on the scenario different filters may be optimal. We propose an adaptive filtering strategy which selects one of several filters to maximise the number of rejections. No additional adjustment for multiplicity has to be included, but a rule has to be considered if the number of rejections is too small.

Conclusions

For a large range of simulation scenarios, the adaptive filter maximises the power while the simulated False Discovery Rate is bounded by the pre-defined significance level. Using the adaptive filter, it is not necessary to pre-specify a single individual filtering method optimised for a specific scenario.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04928-z.

On model-based time trend adjustments in platform trials with non-concurrent controls

BACKGROUND

Platform trials can evaluate the efficacy of several experimental treatments compared to a control. The number of experimental treatments is not fixed, as arms may be added or removed as the trial progresses. Platform trials are more efficient than independent parallel group trials because of using shared control groups. However, for a treatment entering the trial at a later time point, the control group is divided into concurrent controls, consisting of patients randomised to control when that treatment arm is in the platform, and non-concurrent controls, patients randomised before. Using non-concurrent controls in addition to concurrent controls can improve the trial's efficiency by increasing power and reducing the required sample size, but can introduce bias due to time trends.

METHODS

We focus on a platform trial with two treatment arms and a common control arm. Assuming that the second treatment arm is added at a later time, we assess the robustness of recently proposed model-based approaches to adjust for time trends when utilizing non-concurrent controls. In particular, we consider approaches where time trends are modeled either as linear in time or as a step function, with steps at time points where treatments enter or leave the platform trial. For trials with continuous or binary outcomes, we investigate the type 1 error rate and power of testing the efficacy of the newly added arm, as well as the bias and root mean squared error of treatment effect estimates under a range of scenarios. In addition to scenarios where time trends are equal across arms, we investigate settings with different time trends or time trends that are not additive in the scale of the model.

RESULTS

A step function model, fitted on data from all treatment arms, gives increased power while controlling the type 1 error, as long as the time trends are equal for the different arms and additive on the model scale. This holds even if the shape of the time trend deviates from a step function when patients are allocated to arms by block randomisation. However, if time trends differ between arms or are not additive to treatment effects in the scale of the model, the type 1 error rate may be inflated.

CONCLUSIONS

The efficiency gained by using step function models to incorporate non-concurrent controls can outweigh potential risks of biases, especially in settings with small sample sizes. Such biases may arise if the model assumptions of equality and additivity of time trends are not satisfied. However, the specifics of the trial, scientific plausibility of different time trends, and robustness of results should be carefully considered.

Rationale for the update algorithm of the graphical approach to sequentially rejective multiple test procedures

The graphical approach by Bretz et al. is a convenient tool to construct, visualize and perform multiple test procedures that are tailored to structured families of hypotheses while controlling the familywise error rate. A critical step is to update the transition weights following a pre-specified algorithm. In their original publication, however, the authors did not provide a detailed rationale for the update formula. This paper closes the gap and provides three alternative arguments for the update of the transition weights of the graphical approach. It is a legacy of the first author, based on an unpublished technical report from 2014, and after his untimely death reconstructed by the other two authors as a tribute to Willi Maurer's collaboration with Andy Grieve and contributions to biostatistics over many years.

Association of modifiable factors with the development of physical fitness of Austrian primary school children: A 4-year longitudinal study

Physical fitness (PF) shows favourable associations with several health indicators in children. Children's PF depends on a variety of non-modifiable (e.g., sex and age) and modifiable factors (e.g., weight status and sports participation). The aim of this study was to evaluate the impact of modifiable and non-modifiable factors on the development of PF during the 4 years of primary school. A longitudinal study was carried out with 265 children. PF was assessed using the German Motor Performance Test 6-18, whereas modifiable and non-modifiable factors with parent's and children's questionnaires. Total PF z-score increased by 1.4 standard deviations from 1^st to 4^th year and raw values of subtests improved by an average of about 40%. The variables "parents' physical activity", "never being overweight", "sports club participation", and "playing outside" were positively associated with PF development. The present study highlights that a variety of modifiable factors, both from children and their parents, are significantly associated with the development of children's PF during primary education. Interventions should not only focus on direct actions, such as proposing specific exercise programs, but also aim at increasing parents' awareness of their role model function in endorsing their children's healthy active lifestyle, especially at early ages.

