Future Failure Research Articles

Prediction of water–main failures and management of the associated risks using integrated predictive analytics approach

Water distribution networks are vital to delivering potable water. They commonly include interconnected water mains (WMs), pumps and other hydraulic controls. Numerous WM failures have occurred due to ageing and harsh climate. This paper aims to predict the probability of future failures and integrate the predictions into risk-management strategies. The novelty lies in emphasising on the relevance to networks in cold regions like Canada. This study applied clustering and principal component analysis to the WM data from the Canadian City of Kitchener network. Clustering is shown to improve the failure prediction outcomes from the random forest algorithm and risk analysis output. Compared to without implementing clustering, the improvement reached 67–80% for WMs with high-rating risk. This paper successfully produced risk maps for Kitchener’s network, showing that only a small percentage (0.07–1.02%) of the existing WMs needs immediate action (prioritised rehabilitation or replacement). In addition to WM length and diameter, freeze index is shown to be an influence factor for failure predictions. The integrated, proactive approach discussed in this article can be applied to other cold-region WDNs. The results help reduce water losses and develop cost-effective, practical risk-management strategies.

Predicting future failures in generalized order statistics and related models

Quantile regression predictions are considered for generalized order statistics which extend results previously established for record values and order statistics. In order to derive the results, some (univariate and bivariate) distortion representations of generalized order statistics are established. In particular, prediction of the sth generalized order statistic X ( s ) ∗ based on F given a single (generalized) order statistic X ( r ) ∗ with r<s will be addressed. The presentation includes results for both known and unknown baseline distributions. In the latter case, we consider exponential distributions with unknown mean as well as the proportional hazards model. Using unimodality properties of the marginal density functions (pdf) of generalized order statistics, we find a simple representation of the maximum likelihood prediction of X ( s ) ∗ given X ( r ) ∗ .

Rainfall-induced Landslide in the Lesser Himalaya: A Case Study of the Pallotari Landslide, Lamjung, Central-West Nepal

The Pallotari area, located in the Marsyangdi Rural Municipality, Lamjung, central-west Nepal, within the Lesser Himalaya, was impacted by a series of rainfall-induced landslides in July 2020. This study focuses on the Pallotari landslide, one of the major landslides in the area. Geological and engineering geological studies were performed to identify the causes of this landslide, and its impacts to the local community. Our results indicate the major causative factors to be intensive rainfall, steep topography with loose colluvial soil, and some anthropogenic activities such as the construction of the rural roads through the crown area. The study area still has hanging colluvial material on the crown as well as on the left flank of the landslide, and the numerical model for slope stability analysis indicates it to be unstable even in the unsaturated condition. The colluvial material in the middle portion of the landslide also has the risk of failure in the saturation condition which can be due to intensive rainfall. However, the rock slope stability analysis using the kinematic analysis does not show any contribution to the orientation of discontinuities on the slope failure. The presence of several transverse and longitudinal cracks in the surrounding of the landslide are signs of future failure.

Root cause analysis of corrosion failure of a firefighting pipeline

This is a specific case of corrosion damage to underground pipelines in the Arabian Gulf region caused by stray current corrosion. The damage occurred in a fire protection piping system connected to a sprinkler system. The investigation revealed that the corrosion surface morphology was localized and had historically occurred in the same location of previously failed pipe sections. Despite previous attempts to correct the problem, the cause remained undetected and undetermined. It was determined that the failure was due to electromagnetic forces generated by the proximity of high AC and DC voltages. Specifically, the stray current corrosion was caused by interference from electrical cables, including a high-voltage cable and a ground discharge from electrical electrodes. To prevent future failures, it was strongly recommended that all existing conduit pipes in the affected section be insulated with double-layer insulating tape, which has high impedance and dielectric properties.

