Likelihood Of Events Research Articles

An integrated deep learning and natural language processing approach for continuous remote monitoring in digital health

The rapid adoption of digital health technologies generates a vast amount of health data, presenting an opportunity to leverage advanced data analytics and cognitive computing to extract insights and knowledge from this data and improve healthcare outcomes. This research presents an integrated deep learning (DL) and natural language processing (NLP) approach for continuous remote monitoring in digital health. The approach involves using DL algorithms to analyze data collected from wearable devices and remote monitoring tools, while NLP is used to analyze patient feedback and electronic medical records. Various DL algorithms, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), are suggested to analyze medical images and time-series data, and unsupervised learning techniques, such as autoencoders, are recommended for feature extraction. We provide a comparison between our proposed approach and previous related works. We also identify and discuss the limitations of existing works and explain how our approach overcomes these limitations. The study also delivers a review of the prevailing work of data analytics and cognitive computing in digital health, examining the applications of these technologies in various areas of healthcare, identifying the challenges and opportunities of implementing them in healthcare, and proposing research directions that can help accelerate their adoption. The proposed approach can enable health professionals to remotely monitor patients’ health conditions in real-time and predict the likelihood of adverse health events, leading to improved patient outcomes, reduced healthcare costs, and enhanced quality of care. This paper provides insights into current trends, challenges, and research directions in digital health, informing future research and development.

“Technology is killing me!”: the moderating effect of organization home-work interface on the linkage between technostress and stress at work

PurposeThe fear of the pandemic, confinement at home and the need to work created a unique situation. The pandemic catalyzed work-from-anywhere practice by adopting information and communication technologies (ICT) across all industries. While ICT saved organizations, it increased technostress among the workforce. A better understanding of the adverse effects of ICT usage might enable organizations to manage the mental well-being of the workforce. While technostress is gaining increasing interest, scholarly work investigating the dimensions of technostress and its impact on creating stress across various employee demographics and industry types is missing. Contrary to the prevalent assumptions, the authors theorized and tested the adverse moderation effect of the home-work interface on the linkage between technostress dimensions and stress. This paper aims to discuss the aforementioned objective.Design/methodology/approachThe study captures dimensions of technostress and the resulting stress at work using a survey-based analysis of 881 working employees in India, representing multiple industries and functions.FindingsThe study indicates that techno-overload, techno-complexity and techno-invasion significantly impact employees during the pandemic. The authors further found that the home-work-interface is a powerful factor in understanding the complex linkage between dimensions of technostress and its outcomes.Research limitations/implicationsBased on the Conservation of Resources Theory and the Job-Demand-Resources model, this study highlights the adverse impact of this trend on employee well-being. However, the study suffers from a cross-sectional research design. The technostress research has focused primarily on static, at-premise environments and mostly on high ICT usage industries. Due to the pandemic, it has neglected the impact of various technostress dimensions across employee cohorts subjected to rapid technology-enabled working. Further, most studies focus on the voluntary choice of remote work. Employees struggle with the unexpected and involuntary shift to technology-enabled remote work. This study contributes to the literature by examining the consequences of technostress in the context of non-voluntary remote work. Contrary to prevailing assumptions, this study highlights the adverse effect of organizational home-work interface in influencing ICT-created stress.Practical implicationsThe increasing use of ICT enables telecommuting across the workforce while increasing organizational productivity. Due to the pandemic, these trends will likely change the future of work permanently. To minimize employee stress, practitioners need to reconsider the dimensions of technostress. Further, the study cautions against the prevalent interventions used by practitioners. While practitioners facilitate a home-work interface, it could have adverse consequences. Practitioners may consider the adverse consequences of home-work interface while designing organizational policies.Social implicationsThis study during the pandemic is crucial as research forecasts the likelihood of other cataclysmic events, such as future pandemics and political or climate change events, which may sustain technology-driven remote work practices and remain a feature of the future workplace. Hence understanding the implications of the dimensions of technostress would help organizations and policymakers to implement necessary interventions to minimize employee stress.Originality/valueThe present study examines the dimensions of technostress across multiple industries and job functions in an emerging market marked by a high economic growth rate and an Eastern cultural context. This study presents the dark side of excessive ICT adoption and indicates how organizations and HRM practices can help mitigate some of these effects.

