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Background Elexacaftor-Tezacaftor-Ivacaftor (ETI) therapy is showing promising efficacy for treatment of cystic fibrosis (CF) and is becoming more widely available since recent FDA approval. However, little is known about how these drugs will affect lung infections, which are the leading cause of morbidity and mortality among people with CF (pwCF). Methods We analyzed sputum microbiome and metabolome data from pwCF (n=24) before and after ETI therapy using 16S rRNA gene sequencing and untargeted metabolomics. Results The sputum microbiome diversity, particularly its evenness, was increased (p=0.036) and the microbiome profiles were different between individuals before and after therapy (PERMANOVA F=1.92, p=0.044). Despite these changes, the microbiomes remained more similar within an individual than across the sampled population. No specific microbial taxa differed in relative abundance before and after therapy, but the collective log-ratio of classic CF pathogens to anaerobes significantly decreased (p=0.013). The sputum metabolome also showed changes associated with ETI (PERMANOVA F=4.22, p=0.002) and was characterized by greater variation across subjects while on treatment. Changes in the metabolome were driven by a decrease in peptides, amino acids, and metabolites from the kynurenine pathway, which were associated with a decrease in CF pathogens. Metabolism of the three small molecules that make up ETI was extensive, including previously uncharacterized structural modifications. Conclusions ETI therapy is associated with a changing microbiome and metabolome in airway mucus. This effect was stronger on sputum biochemistry, which may reflect changing niche space for microbial residency in lung mucus as the drug's effects take hold. Funding This project was funded by a National Institute of Allergy and Infectious Disease Grant R01AI145925

Introduction Out of hospital cardiac arrest (OHCA) patients are often transported to the closest emergency department (ED) or cardiac center for initial stabilization and may be transferred for further care. We investigated the effects of delay to transfer on in hospital mortality at a receiving facility. Methods We included OHCA patients transported from the ED by a single critical care transport service to a quaternary care facility between 2010 and 2018. We calculated dwell time as time from arrest to critical care transport team contact. We abstracted demographics, arrest characteristics, and interventions started prior to transport arrival. For the primary analysis, we used logistic regression to determine the association of dwell time and in-hospital mortality. As secondary outcomes we investigated for associations of dwell time and mortality within 24 h of arrival, proximate cause of death among decedents, arterial pH and lactate on arrival, sum of worst SOFA subscales within 24 h of arrival, and rearrest during interfacility transport. Results We included 572 OHCA patients transported from an outside ED to our facility. Median dwell time was 113 (IQR = 85–159) minutes. Measured in 30 min epochs, increasing dwell time was not associated with in-hospital mortality, 24-h mortality, cause of death and initial pH, but was associated with lower 24-h SOFA score (p = 0.01) and lower initial lactate (p = 0.03). Rearrest during transport was rare (n = 29, 5%). Dwell time was associated with lower probability of rearrest during transport (OR = 0.847, (95% CI 0.68–1.01), p = 0.07). Conclusions Dwell time was not associated with in-hospital mortality. Rapid transport may be associated with risk of rearrest. Prospective data are needed to clarify optimal patient stabilization and transport strategies.

BACKGROUND: The 12-lead ECG plays an important role in triaging patients with symptomatic coronary artery disease, making automated ECG interpretation statements of “Acute MI” or “Acute Ischemia” crucial, especially during prehospital transport when access to physician interpretation of the ECG is limited. However, it remains unknown how automated interpretation statements correspond to adjudicated clinical outcomes during hospitalization. We sought to evaluate the diagnostic performance of prehospital automated interpretation statements to four well-defined clinical outcomes of interest: confirmed ST- segment elevation myocardial infarction (STEMI); presence of actionable coronary culprit lesions, myocardial necrosis, or any acute coronary syndrome (ACS). METHODS: An observational cohort study that enrolled consecutive patients with non-traumatic chest pain transported via ambulance. Prehospital ECGs were obtained with the Philips MRX monitor from the medical command center and re-processed using manufacturer-specific diagnostic algorithms to denote the likelihood of >>>Acute MI<<< or >>>Acute Ischemia<<

