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Migraine and stroke are two common and heterogeneous neurovascular disorders responsible for a significant burden for those affected and a great economic cost for the society. There is growing evidence that migraine increases the overall risk of cerebrovascular diseases. In this review, based on available literature through a PubMed search, we found that ischaemic stroke in people with migraine is strongly associated with migraine with aura, young age, female sex, use of oral contraceptives and smoking habits. The risk of transient ischaemic attack also seems to be increased in people with migraine, although this issue has not been extensively investigated. Although migraine appears to be associated with haemorrhagic stroke, the migraine aura status has a small influence on this relationship. Neuroimaging studies have revealed a higher prevalence of asymptomatic structural brain lesions in people with migraine. They are also more likely to have unfavourable vascular risk factors; however, the increased risk of stroke seems to be more apparent among people with migraine without traditional risk factors. The mechanism behind the migraine-stroke association is unknown. In light of the higher risk of stroke in people with migraine with aura, it is important to identify and modify any vascular risk factor. There is currently no direct evidence to support that a migraine prophylactic treatment can reduce future stroke in people with migraine.

Background Machine learning models promise to support diagnostic predictions, but may not perform well in new settings. Selecting the best model for a new setting without available data is challenging. We aimed to investigate the transportability by calibration and discrimination of prediction models for cognitive impairment in simulated external settings with different distributions of demographic and clinical characteristics. Methods We mapped and quantified relationships between variables associated with cognitive impairment using causal graphs, structural equation models, and data from the ADNI study. These estimates were then used to generate datasets and evaluate prediction models with different sets of predictors. We measured transportability to external settings under guided interventions on age, APOE ε4, and tau-protein, using performance differences between internal and external settings measured by calibration metrics and area under the receiver operating curve (AUC). Results Calibration differences indicated that models predicting with causes of the outcome were more transportable than those predicting with consequences. AUC differences indicated inconsistent trends of transportability between the different external settings. Models predicting with consequences tended to show higher AUC in the external settings compared to internal settings, while models predicting with parents or all variables showed similar AUC. Conclusions We demonstrated with a practical prediction task example that predicting with causes of the outcome results in better transportability compared to anti-causal predictions when considering calibration differences. We conclude that calibration performance is crucial when assessing model transportability to external settings.

Background In epidemiology, causal inference and prediction modeling methodologies have been historically distinct. Directed Acyclic Graphs (DAGs) are used to model a priori causal assumptions and inform variable selection strategies for causal questions. Although tools originally designed for prediction are finding applications in causal inference, the counterpart has remained largely unexplored. The aim of this theoretical and simulation-based study is to assess the potential benefit of using DAGs in clinical risk prediction modeling. Methods We explore how incorporating knowledge about the underlying causal structure can provide insights about the transportability of diagnostic clinical risk prediction models to different settings. We further probe whether causal knowledge can be used to improve predictor selection in clinical risk prediction models. Results A single-predictor model in the causal direction is likely to have better transportability than one in the anticausal direction in some scenarios. We empirically show that the Markov Blanket, the set of variables including the parents, children, and parents of the children of the outcome node in a DAG, is the optimal set of predictors for that outcome. Conclusions Our findings provide a theoretical basis for the intuition that a diagnostic clinical risk prediction model including causes as predictors is likely to be more transportable. Furthermore, using DAGs to identify Markov Blanket variables may be a useful, efficient strategy to select predictors in clinical risk prediction models if strong knowledge of the underlying causal structure exists or can be learned.

Objective To evaluate the effects of intraoperative protective ventilation on major postoperative respiratory complications and to define safe intraoperative mechanical ventilator settings that do not translate into an increased risk of postoperative respiratory complications.Design Hospital based registry study.Setting Academic tertiary care hospital and two affiliated community hospitals in Massachusetts, United States.Participants 69 265 consecutively enrolled patients over the age of 18 who underwent a non-cardiac surgical procedure between January 2007 and August 2014 and required general anesthesia with endotracheal intubation.Interventions Protective ventilation, defined as a median positive end expiratory pressure (PEEP) of 5 cmH2O or more, a median tidal volume of less than 10 mL/kg of predicted body weight, and a median plateau pressure of less than 30 cmH2O.Main outcome measure Composite outcome of major respiratory complications, including pulmonary edema, respiratory failure, pneumonia, and re-intubation.Results Of the 69 265 enrolled patients 34 800 (50.2%) received protective ventilation and 34 465 (49.8%) received non-protective ventilation intraoperatively. Protective ventilation was associated with a decreased risk of postoperative respiratory complications in multivariable regression (adjusted odds ratio 0.90, 95% confidence interval 0.82 to 0.98, P=0.013). The results were similar in the propensity score matched cohort (odds ratio 0.89, 95% confidence interval 0.83 to 0.97, P=0.004). A PEEP of 5 cmH2O and median plateau pressures of 16 cmH2O or less were associated with the lowest risk of postoperative respiratory complications.Conclusions Intraoperative protective ventilation was associated with a decreased risk of postoperative respiratory complications. A PEEP of 5 cmH2O and a plateau pressure of 16 cmH2O or less were identified as protective mechanical ventilator settings. These findings suggest that protective thresholds differ for intraoperative ventilation in patients with normal lungs compared with those used for patients with acute lung injury.

