Optimal Threshold Research Articles

Optimising Abdominal Aortic Aneurysm Screening of 65 Year Old Men by Exploring Risk Factor Based Targeted Screening Strategies in Light of Declining Prevalence of the Disease

A decline in abdominal aortic aneurysm (AAA) prevalence calls into question the credibility of general population screening of 65 year old men. Selectively targeting high risk individuals among this group could be more effective in preventing death from AAA rupture. This cross sectional study analysed risk factor data in a cohort of 65 year old men screened in the Swedish general population based AAA screening program, with the aim of exploring the effectiveness of hypothetical targeted screening strategies. All men attending AAA screening in four neighbouring counties in Sweden between 2006 and 2010 completed a health questionnaire on smoking habits and medical history. Abdominal aortic aneurysm was defined as measuring ≥ 30 mm. The sensitivity and specificity of different targeted screening strategies, with targeted subpopulations defined by duration of smoking with and without additional risk factors, were explored using receiver operating characteristic (ROC) curves. A total of 16 232 men were screened, with 236 (1.5%) screening detected AAAs. A strategy combining smoking, presence of coronary artery disease (CAD), or both was associated with the mathematically optimal balance between sensitivity and specificity (optimal threshold) in the ROC analysis. The optimal threshold corresponded to targeting men having smoked for thirty years or more, a history of CAD, or both, where 74.0% of all AAAs could be detected by screening 33.0% of the population, compared with general screening. Targeting men that have smoked for ten years or more indicated that 84.0% of all AAAs could be detected by screening 55.0% of the population. A simplified strategy of targeting ever smokers resulted in detecting 85.0% of all AAAs by screening 61.0% of the population. Targeted screening of men at high risk of AAA, focusing on smoking history for inclusion, may be a safe and effective alternative to general population screening.

Improving agreement in assessing subtrochanteric fracture healing among orthopedic surgeons using the Radiographic Union Score for Hip (RUSH)

BackgroundPrompt identification of fracture healing is crucial for medical decision-making and clinical research. This study aims to assess the effectiveness of the Radiographic Union Score for Hip (RUSH) in subtrochanteric fractures and determine the optimal scoring threshold for fracture healing.MethodsWe obtained 94 sets of X-ray films from the postoperative follow-up of 35 patients who underwent intramedullary nail fixation for subtrochanteric fractures. Six orthopedic trauma surgeons evaluated the imaging data and determined fracture healing based on subjective judgment. They then scored the X-ray images using the RUSH form. After four weeks, the same observers re-evaluated 47 randomly selected sets of radiographs. Subsequently, the observers and study designer conducted a consensus meeting where they agreed on whether the fractures had healed. We used Fleiss kappa to evaluate agreement among observers based on subjective impressions, and the intraclass correlation coefficient assessed RUSH score consistency. Regression analysis examined the relationship between scores and fracture healing consensus using a receiver operator characteristic (ROC) curve.ResultsBased on overall impressions, the agreement level among orthopedic trauma surgeons for determining the healing status of subtrochanteric fractures was moderate (Kappa = 0.564, 95% CI: 0.511–0.616). However, utilizing the RUSH scoring system can improve the consistency to a substantial level of agreement (ICC = 0.748, 95% CI: 0.663–0.817). Regarding intraobserver reliability, there were significant differences among orthopedic trauma surgeons in judging fracture healing based on overall impressions. However, using the RUSH scoring form, the attending group achieved better intraobserver consistency than the resident group. Regression analysis and ROC curve analysis revealed a strong correlation between the RUSH total score, cortical bone score, cancellous bone score, and consensus on fracture healing. The AUC values are 0.769 (95% CI: 0.670–0.868), 0.779 (95% CI: 0.681–0.876), and 0.771 (95% CI: 0.674–0.867), respectively.ConclusionsOur study highlights the effectiveness of the RUSH scoring system in enhancing interobserver agreement and intraobserver consistency when evaluating subtrochanteric fracture healing in orthopedic trauma surgeons. We propose setting 21 points as the threshold for the simplified RUSH scoring system to determine fracture healing. This system includes only eight items related to cortical bone, with a total score of 24 points.