To protect water resources, halt waterborne diseases, and prevent future water crises, photocatalytic degradation of water pollutants arouse worldwide interest. However, considering the low degradation efficiency and risk of secondary pollution displayed by most metal-based photocatalysts, highly efficient and environmentally friendly photocatalysts with appropriate band gap, such as carbon dots (CDs), are in urgent demand. In this study, the photocatalytic activity of gel-like CDs (G-CDs) was studied using diverse water pollution models for photocatalytic degradation. The degradation rate constants demonstrated a remarkably enhanced photocatalytic activity of G-CDs compared with most known CD species and comparability to graphitic carbon nitride (g-C3N4). In addition, the rate constant was further improved by 1.4 times through the embedment of g-C3N4 in G-CDs to obtain CD-C3N4. Significantly, the rate constant was also higher than that of g-C3N4 alone, revealing a synergistic effect. Moreover, the use of diverse radical scavengers suggested that the main contributors to the photocatalytic degradation with G-CDs alone were superoxide radicals (O2-) and holes that were, however, substituted by O2- and hydroxyl radicals (OH) due to the addition of g-C3N4. Furthermore, the photocatalytic stabilities of G-CDs and CD-C3N4 turned out to be excellent after four cycles of dye degradation were performed continuously. Eventually, the nontoxicity and environmental friendliness of G-CDs and CD-C3N4 were displayed with sea urchin cytotoxicity tests. Hence, through various characterizations, photocatalytic degradation and cytotoxicity tests, G-CDs proved to be an environmentally friendly and highly efficient future photocatalyst.

Background Emergency medical services (EMS) response volume has been linked to weather and temporal factors in a regional EMS system. We aimed to identify if models of EMS utilization incorporating these data are generalizable through geographically disparate areas in the United States. Methods We performed a retrospective analysis of EMS dispatch data from four regions: New York City, San Francisco, Cincinnati, and Marin County for years 2016–2019. For each model, we used local weather data summarized from the prior 6 h into hourly bins. Our outcome for each model was EMS dispatches as count data. We fit and optimized a negative binomial regression model for each region, to estimate incidence rate ratios. We compared findings to a prior study performed in Western Pennsylvania. Results We included 5,940,637 EMS dispatches from New York City, 809,405 from San Francisco, 260,412 from Cincinnati, and 77,461 from Marin County. Models demonstrated consistency with the Western Pennsylvania model with respect to temperature, season, wind speed, dew point, and time of day; both in terms of direction and effect size when expressed as incidence rate ratios. Precipitation was associated with increasing dispatches in the New York City, Cincinnati, and Marin County models, but not the San Francisco model. Conclusion With minor differences, regional models demonstrated consistent associations between dispatches and time and weather variables. Findings demonstrate the generalizability of associations between these variables with respect to EMS use. Weather and temporal factors should be considered in predictive modeling to optimize EMS staffing and resource allocation.

Introduction The COVID-19 pandemic may affect both use of 9–1-1 systems and prehospital treatment and transport practices. We evaluated EMS responses in an EMS region when it experienced low to moderate burden of COVID-19 disease to assess overall trends, response and management characteristics, and non-transport rates. Our goal is to inform current and future pandemic response in similar regions. Methods We performed a retrospective review of prehospital EMS responses from 22 urban, suburban, and rural EMS agencies in Western Pennsylvania. To account for seasonal variation, we compared demographic, response, and management characteristics for the 2-month period of March 15 to May 15, 2020 with the corresponding 2-month periods in 2016–2019. We then tested for an association between study period (pandemic vs historical control) and incidence of non-transport in unadjusted and adjusted regression. Finally, we described the continuous trends in responses and non-transports that occurred during the year before and initial phase of the COVID-19 pandemic from January 1, 2019 to May 31, 2020. Results Among 103,607 EMS responses in the 2-month comparative periods of March 15 to May 15, 2016–2020, we found a 26.5% [95% CI 26.9%, 27.1%] decrease in responses in 2020 compared to the same months from the four prior years. There was a small increase in respiratory cases (0.6% [95%CI 0.1%, 1.1%]) and greater frequency of abnormal vital signs suggesting a sicker patient cohort. There was a relative increase (46.6%) in non-transports between periods. The pandemic period was independently associated with an increase in non-transport (adjusted OR 1.68; 95%CI 1.59, 1.78). Among 177,194 EMS responses occurring in the year before and during the early period of the pandemic, between January 1, 2019, and May 31, 2020, we identified a 31% decrease in responses and a 48% relative increase in non-transports for April 2020 compared to the previous year's monthly averages. Conclusion Despite a low to moderate burden of infection during the initial period of the COVID-19 pandemic, we found a decline in overall EMS response volumes and an increase in the rate of non-transports independent of patient demographics and other response characteristics.