Background Although an “epidemic” of depression is frequently claimed, empirical evidence is inconsistent, depending on country, study design and depression assessment. Little is known about changes in depression over time in Germany, although health insurance companies report frequency increases. Here we examined time trends in depression prevalence, severity and health-related correlates in the general population. Methods Data were obtained from the mental health module of the “German Health Interview and Examination Survey for Adults” (2009–2012, n  = 3265) and the mental health supplement of the “German National Health Interview and Examination Survey 1998” (1997–1999, n  = 4176), excluding respondents older than 65. 12-month major depressive disorder (MDD), severity and symptoms were assessed based on the WHO Composite International Diagnostic Interview. Health-related quality of life (SF-36), self-reported sick days or days with limitations in normal daily life activities were examined, too. Calculations were carried out population-weighted. Additional age-standardized analyses were conducted to account for demographic changes. Results Overall, MDD 12-month prevalence remained stable at 7.4%. Women showed a shifted age distribution with increased prevalence at younger ages, and increasing MDD severity. Time trends in health-related correlates occurred both in participants with and without MDD. Mental health disability increased over time, particularly among men with MDD, reflected by the mental component score of the SF-36 and days with activity limitation due to mental health problems. Demographic changes had a marginal impact on the time trends. Conclusions In contrast to the ongoing international debate regarding increased depression rates in western countries, we found no increase in overall MDD prevalence in Germany over a long period. In conclusion, increased depression frequencies in national health insurance data and growing health care costs associated with depression are not attributable to overall prevalence changes at a population level. However, shifted age distribution and increased severity among women may reflect a rising depression risk within this specific subgroup, and changes in health-related correlates indicate a growing mental health care need for depression, particularly among men.

Objective To evaluate the association between migraine and incident cardiovascular disease and cardiovascular mortality in women.Design Prospective cohort study among Nurses’ Health Study II participants, with follow-up from 1989 and through June 2011.Setting Cohort of female nurses in United States.Participants 115 541 women aged 25-42 years at baseline and free of angina and cardiovascular disease. Cumulative follow-up rates were more than 90%.Main outcome measures The primary outcome of the study was major cardiovascular disease, a combined endpoint of myocardial infarction, stroke, or fatal cardiovascular disease. Secondary outcome measures included individual endpoints of myocardial infarction, stroke, angina/coronary revascularization procedures, and cardiovascular mortality.Results 17 531 (15.2%) women reported a physician’s diagnosis of migraine. Over 20 years of follow-up, 1329 major cardiovascular disease events occurred and 223 women died from cardiovascular disease. After adjustment for potential confounding factors, migraine was associated with an increased risk for major cardiovascular disease (hazard ratio 1.50, 95% confidence interval 1.33 to 1.69), myocardial infarction (1.39, 1.18 to 1.64), stroke (1.62, 1.37 to 1.92), and angina/coronary revascularization procedures (1.73, 1.29 to 2.32), compared with women without migraine. Furthermore, migraine was associated with a significantly increased risk for cardiovascular disease mortality (hazard ratio 1.37, 1.02 to 1.83). Associations were similar across subgroups of women, including by age (<50/≥50), smoking status (current/past/never), hypertension (yes/no), postmenopausal hormone therapy (current/not current), and oral contraceptive use (current/not current).Conclusions Results of this large, prospective cohort study in women with more than 20 years of follow-up indicate a consistent link between migraine and cardiovascular disease events, including cardiovascular mortality. Women with migraine should be evaluated for their vascular risk. Future targeted research is warranted to identify preventive strategies to reduce the risk of future cardiovascular disease among patients with migraine.

The extent to which people implement government-issued protective measures is critical in preventing further spread of coronavirus disease 2019 (COVID-19) caused by coronavirus SARS-CoV-2. Our study aimed to describe the public belief in the effectiveness of protective measures, the reported implementation of these measures, and to identify communication channels used to acquire information on COVID-19 in European countries during the early stage of the pandemic. An online survey available in multiple languages was disseminated starting on March 19th, 2020. After five days, we computed descriptive statistics for countries with more than 500 respondents. Each day, we assessed enacted community containment measures by stage of stringency (I-IV). In total, 9,796 adults responded, of whom 8,611 resided in the Netherlands (stage III), 604 in Germany (stage III), and 581 in Italy (stage IV). To explore possible dynamics as containment strategies intensified, we also included 1,365 responses submitted during the following week. Participants indicated support for governmental measures related to avoiding social gatherings, selective closure of public places, and hand hygiene and respiratory measures (range for all measures: 95.0%-99.7%). Respondents from the Netherlands less frequently considered a complete social lockdown effective (59.2%), compared to respondents in Germany (76.6%) or Italy (87.2%). Italian residents applied enforced social distancing measures more frequently (range: 90.2%-99.3%, German and Dutch residents: 67.5%-97.0%) and self-initiated hygienic and social distancing behaviors (range: 36.3%-96.6%, German and Dutch residents: 28.3%-95.7%). Respondents reported being sufficiently informed about the outbreak and behaviors to avoid infection (range: 90.2%-91.1%). Information channels most commonly reported included television newspapers, official health websites, and social media. One week later, we observed no major differences in submitted responses. During the early stage of the COVID-19 pandemic, belief in the effectiveness of protective measures among survey respondents from three European countries was high and participants reported feeling sufficiently informed. In March 2020, implementation of measures differed between countries and were highest among respondents from Italy, who were subjected to the most stringent lockdown measures and greatest COVID-19 burden in Europe during this period.

