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Abstract Campi Flegrei is a densely populated volcanic area in Italy. Its inner caldera periodically experiences uplift and subsidence, known as bradyseism, also accompanied by seismic activity. In the last decade, with uplift rates up to 2 cm/month, about nine-thousand earthquakes were recorded. Upon request of the local administration, the most updated data were collected and analyzed to evaluate the risk management strategy consisting of structural retrofitting according to the building code. Here it is shown that the reference moment magnitude is in the range $$\left({{\mathrm{4.4,5.1}}}\right)$$ 4.4, 5.1 , based on fault mapping, geomorphological inference, earthquake relocation, stress-drop analysis, and ground motion modelling. Earthquake forecasting enabled computing the exceedance probabilities of these magnitudes. Earthquake engineering showed that the minimum magnitudes expected to cause exceedance of design ground motion, are larger than the reference magnitudes. Finally, the risk reduction implied by the safety levels of new constructions was assessed for reinforced concrete buildings.

Earthquake forecasting models express hypotheses about seismogenesis that underpin global and regional probabilistic seismic hazard assessments (PSHAs). An implicit assumption is that the comparatively higher spatiotemporal resolution datasets from which regional models are generated lead to more informative seismicity forecasts than global models, which are however calibrated on greater datasets of large earthquakes. Here, we prospectively assess the ability of the Global Earthquake Activity Rate (GEAR1) model and 19 time‐independent regional models to forecast M 4.95+ seismicity in California, New Zealand, and Italy from 2014 through 2021, using metrics developed by the Collaboratory for the Study of Earthquake Predictability (CSEP). Our results show that regional models that adaptively smooth small earthquake locations perform best in California and Italy during the evaluation period; however, GEAR1, based on global seismicity and geodesy datasets, performs surprisingly well across all testing regions, ranking first in New Zealand, second in California, and third in Italy. Furthermore, the performance of the models is highly sensitive to spatial smoothing, and the optimal smoothing likely depends on the regional tectonic setting. Acknowledging the limited prospective test data, these results provide preliminary support for using GEAR1 as a global reference M 4.95+ seismicity model that could inform eight‐year regional and global PSHAs.

Measurement(s) Earthquakes location and magnitude Technology Type(s) Earthquakes location codes Factor Type(s) Hypocenters Sample Characteristic - Environment tectonic earthquake Sample Characteristic - Location Italy

Abstract Background Although the lack of estrogen receptor β (ERβ) is a risk factor for the development of inflammatory bowel disease (IBD) and psychiatric disorders, the underlying cellular and molecular mechanisms are not fully understood. Herein, we revealed the role of gut microbiota in the development of IBD and related anxiety-like behavior in ERβ-deficient mice. Results In response to dextran sodium sulfate (DSS) insult, the ERβ knockout mice displayed significant shift in α and β diversity in the fecal microbiota composition and demonstrated worsening of colitis and anxiety-like behaviors. In addition, DSS-induced colitis also induced hypothalamic-pituitary-adrenal (HPA) axis hyperactivity in ERβ-deficient mice, which was associated with colitis and anxiety-like behaviors. In addition, RNA sequencing data suggested that ErbB4 might be the target of ERβ that is involved in regulating the HPA axis hyperactivity caused by DSS insult. Gut microbiota remodeling by co-housing showed that both the colitis and anxiety-like behaviors were aggravated in co-housed wild-type mice compared to single-housed wild-type mice. These findings suggest that gut microbiota play a critical role in mediating colitis disease activity and anxiety-like behaviors via aberrant neural processing within the gut-brain axis. Conclusions ERβ has the potential to inhibit colitis development and anxiety-like behaviors via remodeling of the gut microbiota, which suggests that ERβ is a promising therapeutic target for the treatment of IBD and related anxiety-like behaviors. Video Abstract

The authors introduce a new perspective to study the spatiotemporal behavior of the magnitude–frequency distribution: spatially isolating seismogenic zones to provide an appropriate scale to resolve the b-value. Among those zones, the b-value behaved remarkably throughout the 2016 central Italy sequence.