Developments with CROSS – Collaborative Reporting for Safer Structures

CROSS (Collaborative Reporting for Safer Structures) was formed in 2005 to capture structural safety concerns and events from confidentially submitted reports, and to share lessons learned from them. The objective is to identify precursors and help prevent future failures and loss of life. Reports are published on-line, and examples of reported concerns and safety events will be given. In 2017, a fire in Grenfell Tower in London resulted in 72 deaths. In response, an independent review of building regulations and fire safety recommended that CROSS should be expanded to include fire safety. Results from CROSS about structural and fire safety are available to all at no cost, thanks to funding support from UK professional institutions. As CROSS became established, there was interest from like-minded groups in other countries, and currently there are schemes in the US and Australasia with interest from others including in German. The ultimate aim is to have a global network of CROSS communities who exchange reports and publish material that will help to keep users of buildings safer. This will be a resource for owners, design practitioners, builders, regulators, academics and of course the public.

Usługi wczesnego wspomagania rozwoju dziecka w prawie oświatowym

Early support for child development is a form of targeted and specialized support for a child who has not yet started fulfilling educational obligations. It is implemented in order to stimulate the child’s psychomotor and social development, from the moment of detecting a disability until the child starts school. It is intended to prevent potential future failures in school education. Early support for child development is a conglomerate of public services whose type, scope and frequency of provision are adapted to the needs of a specific child, and take into account their individual limitations. The right to use these services stems from an opinion issued by the adjudicating panel of a public psychological and pedagogical counseling center confirming the child’s need for early development support. The article discusses the legal aspects of the public task of organizing and providing services in the field of early development support. The aim is to explain the meaning of the concept of early support for child development, discuss the legal provisions regulating them and determine the ratio legis of their introduction into the Polish legal system. It also involves identifying intangible services falling within the scope of early support for child development, determines their beneficiaries and identifying the entities providing them. In the context of acquiring the right to use these services, special attention will be paid to the opinion issued on the need to support early child development, in particular, the procedure for its issuance it and its components. In order to achieve the research goals, the dogmatic-legal method will be used, consisting of the analysis and interpretation of the texts of legal acts. Administrative court jurisprudence regarding the subject of the article will also be taken into account to the required extent.

Interactive Changes in Climatic and Hydrological Droughts, Water Quality, and Land Use/Cover of Tajan Watershed, Northern Iran

In response to novel and complex uncertainties, the present research is conducted to characterize the most significant indicators of watershed health including drought, water quality, and vegetation for the Tajan watershed, Mazandaran, Iran. The Standardized Precipitation Index (SPI) and Streamflow Drought Index (SDI) are, respectively, used to quantify the meteorological and hydrological droughts in the present (1993–2020) and future (2023–2050) employing optimistic RCP2.6 and pessimistic RCP8.5 scenarios. To concoct discharge data for the future, IHACRES v1.0 software is used with a Nash–Sutcliffe coefficient (NSE) of 0.48 and a coefficient of determination (R2) of 0.58. Maps of land use and Normalized Difference Vegetation Index (NDVI) are also prepared using Landsat images. Subsequently, the surface water quality is assessed using AqQA v1.1.0 software. The results show the difference in the severity of future meteorological droughts in different stations. In addition, the predominance of non-drought (SDI ≥ 0) or mild drought (−1 ≤ SDI &lt; 0) is indicated for future hydrology. The land use changes show a decrease in rangeland (−5.47%) and an increase in residential land (9.17%). The water quality analysis also indicates an increase in carbonate ions in the watershed outlet. Communicating the relationships between study indicators, which is a big gap in the current watershed management approach, avoids future failures and catastrophes.

Real-time pavement temperature prediction through ensemble machine learning

Pavement temperature is crucial for assessing asphalt pavement's performance and structural integrity due to its viscoelastic behavior. Currently, asphalt temperature prediction includes analytical, numerical, and statistical methods and relies on field investigation with intensive labor and time to hinder routine practice. Machine learning (ML) offers a promising solution for reliable and accurate real-time predictions by considering various dynamic environmental factors. This research employs four ensemble ML algorithms: eXtreme Gradient Boosting (XGB), Light Gradient Boosting Machine (LGBM), Random Forest (RF), and Adaptive Boosting (AdaBoost) to predict pavement temperature at different depths. XGB consistently outperformed other ensemble models, boasting the highest average R2 value (97.92%) and lower MAE and RMSE than LGBM, RF, and AdaBoost. XGB also significantly outperformed other commonly used models (linear regression, SVR, ANN, LSTM, and GRU) with an average reduction in errors of 35.29%, 63.75%, 42.75%, and an increase in R2 by 4.39% for MAE, MSE, RMSE, and R2, respectively. The Shapley additive explanation (SHAP) was applied to interpret the underlying influencing factors and their interactions, and revealed atmospheric temperature as the most impactful feature, contributing over 40.58% among the significant features.Furthermore, the predictive performance of XGB was enhanced by incorporating Principal Component Analysis to reduce computational consumption with average reductions of 8.98%, 16.59%, 9.01%, and 7.89% in MAE, MSE, MAPE, and RMSE. XGB with PCA emerges as the most effective and efficient model for predicting pavement temperatures at various depths to facilitate timely decision-making for preventive maintenance and rehabilitation and prevent future catastrophic failures.