Migraine and stroke are two common and heterogeneous neurovascular disorders with complex relations. Data show no firm association between stroke and migraine without aura—by far the most common type of migraine—but a doubling of the risk of ischaemic stroke in people who have migraine with aura. Migraine with aura is characterised by a low brain threshold for cortical spreading depression, the biological substrate of the aura, which can be triggered by many factors, including specific diseases that can by themselves increase the risk of ischaemic stroke. Whether the increased risk of ischaemic stroke applies to migraine with aura as a primary headache disorder or is partly due to migraine with aura secondary to other disorders remains to be elucidated.

Benchmarking an observational analysis against a randomized trial can increase confidence in the use of observational data to complement inferences made in trials. Until now, few examples of benchmarking have been within oncology. However, benchmarking trials of a cancer treatment poses a unique set of challenges, such as defining composite outcomes like disease-free survival. We designed a target trial with a protocol as similar as possible to the B-31 and N9831 randomized trials, which estimated the effect of adjuvant trastuzumab plus chemotherapy compared with chemotherapy alone in individuals with early human epidermal growth factor receptor 2-positive breast cancer. We then carried out an observational analysis by emulating the target trial using routinely collected data from Swedish registries to understand if we can estimate a similar effect of trastuzumab as the trial. The primary endpoint was the composite of disease-free survival consisting of the earliest of (1) local or regional recurrences, (2) distant recurrences, (3) contralateral breast cancer, (4) other second primary cancer, or (5) death from any cause. Individuals who had data compatible with both treatment strategies at baseline were cloned and one copy was assigned to each arm. We applied inverse probability weights to adjust for baseline and time-varying confounding (e.g., age and hematological events like neutropenia). Our observational analysis included 1,578 women, with a median age of 59 years, and who were diagnosed between 2008 and 2015. We estimated a similar effect after five years of follow-up (RR: 0.54, 95% CI [0.44, 0.67]) for the composite endpoint of disease-free survival as the two jointly analyzed B-31 and N9831 trials (HR: 0.48, 95% CI [0.39, 0.59]). While the comparability of results increases confidence in our estimates, there remains a risk of residual and unmeasured confounding, as is the case with all observational analyses. We successfully benchmarked an observational analysis against the B-31 and N9831 trials. By aligning protocols and using appropriate methodological approaches, we show that observational data can be used to estimate similar results as randomized trials of cancer treatments, like trastuzumab. This opens the door to using observational data to complement results from randomized trials of cancer treatments which can provide quick, cheap, and robust evidence to support decision-making where trials leave evidence gaps.

Background Seasonal influenza can lead to severe complications and death, resulting in high disease burden each year. The European Centre for Disease Prevention and Control introduced the Burden of Communicable diseases in Europe (BCoDE) project, quantifying the disease burden of infectious diseases in disability-adjusted life years (DALY). DALYs for influenza exceed those of Tuberculosis, HIV, and Invasive pneumococcal disease. As data on disease burden are limited, this study aims to calculate the seasonal influenza burden for Germany between 2015 and 2020. Methods The BCoDE-toolkit developed by the European Centre for Disease Prevention and Control was used, calculating country-specific DALYs. Information on incidence, population data, and underestimation were taken from the Robert Koch-Institute and the Federal Statistical Office of Germany. Outcome trees were created based on information from a rapid review and previous publications. Baseline, lower-bound and upper-bound scenarios were developed to assess the disease burden under varying conditions. Results Estimates range from 127,100 DALYs (153 DALYs per 100,000 population) and 1,171,115 DALYs (1,414 DALYs per 100,000 population) depending on the scenario and year examined. The main contributors to the disease burden are sequelae, primarily pneumonia, encephalitis, and myocarditis. The highest burden estimates are observable for infants, children under the age of five and the elderly. Conclusions Using a composite health measure like DALY can offer valuable insight into a disease’s impact on population health. Our results indicate a high disease burden due to seasonal influenza in Germany, indicating further research into complication rates, underestimation, and intervention programs for vulnerable populations, e.g., vaccination in infants, children under age of five and elderly population.