Abstract Foreshock analysis promises new insights into the earthquake nucleation process and could potentially improve earthquake forecasting. Well‐performing clustering models like the Epidemic‐Type Aftershock Sequence (ETAS) model assume that foreshocks and general seismicity are generated by the same physical process, implying that foreshocks can be identified only in retrospect. However, several studies have recently found higher foreshock activity than predicted by ETAS. Here, we revisit the foreshock activity in southern California using different statistical methods and find anomalous foreshock sequences, that is, those unexplained by ETAS, mostly for mainshock magnitudes below 5.5. The spatial distribution of these anomalies reveals a preferential occurrence in zones of high heat flow, which are known to host swarm‐like seismicity. Outside these zones, the foreshocks generally behave as expected by ETAS. These findings show that anomalous foreshock sequences in southern California do not indicate a pre‐slip nucleation process, but swarm‐like behavior driven by heat flow.

Knowledge of the global rates of volcanism is fundamental for modeling the Earth, as those rates closely relate to plate tectonics, crustal growth, mantle dynamics, atmospheric evolution, climate change, and virtually any aspect of the global Earth dynamics. In spite of their huge relevance, the global rates of volcanism have remained unknown, hidden within data that appeared disordered, largely fragmented and incomplete, reflecting poor preservation of small eruptions in the geological record, rareness of large eruptions, and distributions far from normal. Here we describe and validate a model that reproduces global volcanism to high statistical significance, and that is so simple to comfortably fit on a t-shirt. We use the model to compute the expected rates of global terrestrial volcanism over time windows from 1 to 100,000 years, and validate it by comparing with observations back to a few million years. Notably, the model can be tested against independent observations collected in the near future, a feature which is relatively uncommon among global models of Solid Earth dynamics.

Operational Earthquake Forecasting (OEF) aims to deliver timely and reliable forecasts that may help to mitigate seismic risk during earthquake sequences. In this paper, we build the first OEF system for the State of Israel, and we evaluate its reliability. This first version of the OEF system is composed of one forecasting model, which is based on a stochastic clustering Epidemic Type Earthquake Sequence (ETES) model. For every day of the forecasting time period, January 1, 2016 - November 15, 2020, the OEF-Israel system produces a weekly forecast for target earthquakes with local magnitudes greater than 4.0 and 5.5 in the entire State of Israel. Specifically, it provides space-time-dependent seismic maps of the weekly probabilities, obtained by using a fixed set of the model’s parameters, which are estimated through the maximum likelihood technique based on a learning period of about 32 years (1983–2015). According to the guidance proposed by the Collaboratory for the Study of Earthquake Predictability (CSEP), we also perform the N- and S-statistical tests to verify the reliability of the forecasts. Results show that the OEF system forecasts a number of events comparable to the observed one, and also captures quite well the spatial distribution of the real catalog with the exception of two target events that occurred in low seismicity regions.

Abstract We summarize major findings and best-practice recommendations from three Volcano Observatory Best Practices (VOBP) workshops, which were held in 2011, 2013 and 2016. The workshops brought together representatives from the majority of the world’s volcano observatories for the purpose of sharing information on the operation and practice of these institutions and making best practice recommendations. The first workshop focused on eruption forecasting, the second on hazard communication, and the third on long-term hazard assessment. Subsequent VOBP workshops will address additional issues of broad interest to the international volcano observatory community. The objective of VOBP is to develop synergy among volcano hazards programs and their observatories internationally, so as to more rapidly and broadly advance the field of applied volcanology. Each of the workshop summaries presented here include best practice recommendations for consideration by the world’s volcano observatories.