Opportunistic maintenance for a novel load-sharing system with dependent degradation rate and volatility

For traditional degrading load-sharing systems, a typical assumption lies in the only effect of unit load on its degradation rate. However, motivated by a laser system example with positive correlation between degradation rate and volatility, we present a novel load-sharing system with general degradation rate-volatility-load correlation. Furthermore, to take account for unit economic dependence caused by sharable maintenance set-up cost, and the window period generated by the maintenance on some unit, opportunistic maintenance (OM) strategy is introduced to offer the opportunity of simultaneously maintaining another working unit under control-limit criteria. Based on the semi-regenerative process, the long-run average cost rate is minimized to obtain the optimal inspection interval, preventive maintenance and OM thresholds. Compared to the traditional condition-based maintenance strategy separately for each unit, the effectiveness of OM strategy is validated through numerical examples and case studies, offering broad managerial insights for engineers to reduce maintenance expenses.

Restrictive vs Liberal Transfusion Strategy in Patients With Acute Brain Injury

Blood transfusions are commonly administered to patients with acute brain injury. The optimal hemoglobin transfusion threshold is uncertain in this patient population. To assess the impact on neurological outcome of 2 different hemoglobin thresholds to guide red blood cell transfusions in patients with acute brain injury. Multicenter, phase 3, parallel-group, investigator-initiated, pragmatic, open-label randomized clinical trial conducted in 72 intensive care units across 22 countries. Eligible patients had traumatic brain injury, aneurysmal subarachnoid hemorrhage, or intracerebral hemorrhage; hemoglobin values below 9 g/dL within the first 10 days after injury; and an expected intensive care unit stay of at least 72 hours. Enrollment occurred between September 1, 2017, and December 31, 2022. The last day of follow-up was June 30, 2023. Eight hundred fifty patients were randomly assigned to undergo a liberal (transfusion triggered by hemoglobin <9 g/dL; n = 408) or a restrictive (transfusion triggered by hemoglobin <7 g/dL; n = 442) transfusion strategy over a 28-day period. The primary outcome was occurrence of an unfavorable neurological outcome, defined as a Glasgow Outcome Scale Extended score between 1 and 5, at 180 days following randomization. There were 14 prespecified serious adverse events, including occurrence of cerebral ischemia after randomization. Among 820 patients who completed the trial (mean age, 51 years; 376 [45.9%] women), 806 had available data on the primary outcome, 393 in the liberal strategy group and 413 in the restrictive strategy group. The liberal strategy group received a median of 2 (IQR, 1-3) units of blood, and the restrictive strategy group received a median of 0 (IQR, 0-1) units of blood, with an absolute mean difference of 1.0 unit (95% CI, 0.87-1.12 units). At 180 days after randomization, 246 patients (62.6%) in the liberal strategy group had an unfavorable neurological outcome compared with 300 patients (72.6%) in the restrictive strategy group (absolute difference, -10.0% [95% CI, -16.5% to -3.6%]; adjusted relative risk, 0.86 [95% CI, 0.79-0.94]; P = .002). The effect of the transfusion thresholds on neurological outcome at 180 days was consistent across prespecified subgroups. In the liberal strategy group, 35 (8.8%) of 397 patients had at least 1 cerebral ischemic event compared with 57 (13.5%) of 423 in the restrictive strategy group (relative risk, 0.65 [95% CI, 0.44-0.97]). Patients with acute brain injury and anemia randomized to a liberal transfusion strategy were less likely to have an unfavorable neurological outcome than those randomized to a restrictive strategy. ClinicalTrials.gov Identifier: NCT02968654.

The role of plant-derived melanin in enhancing &lt;i&gt;in vitro&lt;/i&gt; growth and nutrient accumulation in potato varieties