Selective COX-2 inhibitors do not increase gastrointestinal reactions after colorectal cancer surgery: a systematic review and meta-analysis

BackgroundThe effectiveness of selective COX-2 inhibitors in preventing colorectal cancer recurrence has been demonstrated, however it is unknown how safe and successful they will be over the long term. As a result, we looked at the efficacy, safety, and consequences of adding COX-2 inhibitors to the treatment plan afterward.MethodsIn patients with advanced colorectal cancer, we compared the efficacy of celecoxib at two different doses (200 mg twice day and 400 mg twice daily) with placebo. To evaluate the impacts of post-treatment, several datasets from inception to June 2022 were searched. Response rate, illness control rate, and 3-year survival were the main results. And evaluated several safety outcomes, particularly those that were susceptible to adverse events.ResultsThe study comprised a total of 9 randomized controlled trials (3206 participants). Celecoxib and rofecoxib doidn’t significantly improved the 1–3 year remission rate (OR, 1.57 [95% CI: 0.95–2.57]) and disease control rate (OR, 1.08 [95% CI: 0.99–1.17]). Subgroup analysis of different doses showed that 400 mg of celecoxib significantly improved the response rate (OR, 2.82 [95%CI: 1.20–6.61]). 200 mg celecoxib was not significant (OR, 1.28 [95% CI: 0.66–2.49]). Rofecoxib also did not fully improve disease response rates. Celecoxib at any dose improved 3-year survival (OR, 1.21 [95% CI: 1.02–1.45]). It is important to note that COX-2 inhibitors did not significantly enhance the likelihood of adverse events including gastrointestinal or cardiovascular side effects at any dose.ConclusionsFor patients with advanced colorectal cancer, a reasonable chemoprevention regimen can include celecoxib 400 mg twice daily.

The effect of a multi-component behavior change technique intervention on medication adherence among individuals on primary prevention statin therapy: a dose-finding protocol

BackgroundIn the USA, the primary cause of death and morbidity continues to be cardiovascular disease (CVD). Numerous trials have shown that statin medication reduces the likelihood of CVD events; it is a cornerstone of CVD prevention. However, studies have also indicated that up to 60% of the estimated 26.8 million Americans prescribed primary prevention statin treatment are nonadherent during the first year. Multi-component behavioral change technique (BCT) therapies have shown moderate promise in improving medication adherence as well as other positive health behaviors (such as physical activity). However, no research has looked at the duration of multi-component BCT intervention needed to result in a clinically significant improvement in statin adherence behaviors. This study aims to determine the necessary dose of a multi-component BCT intervention (defined as duration in weeks) to promote adherence to statin medication among those on primary prevention statin treatment by utilizing the modified time-to-event continuous reassessment method (TiTE-CRM).Methods and designThe study will utilize the modified TiTE-CRM in 42 participants, recruited in 14 cohorts of 3 participants each. The goal of this analysis is to identify the minimum effective dose (MED) of a multi-behavior change technique (BCT) intervention required to increase adherence to statins by 20% between baseline and follow-up periods. Using the TiTE-CRM method, the dose of the behavior intervention in weeks will be assigned to each cohort based on the performance of the prior cohort. At the end of the study, the intervention dose that has been found to be associated with a 20% increase in statin adherence among 80% of participants assigned to that dose will be identified as the MED.DiscussionIf successful, the current trial will provide additional guidance to researchers and clinicians seeking to increase statin medication adherence using a BCT intervention by identifying the dose (i.e., the duration) of an intervention required to meaningfully increase adherence.Trial registrationClinicalTrials.gov NCT05273736. Registered on March 10, 2022. https://www.clinicaltrials.gov/ct2/show/NCT05273736