A prominent feature of earthquakes is their empirical laws, including memory (clustering) in time and space. Several earthquake forecasting models, such as the epidemic-type aftershock sequence (ETAS) model, were developed based on these empirical laws. Yet, a recent study [ 1 ] showed that the ETAS model fails to reproduce the significant long-term memory characteristics found in real earthquake catalogs. Here we modify and generalize the ETAS model to include short- and long-term triggering mechanisms, to account for the short- and long-time memory (exponents) discovered in the data. Our generalized ETAS model accurately reproduces the short- and long-term/distance memory observed in the Italian and Southern Californian earthquake catalogs. The revised ETAS model is also found to improve earthquake forecasting after large shocks.

Earthquakes involve complex processes that span a wide range of spatial and temporal scales. The limited earthquake predictability is partly due to the erratic nature of earthquakes and partly due to the lack of understanding of the underlying mechanisms of earthquakes. To improve our understanding and possibly the predictability of earthquakes, we develop here a lagged conditional probability method to study the spatial and temporal long-term memory of interevent earthquakes above a certain magnitude. We find, in real data from different locations, that the lagged conditional probabilities show long-term memory for both the interevent times and interevent distances and that the memory functions obey scaling and decay slowly with time, while, at a characteristic time (crossover), the decay rate becomes faster. We also show that the epidemic-type aftershock sequence model, which is often used to forecast earthquake events, fails in reproducing the scaling function of real catalogs as well as the crossover in the scaling function. Our results suggest that aftershock rate is a critical factor to control the long-term memory.

Objective: To determine the incidence and time sequence of mortality and major morbidity after ambulatory surgery.Design: Prospective outcome survey of patients at 16 to 72 hours and 30 days after their surgical procedures.Setting: A tertiary care rural referral center providing ambulatory care.Patients: A total of 38,598 patients aged 18 years and older undergoing 45,090 consecutive ambulatory procedures and anesthetics. Contact rates for 72 hours and 30 days were 99.94% and 95.9%, respectively.Main Outcome Measures: Mortality and major morbidity incidences, including myocardial infarction, central nervous system deficit, pulmonary embolism, and respiratory failure.Results: Thirty-three patients either experienced major morbidity or died (1:1366 [proportional risk]). Four patients died (1:11,273), two of myocardial infarction and two in automobile accidents. No patient died of a medical complication within 1 week of surgery. Of the 31 patients who developed a major morbidity (1:1455), 14 (45%) had myocardial infarction (1:3220), seven (23%) had a central nervous system deficit (1:6441), five (16%) had pulmonary embolism (1:9018), and five (16%) had respiratory failure (1:9018). Four events (13%) occurred within 8 hours of surgery (1:11,273), 15 (48%) in the next 40 hours (1:3006), and 12 (39%) in the next 28 days (1:3758).Conclusion: In this ambulatory surgical population, more than one third of major morbidity occurred 48 hours or later after surgery. Overall morbidity and mortality rates, however, were very low. [ABSTRACT FROM AUTHOR]

Volcanic water-sediment flows, commonly known as lahars, can often pose a higher threat to population and infrastructure than primary volcanic hazardous processes such as tephra fallout and Pyroclastic Density Currents (PDCs). Lahars are volcaniclastic flows of water, volcanic debris and entrained sediments that can travel long distances from their source, causing severe damage by impact and burial. Lahars are frequently triggered by intense or prolonged rainfall occurring after explosive eruptions, and their occurrence depends on numerous factors including the spatio-temporal rainfall characteristics, the spatial distribution and hydraulic properties of the tephra deposit, and the pre- and post-eruption topography. Modeling (and forecasting) such a complex system requires the quantification of aleatory variability in the lahar triggering and propagation. To fulfill this goal, we develop a novel framework for probabilistic hazard assessment of lahars within a multi-hazard environment, based on coupling a versatile probabilistic model for lahar triggering (a Bayesian Belief Network: Multihaz) with a dynamic physical model for lahar propagation (LaharFlow). Multihaz allows us to estimate the probability of lahars of different volumes occurring by merging varied information about regional rainfall, scientific knowledge on lahar triggering mechanisms and, crucially, probabilistic assessment of available pyroclastic material from tephra fallout and PDCs. LaharFlow propagates the aleatory variability modeled by Multihaz into hazard footprints of lahars. We apply our framework to Somma-Vesuvius (Italy) because: (1) the volcano is strongly lahar-prone based on its previous activity, (2) there are many possible source areas for lahars, and (3) there is high density of population nearby. Our results indicate that the size of the eruption preceding the lahar occurrence and the spatial distribution of tephra accumulation have a paramount role in the lahar initiation and potential impact. For instance, lahars with initiation volume ≥105 m3 along the volcano flanks are almost 60% probable to occur after large-sized eruptions (~VEI ≥ 5) but 40% after medium-sized eruptions (~VEI4). Some simulated lahars can propagate for 15 km or reach combined flow depths of 2 m and speeds of 5–10 m/s, even over flat terrain. Probabilistic multi-hazard frameworks like the one presented here can be invaluable for volcanic hazard assessment worldwide.