Validation of bedside ultrasound to predict lumbar muscle area in the computed tomography in 200 non-critically ill patients: The USVALID prospective study

BACKGROUND & AIMS

Skeletal muscle area (SMA) in the computed tomography (CT) at the third lumbar vertebra (L3) level is a proxy for whole-body muscle mass but is only performed for clinical reasons. Ultrasound is a promising tool to determine muscle mass at the bedside. It is still unclear how well ultrasound and which ultrasound measuring points can predict CT L3 SMA.

METHODS

This prospective observational trial included 200 non-critically ill patients, who underwent an abdominal CT scan for any clinical reason within 48 h before the ultrasound examination. Ultrasound muscle thickness was evaluated at 3 measuring points on the thigh and 2 measuring points on the upper arm with minimal compression. On the CT scan, the entire L3 SMA was measured based on Hounsfield units. Using a model selection algorithm based on the Bayesian information criterion (BIC) and clinical considerations, a linear prediction model for CT L3 SMA based on the ultrasound muscle thickness and other independent variables was fitted and assessed with cross-validation.

RESULTS

67,5% and 32,5% of the patients were from surgical and medical wards, respectively. Mean ultrasound muscle thickness values were between 2,2 and 3,6 cm on the thigh and between 1,4 and 2,8 cm on the upper arm. All ultrasound muscle thickness values were higher in men than in women (P < 0,05). CT L3 SMA was 40 cm² higher in men than in women (P < 0,001). The final prediction model for CT L3 SMA included the following 4 independent variables: ultrasound muscle thickness at the ventral measuring point of the thigh in the short-axis plane, sex, weight, and height. It had a similar BIC (BIC of 1515) compared to larger models with 6-8 independent variables including multiple ultrasound measuring points (BIC of 1506-1519). Additional clinical considerations to choose the final model were less time consumption when measuring a single ultrasound measuring point and better anatomical overview at the short-axis plane. The final model predicted CT L3 SMA with a R² of 0,74 (P < 0,001) and a cross-validated R² of 0,65.

CONCLUSIONS

One single ultrasound measuring point at the thigh together with sex, height and weight very well predicts CT L3 SMA across different clinical populations. Ultrasound is a safe and bedside method to measure muscle thickness longitudinally to monitor the effects of nutrition and physical therapy.

Sex Differences in Kidney Transplantation: Austria and the United States, 1978–2018

Background

Systematic analyses about sex differences in wait-listing and kidney transplantation after dialysis initiation are scarce. We aimed at identifying sex-specific disparities along the path of kidney disease treatment, comparing two countries with distinctive health care systems, the US and Austria, over time.

Methods

We analyzed subjects who initiated dialysis from 1979–2018, in observational cohort studies from the US and Austria. We used Cox regression to model male-to-female cause-specific hazard ratios (csHRs, 95% confidence intervals) for transitions along the consecutive states dialysis initiation, wait-listing, kidney transplantation and death, adjusted for age and stratified by country and decade of dialysis initiation.

Results

Among 3,053,206 US and 36,608 Austrian patients starting dialysis, men had higher chances to enter the wait-list, which however decreased over time [male-to-female csHRs for wait-listing, 1978–1987: US 1.94 (1.71, 2.20), AUT 1.61 (1.20, 2.17); 2008–2018: US 1.35 (1.32, 1.38), AUT 1.11 (0.94, 1.32)]. Once wait-listed, the advantage of the men became smaller, but persisted in the US [male-to-female csHR for transplantation after wait-listing, 2008–2018: 1.08 (1.05, 1.11)]. The greatest disparity between men and women occurred in older age groups in both countries [male-to-female csHR for wait-listing after dialysis, adjusted to 75% age quantile, 2008–2018: US 1.83 (1.74, 1.92), AUT 1.48 (1.02, 2.13)]. Male-to-female csHRs for death were close to one, but higher after transplantation than after dialysis.

Conclusions

We found evidence for sex disparities in both countries. Historically, men in the US and Austria had 90%, respectively, 60% higher chances of being wait-listed for kidney transplantation, although these gaps decreased over time. Efforts should be continued to render kidney transplantation equally accessible for both sexes, especially for older women.

