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Background: We assessed the efficacy and safety of mechanical thrombectomy (MT) in adult stroke patients with anterior circulation large vessel occlusion presenting in the late time window not fulfilling the DEFUSE-3 (Thrombectomy for Stroke at 6 to 16 Hours With Selection by Perfusion Imaging trial) and DAWN (Thrombectomy 6 to 24 Hours After Stroke With a Mismatch Between Deficit and Infarct trial) inclusion criteria. Methods: Cohort study of adults with anterior circulation large vessel occlusion admitted between 6 and 24 hours after last-seen-well at 5 participating Swiss stroke centers between 2014 and 2021. Mismatch was assessed by computer tomography or magnetic resonance imaging perfusion with automated software (RAPID or OLEA). We excluded patients meeting DEFUSE-3 and DAWN inclusion criteria and compared those who underwent MT with those receiving best medical treatment alone by inverse probability of treatment weighting using the propensity score. The primary efficacy end point was a favorable functional outcome at 90 days, defined as a modified Rankin Scale score shift toward lower categories. The primary safety end point was symptomatic intracranial hemorrhage within 7 days of stroke onset; the secondary was all-cause mortality within 90 days. Results: Among 278 patients with anterior circulation large vessel occlusion presenting in the late time window, 190 (68%) did not meet the DEFUSE-3 and DAWN inclusion criteria and thus were included in the analyses. Of those, 102 (54%) received MT. In the inverse probability of treatment weighting analysis, patients in the MT group had higher odds of favorable outcomes compared with the best medical treatment alone group (modified Rankin Scale shift: acOR, 1.46 [1.02–2.10]; P =0.04) and lower odds of all-cause mortality within 90 days (aOR, 0.59 [0.37–0.93]; P =0.02). There were no significant differences in symptomatic intracranial hemorrhage (MT versus best medical treatment alone: 5% versus 2%, P =0.63). Conclusions: Two out of 3 patients with anterior circulation large vessel occlusion presenting in the late time window did not meet the DEFUSE-3 and DAWN inclusion criteria. In these patients, MT was associated with higher odds of favorable functional outcomes without increased rates of symptomatic intracranial hemorrhage. These findings support the enrollment of patients into ongoing randomized trials on MT in the late window with more permissive inclusion criteria.

Background: The DEFUSE-3 and DAWN trials showed that mechanical thrombectomy (MT) improves the outcome of selected patients with anterior circulation large vessel occlusions (LVO) up to 24 h after stroke onset. However, it is unknown whether only those patients fulfilling the trial inclusion criteria benefit, or whether benefit is seen in a broader range of patients presenting between 6 and 24 h. Aims: We determined whether fulfilling the DEFUSE-3 and DAWN selection criteria affects outcomes in MT patients in clinical practice. Methods: We reviewed adult patients with LVO treated with MT between 6 and 24 h after stroke onset at five Swiss stroke centers between 2014 and 2021. We compared two groups: (1) patients who satisfied neither DEFUSE-3 nor DAWN criteria (NDND) and (2) those who satisfied DEFUSE-3 or DAWN criteria (DOD). We used logistic regression to examine the impact of trial eligibility on two safety outcomes (symptomatic intracranial hemorrhage [sICH] and all-cause mortality at 3 months) and two efficacy outcomes (modified Rankin Score [mRS] shift toward lower categories and mRS of 0–2 at 3 months). Results: Of 174 patients who received MT, 102 (59%) belonged to the NDND group. Rates of sICH were similar between the NDND group and the DOD group (3% vs. 4%, p = 1.00). Multivariable regression revealed no differences in 3-month all-cause mortality (aOR 2.07, 95% CI 0.64–6.84, p = 0.23) or functional outcomes (mRS shift: acOR 0.81, 95% CI 0.37–1.79, p = 0.60; mRS 0–2: aOR 0.91, 95% CI 0.31–2.57, p = 0.85). Conclusion: Among adult patients with LVO treated with MT between 6 and 24 h, safety and efficacy outcomes were similar between DEFUSE-3/DAWN eligible and ineligible patients. Our data provide a compelling rationale for randomized trials with broader inclusion criteria for MT.