Biases in Estimating Long‐Term Recurrence Intervals of Extreme Events Due To Regionalized Sampling

AbstractPreparing for environmental risks requires estimating the frequencies of extreme events, often from data records that are too short to confirm them directly. This requires fitting a statistical distribution to the data. To improve precision, investigators often pool data from neighboring sites into single samples, referred to as “superstations,” before fitting. We demonstrate that this technique can introduce unexpected biases in typical situations, using wind and rainfall extremes as case studies. When the combined locations have even small differences in the underlying statistics, the regionalization approach gives a fit that may tend toward the highest levels suggested by any of the individual sites. This bias may be large or small compared to the sampling error, for realistic record lengths, depending on the distribution of the quantity analyzed. The results of this analysis indicate that previous analyses could potentially have overestimated the likelihood of extreme events arising from natural weather variability.

Behavioral Health Decision Support Systems and User Interface Design in the Emergency Department.

The objective of this qualitative study is to gauge physician sentiment about an emergency department (ED) clinical decision support (CDS) system implemented in multiple adult EDs within a university hospital system. This CDS system focuses on predicting patients' likelihood of ED recidivism and/or adverse opioid-related events. The study was conducted among adult emergency physicians working in three EDs of a single academic health system in Rhode Island. Qualitative, semistructured interviews were conducted with ED physicians. Interviews assessed physicians' prior experience with predictive analytics, thoughts on the alert's placement, design, and content, the alert's overall impact, and potential areas for improvement. Responses were aggregated and common themes identified. Twenty-three interviews were conducted (11 preimplementation and 12 postimplementation). Themes were identified regarding each physician familiarity with predictive analytics, alert rollout, alert appearance and content, and on alert sentiments. Most physicians viewed these alerts as a neutral or positive EHR addition, with responses ranging from neutral to positive. The alert placement was noted to be largely intuitive and nonintrusive. The design of the alert was generally viewed positively. The alert's content was believed to be accurate, although the decision to respond to the alert's call-to-action was physician dependent. Those who tended to ignore the alert did so for a few reasons, including already knowing the information the alert contains, the alert offering information that is not relevant to this particular patient, and the alert not containing enough information to be useful. Ultimately, this alert appears to have a marginally positive effect on ED physician workflow. At its most beneficial, the alert reminded physicians to deeply consider the care provided to high-risk populations and to potentially adjust their care and referrals. At its least beneficial, the alert did not affect physician decision-making but was not intrusive to the point of negatively impacting workflow.

Aso volcano, Japan: assessing the 100-year probability of a new caldera-forming eruption based on expert judgements with Bayes Net and Importance Sampling uncertainty analysis

The Aso-4 explosive eruption on Kyushu, Japan, 89,500 years ago was one of the biggest eruptions in the last one hundred millennia, with a magnitude of approximately M8. Modern society requires the likelihood of natural events with potentially disastrous consequences to be evaluated, even if probabilities of occurrence are diminishingly small. For some situations, it is not satisfactory to assert an event scenario probability is “negligible” or can be “ignored”. Judicial hearings or litigation may require risk levels to be quantified, in which case, statements of scientific confidence could be decisive. Internationally, e.g., for nuclear site safety evaluations, event likelihoods on order of 10–7/year are often considered for quantitative assessment. At such hazard levels, this might include evaluating the proposition that a particular volcano can deliver a future super-eruption, a supposition that could be attached to Aso volcano. But, simplistically taking the average recurrence interval between past caldera-forming eruptions at a given volcano is an unreliable guide to the likelihood of a future repeat: each past event represented a unique set of tectonic and magmatic conditions within a continually evolving volcanic system. Such processes are not temporally stationary nor statistically uniform. To evaluate the probability of a new M8 event at Aso, within the next 100 years, we performed a comprehensive stochastic probability uncertainty analysis using a model implemented with advanced computational Bayes Net (BN) software. Our eruption process model is informed by multiple strands of evidence from volcanology, petrology, geochemistry and geophysics, together with estimates of epistemic (knowledge) uncertainty, adduced from reviews of published data, modelling and from expert judgement elicitation. Several lines of evidence characterise the likely structure, magmatic composition and eruptive state of the present-day Aso volcano, which has had numerous smaller eruptions since Aso-4. To calculate the probability of another M8 eruption of Aso, we implemented probabilistic ‘Importance Sampling’ in our model. With this approach, we find the chance of an Aso-4 scale eruption (characterised by mean volume 500 km3 DRE and approximate 90% credible interval [210 ‥ 1200] km3 DRE) is less than 1–in–1 billion in the next 100 years (i.e., < 10–9 probability). Based on current volcanological understanding and evidence, we believe this probability estimate is robust to within an order of magnitude.