Robust group sequential designs for trials with survival endpoints and delayed response

Randomized clinical trials in oncology typically utilize time-to-event endpoints such as progression-free survival or overall survival as their primary efficacy endpoints, and the most commonly used statistical test to analyze these endpoints is the log-rank test. The power of the log-rank test depends on the behavior of the hazard ratio of the treatment arm to the control arm. Under the assumption of proportional hazards, the log-rank test is asymptotically fully efficient. However, this proportionality assumption does not hold true if there is a delayed treatment effect. Cancer immunology has evolved over time and several cancer vaccines are available in the market for treating existing cancers. This includes sipuleucel-T for metastatic hormone-refractory prostate cancer, nivolumab for metastatic melanoma, and pembrolizumab for advanced nonsmall-cell lung cancer. As cancer vaccines require some time to elicit an immune response, a delayed treatment effect is observed, resulting in a violation of the proportional hazards assumption. Thus, the traditional log-rank test may not be optimal for testing immuno-oncology drugs in randomized clinical trials. Moreover, the new immuno-oncology compounds have been shown to be very effective in prolonging overall survival. Therefore, it is desirable to implement a group sequential design with the possibility of early stopping for overwhelming efficacy. In this paper, we investigate the max-combo test, which utilizes the maximum of two weighted log-rank statistics, as a robust alternative to the log-rank test. The new test is implemented for two-stage designs with possible early stopping at the interim analysis time point. Two classes of weights are investigated for the max-combo test: the Fleming and Harrington (1981) G ρ , γ weights and the Magirr and Burman (2019) modest ( τ ∗ )  weights.

Growth prediction model for abdominal aortic aneurysms

BACKGROUND

The most relevant determinant in scheduling monitoring intervals for abdominal aortic aneurysms (AAAs) is maximum diameter. The aim of the study was to develop a statistical model that takes into account specific characteristics of AAA growth distributions such as between-patient variability as well as within-patient variability across time, and allows probabilistic statements to be made regarding expected AAA growth.

METHODS

CT angiography (CTA) data from patients monitored at 6-month intervals with maximum AAA diameters at baseline between 30 and 66 mm were used to develop the model. By extending the model of geometric Brownian motion with a log-normal random effect, a stochastic growth model was developed. An additional set of ultrasound-based growth data was used for external validation.

RESULTS

The study data included 363 CTAs from 87 patients, and the external validation set comprised 390 patients. Internal and external cross-validation showed that the stochastic growth model allowed accurate description of the distribution of aneurysm growth. Median relative growth within 1 year was 4.1 (5-95 per cent quantile 0.5-13.3) per cent. Model calculations further resulted in relative 1-year growth of 7.0 (1.0-16.4) per cent for patients with previously observed rapid 1-year growth of 10 per cent, and 2.6 (0.3-8.3) per cent for those with previously observed slow growth of 1 per cent. The probability of exceeding a threshold of 55 mm was calculated to be 1.78 per cent at most when adhering to the current RESCAN guidelines for rescreening intervals. An online calculator based on the fitted model was made available.

CONCLUSION

The stochastic growth model was found to provide a reliable tool for predicting AAA growth.

An international comparison of age and sex dependency of COVID-19 deaths in 2020: a descriptive analysis

The number of reported coronavirus disease (COVID-19) deaths per 100,000 persons observed so far in 2020 is described in 15 European countries and the USA as dependent on age groups and sex. It is compared with the corresponding historic all-cause mortality per year depending on age and sex observed in these countries. Some common features exist although substantial differences in age and sex dependency of COVID-19 mortality were noted between countries. An exponential increase with age is a good model to describe and analyze both COVID-19 and all-cause mortality above 40 years old, where almost all COVID-19 deaths occur. Moreover, age dependency is stronger for COVID-19 mortality than for all-cause mortality, and males have an excess risk compared with women, which is less pronounced in the higher age groups. Additionally, concerning calendar time, differences in the age and sex dependency between countries were noted with the common tendency that male excess risk for COVID-19 mortality was smaller in the second half of the year.

Variations in end-of-life practices in intensive care units worldwide (Ethicus-2): a prospective observational study

BACKGROUND

End-of-life practices vary among intensive care units (ICUs) worldwide. Differences can result in variable use of disproportionate or non-beneficial life-sustaining interventions across diverse world regions. This study investigated global disparities in end-of-life practices.