Background: Compared to day workers, shift workers face an elevated risk of cardiovascular disease. We reviewed the evidence to address the research question: Does acute exposure to shift work impact (blunt) the natural drop (dip) in Blood Pressure (BP) occurring during sleep and/or nighttime hours? (PROSPERO CRD42018110847). Methods: We performed a systematic review of five databases. We compared pooled estimates of mean BP stratified by periods of shift work, rest/leisure, and sleep, and evaluated the quality of evidence with the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework. Results: Our search covered 1/1/1980-10/24/2018 and yielded 1,636 records. Inter-rater agreement during screening was high (Kappa=0.87). We retained 44 studies described in 50 publications. We identified wide variation in shift worker type, shift schedules, and regularity of BP measurements. Most studies examined BP during one shift workday and one rest/leisure day. No study examined the impact of repeated exposure to shift work on the sleep-related dip in BP. Eighteen studies examined night shifts and one reported on BP during sleep post night shift. Compared to BP measured during shift work, BP measured during any sleep period separate from shift work was lower by 17.5 mmHg Systolic BP (95%CI 15.75, 19.27) and 15.4 mmHg lower for Diastolic BP (95%CI 14.38, 16.42) (p Conclusions: There is limited research exploring the acute and long-term impact of shift work on BP during sleep. The available evidence is heterogenous, low quality, and suggests that the mean dip in BP during sleep separate from shift work is not blunted.

Background Delay in seeking medical treatment for suspected acute coronary syndrome can lead to negative patient outcomes. Objective Our aim was to evaluate the prevalence and predictors of delay in seeking care in high-risk chest pain patients with or without acute coronary syndrome (ACS). Methods This was a secondary analysis of an observational cohort study of patients transported by Emergency Medical Services for a chief complaint of chest pain. Important demographic and clinical characteristics were extracted from electronic health records. Two independent reviewers adjudicated the presence of ACS. Logistic regression was used to model the predictors of delay in seeking care. Results The final sample included 743 patients (99% non-Hispanic). Overall, 24% presented > 12 h from onset of symptoms. Among those with ACS (n = 115), 14% presented > 12 h after onset of symptoms. Race, smoking, diabetes, and related symptoms were associated with delayed seeking behavior. In multivariate analysis, non-Caucasian race (black or others) was the only independent predictor of > 12 h delay in seeking care (odds ratio 1.4; 95% confidence interval 1.0–1.9). Conclusions One in four patients with chest pain, including 14% of those with ACS, wait more than 12 h before seeking care. Compared to non-blacks, black patients are 40% more likely to delay seeking care > 12 h.

Background Sleep deprivation is common in shift work occupations, including safety-sensitive occupations. While extending sleep prior to scheduled shifts (i.e., “banking sleep”) may be an intuitive strategy for fatigue mitigation, the evidence behind this strategy is unclear. Methods We performed a systematic review of literature retrieved in searches of four databases. We examined agreement between two independent screeners, abstracted key findings, reviewed and synthesized findings, and evaluated the quality of evidence using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology. The Cochrane Collaboration's risk of bias tool was used to evaluate bias of individual studies. We reported findings as prescribed by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Results Of the 3007 records screened, five met inclusion criteria. The inter-rater agreement for inclusion/exclusion was high (κ = 0.87). One study addressed patient safety outcomes. Four studies assessed the impact of banking sleep on performance, five assessed measures of acute fatigue, and three evaluated banking sleep on indicators of health. All five studies presented a very serious risk of bias and the quality of evidence was very low. Given these caveats, the findings, in aggregate, support banking sleep as a strategy to improve indicators of performance and acute fatigue. Conclusions This systematic review identifies gaps in research of shift workers on the efficacy of banking sleep as a fatigue risk management strategy. The available evidence supports banking sleep prior to shiftwork as a strategy for improved patient safety, performance, and reducing acute fatigue.