Basal Microvascular Resistance - Another Invasively Measured Physiological Index for Predicting Future Heart Failure Events.

Basal Microvascular Resistance - Another Invasively Measured Physiological Index for Predicting Future Heart Failure Events.

Chronic Deltoid Insufficiency in Stage IV Adult Acquired Flatfoot Deformity: Do We Have a Good Answer?

Stage IV adult acquired flatfoot deformity (AAFD) with secondary chronic deltoid ligament insufficiency is a challenging deformity to treat, with minimal consensus in the literature concerning its surgical management. Many surgical treatment options have been described, including joint-sparing techniques, fusions, osteotomies, and even arthroplasties. However, questions remain as to what, if any, treatment is optimal. This contribution reviews studies on surgical treatments for stage IV AAFD with deltoid ligament failure and provides a critical analysis regarding the quality of outcomes reported for those different treatment options. PubMed and Google Scholar databases were searched between June 1, 2022, and August15, 2022, for studies published between 1990 and 2022 that describe the treatment of stage IV AAFD with deltoid ligament insufficiency. Articles included in the study focused on subjects with stage IV AAFD and associated deltoid ligament insufficiency undergoing surgical correction. Exclusion criteria included stage I, II, and III AAFD, as well as deltoid ligament repair following acute injury/rupture. Nine studies covering five different treatment options for patients with stage IV AAFD and chronic deltoid insufficiency were included, with minimal overlap in outcome measures used to assess the efficacy of the procedure. Triple arthrodesis with deltoid ligament reconstruction resulted in a 62.5% (5/8) success rate with a residual tibiotalar (TT) angulation of 2°(success defined as <3°). Tibiotalar arthrodesis of four patients resulted in an average post-operative tibiotalar angulation of 4.8°with all patients showing progressive destabilization of the hindfoot complex at 12-18 year follow-ups. Deltoid arthroscopic laminoplasty (Brostrom) resulted in an increased American Orthopaedic Foot and Ankle Society (AOFAS) score from 49.7 pre-op to 91.9 post-op. There was no long-term follow-up of these patients. Deltoid ligament reconstruction using autografts of the peroneus longus resulted in a post-operative valgus of 2.1°in one study and <5°in another. Deltoid ligament reconstruction using an anterior tibial tendon autograft resulted in a gain of 126.4 + 40.2% in stiffness compared to an intact ligament. Twinfix suture anchors resulted in a post-operative hindfoot angle averaging 5.3°. Combined deltoid and spring ligament reconstruction resulted in a 5.1°valgus angulation. There is currently no standard of care or clinical consensus regarding surgical treatment for stage IV AAFD with deltoid insufficiency. Several studies imply that mild valgus malalignment around the tibiotalar joint can result in satisfactory outcomes. A few studies even deemed <5°of valgus tilt post-operatively successful. However, it has been described that any imbalance in tibiotalar tilt is a significant risk factor for progressive arthritis and future ligamentous failure. No treatment option was able to correct valgus tilt to an anatomical standard (i.e., to normal anatomy). These varied findings, along with the lack of consensus on post-surgical measures to assess efficacy, are worrisome and emphasize the need for better surgical options. Moreover, there is a critical need for additional research on the long-termoutcomes following stage IV AAFD and deltoid insufficiency repair, particularly, as over five million people in the United States and 10% of the geriatric population are affected by AAFD with a risk of progressing to stage IV.