The quantitative assessment of the performance of earthquake prediction and/or forecast models is essential for evaluating their applicability for risk reduction purposes. Here we assess the earthquake prediction performance of the CN model applied to the Italian territory. This model has been widely publicized in Italian news media, but a careful assessment of its prediction performance is still lacking. In this paper we evaluate the results obtained so far from the CN algorithm applied to the Italian territory, by adopting widely used testing procedures and under development in the Collaboratory for the Study of Earthquake Predictability (CSEP) network. Our results show that the CN prediction performance is comparable to the prediction performance of the stationary Poisson model, that is, CN predictions do not add more to what may be expected from random chance.

This study presents the strategies adopted to modify the Proportional Hazard Model to fit the requirements for forecasting testing within the Collaboratory Study for Earthquake Predictability (CSEP) experiment. The model was originally proposed to study the spatiotemporal distribution of M5.5+ seismicity in Italy, through two spatial models: a regular grid, and a seismotectonic zonation. A prospective 10-year-forecast test has already been ongoing since 2005, and the results are available on the internet (http://www.bo.ingv.it/earthquake/ ITALY/forecasting/M5.5+/). For that test, we have reported the probability maps of M5.5+ earthquakes for the next 10 years for the two spatial models. As the original model is time-dependent, it is updated every year, and also immediately after the occurrence of a target event, e.g., Mw5.5. Although this prospective test is continuing and the model updates probabilities that are different from those of the CSEP experiments, we argue that a full evaluation of the model can only be achieved through this CSEP testing, where the performances of different models are compared using the same rules and tests. The major modification we have introduced into our model is the simulation of the expected numbers of events in the exposure time Dx. This is performed considering the probability that an event occurs in Dx, and evaluating the change this will cause in the expected number of events. This procedure is also implemented for the first and second generation of aftershocks.

We describe here the setting up of the first earthquake forecasting experiment for Italy within the Collaboratory for the Study of Earthquake Predictability (CSEP). The CSEP conducts rigorous and actual prospective forecast experiments for different tectonic environments in several forecast-testing centers around the globe. These forecasts are issued for future periods, and are tested only against future observations, to avoid any possible bias. As such, the experiments need to be completely defined. This includes exact definitions of the testing area, of the learning data for the forecast models, and of the observation data against which the forecasts will be tested to evaluate their performance. We present the rules that were taken from the Regional Earthquake Likelihood Models experiments and extended and modified for the Italian experiment. We also present the characterizations of the learning and observational catalogs that describe the completeness of these catalogs, and reveal inhomogeneities in the magnitudes between these catalogs. A particular focus lies on the stability of the earthquake recordings of the observational network. These catalog investigations provide guidance for CSEP modelers for the development of earthquakes forecasts for submission to the forecast experiments in Italy.