Effective risk factor modification is the prerequisite to prevent neurovascular disease such as stroke or vascular dementia. Non-traditional vascular risk factors (nt-vrfs) including stress significantly add to the risk of neurovascular disease arising from traditional vascular risk factors (t-vrfs). In order to discover sex-specific changes that may underlie previously reported inclines in the prevalence of neurovascular and cardiovascular disease in women, 10-year trends in the prevalence of vrfs in Switzerland were assessed.Anonymized data from 22,134 participants (51% women) of the governmental Swiss Health Survey, performed every 5 years (2007, 2012 and 2017), were obtained. Epidemiological parameters, t-vrfs and nt-vrfs were analyzed in a cross-sectional study design.Over the observation period, the number of women having full-time jobs increased considerably (2007 38%, 2012 39%, 2017 44%). This was accompanied by a substantial rise in the prevalence of nt-vrfs in women and men including stress at work (2007, not available; 2012 women/men 58%/60%; 2017 women/men 66%/65%), low locus of control (women/men: 2007 21%/19%, 2012 22%/19%, 2017 25%/22%) and sleep disorders (women/men: 2007 30%/22%, 2012 28%/20%, 2017 32%/26%). Amongst t-vrfs, only the prevalence of obesity and hypercholesterolemia increased over time in both sexes, whilst other t-vrfs remained stable (hypertension [27%], diabetes [5%]) or decreased (smoking [9.4 cigarettes/day]).A rise in women's economic participation alongside a higher affection with nt-vrfs in the female Swiss population emphasizes the need to improve vascular risk stratification and implement effective preventive measures for neurovascular and cardiovascular disease.

Climate change not only impacts production and market consumption but also the relative scarcity of nonmarket goods, such as environmental amenities. We study fundamental drivers of the resulting relative price changes, their potential magnitude, and their implications for climate policy in Nordhaus’s Dynamic Integrated Climate-Economy (DICE) model, thereby addressing one of its key criticisms. We propose plausible ranges for these relative prices changes based on best available evidence. Our central calibration reveals that accounting for relative prices is equivalent to decreasing pure time preference by 0.6 percentage points and leads to a more than 50 percent higher social cost of carbon. (JEL D61, H43, Q51, Q54, Q58)

Supplemental material, sj-docx-1-wso-10.1177_17474930221140793 for Mechanical thrombectomy for large vessel occlusion between 6 and 24 h: outcome comparison of DEFUSE-3/DAWN eligible versus non-eligible patients by Tolga D Dittrich, Peter B Sporns, Lilian F Kriemler, Salome Rudin, Anh Nguyen, Annaelle Zietz, Alexandros A Polymeris, Christopher Tränka, Sebastian Thilemann, Benjamin Wagner, Valerian L Altersberger, Ines Piot, Filip Barinka, Martin Hänsel, Henrik Gensicke, Stefan T Engelter, Philippe A Lyrer, Raoul Sutter, Christian H Nickel, Mira Katan, Nils Peters, Lars Michels, Zsolt Kulcsár, Grzegorz M Karwacki, Marco Pileggi, Carlo Cereda, Susanne Wegener, Leo H Bonati, Urs Fischer, Marios Psychogios and Gian Marco De Marchis in International Journal of Stroke

The extent of future climate change is a policy choice. Using an integrated climate-economy assessment model, we estimate climate policy curves (CPCs) that link the price of carbon dioxide (CO2) to subsequent global temperatures. The resulting downward sloping CPCs quantify the inverse relationship between carbon prices and future temperatures and illustrate how climate policy choices determine climate outcomes. Our analysis can account for a variety of climate policies – for example, carbon or fuel taxes, emissions trading programs, green subsidies, and energy-efficiency regulations – all of which can be summarized by means of an effective CO2 price. Importantly, we also examine CPC uncertainty, for example, by perturbing the model's equilibrium climate sensitivity to trace out the temperature range associated with a given CO2 price. Finally, based on the latest Intergovernmental Panel on Climate Change (IPCC) integrated-assessment model scenarios, we estimate an implicit CPC, which provides a high-level IPCC summary of the climate policy actions required to achieve global climate targets.

In many medical applications, interpretable models with high prediction performance are sought. Often, those models are required to handle semi-structured data like tabular and image data. We show how to apply deep transformation models (DTMs) for distributional regression which fulfill these requirements. DTMs allow the data analyst to specify (deep) neural networks for different input modalities making them applicable to various research questions. Like statistical models, DTMs can provide interpretable effect estimates while achieving the state-of-the-art prediction performance of deep neural networks. In addition, the construction of ensembles of DTMs that retain model structure and interpretability allows quantifying epistemic and aleatoric uncertainty. In this study, we compare several DTMs, including baseline-adjusted models, trained on a semi-structured data set of 407 stroke patients with the aim to predict ordinal functional outcome three months after stroke. We follow statistical principles of model-building to achieve an adequate trade-off between interpretability and flexibility while assessing the relative importance of the involved data modalities. We evaluate the models for an ordinal and dichotomized version of the outcome as used in clinical practice. We show that both, tabular clinical and brain imaging data, are useful for functional outcome prediction, while models based on tabular data only outperform those based on imaging data only. There is no substantial evidence for improved prediction when combining both data modalities. Overall, we highlight that DTMs provide a powerful, interpretable approach to analyzing semi-structured data and that they have the potential to support clinical decision making., Preprint under review