Cliff Retreat Rates Associated with a Low-Level Radioactive Waste Disposal Facility in Los Alamos, New Mexico, USA

We present an analysis and interpretation of potential cliff stability at a low-level waste disposal facility at Los Alamos National Laboratory, New Mexico, using cliff morphologic and fracture characteristics coupled with carbon-14 surface exposure dating. Our study is important as it directly bears on the licensing criteria for low-level radioactive waste sites. We find that future characteristic cliff failures will likely not breach disposal pits and shafts over the 1000-year minimum regulatory period. Further, we find, using a multivariate regression model, that slope angle and cliff face aspect are sub-equal in importance to predict regions of high risk of failure when combined with surface exposure ages and assuming that old exposure ages are most indicative of stability (instability) and therefore can aid decision making in final design implementation.

Failure analysis of abnormal leakage in hydrogen cyanide reactor

Hydrogen cyanide (HCN) is a crucial building block for various industrial chemicals in organic synthesis. Due to its high toxicity to humans and the environment, meticulous care is required in the synthesis, use, and disposal of HCN and its derivatives. This study investigated the premature failure of the HCN reactor, a core component of the HCN production system. Despite a design life of 20 years, the reactor experienced abnormal leakage after only 4 years of operation. Comprehensive investigations revealed that corrosion pits caused by localized corrosion formed at the circumferential welding seam of the reactor shell. This problem was further aggravated by vortex scouring from the pressurized water medium. Additionally, residual stress at the welding seam contributed to decreased toughness. The analysis highlighted the intricate relationship between localized corrosion and vortex scouring as the primary mechanisms leading to perforation and leakage of the reactor shell. Based on these findings, effective countermeasures were proposed to prevent similar future failures, potentially enhancing the operational safety and reliability of the HCN production system.

Artificial intelligence enabled electrocardiogram for mortality and ventricular arrhythmia prediction

Abstract Background Artificial intelligence-enhanced electrocardiograms (AI-ECG) can be used to predict risk of events but existing models suffer from lack of actionability, explainability and biological plausibility, and therefore are not used clinically. Purpose We sought to address these limitations of previous AI-ECG approaches by developing the AI-ECG risk estimator (AIRE). Methods AIRE was developed in a dataset of 1,163,401 ECGs from 189,539 patients from a secondary care setting in the USA. Uniquely, AIRE uses deep learning with a residual convolutional neural network with a discrete-time survival loss function to create a subject-specific survival curve using a single ECG. AIRE was trained to predict time-to-mortality and fine-tuned for the additional endpoints described below. Results AIRE outputs a subject-specific survival curve that predicts not only mortality but time-to-mortality, using only a single ECG (Figure 1A). AIRE accurately predicts risk of all-cause mortality (C-index 0.775 (0.773-0.776), Figure 2) and can differentiate prognosis in high and low risk subjects even when only cardiologist reported normal ECGs are considered (Figure 2). AIRE also accurately predicted cardiovascular (CV) death 0.832 (0.831-0.834), future ventricular arrhythmia (0.760 (0.756-0.763)), future atherosclerotic cardiovascular disease (0.696 (0.694-0.698)) and future heart failure (0.787 (0.785-0.889))). In particular AIRE was superior to left ventricular ejection fraction (LVEF) in predicting risk of future ventricular arrhythmias in subjects with LVEF &amp;lt;50% (C-index 0.649 (0.638 – 0.660) vs 0.615 (0.603 – 0.626) p &amp;lt; 0.0001 ) and in dilated cardiomyopathy (C-index 0.690 (0.669-0.711) vs 0.608 (0.584 – 0.631), p &amp;lt; 0.0001). We used a variational autoencoder (VAE) to visualise the features most correlated with the mortality predictions. Features of QRS morphology, particularly broader and more left bundle branch block morphologies, inverted and biphasic T waves as well as ST segment changes were associated with high predicted mortality (Figure 1B). We externally validated our findings in four diverse, transnational cohorts from Brazil and the UK including volunteers and primary care subjects (Figure 2), and found AIRE accurately predicted all-cause mortality in all four external cohorts. Through phenome- and genome-wide association studies, we identified candidate biological pathways for the prediction of increased risk, including changes in cardiac structure and function (LV mass, LVEF, LV trabeculation), and genes associated with cardiac structure, QT interval, biological aging and metabolic syndrome (VGLL2, KCNQ1, CCDC91, TBX3). Conclusion AIRE is an explainable, biologically plausible and actionable AI-ECG risk estimation platform that has the potential for use worldwide across a wide range of clinical contexts for short- and long-term risk estimation.Figure 1Figure 2