This study investigates the basic properties of the recent shallow seismicity in Italy, through stochastic modeling and statistical methods. Assuming that earthquakes are the realization of a stochastic point process, we have modeled the occurrence rate density in space, time and magnitude using an epidemic-type aftershock sequence model. By applying the maximum likelihood procedure, we estimated the parameters of the model that best fit the Italian instrumental catalog, as recorded by the Istituto Nazionale di Geofisica e Vulcanologia (INGV) from April 16, 2005, to June 1, 2009. Then we applied the estimated model to a second independent dataset (June 1, 2009, to September 1, 2009). We show that the model performed well on this second database, through the relevant statistical tests. The model proposed in the present study is suitable for computing earthquake occurrence probability in real time, and to take part in international initiatives such as the Collaboratory Study for Earthquake Predictability, where we have submitted this model for daily forecasting of Italian seismicity for ML>4.0.

On August 1, 2009, the global Collaboratory for the Study of Earthquake Predictability (CSEP) launched a prospective and comparative earthquake predictability experiment in Italy. The goal of this CSEP-Italy experiment is to test earthquake occurrence hypotheses that have been formalized as probabilistic earthquake forecasts over temporal scales that range from days to years. In the first round of forecast submissions, members of the CSEP-Italy Working Group presented 18 five-year and ten-year earthquake forecasts to the European CSEP Testing Center at ETH Zurich. We have considered here the twelve time-independent earthquake forecasts among this set, and evaluated them with respect to past seismicity data from two Italian earthquake catalogs. We present the results of the tests that measure the consistencies of the forecasts according to past observations. As well as being an evaluation of the time-independent forecasts submitted, this exercise provides insight into a number of important issues in predictability experiments with regard to the specification of the forecasts, the performance of the tests, and the trade-off between robustness of results and experiment duration. We conclude with suggestions for the design of future earthquake predictability experiments.

The purpose of this study was to apply a double-branching model to forecasting of moderate-to-large Italian seismicity within the Collaboratory Study for Earthquake Predictability project. This project is designed for statistical evaluations and comparisons of various forecasting models, on both the global and regional scales. This proposed double-branching model is time-dependent, as it assumes that each earthquake can generate, or is correlated with, other earthquakes through physical mechanisms that act on different spatio-temporal scales. Specifically, it consists of an application of two branching processes, in which any earthquake can trigger a family of later events on different space-time scales. In our recent study [Lombardi and Marzocchi 2009], we applied this model to a declustered historical database that included the strong Italian seismicity from over the last few centuries. This catalog only allowed us to describe the long-term time evolution of moderate-to-strong seismicity. Here, we have applied this double-branching model to a new database that has allowed us to describe both short-term clustering and long-term features at the same time. As the model can produce forecasting calculations of future seismicity, we provide some probability maps of occurrence of predicted events over different temporal windows.

A workshop on Operational earthquake forecasting and decision making was convened in Varenna, Italy, on June 8-11, 2014, under the sponsorship of the EU FP 7 REAKT (Strategies and tools for Real-time EArthquake risK reducTion) project, the Seismic Hazard Center at the Istituto Nazionale di Geofisica e Vulcanologia (INGV), and the Southern California Earthquake Center (SCEC). The main goal was to survey the interdisciplinary issues of operational earthquake forecasting (OEF), including the problems that OEF raises for decision making and risk communication. The workshop was attended by 64 researchers from universities, research centers, and governmental institutions in 11 countries. Participants and the workshop agenda are listed in the appendix.The workshop comprised six topical sessions structured around three main themes: the science of operational earthquake forecasting, decision making in a low-probability environment, and communicating hazard and risk. Each topic was introduced by a moderator and surveyed by a few invited speakers, who were then empaneled for an open discussion. The presentations were followed by poster sessions. During a wrap-up session on the last day, the reporters for each topical session summarized the main points that they had gleaned from the talks and open discussions. This report attempts to distill this workshop record into a brief overview of the workshop themes and to describe the range of opinions expressed during the discussions.