METHODS

In this prospective, multinational, observational study, consecutive adult ICU patients who died or had a limitation of life-sustaining treatment (withholding or withdrawing life-sustaining therapy and active shortening of the dying process) during a 6-month period between Sept 1, 2015, and Sept 30, 2016, were recruited from 199 ICUs in 36 countries. The primary outcome was the end-of-life practice as defined by the end-of-life categories: withholding or withdrawing life-sustaining therapy, active shortening of the dying process, or failed cardiopulmonary resuscitation (CPR). Patients with brain death were included in a separate predefined end-of-life category. Data collection included patient characteristics, diagnoses, end-of-life decisions and their timing related to admission and discharge, or death, with comparisons across different regions. Patients were studied until death or 2 months from the first limitation decision.

FINDINGS

Of 87 951 patients admitted to ICU, 12 850 (14·6%) were included in the study population. The number of patients categorised into each of the different end-of-life categories were significantly different for each region (p<0·001). Limitation of life-sustaining treatment occurred in 10 401 patients (11·8% of 87 951 ICU admissions and 80·9% of 12 850 in the study population). The most common limitation was withholding life-sustaining treatment (5661 [44·1%]), followed by withdrawing life-sustaining treatment (4680 [36·4%]). More treatment withdrawing was observed in Northern Europe (1217 [52·8%] of 2305) and Australia/New Zealand (247 [45·7%] of 541) than in Latin America (33 [5·8%] of 571) and Africa (21 [13·0%] of 162). Shortening of the dying process was uncommon across all regions (60 [0·5%]). One in five patients with treatment limitations survived hospitalisation. Death due to failed CPR occurred in 1799 (14%) of the study population, and brain death occurred in 650 (5·1%). Failure of CPR occurred less frequently in Northern Europe (85 [3·7%] of 2305), Australia/New Zealand (23 [4·3%] of 541), and North America (78 [8·5%] of 918) than in Africa (106 [65·4%] of 162), Latin America (160 [28·0%] of 571), and Southern Europe (590 [22·5%] of 2622). Factors associated with treatment limitations were region, age, and diagnoses (acute and chronic), and country end-of-life legislation.

INTERPRETATION

Limitation of life-sustaining therapies is common worldwide with regional variability. Withholding treatment is more common than withdrawing treatment. Variations in type, frequency, and timing of end-of-life decisions were observed. Recognising regional differences and the reasons behind these differences might help improve end-of-life care worldwide.

FUNDING

None.

Analysis of the specificity of a COVID-19 antigen test in the Slovak mass testing program

AIMS

Mass antigen testing programs have been challenged because of an alleged insufficient specificity, leading to a large number of false positives. The objective of this study is to derive a lower bound of the specificity of the SD Biosensor Standard Q Ag-Test in large scale practical use.

METHODS

Based on county data from the nationwide tests for SARS-CoV-2 in Slovakia between 31.10.-1.11. 2020 we calculate a lower confidence bound for the specificity. As positive test results were not systematically verified by PCR tests, we base the lower bound on a worst case assumption, assuming all positives to be false positives.

RESULTS

3,625,332 persons from 79 counties were tested. The lowest positivity rate was observed in the county of Rožňava where 100 out of 34307 (0.29%) tests were positive. This implies a test specificity of at least 99.6% (97.5% one-sided lower confidence bound, adjusted for multiplicity).

CONCLUSION

The obtained lower bound suggests a higher specificity compared to earlier studies in spite of the underlying worst case assumption and the application in a mass testing setting. The actual specificity is expected to exceed 99.6% if the prevalence in the respective regions was non-negligible at the time of testing. To our knowledge, this estimate constitutes the first bound obtained from large scale practical use of an antigen test.

The use of external controls: To what extent can it currently be recommended?

With more and better clinical data being captured outside of clinical studies and greater data sharing of clinical studies, external controls may become a more attractive alternative to randomized clinical trials (RCTs). Both industry and regulators recognize that in situations where a randomized study cannot be performed, external controls can provide the needed contextualization to allow a better interpretation of studies without a randomized control. It is also agreed that external controls will not fully replace RCTs as the gold standard for formal proof of efficacy in drug development and the yardstick of clinical research. However, it remains unclear in which situations conclusions about efficacy and a positive benefit/risk can reliably be based on the use of an external control. This paper will provide an overview on types of external control, their applications and the different sources of bias their use may incur, and discuss potential mitigation steps. It will also give recommendations on how the use of external controls can be justified.