Background: Melanins are versatile biopolymers found in a wide range of living organisms, contributing to the diverse colors observed in nature. Beyond their pigmentation role, melanins exhibit a variety of biological activities, including antioxidant, antitoxic, antitumor, photoprotective, antimicrobial, and radioprotective properties. These attributes make melanins valuable in fields such as medicine, pharmaceuticals, and agriculture. In this study, we investigated grape marc, a byproduct of wine production, as a novel source of water-soluble melanin extracted using sodium hydroxide. This approach not only repurposes agricultural waste but also explored melanin's role in optimizing in vitro plant cultivation. We evaluated the impact of melanin on the biochemical properties of potato plants, focusing on improvements in growth, rhizogenesis, and the nutritional composition of tubers. Objective: The aim of this study was to evaluate the effects of plant-derived melanin on the in vitro growth characteristics and biochemical composition of two potato varieties. Methods: This study took place in the tissue culture laboratory at the Scientific Center of Agrobiotechnology from 2021 to 2024. Apical meristems from the Nevsky and Impala potato varieties were used for in vitro regeneration. The research focused on the in vitro growth and adaptation of these plants under different melanin concentrations. Key growth parameters, chlorophyll content, and biochemical composition were analyzed to assess the impact of melanin on potato development. Results: The study found that melanin at a concentration of 0.028% significantly enhanced the in vitro growth and rhizogenesis of potato microstems, with optimal results in root number (12.30 per shoot) and shoot length (16.91 cm). Plants also showed earlier and more vigorous root formation, resembling an auxin-like effect. Higher melanin concentrations reduced these benefits. Additionally, plants treated with 0.028% melanin had a high acclimatization success rate (96%) and improved biochemical composition in tubers, with increases in dry matter, sugars, starch, and ascorbic acid, particularly in the Nevsky variety. Conclusion: Melanin significantly stimulated the in vitro growth and development of potato plants. Increasing melanin levels to an optimal threshold accelerated rhizogenesis and promoted vigorous root and shoot growth, evidenced by increased length and thickness. Acting similarly to auxin, melanin not only encouraged root formation but also enhanced shoot development, leading to improved plant adaptation. Additionally, melanin influenced the biochemical composition of potato tubers, including their nutritional content. These findings highlight the crucial role of melanin concentration in optimizing the growth and biochemical properties of potato varieties. Keywords: in vitro propagation, potato, melanin, plant adaptation, biochemical compound, micropropagation

Mitigating Intermittent Connectivity Problems in Vehicle-to-Vehicle Communication (V2VC): A Sparse Network Computational Model (SNCM)

INTRODUCTION: Wireless communication has made remarkable progress, by the rapid development of wireless technology in Artificial Intelligence (AI). Intelligent Transportation Systems (ITS), and Vehicular Ad Hoc Networks (VANETs) have received significant attention to ensure safety. However, V2V communication in VANETs faces uncontrollable challenges due to frequent intermittent connectivity issues in infrastructure-less networks. Addressing these problems in both safety and non-safety applications is a complex task.OBJECTIVES: To mitigate the intermittent connectivity problems, a novel Sparse Network Computational Model (SNCM) was proposed.METHODS: Extensive simulations using MATLAB to analyze the impact of spatial-temporal variations under different traffic flow densities. We varied the sensitivity factor (λ) at different time intervals while maintaining a constant traffic density. RESULTS: The findings indicate that there is no need to increase λ beyond certain thresholds for each level of service. The simulation results provide valuable guidelines for designing sparse networks, effectively mitigating frequent intermittent disconnections. Simulation experiments revealed an optimal threshold for the sensitivity factor λ for each level of service. Increasing λ beyond certain thresholds did not yield significant improvements in mitigating disconnections in V2V communication.CONCLUSION: The results provide valuable insights and guidelines for designing sparse networks to enhance connectivity and address intermittent disconnection issues. This paper presents a groundbreaking endeavor, and therefore, direct comparisons with existing protocols to evaluate its overall performance are beyond the scope of this paper. Instead, the SNCM protocol is intended to set a standard for future researchers to benchmark their research contributions against.

Impact of Hypoalbuminemia on Outcomes Following Hepatic Resection: A NSQIP Retrospective Cohort Analysis of 26,394 Patients

Background/Objectives: Efforts to preoperatively risk stratify and optimize patients before liver resection allow for improvements in postoperative outcomes, with hypoalbuminemia being increasingly researched as a surrogate for nutrition, overall health and functional status. Given the paucity of studies examining the relationship between hypoalbuminemia and liver resection, this study aims to determine the impact of hypoalbuminemia on outcomes following liver resections using a large multicenter database. Methods: The American College of Surgeons–National Surgical Quality Improvement Program (2017–2021) database was used to extract the data of patients who underwent a hepatic resection. Two cohorts were defined; those with hypoalbuminemia (HA; &lt;3.0 g/L) and those with normal albumin levels (≥3.0 g/L). Both baseline characteristics and 30-day postoperative complication rates were compared between the two cohorts. Multivariable logistic regression models were used to assess the independent effect of HA on various outcomes. Area under curve–receiver operating characteristic (AUC-ROC) curves were used to identify optimal albumin thresholds for both serious complications and mortality. Results: We evaluated 26,394 patients who underwent liver resections, with 1347 (5.1%) having preoperative HA. The HA patients were older (62.3 vs. 59.8; p &lt; 0.001) and more likely to be of an ASA class ≥ 4 (13.0% vs. 6.5%; p &lt; 0.001). The patients with HA had significantly more complications such as an increased length of stay, readmission, reoperation, sepsis, surgical site infection, bile leak, and need for transfusion. After controlling for demographics and comorbidities, HA remained a significant independent predictor associated with both 30-day serious complication rates (aOR 2.93 [CI 95% 2.36–3.65, p &lt; 0.001]) and mortality (aOR 2.15 [CI 95% 1.38–3.36, p = 0.001]). The optimal cut-off for albumin with respect to predicting serious complications was 4.0 g/dL (sensitivity 59.1%, specificity 56.8%, AUC-ROC 0.61) and 3.8 g/dL (sensitivity 56.6%, specificity 68.3%, AUC-ROC 0.67) for mortality. Conclusions: In this large, retrospective database analysis, preoperative HA was significantly associated with 30-day morbidity and mortality rates following hepatic resection. Preoperative albumin may serve as a useful marker for risk stratification in conjunction with pre-existing calculators. Future studies evaluating the risk mitigation impact of nutrition and exercise prehabilitation in these patients and its capacity to modify hypoalbuminemia would be beneficial.