#559 Validation of the Kidney Failure Risk Equation (KFRE) in individuals with chronic kidney disease and multimorbidity

Abstract Background and Aims Increasing numbers of individuals with chronic kidney disease (CKD) experience multiple long-term conditions (multimorbidity). Clinical guidance recommends the use of validated risk prediction equations, such as the kidney failure risk equation (KFRE), to guide referral to specialist kidney care services. However, multimorbidity may impact the accuracy of creatinine-based eGFR and bias the prognostic utility of KFRE. Equations with alternative filtration markers, such as Cystatin C eGFR (eGFRcys) or the combined creatinine and Cystatin C eGFR (eGFRcrcys), may improve KFRE's risk stratification and discrimination of future kidney failure risks. This study aimed to validate the four-variable KFRE in individuals with CKD, with and without multimorbidity in a research-based cohort (UK Biobank) and a population-based cohort (Stockholm Creatinine Measurements project (SCREAM)). The study also assessed the performance of KFRE when using eGFRcr, eGFRcys and eGFRcrcys. Method Individuals from both cohorts were included if they had CKD, defined as eGFR&amp;lt;60 mL/min/1.73 m2 by any of the three eGFR equations (eGFRcr, eGFRcys and eGFRcrcys), and had available proteinuria measurement at time of testing or within the previous 12 months. Multimorbidity was defined as the presence of two or more long-term conditions in addition to CKD and was grouped into multimorbidity clusters based on previous research. The outcome was kidney failure, defined as the need for long-term dialysis or kidney transplantation. KFRE performance at 2- and 5-years was assessed using the area under the receiver operating characteristic curve and c-index for discrimination and calibration curves for calibration. Results We included 24 489 individuals from UK Biobank and 42 902 individuals from SCREAM (mean age 62.8 (SD 5.6) and 70.1 (SD14.1), 54% and 66% female, respectively). In UK biobank, 14 998 individuals had multimorbidity, of which 5 375 had cardiometabolic multimorbidity. In SCREAM, 30 147 had multimorbidity and 17 854 cardiometabolic multimorbidity. Overall, there were 252 and 312 kidney failure events and 1 108 and 1 471 death events in UK Biobank and 918 and 1 098 kidney failure events and 8 785 and 10 152 death events in SCREAM within 2- and 5-years respectively. Model performance was consistent across both cohorts. Discrimination power of KFRE was good in individuals with and without multimorbidity and across the 2-year and 5-year models (Table 1). Calibration plots revealed over-estimation of risk at 2-years in both cohorts and under-estimation of risk at 5-years in patients with multimorbidity in UK Biobank. There was no improvement in model performance when using eGFRcys or eGFRcrcys compared to eGFRCr. There was a higher cumulative incidence of both kidney failure and death in the multimorbidity group, with a prominent increase in risk of death over time compared to the no multimorbidity group. This was most evident in the SCREAM cohort (Fig. 1). Conclusion KFRE adequately predicts kidney failure in individuals with multimorbidity and either creatinine or cystatin C can be used. Given the high rates of mortality amongst people with multimorbidity, exploration of models that account for the competing risk of death is warranted.

Remaining Life Assessment of Kotabaru 2x7 MW Coal Fired Power Plant Circulating Water A252 Gr 2 Intake Pipe by Inspection Method