Optimizing subgroup selection in two-stage adaptive enrichment and umbrella designs

We design two‐stage confirmatory clinical trials that use adaptation to find the subgroup of patients who will benefit from a new treatment, testing for a treatment effect in each of two disjoint subgroups. Our proposal allows aspects of the trial, such as recruitment probabilities of each group, to be altered at an interim analysis. We use the conditional error rate approach to implement these adaptations with protection of overall error rates. Applying a Bayesian decision‐theoretic framework, we optimize design parameters by maximizing a utility function that takes the population prevalence of the subgroups into account. We show results for traditional trials with familywise error rate control (using a closed testing procedure) as well as for umbrella trials in which only the per‐comparison type 1 error rate is controlled. We present numerical examples to illustrate the optimization process and the effectiveness of the proposed designs.

Collaborative Platform Trials to Fight COVID-19: Methodological and Regulatory Considerations for a Better Societal Outcome

For the development of coronavirus disease 2019 (COVID‐19) drugs during the ongoing pandemic, speed is of essence whereas quality of evidence is of paramount importance. Although thousands of COVID‐19 trials were rapidly started, many are unlikely to provide robust statistical evidence and meet regulatory standards (e.g., because of lack of randomization or insufficient power). This has led to an inefficient use of time and resources. With more coordination, the sheer number of patients in these trials might have generated convincing data for several investigational treatments. Collaborative platform trials, comparing several drugs to a shared control arm, are an attractive solution. Those trials can utilize a variety of adaptive design features in order to accelerate the finding of life‐saving treatments. In this paper, we discuss several possible designs, illustrate them via simulations, and also discuss challenges, such as the heterogeneity of the target population, time‐varying standard of care, and the potentially high number of false hypothesis rejections in phase II and phase III trials. We provide corresponding regulatory perspectives on approval and reimbursement, and note that the optimal design of a platform trial will differ with our societal objective and by stakeholder. Hasty approvals may delay the development of better alternatives, whereas searching relentlessly for the single most efficacious treatment may indirectly diminish the number of lives saved as time is lost. We point out the need for incentivizing developers to participate in collaborative evidence‐generation initiatives when a positive return on investment is not met.

Prediction of plant species occurrence as affected by nitrogen deposition and climate change on a European scale

Plant species occurrence in Europe is affected by changes in nitrogen deposition and climate. Insight into potential future effects of those changes can be derived by a model approach based on field-based empirical evidence on a continental scale. In this paper, we present a newly developed empirical model PROPS, predicting the occurrence probabilities of plant species in response to a combination of climatic factors, nitrogen deposition and soil properties. Parameters included were temperature, precipitation, nitrogen deposition, soil pH and soil C/N ratio. The PROPS model was fitted to plant species occurrence data of about 800,000 European relevés with estimated values for pH and soil C/N ratio and interpolated climate and modelled N deposition data obtained from the Ensemble meteo data set and EMEP model results, respectively. The model was validated on an independent data set. The test of ten species against field data gave an average Pearson's r-value of 0.79. PROPS was applied to a grassland and a heathland site to evaluate the effect of scenarios for nitrogen deposition and climate change on the Habitat Suitability Index (HSI), being the average of the relative probabilities, compared to the maximum probability, of all target species in a habitat. Results for the period 1930-2050 showed that an initial increase and later decrease in nitrogen deposition led to a pronounced decrease in HSI, and with dropping nitrogen deposition to an increase of the HSI. The effect of climate change appeared to be limited, resulting in a slight increase in HSI.

Accidents during mountain hiking and alpine skiing – epidemiological data from the Austrian Alps

This article presents epidemiological data on traumatic accidents during mountain hiking in the summer season and recreational alpine skiing in the Austrian Alps. In mountain hiking, the absolute number of fatalities remained stable from 2006-2014 (32 to 46 victims per year), whereas the number of non-fatal accidents increased by about 5% per year implying a decreasing mortality index. About 75% of all falls happened during the descent and 70% of the victims who sustained a fall-related injury showed defective vision. Mountain hikers should pay attention to sufficient regeneration before and breaks during descending. Additionally, a regular check of visual aids (glasses, contact lenses) can be recommended. In recreational alpine skiing, the injury rate is estimated to be less than 1 injury per 1000 skier days and the traumatic fatality rate amounts to 0.36 traumatic deaths per million skier days. A tear of the anterior cruciate ligament is the most common diagnosis with about 15-21% of all injuries and the risk is 3 times higher in women than in men. Protective equipment and an appropriate skiing speed, depending on skill level, represent preventive measures to reduce injuries and traumatic deaths. Key Words: Traumatic Accidents,Falls, Injuries, Anterior Cruciate Ligament