Extreme Events Analysis Using LH-Moments Method and Quantile Function Family

A direct way to estimate the likelihood and magnitude of extreme events is frequency analysis. This analysis is based on historical data and assumptions of stationarity, and is carried out with the help of probability distributions and different methods of estimating their parameters. Thus, this article presents all the relations necessary to estimate the parameters with the LH-moments method for the family of distributions defined only by the quantile function, namely, the Wakeby distribution of 4 and 5 parameters, the Lambda distribution of 4 and 5 parameters, and the Davis distribution. The LH-moments method is a method commonly used in flood frequency analysis, and it uses the annual series of maximum flows. The frequency characteristics of the two analyzed methods, which are both involved in expressing the distributions used in the first two linear moments, as well as in determining the confidence interval, are presented. The performances of the analyzed distributions and the two presented methods are verified in the following maximum flows, with the Bahna river used as a case study. The results are presented in comparison with the L-moments method. Following the results obtained, the Wakeby and Lambda distributions have the best performances, and the LH-skewness and LH-kurtosis statistical indicators best model the indicators’ values of the sample (0.5769, 0.3781, 0.548 and 0.3451). Similar to the L-moments method, this represents the main selection criterion of the best fit distribution.

Comparative clinical and placental pathologic characteristics in pregnancies with and without SARS-CoV-2 infection.

To compare the clinical and morphological characteristics of the "mother-placenta-fetus" system in high risk pregnant women of three groups: no SARS-CoV-2 infection, mild SARS-CoV-2 infection, and severe SARS-CoV-2 infection. A case-control study was performed for all deliveries, at 28weeks' gestation or greater, who had standard indications for placental pathologic examination. Three groups were formed: (1) control group (no SARS-CoV-2 infection), (2) mild SARS-CoV-2 infection, (3) severe SARS-CoV-2 infection. High-risk pregnancies were registered in all cases inthe study groups. The examination of the placenta and theselection of fragments of placental tissue were carried outin accordance with the consensus recommendations of the Amsterdam Placental Workshop Group. The sections were subjected to standard processing and stained with hematoxylin and eosin according to the standard protocol. All caseswere reviewed by two pathologists, which did not know anyinformation on pregnancy outcome and clinical data. Statistical analysis was performed using SPSS, p<0.05 was considered statistically significant. Women with severe SARS-CoV-2 infection had an increased rate of multimorbidity including diabetes, chronic hypertension and obesity (p<0.01) compared with the other groups. Placentas at severe COVID-19 course were damaged by both chronic and acute injuries, in comparison to the mild and control groups (p<0.001). Also an important finding in severe COVID-19 was diffuse necrosis of the villous trophoblast- homogenization, diffuse circular eosinophilic masses surrounding the chorionic villi. Women with multimorbidity are an "at-risk" subgroup for severe SARS-CoV-2 infection and greater likelihood of both placental damage and perinatal hypoxic-ischemic events. These results suggest that patient education, SARS-CoV-2 disease monitoring and preventive measures would be of benefit to this group.