BACKGROUND: Nonspecific ST-T repolarization (NST) abnormalities alter the ST-segment for reasons often unrelated to acute myocardial ischemia, which could contribute to misdiagnosis or inappropriate treatment. We sought to define the prevalence of NST patterns in patients with chest pain and evaluate how such patterns correlate with the eventual etiology of chest pain and course of hospitalization. METHODS: This was a prospective observational study that included consecutive prehospital chest pain patients from three tertiary care hospitals in the U.S. Two independent reviewers blinded from clinical data audited the prehospital 12-lead ECG for the presence or absence of NST patterns (i.e., right or left bundle branch block, left ventricular hypertrophy with strain pattern, ventricular pacing, ventricular rhythm, or coarse atrial fibrillation). The primary outcome was 30-day major adverse cardiac events (MACE) defined as cardiac arrest, acute heart failure, post-discharge infarction, or all-cause death. RESULTS: The final sample included 750 patients (age 59±17, 58% males). A total of 40 patients (5.3%) experienced 30-MACE and 131 (17.5%) had NST patterns. The presence of NST patterns was an independent multivariate predictor of 30-day MACE (9.9% vs. 4.4%, OR = 2.2 [95% CI = 1.1–4.5]. Patients with NST patterns had increased median length of stay (1.0 [IQR 0.5–3] vs. 2.0 [IQR 1–4] days, p

Introduction Appropriate prehospital (PH) triage of patients with chest pain can significantly improve outcomes in acute myocardial infarction (MI). We sought to explore how PH providers triage chest pain as high versus low risk and to evaluate the accuracy and predictors of their triage decision. Methods This was a prospective, observational cohort study that enrolled consecutive patients with chest pain transported by emergency medical services (EMS) to 3 tertiary care hospitals in the US. EMS triage decision (high risk versus low-risk) was defined based on the transmission of PH electrocardiogram (ECG) to a command center for medical consultation with or without catheter laboratory activation. Two independent reviewers examined in-hospital medical records to adjudicate the presence of acute MI and to audit the findings on the presenting ECG. Results We enrolled 2,065 patients (aged 56 ± 17, 53% male) of whom 768 (37%) were triaged as high risk. Those triaged as high risk were older, were more likely to be men or have significant cardiac history, and had a higher rate of acute MI events (14.2% versus 3.5%). The sensitivity and specificity for triaging MI events as high risk were 70% and 97%, respectively. A total of 46/155 (30%) MI events were misclassified as low risk. No previous coronary revascularization and ECG misinterpretation were strong independent predictors of such undertriage. Conclusions PH providers have moderate sensitivity in triaging high-risk patients; 1 in 3 MI events are undertriaged. Emergency nurses need to pay special attention to patients with benign past histories during transition of care and should always reinterpret ECGs for subtle ischemic changes.

Materialism is the focus of much research due to its negative consequences for individuals and societies. While recent research indicates that the strength of materialistic value orientations changes with age during adulthood, little is known about the processes that cause these age-related changes. We propose that changes in materialism, as people grow older, are rooted in changes in self-uncertainty. We find evidence for this idea in two studies and across different measures of self-uncertainty. In addition, we show that the changes in materialism cannot be explained by (age-related) differences in socio-demographic variables. Finally, our results indicate that changes in self-uncertainty provide a better account for changes in materialism than age-related changes in self-esteem.

Study objective It is unknown whether regionalization of postarrest care by interfacility transfer to cardiac arrest receiving centers reduces mortality. We seek to evaluate whether treatment at a cardiac arrest receiving center, whether by direct transport or early interfacility transfer, is independently associated with long-term outcome. Methods We performed a retrospective cohort study including adults resuscitated from out-of-hospital cardiac arrest in southwestern Pennsylvania and neighboring Ohio, West Virginia, and Maryland, which includes approximately 5.7 million residents in urban, suburban, and rural counties. Patients were treated by 1 of 78 ground emergency medical services agencies or 2 air medical transport agencies between January 1, 2010, and November 30, 2014. Our primary exposures of interest were interfacility transfer to a cardiac arrest receiving center within 24 hours of arrest or any treatment at a cardiac arrest receiving center regardless of transfer status. Our primary outcome was vital status, assessed through December 31, 2014, with National Death Index records. We used unadjusted and adjusted survival analyses to test the independent association of cardiac arrest receiving center care, whether through direct or interfacility transport, on mortality. Results Overall, 5,217 cases were observed for 3,629 person-years, with 3,865 total deaths. Most patients (82%) were treated at 42 non–cardiac arrest receiving centers with median annual volume of 17 cases (interquartile range 1 to 53 cases per center annually), whereas 18% were cared for at cardiac arrest receiving centers receiving at least 1 interfacility transfer per month. In adjusted models, treatment at a cardiac arrest receiving center was independently associated with reduced hazard of death compared with treatment at a non–cardiac arrest receiving center (adjusted hazard ratio 0.84; 95% confidence interval 0.74 to 0.94). These effects were unchanged when analysis was restricted to patients brought from the scene to the treating hospital. No other hospital characteristic, including total out-of-hospital cardiac arrest patient volume and cardiac catheterization capabilities, independently predicted outcome. Conclusion Both early interfacility transfer to a cardiac arrest receiving center and direct transport to a cardiac arrest receiving center from the scene are independently associated with reduced mortality.