Supplemental material, sj-docx-2-wso-10.1177_17474930221140793 for Mechanical thrombectomy for large vessel occlusion between 6 and 24 h: outcome comparison of DEFUSE-3/DAWN eligible versus non-eligible patients by Tolga D Dittrich, Peter B Sporns, Lilian F Kriemler, Salome Rudin, Anh Nguyen, Annaelle Zietz, Alexandros A Polymeris, Christopher Tränka, Sebastian Thilemann, Benjamin Wagner, Valerian L Altersberger, Ines Piot, Filip Barinka, Martin Hänsel, Henrik Gensicke, Stefan T Engelter, Philippe A Lyrer, Raoul Sutter, Christian H Nickel, Mira Katan, Nils Peters, Lars Michels, Zsolt Kulcsár, Grzegorz M Karwacki, Marco Pileggi, Carlo Cereda, Susanne Wegener, Leo H Bonati, Urs Fischer, Marios Psychogios and Gian Marco De Marchis in International Journal of Stroke

We model a stylized economy dependent on agriculture and fisheries to study optimal environmental policy in the face of interacting external effects of ocean acidification, global warming, and eutrophication. This allows us to capture some of the latest insights from research on ocean acidification. Using a static two-sector general equilibrium model we derive optimal rules for national taxes on (Formula presented.) emissions and agricultural run-off and show how they depend on both isolated and interacting damage effects. In addition, we derive a second-best rule for a tax on agricultural run-off of fertilizers for the realistic case that effective internalization of (Formula presented.) externalities is lacking. The results contribute to a better understanding of the social costs of ocean acidification in coastal economies when there is interaction with other environmental stressors. Recommendations for Resource Managers: Marginal environmental damages from (Formula presented.) emissions should be internalized by a tax on (Formula presented.) emissions that is high enough to not only reflect marginal damages from temperature increases, but also marginal damages from ocean acidification and the interaction of both with regional sources of acidification like nutrient run-off from agriculture. In the absence of serious national policies that fully internalize externalities, a sufficiently high tax on regional nutrient run-off of fertilizers used in agricultural production can limit not only marginal environmental damages from nutrient run-off but also account for unregulated carbon emissions. Putting such regional policies in place that consider multiple important drivers of environmental change will be of particular importance for developing coastal economies that are likely to suffer the most from ocean acidification.

We develop a model of optimal carbon taxation and redistribution taking into account horizontal equity concerns by considering heterogeneous energy efficiencies. By deriving first- and second-best rules for policy instruments including carbon taxes, transfers and energy subsidies, we then investigate analytically how horizontal equity is considered in the social welfare maximizing tax structure. We calibrate the model to German household data and a 30 percent emission reduction goal. Our results show that energy-intensive households should receive more redistributive resources than energy-efficient households if and only if social inequality aversion is sufficiently high. We further find that redistribution of carbon tax revenue via household-specific transfers is the first-best policy. Equal per-capita transfers do not suffer from informational problems, but increase mitigation costs by around 15 percent compared to the first- best for unity inequality aversion. Adding renewable energy subsidies or non-linear energy subsidies, reduces mitigation costs further without relying on observability of households’ energy efficiency.

We develop a model of optimal carbon taxation and redistribution taking into account horizontal equity concerns by considering heterogeneous energy efficiencies. By deriving first- and second-best rules for policy instruments including carbon taxes, transfers and energy subsidies, we then investigate analytically how horizontal equity is considered in the social welfare maximizing tax structure. We calibrate the model to German household data and a 30 percent emission reduction goal. Our results show that energy-intensive households should receive more redistributive resources than energy-efficient households if and only if social inequality aversion is sufficiently high. We further find that redistribution of carbon tax revenue via household-specific transfers is the first-best policy. Equal per-capita transfers do not suffer from informational problems, but increase mitigation costs by around 15 percent compared to the first- best for unity inequality aversion. Adding renewable energy subsidies or non-linear energy subsidies, reduces mitigation costs further without relying on observability of households’ energy efficiency., CEPA Discussion Papers; 28