Predicting Compound Coastal Flooding in Embayment-Backed Urban Catchments: Seawall and Storm Drain Implications

Urban coastal flooding is a global humanitarian and socioeconomic hazard. Rising sea levels will increase the likelihood of hydrologic events interacting with high marine water levels. These compound events may, in turn, nonlinearly interact with urban infrastructure, potentially resulting in more extreme coastal flooding events. Here, an integrated Delft3D-FM based numerical modeling framework is used to concomitantly resolve multi-source flood processes (i.e., high marine water levels, precipitation) and infrastructure (e.g., seawalls, storm drains). Hydrodynamic model results are validated with embayment pressure sensor data and photographic observations from historical events. The impact of tide and precipitation phasing are examined. Multiple storm drain characterizations are presented and evaluated. Results show seawall and storm drain infrastructure is fundamental to accurately resolving spatial and temporal flood dynamics. Importantly, coastal management strategies such as raising seawall elevations to mitigate tidal flooding may exacerbate precipitation-based flooding in low-lying urban regions.

Wave damping by giant kelp, Macrocystis pyrifera.

The increased likelihood and severity of storm events has brought into focus the role of coastal ecosystems in provision of shoreline protection by attenuating wave energy. Canopy-forming kelps, including giant kelp (Macrocystis pyrifera), are thought to provide this ecosystem service, but supporting data are extremely limited. Previous in situ examinations relied mostly on comparisons between nominally similar sites with and without kelp. Given that other factors (especially seafloor bathymetry and topographic features) often differ across sites, efforts to isolate the effects of kelp on wave energy propagation confront challenges. In particular, it can be difficult to distinguish wave energy dissipation attributable to kelp from frictional processes at the seabed that often covary with the presence of kelp. Here, we use an ecological transition from no kelp to a full forest, at a single site with static bathymetry, to resolve unambiguously the capacity of giant kelp to damp waves. We measured waves within and outside rocky reef habitat, in both the absence and the presence of giant kelp, at Marguerite Reef, Palos Verdes, CA, USA. Nested within a broader kelp restoration project, this site transitioned from a bare state to one supporting a fully formed forest (density of 8 stipes m-2). We quantified, as a function of incident wave conditions, the decline in wave energy flux attributable to the presence of kelp, as waves propagated from outside and into reef habitat. The kelp forest damped wave energy detectably, but to a modest extent. Interactions with the seabed alone reduced wave energy flux, on average, by 12 ± 1.4 % over 180 m of travel. The kelp forest induced an additional 7 ± 1.2 % decrease. Kelp-associated declines in wave energy flux were slightly greater for waves of longer periods and smaller wave heights. Macrocystis pyrifera forests have a limited, albeit measurable, capacity to enhance shoreline protection from nearshore waves. Expectations that giant kelp forests, whether extant or enhanced through restoration, have substantial impacts on wave-induced coastal erosion might require re-evaluation.

Research on Financial Default Model with Stochastic Intensity Using Filtered Likelihood Method

This paper investigates the financial default model with stochastic intensity by incomplete data. On the strength of the process-designated point process, the likelihood function of the model in the parameter estimation can be decomposed into the factor likelihood term and event likelihood term. The event likelihood term can be successfully estimated by the filtered likelihood method, and the factor likelihood term can be calculated in a standardized manner. The empirical study reveals that, under the filtered likelihood method, the first model outperforms the other in terms of parameter estimation efficiency, convergence speed, and estimation accuracy, and has a better prediction effect on the default data in China’s financial market, which can also be extended to other countries, which is of great significance in the default risk control of financial institutions.