On May 20, 2012, at 02:03 UTC, a magnitude Ml 5.9 earthquake hit part of the Po Plain area (latitude, 44.89 ˚N; longitude, 11.23 ˚E) close to the village of Finale-Emilia in the Emilia-Romagna region (northern Italy). This caused a number of human losses and significant economic damage to buildings, and to local farms and industry. This earthquake was preceded by an increase in the seismicity the day before, with the largest shock of Ml 4.1 at 23:13 UTC (latitude, 44.90 ˚N; longitude, 11.26 ˚E). It was then followed by six other Ml 5.0 or greater events in the following weeks. The largest of these six earthquakes occurred on May 29, 2012, at 07:00 UTC (Ml 5.8), and was located 12 km southwest of the May 20, 2012, main event (latitude, 44.85 ˚N; longitude, 11.09 ˚E), resulting in the collapse of many buildings that had already been weakened, a greater number of victims, and most of the economic damage (see Figure 1). This sequence took place in one of the Italian regions that is considered to be at small-to-moderate seismic hazard [Gruppo di Lavoro MPS 2004]. Earthquakes of the M6 class have occurred in the past in this zone [Gruppo di Lavoro CPTI 2004], but with a much smaller time frequency with respect to the most seismically hazardous parts of Italy. […]

In his commentary on the International Commission on Earthquake Forecasting (ICEF) report [Jordan et al. 2011], Crampin [2012] claims that observable changes in shear-wave splitting can predict large earthquakes on short time scales with high reliability and skill, and he challenges a central ICEF finding—that no method has yet demonstrated such a predictive capability. In particular, Crampin asserts that "observations of seismic shear-wave splitting monitored at a three-borehole Stress-Monitoring Site (SMS) in central Italy could monitor stress-accumulation and stress-relaxation (crack-coalescence) before all damaging (M ≥ 5) earthquakes within 1000 km of the SMS […] This means that installation of one expensive SMS (preferably two throughout the length of Italy) would stress-forecast the time, magnitude, and in some circumstances fault-break of all potentially damaging on the mainland of Italy".Crampin's assertions are based on prediction methods he has advocated for several decades [e.g., Crampin et al. 1984; Crampin et al. 1990]. As part of the ICEF study, we reviewed the literature on these methods. Nothing contained in the present commentary compels us to alter our previous findings. [...]