Kotabaru power plant is a power plant that was built in 2010 and currently the construction work is pending. The construction work stopped in 2014 and based on Kotabaru power plant construction final quantity report, Kotabaru construction work progress is 79,61% up to now. Kotabaru power plant uses open cooling system and takes seawater as cooling water resources. The seawater distribute through intake pipeline which use A252 grade 2 material 600 mm and 800 mm diameter pipeline with 3PL coating and rubber lining inside the pipe. The pipeline distribute the water in 3.184.739 kg/hr flow rate and 5 kg/cm2 G pressure. These pipeline material was on site in 2013 and it was not constructed yet. In 2022 Kotabaru power plant is planned to continue the construction work progress. It was about 9 years of pipeline material on Kotabaru power plant site and these pipeline is exposed to the environment such as sunlight, temperature, oxygen, water, and contaminants and cause a primer failure, especially ultraviolet light (UV) from the sunlight is the main damaging factor. Ultraviolet light from sunlight is high enough to break the coating of pipeline. Inspection and assess the pipeline can help the management to figure out pipeline actual condition. More effective inspections can reduce the risk level by reducing the frequency of future failures, through corrective and preventive action. In general, the purpose of this method is classify all risk level equipment, calculate the risk value of all equipment and it can help to make a decision to the next construction period. The service lifetime of pipeline prediction can be determined by actual pipe condition by use corrosion test and actual thickness dimension of the pipeline. This method will inform the life time prediction of the pipeline that should be meet the 15 years life time required and also inform the risk matrix value of all pipeline equipment on the site.

Redefinition of failure envelope of composite materials considering uncertainty of test data

After conducting three World-Wide Failure Exercises (WWFEs), it has become apparent that existing strength theories or criteria have certain deficiencies, and no single theory can accurately match all experimental results. As a result, there is a growing focus on the uncertainties present in the macrocosm test data of composite materials. The paper introduces the concept of uncertainty into the collection of test data for the classical Tsai-Wu failure criterion and Hashin criterion. The method proposed involves fitting the coefficients of the failure criteria by treating experimental data as random variables, a technique that diverges significantly from the conventional method of using composite allowable values to define these coefficients. It also uses the probability of success as a constraint and defines the fitted error as an optimization objective. Monte Carlo sampling is employed to perform a reliability analysis, and six sigma is used for a reliability-based optimization of the failure criteria. The Multi-Island Genetic Algorithm is utilized to search for the optimal value. The approach presented in this study provides the ability to predict future failures in composite materials by considering the uncertainty of the test data. By incorporating uncertainties into the analysis and design process, a more accurate and reliable assessment of the performance of composite materials can be achieved. Moreover, there seems to be a significant difference in the fitting error between the mean data and the normal distribution data. Additionally, when Hashin criterion is modified, the test data matches the failure envelope more closely and the degree of fit between the experimental data and the failure envelope is higher.

Students' Experiences with the Science and Engineering Practices in a Workshop-Based Undergraduate Research Experience.

This paper presents a phenomenographic investigation on students' experiences about research and poster presentations in a workshop-based undergraduate research experience with a focus on how the experience connects to the Science and Engineering Practices (SEPs) of the NRC A Framework for K-12 Science Education and the principles of CUREs. This provides insight into how these structured research experiences reflect particular SEPs and also elements of scientific practice that are not captured in the SEPs as they have been formulated previously. This work showcases the importance of future applications, failure, and creativity as additional science practices necessary for students to engage in authentic science. The SEPs and the additional elements of scientific practice are related to how students experience meaningful learning in the cognitive, psychomotor, and affective domains. Students highlighted the components of CUREs: importance of contributing relevant discoveries as a motivation for their research, the value of repetition and iteration in ensuring reliable and valid results, and the role of collaboration in seeing new perspectives and solving problems. As a result of presenting their results through a poster, students reported deeper understanding of their research topic, increased ability to articulate scientific concepts, and a better understanding of how to create a visually appealing poster. Students changed the vocabulary they used in their presentations to fit the knowledge level of their audience and highlighted their data in figures and explained other parts of their work in text. Moreover, they saw the poster as an outlet for their creativity.

Pre-Coronary Artery Bypass Grafting Computed Tomography-Based Fractional Flow Reserve Predicts Graft Failure: Implications for Planning Invasive Treatment of Coronary Artery Disease.