The impact of heatwaves on human perceived thermal comfort and thermal resilience potential in urban public open spaces

Climate change increases the likelihood of heatwave events, causing human thermal discomfort and even mortality. However, it is not clear to what extent humans with long-term and short-term experience of hot-summer exposure can adapt to thermal comfort in urban public open spaces when both experience their heatwave periods. Therefore, this study aims to investigate outdoor perceived thermal comfort in urban public open spaces during heatwave periods between two groups of people who have long-term and short-term experience of hot-summer exposure. Field surveys were conducted in public squares and parks during the heatwaves in Chongqing, China and Reading, the UK. Chongqing is known as a ‘furnace city’ and people have been living in a hot summer for a long time, while in Reading the summer is warm and people unusually experience the heatwave. The main results show that Chongqing respondents living in a hot climate for a longer period can endure more heat than Reading respondents during the heatwaves, indicating that Chongqing respondents have more thermal resilience. Besides, different behavioural adaptation measures show that people are active participants to choose their thermal preferences, rather than passive recipients of the thermal environments. The research implication contributes that protective measures against heatwaves need to be taken for pedestrians, including more shaded places with efficient ventilation design for sheltering and handy facilities such as drinking fountains and water spray. The research has novelty in deepening the dynamic theory of human thermal comfort and providing empirical evidence of thermal adaptation in extreme-high temperature events.

Analysis of Legal Risk in Farms of Intensive Chicken Production - The Case of Kosovo

The intensive poultry industry in Kosovo fulfills a significant portion of the local demand for eggs. Considering this context, the sustainable development of this industry necessitates specific attention due to potential risks and threats. This paper aims to identify and evaluate legal risk events associated with the industry. We created a questionnaire with eight questions, using information from previous research and considering the actual conditions of the intensive poultry industry in Kosovo. Through face-to-face interviews with farmers and agricultural economists, we empirically assessed the likelihood and impact of each legal risk event. We set using a Likert scale ranging from 1 (very low) to 5 (very high). Both qualitative and quantitative methods were employed to evaluate the risk level of each event. The qualitative analysis and interpretation of the results emphasized the risk factors, which were categorized based on severity. The findings indicate that two events exhibit a mouse-like level of aggressiveness; one mirrors the aggressiveness of a rabbit, another resembles that of a shark, and four display the hostility of a lion. The quantitative analysis and interpretation of the results revealed a relatively high distribution of 75%, with a standard deviation of 9,608 euros and a considerably high coefficient of variation (95%) if these events were to occur. To mitigate the adverse impact of legal risk events, we recommend that farmers seek additional information and consult with professionals such as economists, veterinarians, animal husbandry experts, and lawyers.

Projected increases in extreme drought frequency and duration by 2040 affect specialist habitats and species in Scotland

Abstract Climate‐driven increases in drought occurrence are an overlooked risk in temperate climates, which may be less resilient to water scarcity than arid habitats. Scotland provides an example of a temperate oceanic climate in which drought risk is understudied, but could have substantial ecological impacts, particularly in combination with additional stressors. We modelled changes to risk of extreme drought occurrence in Scotland, and considered potential impacts of these changes on two key habitats, ombrotrophic (precipitation fed) wetlands and temperate rainforest. Using temperature and precipitation data from the UK Climate Projections 2018 and the drought index Standardized Precipitation‐Evapotranspiration Index, we calculated and mapped likely changes in extreme drought for the near future (2021–2040) in comparison to a baseline (1981–2001). We found likelihood of extreme drought events increased from an average of one event every 20 years in the baseline period, to one event every 3 years by 2040. Typical events were projected to be up to 2–3 months longer, with an average of 11 extra drought months per decade. Increases were projected throughout the country, but the effect was most severe in the east, and during autumn. Ombrotrophic wetlands have some level of adaptive resilience to drought, but are considered at high risk as several key sites are in drought hotspot areas. In contrast, Scotland's temperate rainforest is located in lower risk areas, but is typically less drought resilient. Potential impacts on these habitats include reductions in ecosystem services including carbon capture, reduced breeding success for multiple taxa and increased competition among plant communities, which threatens drought‐sensitive species. These projections suggest that climate‐driven drought risk is a significant and imminent threat, even in wet climates. In Scotland, the results can direct mitigation and management actions to areas likely to be at greatest risk, as well as informing conservation interventions that can cope with drought. Additionally, other areas with a temperate oceanic climate may be at risk of extreme drought and could experience similar consequences. Therefore, these results have implications both for facilitating improved resilience to extreme drought in Scotland and for potentially overlooked impacts of drought in oceanic climates elsewhere.