An integrated method for detecting lung cancer via CT scanning via optimization, deep learning, and IoT data transmission.

With its increasing global prevalence, lung cancer remains a critical health concern. Despite the advancement of screening programs, patient selection and risk stratification pose significant challenges. This study addresses the pressing need for early detection through a novel diagnostic approach that leverages innovative image processing techniques. The urgency of early lung cancer detection is emphasized by its alarming growth worldwide. While computed tomography (CT) surpasses traditional X-ray methods, a comprehensive diagnosis requires a combination of imaging techniques. This research introduces an advanced diagnostic tool implemented through image processing methodologies. The methodology commences with histogram equalization, a crucial step in artifact removal from CT images sourced from a medical database. Accurate lung CT image segmentation, which is vital for cancer diagnosis, follows. The Otsu thresholding method and optimization, employing Colliding Bodies Optimization (CBO), enhance the precision of the segmentation process. A local binary pattern (LBP) is deployed for feature extraction, enabling the identification of nodule sizes and precise locations. The resulting image underwent classification using the densely connected CNN (DenseNet) deep learning algorithm, which effectively distinguished between benign and malignant tumors. The proposed CBO+DenseNet CNN exhibits remarkable performance improvements over traditional methods. Notable enhancements in accuracy (98.17%), specificity (97.32%), precision (97.46%), and recall (97.89%) are observed, as evidenced by the results from the fractional randomized voting model (FRVM). These findings highlight the potential of the proposed model as an advanced diagnostic tool. Its improved metrics promise heightened accuracy in tumor classification and localization. The proposed model uniquely combines Colliding Bodies Optimization (CBO) with DenseNet CNN, enhancing segmentation and classification accuracy for lung cancer detection, setting it apart from traditional methods with superior performance metrics.

6818 Adherence Risk Management in Patients on Recombinant Human Growth Hormone Therapy, With Traffic Light Alerting Systems Tailored for Both Weekday and Weekend Adherence