The aim of the study is to evaluate whether a pre-coronary artery bypass grafting (CABG) coronary computed tomography-based fractional flow reserve (FFR-CT) result at the site of a future anastomosis would predict the graft failure in patients undergoing CABG. In 43 patients who had coronary computed tomography angiography (CCTA) prior to the CABG, follow-up CCTA were acquired >12 months post-CABG procedure. The FFR-CT values were simulated on the basis of the pre-CABG CCTA. Based on follow-up CCTA, the anastomosis sites and the graft patency were determined. The graft failure was defined as either its stenosis >50% or occlusion. Ninety eight (44 saphenous, 54 left or right internal mammary artery) grafts were assessed. Eighteen grafts from 16 patients were dysfunctional on follow-up CCTA. The FFR-CT values at the location of future anastomosis were higher in dysfunctional than in normal grafts (0.77 [0.71-0.81] vs 0.60 [0.56-0.66], respectively, P = 0.0007). Pre-CABG FFR-CT (hazard ratio = 1.1; 95% CI: 1.012-1.1, P = 0.0230), and bypass graft to right coronary artery (hazard ratio = 3.7; 95% CI: 1.4-9.3 vs left anterior descending artery) were independent predictors of graft dysfunction during follow-up. The optimal threshold of FFR-CT to predict graft failure was >0.68 (sensitivity 88.9% (95% CI: 65.3-98.6), specificity 63.7% (95% CI: 52.2-74.2), positive predictive value 35.6% (95% CI: 28.3%-43.5%), negative predictive value 96.2% (95% CI: 87.2%-99.0%)). Pre-CABG functional FFR-CT predicts future coronary bypass graft failure. This shows utility of FFR-CT for guiding coronary revascularization and also suggests significance of physiological assessment prior to CABG.

Mechanical excavation of wetland habitat failed to eradicate invasive American red swamp crayfish (Procambarus clarkii) in Malta

Abstract Invasive crayfish are an important ecological concern in many freshwater ecosystems. Many efforts have been made to eradicate them, but there is very little documentation of the effectiveness of these efforts. Between 2019 and 2020, a restoration project funded by the European Regional Development Fund tried to eradicate invasive American red swamp crayfish Procambarus clarkii from the Fiddien valley system in Malta by mechanically excavating the valley's stream bed and exporting contaminated debris securely off‐site to a dry quarry. Three years post‐intervention, we systematically surveyed the valley system to explore the distribution and relative abundance of the invasive crayfish population. We placed traps in a stratified random sample of stream segments (both those that were included in the original restoration project and those that were not) and recorded catch per unit effort (crayfish caught per trap night) and the size/frequency distribution of crayfish caught. The invasive crayfish were still abundant in the upper reaches of the valley system, and, despite the excavation effort, crayfish were present at the highest relative abundance (4.3–14.8 CPUE, median = 12.3) within the restored area. Despite substantial effort and spending of more than 700,000 €, mechanical excavation did not eradicate invasive crayfish populations. We urge caution for future projects planning to attempt crayfish eradication using this approach and call for much greater impact evaluation, and at the very least post‐project monitoring, to ensure lessons can be learnt from such failures in future.

Use of kidney failure risk equation as a tool to evaluate referrals from primary care to specialist nephrology care.

With rising costs and burden of chronic kidney disease (CKD), timely referral of patients to a kidney specialist is crucial. Currently, Kidney Health Australia (KHA) uses a 'heat map' based on severity and not future risk of kidney failure, whereas the kidney failure risk equation (KFRE) score predicts future risk of progression. Evaluate whether a KFRE score assists with timing of CKD referrals. Retrospective cohort of 2137 adult patients, referred to tertiary hospital outpatient nephrologist between 2012 and 2020, were analysed. Referrals were analysed for concordance with the KHA referral guidelines and, with the KFRE score, a recommended practice. Of 2137 patients, 626 (29%) did not have urine albumin-to-creatinine ratio (UACR) measurement at referral. For those who had a UACR, the number who met KFRE preferred referral criteria was 36% less than KHA criteria. If the recommended KFRE score was used, then fewer older patients (≥40 years) needed referral. Positively, many diabetes patients were referred, even if their risk of kidney failure was low, and 29% had a KFRE over 3%. For patients evaluated meeting KFRE criteria, a larger proportion (76%) remained in follow-up, with only 8% being discharged. KFRE could reduce referrals and be a useful tool to assist timely referrals. Using KFRE for triage may allow those patients with very low risk of future kidney failure not be referred, remaining longer in primary care, saving health resources and reducing patients' stress and wait times. Using KFRE encourages albuminuria measurement.