Following the 2009 L'Aquila earthquake, the Dipartimento della Protezione Civile Italiana (DPC), appointed an International Commission on Earthquake Forecasting for Civil Protection (ICEF) to report on the current state of knowledge of short-term prediction and forecasting of tectonic earthquakes and indicate guidelines for utilization of possible forerunners of large earthquakes to drive civil protection actions, including the use of probabilistic seismic hazard analysis in the wake of a large earthquake. The ICEF reviewed research on earthquake prediction and forecasting, drawing from developments in seismically active regions worldwide. A prediction is defined as a deterministic statement that a future earthquake will or will not occur in a particular geographic region, time window, and magnitude range, whereas a forecast gives a probability (greater than zero but less than one) that such an event will occur. Earthquake predictability, the degree to which the future occurrence of earthquakes can be determined from the observable behavior of earthquake systems, is poorly understood. This lack of understanding is reflected in the inability to reliably predict large earthquakes in seismically active regions on short time scales. Most proposed prediction methods rely on the concept of a diagnostic precursor; i.e., some kind of signal observable before earthquakes that indicates with high probability the location, time, and magnitude of an impending event. Precursor methods reviewed here include changes in strain rates, seismic wave speeds, and electrical conductivity; variations of radon concentrations in groundwater, soil, and air; fluctuations in groundwater levels; electromagnetic variations near and above Earth's surface; thermal anomalies; anomalous animal behavior; and seismicity patterns. The search for diagnostic precursors has not yet produced a successful short-term prediction scheme. Therefore, this report focuses on operational earthquake forecasting as the principle means for gathering and disseminating authoritative information about time-dependent seismic hazards to help communities prepare for potentially destructive earthquakes. On short time scales of days and weeks, earthquake sequences show clustering in space and time, as indicated by the aftershocks triggered by large events. Statistical descriptions of clustering explain many features observed in seismicity catalogs, and they can be used to construct forecasts that indicate how earthquake probabilities change over the short term. Properly applied, short-term forecasts have operational utility; for example, in anticipating aftershocks that follow large earthquakes. Although the value of long-term forecasts for ensuring seismic safety is clear, the interpretation of short-term forecasts is problematic, because earthquake probabilities may vary over orders of magnitude but typically remain low in an absolute sense (< 1% per day). Translating such low-probability forecasts into effective decision-making is a difficult challenge. Reports on the current utilization operational forecasting in earthquake risk management were compiled for six countries with high seismic risk: China, Greece, Italy, Japan, Russia, United States. Long-term models are currently the most important forecasting tools for civil protection against earthquake damage, because they guide earthquake safety provisions of building codes, performance-based seismic design, and other risk-reducing engineering practices, such as retrofitting to correct design flaws in older buildings. Short-term forecasting of aftershocks is practiced by several countries among those surveyed, but operational earthquake forecasting has not been fully implemented (i.e., regularly updated and on a national scale) in any of them. Based on the experience accumulated in seismically active regions, the ICEF has provided to DPC a set of recommendations on the utilization of operational forecasting in Italy, which may also be useful in other countries. The public should be provided with open sources of information about the short-term probabilities of future earthquakes that are authoritative, scientific, consistent, and timely. Advisories should be based on operationally qualified, regularly updated seismicity forecasting systems that have been rigorously reviewed and updated by experts in the creation, delivery, and utility of earthquake information. The quality of all operational models should be evaluated for reliability and skill by retrospective testing, and they should be under continuous prospective testing against established long-term forecasts and alternative time-dependent models. Alert procedures should be standardized to facilitate decisions at different levels of government and among the public. Earthquake probability thresholds should be established to guide alert levels based on objective analysis of costs and benefits, as well as the less tangible aspects of value-of-information, such as gains in psychological preparedness and resilience. The principles of effective public communication established by social science research should be applied to the delivery of seismic hazard information.

«A hypothesis that cannot in principle be put to the test of evidence may be interesting, but it is not scientifically useful.» [AAAS 1989]This statement was reported by the American Association for the Advancement of Science – the largest general scientific society in the World – and it describes well the basic rationale that stands at the root of the Collaboratory for the Study of Earthquake Predictability (CSEP; www.cseptesting.org), a project initiated by the Southern California Earthquake Center...

Background: Hospitalization represents a major access point for prescription opioids, yet little is known regarding patterns and outcomes of opioid exposures before and after hospitalization for critical illness. Methods: This is an observational, population-based cohort study of adults (≥18 years) hospitalized for critical illness from 2010 to 2019. Multivariable models assess associations between opioid exposures prior to hospitalization, classified according to the Consortium to Study Opioid Risks and Trends, and posthospitalization opioid exposures and clinical outcomes through 1-year posthospitalization. Results: Of 11 496 patients, 6318 (55%) were men with a median age of 66 (51, 79) years and 40% (n = 4623) surgical admissions. Prehospitalization opioid availability included 8449 (73%) none, 2117 (18%) short-term, 471 (4%) episodic, and 459 (4%) long-term. Thirty-nine percent (4144/10 708) of hospital survivors were discharged with opioids, with higher prescribing rates for surgical admissions (55%). Greater preadmission opioid exposures were associated with higher prevalent opioid availability at 1 year (odds ratio [95% confidence interval] 24.1 [18.3-31.8], 9.42 [7.18-12.3], and 2.55 [2.08-3.12] for long-term, episodic, and short-term exposures, respectively, vs none, P  < .001). Greater preadmission opioid exposures were associated with longer hospitalizations (1.13 [1.04-1.23], 1.15 [1.06-1.25], and 1.08 [1.04-1.13] multiplicative increase in geometric mean, P  < .001), more readmissions (hazard ratio [HR] 2.08 [1.74-2.49], 1.88 [1.56-2.26], and 1.48 [1.33-1.64], P  < .001), and higher 1-year mortality (HR 1.59 [1.28-1.98], 1.75 [1.41-2.18], and 1.49 [1.32-1.69], P  < .001). Similar associations were observed across surgical and nonsurgical admissions. Conclusions: Prehospitalization opioid exposures in survivors of critical illness are associated with clinical outcomes through 1 year and may serve as important prognostic markers., Competing Interests: Declaration of Conflicting InterestsThe authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Matthew Warner receives research support from the National Institutes of Health; serves on the board of directors for the Society for the Advancement of Patient Blood Management. Nafisseh Warner receives research support from the National Institutes of Health; serves on editorial board of the journal Pain Medicine and Anesthesia & Analgesia. Other authors have no conflicts of interest to disclose.