Managing out-of-hospital cardiac arrest involves unique challenges, including delays in the initiation of advanced interventions and a limited number of trained personnel on scene. Recent out-of-hospital randomized controlled trials, systematic reviews, and metaanalyses provide key insights into what interventions are best proven to positively impact patient outcomes from out-of-hospital cardiac arrest. We review the literature on medications used in out-of-hospital cardiac arrest and summarize evidence-based guidelines from the American Heart Association that form the basis for most emergency medical services cardiac arrest protocols across the United States.

Objective To develop and internally validate a metalearner algorithm to predict the hourly rate of emergency medical services (EMS) dispatches in an urban setting. Methods We performed an analysis of EMS data from New York City between years 2015-2019. Our outcome was hourly EMS dispatches, expressed as continuous data. Hours were split into derivation (75%) and validation (25%) datasets. Candidate variables included averages of prior rates, temporal and weather characteristics. We used a metalearner to evaluate and aggregate individual learners (generalized linear model, generalized additive model, random forest, multivariable adaptive regression splines, and extreme gradient boost). Four models were investigated: 1) temporal variables, 2) weather and temporal variables, and datasets in which weather data were lagged by 3) six and 4) twelve hours. In exploratory analyses, we constructed learners for high acuity and trauma encounters. Results 7,364,275 EMS dispatches occurred during the 43,823-hour period. When using temporal variables, the mean absolute error (MAE) rate was 11.5 dispatches in the validation dataset. These were slightly improved following incorporation of weather variables (MAE 11.3). When using 6- and 12-hour lagged weather variables, learners demonstrated lower accuracy (MAE 11.8 in 6-hour lagged datasets; 12.2 in 12-hour lagged dataset). All models had a coefficient of determination (R2) ≥0.91. The extreme gradient boosting and random forest learners were assigned the highest coefficients. In an investigation of variable importance, hour of day and average EMS dispatches over the previous six hours were the most important variables in both the extreme gradient boosting and random forest learners. The algorithm performed well at predicting frequently occurring peaks, with greater challenges at both extremes. Learners created high-acuity and for trauma-related encounters demonstrated superior MAE, but with lower R2 in the validation cohort (MAE 6.9 and R2 0.84 for high acuity encounters; MAE 5.3 and R2 0.79 for trauma in learners using time and weather variables). Conclusion We developed an ensemble machine learning algorithm to predict EMS dispatches in an urban setting. These models demonstrated high accuracy, with MAEs

Resume La trompe d’Eustache (tube auditif) et les cavites tympanomastoidiennes forment un ensemble anatomique et fonctionnel difficilement dissociable, d’ou l’appellation « systeme tubotympanique ». L’etude de ce systeme a fait l’objet de nombreux travaux dont les resultats complexes et parfois contradictoires rendent difficile une vue d’ensemble de son fonctionnement. L’objectif cet article est d’en synthetiser les connaissances actuelles, prealable indispensable a la comprehension de son dysfonctionnement et notamment de la genese de l’otite chronique. L’ensemble du systeme est tapisse par une muqueuse qui en assure la continuite, bien qu’elle comporte certaines particularites selon la zone concernee, et y joue un role primordial. Ainsi, dans des conditions physiologiques, la diffusion gazeuse a travers la muqueuse tympanomastoidienne assure l’essentiel de l’equilibre pressionnel regnant entre l’oreille moyenne (OM) et le monde exterieur, l’ouverture tubaire n’intervenant que tres peu. Lors des changements rapides et importants de la pression atmospherique, la fonction ventilatoire de la trompe est alors mise en jeu, sous l’effet d’un mecanisme reflexe. Le systeme possede en outre d’autres fonctions indispensables au bon fonctionnement de l’OM, une fonction de protection vis-a-vis des secretions et agents pathogenes en provenance du rhinopharynx, mais aussi de certains bruits physiologiques, une fonction de clairance des cavites de l’OM dependant du transport mucociliaire des pathogenes, liee en partie a la secretion des glandes sous-muqueuses et une fonction de defense immunitaire.