Abstract Disclosure: S. Loche: Advisory Board Member; Self; SL has received advisory board fees from Merck KGaA, Darmstadt, Germany. Consulting Fee; Self; SL has received consultancy fees from Merck KGaA, Darmstadt, Germany. Speaker; Self; SL has received lecture fees from Merck KGaA, Darmstadt, Germany. P. van Dommelen: Consulting Fee; Self; PvD has a consultancy agreement with Merck KGaA, Darmstadt, Germany. V. Tornincasa: Employee; Self; VT is an employee of Ares Trading SA, an affiliate of Merck KGaA. L. Arnaud: Employee; Self; LA is an employee of Ares Trading SA, an affiliate of Merck KGaA. E. Koledova: Employee; Self; EK is an employee of Merck KGaA,Darmstadt, Germany. Stock Owner; Self; EK is an employee of Merck KGaA,Darmstadt, Germany. Background: The integration of data-driven strategies, such as clustering analysis with an alerting system, empowers healthcare professionals with actionable insights. In this study, we focused on clustering adherence patterns during the weekdays and weekends in the first 12 weeks of treatment. Our aim is to develop a data-driven clinical decision support system based on "traffic light" visualizations addressing adherence challenges during both weekdays and weekends in patients receiving Recombinant Human Growth Hormone Therapy. Data and Methods: Adherence data between March-November 2023 were extracted from the newly launched third generation of easypod™ device (EP3) and GrowZen Connect Next ecosystem. EP3 is the only connected device that delivers r-hGH and monitors real-time adherence to therapy. EP3 was perceived by health care professionals as more intuitive, comfortable, user-friendly, simpler, and easier to use than previous EP2. Patients with age 2-18 years at treatment start, a 7-day regimen and complete adherence data available between 1-12 weeks of treatment were selected. Patients’ adherence to therapy was represented using mean and standard deviation (SD) of adherence (%) and the interquartile range (IQR) of the timing of injections throughout the day in minutes aggregated by weekday (Monday-Thursday) and weekend day (Friday-Sunday). Cluster analysis was used to categorize adherence patterns using a Gaussian mixture model. Following a traffic lights-inspired visualization approach, the algorithm was set to create three clusters: high (green), medium (yellow), and low adherence (red). The area under the receiver operating characteristic curve (AUC-ROC) was used to find optimum thresholds for independent traffic lights. Results: Data for 232 patients (124 boys and 108 girls, median (Q25-Q75) age at treatment start was 10.5 (7.6-12.3)) were available. The most appropriate traffic light used the SD of adherence during the weekend, with an AUC-ROC value of 0.87. For the weekday, adherence-based traffic lights using optimum thresholds were &amp;gt;98% (SD&amp;lt;10.2), 88-98% (SD:10.2-22.8) and &amp;lt;88% (SD&amp;gt;22.8) for high, medium, and low adherence, respectively. For IQR of the timing of injections throughout the weekday, optimum thresholds were &amp;lt;38, 38-70 and &amp;gt;70 (min). For the weekend, optimum thresholds were &amp;gt;96% (SD&amp;lt;7.7), 86-96% (SD:7.7-21.5) and &amp;lt;86% (SD&amp;gt;21.5). For IQR of the timing of injections throughout the weekend, optimum thresholds were &amp;lt;56, 56-84 and &amp;gt;84 (min). Conclusions: Our research indicates that implementing a practical data-driven alert system, utilizing our proposed traffic-light coding, would empower healthcare practitioners to monitor patients' adherence to growth hormone therapy comprehensively. By understanding patient behavior during the weekdays and weekend, healthcare practitioners can tailor interventions for improved treatment outcomes. Presentation: 6/3/2024

Fecal zonulin as a prognostic marker of atopic march in children with food allergy

Introduction. The onset of allergic diseases most often occurs in early childhood with the onset of food allergies, which can subsequently lead to the implementation of the atopic march. Increased intestinal permeability with high production of zonulin, the main moderator of intestinal tight junctions, can be an important link in the development of comorbid allergic diseases.Material and methods. In order to study the significance of fecal zonulin as a marker for predicting the atopic march in children with food allergy, a cross-sectional retrospective study was conducted on 73 children aged 5 years who were diagnosed with food allergy (FA) to cow’s milk proteins in the first year of life. In all children, when the diagnosis was made in the first year of life, the content of zonulin in feces was determined using the ELISA method.Results. As a result of dynamic observation, all children with food allergy were divided into 2 groups: the first group consisted of children with food allergy who developed allergic rhinitis and/or bronchial asthma within 5 years (group I, n = 39), group 2 consisted of 34 children with food allergy who did not implement the atopic march within 5 years of observation (group II, n = 34). Our study showed statistically significant differences in the fecal zonulin level in the first year of life: group I Me = 2.39 ng/ml (Q1-Q3: 1.78–2.65 ng/ml), group II Me = 1.85 ng/ml (Q1-Q3: 0.49–0.91 ng/ml), p = 0.034. Strong direct correlations were found (Spearman correlation coefficient S = 0.681 (p &lt; 0.05)) between the zonulin level in feces at the onset of the disease and the development of allergic rhinitis and/or bronchial asthma up to 5 years of age, the data were confirmed by comparing the areas under the curves during ROC analysis, AUC in the study of fecal zonulin as a prognostic marker of the risk of atopic march in children is 0.887, the optimal threshold (cutoff point) is 1.94 ng/ml.Conclusions. Fecal zonulin level in children with food allergy can be an effective prognostic marker of atopic march development, its values in feces above 1.94 ng/ml allow us to predict with a high degree of probability the risk of atopic march development in children with food allergy to cow’s milk proteins within 5 years

Calf circumference-albumin index significantly predicts the prognosis of older patients with cancer cachexia: A multicenter cohort study