Competing Interests: Conflicts of Interest, Funding: Please see DISCLOSURES at the end of this article.

Background: Some patients express concerns regarding receipt of allogeneic blood transfusions from donors potentially vaccinated against SARS-CoV-2 (COVID-19). However, limited information exists about patients' expression of these concerns or how to address them during the blood transfusion consent process. In this study, we describe our experience of working collaboratively with patients with vaccine-related transfusion concerns prior to elective surgery, summarizing treatment decisions and clinical outcomes., Study Design and Methods: This observational descriptive study includes patients seen in our Bloodless Medicine and Surgery clinic between June 2022 and June 2024 for vaccine-related transfusion concerns prior to elective surgery. A shared decision-making framework was employed to foster conversation, share information, provide reassurance, reconcile conflict, and match preferences with available care options. Patient characteristics, treatment decisions, and surgical outcomes were reviewed and summarized., Results: Thirty-five patients were included, with median (1st, 3rd quartile) age of 61 (53, 69) years. Cardiac surgery was the most common type of surgery (29%). Twelve patients (34%) were anemic preoperatively, and all received preoperative treatment. After discussion with a Bloodless Medicine specialist, 24 (68.6%) decided to consent to the use of all blood products, 5 (14.3%) accepted only red blood cells, and 6 (17.1%) declined all blood products. Among 28 patients undergoing surgery, only 4 (14%) received allogeneic transfusion perioperatively., Conclusion: Many patients concerned about the vaccination status of blood donors may ultimately consent to allogeneic blood products after shared decision-making with a Bloodless Medicine specialist, highlighting the importance of patient empowerment and collaborative care., (© 2024 AABB.)

Preoperative anemia is common and associated with worse outcomes in cardiac surgery including acute kidney injury, red blood cell transfusion, cardiovascular complications, stroke, infection, and death. Patient blood management programs, which include dedicated clinical programs to diagnose and treat anemia in advance of surgery (ie, preoperative anemia programs), have been highlighted as a means to optimize the blood health of each patient, thereby decreasing risk for allogeneic transfusion and improving clinical outcomes. However, there remain implementation challenges for preoperative anemia programs, including difficulties with education of patients and staff, short lead times to address anemia, infrastructure and staffing limitations, lack of clear leadership or ownership of preoperative anemia, the need to develop treatment algorithms and ensure appropriate infusion therapy support, lack of capital support, and insurance/reimbursement concerns, amongst others. The purpose of this advisory from the Society of Cardiovascular Anesthesiologists (SCA) Clinical Practice Improvement Committee and the Subcommittee on Patient Blood Management with endorsement from the Society for the Advancement of Patient Blood Management (SABM) is to provide guidance on the development and implementation of a preoperative anemia clinic or service line, including identification and navigation through potential logistical barriers. A detailed analysis of financial incentives is highlighted in our companion article in this edition focuses on the return on investment of anemia management. Although originating with a focus on anemia before cardiac surgery, this advisory is broadly applicable to all perioperative patients., Competing Interests: Conflicts of Interest, Funding: Please see DISCLOSURES at the end of this article., (Copyright © 2024 International Anesthesia Research Society.)