Efficacy and safety of belimumab therapy for patients with lupus nephritis: A meta-analysis and a propensity score-matched case-control study.

In this study, we performed a meta-analysis and a propensity score-matched case-control study to evaluate the efficacy and safety of belimumab in patients with lupus nephritis(LN). We analyzed the data from three randomized controlled trials (RCTs) to assess the effects of belimumab treatment on renal improvement and adverse effects. Our study included a total of six LN patients who received belimumab treatmentand an additional six LN patients who received standard therapy. All participants were followed up for a duration exceeding 96 weeks to evaluate the outcomes of the treatments. Our meta-analysis incorporated data from three articles involving a total of 666 patients. The results of the analysis revealed that a higher proportion of patients who received belimumab treatment experienced renal improvement compared to those in the control group. The patients in belimumab group had a higher renal complete response rate and proteinuria improvement rate compared to the control group. However, belimumab treatment did not increase the renal partial response rate compared to the control group. The belimumab group also exhibited a higher proportion of patients who achieved normalization of antidouble-stranded DNA, as well as normalization of low C3and C4 levels. In our case-control study, significant improvement in proteinuria was demonstrated with belimumab at Week 48 (p = 0.037) and at all subsequent time points (all p < 0.05). Over the course of 96 weeks, belimumab treatment was associated with renal function stabilization and an increase in C3 and C4 levels. Moreover, the use of belimumab resulted in a reduction in glucocorticoid dosage at Week24 (p = 0.02). Additionally, patients receiving belimumab treatment had a lower risk of severe treatment-emergent adverse events, and no other significant adverse effects were observed between the two groups. In patients with LN, the utilization of belimumab therapy has demonstrated notable improvements in renal response rates. Additionally, it has shown a decreased likelihood of serious treatment-related adverse events and a diminished need for glucocorticoid dosage when compared to the active control group.

Endotracheal Intubation of Difficult Airways in Emergency Settings: A Guide for Innovators.

Over 400,000 Americans are intubated in emergency settings annually, with indications ranging from respiratory failure to airway obstructions to anaphylaxis. About 12.7% of emergency intubations are unsuccessful on the first attempt. Failure to intubate on the first attempt is associated with a higher likelihood of adverse events, including oxygen desaturation, aspiration, trauma to soft tissue, dysrhythmia, hypotension, and cardiac arrest. Difficult airways, as classified on an established clinical scale, are found in up to 30% of emergency department (ED) patients and are a significant contributor to failure to intubate. Difficult intubations have been associated with longer lengths of stay and significantly greater costs than standard intubations. There exists a wide range of airway management devices, both invasive and noninvasive, which are available in the emergency setting to accommodate difficult airways. Yet, first-pass success rates remain variable and leave room for improvement. In this article, we review the disease states most correlated with intubation, the current landscape of emergency airway management technologies, and the market potential for innovation. The aim of this review is to inspire new technologies to assist difficult airway management, given the substantial opportunity for translation due to two key-value signposts of medical innovation: the potential to decrease cost and the potential to improve clinical outcomes.

Reconnoitering NGOs strategies to strengthen disaster risk communication (DRC) in Pakistan: A conventional content analysis approach