Clinical heart failure (HF) occurs frequently after ST-segment elevation myocardial infarction (STEMI), and is associated with increased mortality. We assessed the impact of remote ischemic peri-conditioning (RIPC) during inter-facility air medical transport of STEMI patients on clinical HF following primary percutaneous coronary intervention (pPCI).Data from Acute Coronary Treatment and Intervention Outcomes Network Registry®-Get With the Guidelines™ (ACTION Registry-GWTG) from two PCI-hospitals that are utilizing RIPC during inter-facility helicopter transport of STEMI patients for pPCI between March, 2013 and September, 2015 were used for this study. The analyses were limited to inter-facility STEMI patients transported by helicopter with LVEF55% after pPCI. The outcome measures were occurrence of clinical HF and serum level of brain-type natriuretic peptide (BNP).Out of the 150 STEMI patients in this analysis, 92 patients received RIPC and 58 did not. The RIPC and non-RIPC groups were generally similar in demographic and clinical characteristics except for lower incidence of cardiac arrest in the RIPC group (3/92 [3.3%] versus 13/58 [22.4%], p=0.002). STEMI patients who received RIPC were less likely to have in-hospital clinical HF compared to patients who did not receive RIPC (3/92 [3.3%] versus 7/58 [12.1%]; adjusted OR=0.22, 95% CI 0.05-0.92, p=0.038) after adjusting for baseline differences. In subgroup analysis, RIPC was associated with lower BNP (123 [interquartile range, 17.0-310] versus 319 [interquartile range, 106-552], p=0.029).RIPC applied during inter-facility air transport of STEMI patients for pPCI is associated with reduced incidence of clinical HF and serum BNP.

Resume Introduction Les nocardioses sont rares, de diagnostic clinique et microbiologique difficile, avec une morbi-mortalite importante, et surviennent souvent sur terrain debilite. Peu de donnees existent en France. Methodes Etude retrospective monocentrique de 2002 a 2014 incluant tous les patients avec au moins un prelevement microbiologique positif a Nocardia. Resultats Dix-neuf patients, dont 15 hommes, ont ete inclus, d’âge moyen 58 ans (25–85). Dix-sept presentaient un terrain a risque (pathologies pulmonaires 13, corticotherapie 12, tumeurs 2, infection par le VIH 2, diabete 3, greffe renale 2, lymphopenie 1). On denombre 12 infections pulmonaires, 3 infections cerebrales, 2 infections cutanees, 1 infection ganglionnaire, et 1 infection corneenne. La croissance souvent lente du germe conduit a un delai median de resultat de 35 jours (3–95). Neuf especes ont ete retrouvees. Quinze patients (79 %) ont recu une ou plusieurs lignes antibiotiques comprenant entre autres : cotrimoxazole (n = 9), amoxicilline (n = 7) cefotaxime/ceftriaxone (n = 7), imipeneme (n = 3) ou amikacine (n = 3). La duree moyenne de l’antibiotherapie etait de 207 jours. Quatre patients n’ont pas recu d’antibiotiques a cause d’un resultat tardif ou d’une co-infection bacterienne masquant la nocardiose. On deplore 5 deces (26 %) dont 2 imputables a une atteinte cerebrale. Six patients ont gueri, 4 ont rechute, l’evolution est inconnue pour 4, et 1 est encore en cours de traitement. Conclusion La prise en charge des nocardioses est compliquee. Une meilleure connaissance de celles-ci par une etude clinico-microbiologique nationale semble necessaire.

The 2017 federal elections in Germany propelled the far-right party "Alternative fur Deutschland" ("Alternative for Germany" – AfD) to become the third largest party in the federal parliament. I argue that this strong result of a party that is at odds with much of the post war German political consensus can be explained by a) the move of the Christian-Democratic CDU/CSU to the political center and the resulting increase in similarity between center-left and center-right political forces; b) a de-politicization of politics, especially in the aftermath of the world financial and economic crisis and during the reign of the grand coalition. Drawing on data from the Chapel Hill Expert Survey and the Party Manifesto Project, I show that the AfD inhabits an otherwise unpopulated region of the policy space where it puts particular emphasis on anti-EU positions. In the next step, drawing on data from the Federal Returning Office, I show that the AfD was able to mobilize the electorate more successfully than other parties and that the party's electoral success was in large part due to this mobilization success with the change in turnout the second strongest predictor of AfD vote shares.