Risk communication is crucial since individuals need to understand how they are at risk and what proper steps to deal with flood events. Sharing information with the public opens the door for two-way communication about risks, wherein you learn about people's perspectives and work together to find ways to mitigate the risks. Beyond government scope, relief organizations play a big part in advising individuals about the likelihood of catastrophic events as they possess the commonalities that define community engagement. In numerous accounts of devastating events, the failure of risk management groups to coordinate their efforts and the public's mistrust of relief agencies are highlighted. One possible explanation for this skepticism could be relief organizations' failures in communicating risks. In addition, individuals' lack of skills and experience with catastrophes has left rural residents unprepared, which is why relief agencies need to raise their efforts or measures to communicate with people about possible risks. If these measures are uncovered, it could improve public communication and provide information for formulating recommendations to prevent fatalities. This study identifies the strategies used by relief organizations in enhancing disaster risk communication across four severely affected districts in Khyber Pakhtunkhwa, Pakistan. The qualitative research used semi-structured interviews with 50 participants from relief organizations, local institutions, and affected households. We employed qualitative content analysis and NVivo software to analyze the data. The findings of this study highlighted some significant strategies that relief organizations adopted in this line of work: the administration of educational and information transmission, managing obstacles in communication, and managing inter-organizational communications. The findings validate the potential for relief organizations to become change agents, facilitate communication between the public and relief organizations, and ultimately strengthen community resilience and reduce disaster risks as part of local responses.

Attribution of the heavy rainfall events leading to severe flooding in Western Europe during July 2021

In July 2021 extreme rainfall across Western Europe caused severe flooding and substantial impacts, including over 200 fatalities and extensive infrastructure damage within Germany and the Benelux countries. After the event, a hydrological assessment and a probabilistic event attribution analysis of rainfall data were initiated and complemented by discussing the vulnerability and exposure context. The global mean surface temperature (GMST) served as a covariate in a generalised extreme value distribution fitted to observational and model data, exploiting the dependence on GMST to estimate how anthropogenic climate change affects the likelihood and severity of extreme events. Rainfall accumulations in Ahr/Erft and the Belgian Meuse catchment vastly exceeded previous observed records. In regions of that limited size the robust estimation of return values and the detection and attribution of rainfall trends are challenging. However, for the larger Western European region it was found that, under current climate conditions, on average one rainfall event of this magnitude can be expected every 400 years at any given location. Consequently, within the entire region, events of similar magnitude are expected to occur more frequently than once in 400 years. Anthropogenic climate change has already increased the intensity of the maximum 1-day rainfall event in the summer season by 3–19 %. The likelihood of such an event to occur today compared to a 1.2 ^{circ }C cooler climate has increased by a factor of 1.2–9. Models indicate that intensity and frequency of such events will further increase with future global warming. While attribution of small-scale events remains challenging, this study shows that there is a robust increase in the likelihood and severity of rainfall events such as the ones causing extreme impacts in July 2021 when considering a larger region.

Immediate Prepectoral Breast Reconstruction Without Acellular Dermal Matrices: Preliminary Results.

Background: In an effort to shed light on the recent resurgence of prepectoral breast reconstruction and mounting concerns regarding acellular dermal matrices (ADMs), the senior author's experience with non-ADM-assisted immediate prepectoral breast reconstruction and its associated complications are presented. Methods: A retrospective cohort study of the senior author's prepectoral breast reconstruction practice without ADM from November 2019 to May 2021 was carried out. Data regarding patient demographics, oncologic management, and surgical outcomes were recorded. Results: A total of 66 patients (88 breasts) were included, with an average follow-up of 7.8 months (SD: 5.4). Of these, 24 (36.4%) underwent immediate expander and 42 (63.6%) direct-to-implant (DTI) reconstructions. Major complications included nipple-areolar complex necrosis (2%), hematoma (3%), device exposure (2%), and periprosthetic infections (5.7%). The overall rate of implant failure was 5.7%. Minor complications included simple cellulitis (10%) and minor wound dehiscence (4.5%). Increasing implant size (p < .005) in the DTI cohort and increasing body mass index (BMI) were associated with an increased likelihood of adverse events. Postmastectomy radiation had no effect on surgical complications. Conclusions: The authors hope that in the absence of large, prospective trials, our data demonstrate the safety of immediate prepectoral breast reconstruction without ADM. Our data demonstrate that our algorithm is particularly safe in patients with a low BMI and with an implant size <500cc in DTI reconstruction. Further large prospective studies are required to further support our data in demonstrating that foregoing ADM in immediate prepectoral reconstruction is a safe option.