ObjectivesThe aim of this study was to evaluate the combined prognostic value of calf circumference (CC) and serum albumin on mortality in patients with cancer cachexia aged ≥65 years. MethodsThis multicenter cohort study involved 5322 older patients in hospital with cancer cachexia. The combined indicator of CC and albumin was defined as the calf circumference-albumin (CCA) index. Harrell's C index, a time-dependent receiver operating characteristic curve analysis, was used to assess the prognostic performance of the CCA index and other indices. The optimal thresholds method was used to determine the cutoff values of CC and albumin, and the association between the CCA index and all-cause mortality was assessed using Kaplan-Meier analysis and Cox proportional hazard regression models. ResultsA total of 3875 men and 1447 women with a mean age of 72.0 years (range: 68.0–78.0 years) and a mean follow-up time of 55.0 months (range: 25.0–85.0 months) were included in the study. A total of 1269 patients were classified into the low CCA index group (0 score) by the optimal thresholds method. In the overall population, the CCA index showed better differentiating power at predicting mortality in older patients with cancer cachexia compared with CC or albumin alone (C index = 0.639; 95% CI: 0.612–0.666; P < 0.05). The time-dependent receiver operating characteristic curve showed that the CCA index had the highest prognostic value of all the measures studied (P < 0.05). In the overall population, male and female patients with a high CCA index (2 score) showed better performance than those with a low CCA index (0 or 1 score). ConclusionsThe CCA index could significantly predict the mortality of older patients with cancer cachexia, which might provide renewed assistance for future clinical management.

Evaluating the impact of biogenic nanoparticles and pesticide application in controlling cotton leaf curl virus disease (CLCuD) in cotton (Gossypium hirsutum L.)

BackgroundCotton leaf curl virus disease (CLCuD) is one of the major concerns for cotton growers. The traditional approach to managing CLCuD involves the control of the vector (whitefly) population through the use of pesticides. This study compares the efficacy of zinc oxide, iron oxide, copper and silver nanoparticles with conventional pesticides. Nanoparticles dose was optimized by evaluating their phytotoxic threshold in our previous study. In this study, optimized doses of nanoparticles such as zinc oxide (100 ppm), iron oxide (50 ppm), copper (50 ppm) and silver nanoparticles (25 ppm) were applied in a field trial of cotton against cotton leaf curl virus disease (CLCuD). Morphological parameters (height of stem, monopodial branches, sympodial branches, staple length, boll weight and number of bolls), yield parameters (seed cotton yield and ginning outturn), chlorophyll content (chlorophyll a, chlorophyll b, carotenoids and total chlorophyll), biochemical parameters (superoxide dismutase (SOD), peroxidase (POD), ascorbate peroxidase (APX), catalase (CAT), hydrogen peroxide (H2O2) and electrolyte leakage) and disease parameters (reduction infection, disease severity and disease incidence) were determined in this study.ResultsThe incidence of cotton leaf curl virus was confirmed by triple antibody sandwich–enzyme-linked immunosorbent assay (TAS-ELISA). The pesticide Imidacloprid significantly reduced the infection by 79.3%. However, in comparison to pesticide, application of nanoparticles also reduced the infection. ZnO NPs reduced the infection by 42.33%, FeO NPs by 41%, Cu NPs by 34.7%, and Ag NPs by 44.8%. Moreover, these nanoparticles also improved the plant growth parameters as compared to control treatment. ZnO NPs enhanced morphological, yield parameters, and chlorophyll content by 36%, 22%, and 29%, respectively. FeO NPs showed improvements by 38%, 21%, and 29%; Cu NPs 39%, 25%, and 29%; and Ag NPs 31%, 19%, and 18%, respectively.ConclusionAlthough treatment pesticide showed the least disease incidence compared to nanoparticles, nanoparticles are eco-friendly and safe as compared to pesticides. Farmers can apply these nanoparticles at their optimal thresholds through foliar application as an alternative to traditional pesticides. It is concluded that nanocomposites and hybrid modes may be used for managing CLCuD efficiently in the future.Graphical abstract

Sensor placement method for water distribution networks based on sampling of non-bandlimited graph signals

Monitoring water distribution networks (WDNs) requires careful consideration of sensor placement, which is essential for obtaining comprehensive information about the network. A natural graphical structure underlies WDN, making graph sampling theory advantageous for selecting monitoring nodes. However, graph sampling theory is only applied only to restrictive band-limited signals, while the pressure data of WDN is a restrictive non-band-limited signal. To address this issue, this paper presents an approximate conversion method for transforming non-band-limited signals into band-limited signals, accompanied by an optimal spectrum threshold formula. This formula is used to perform spectral screening in the graph frequency domain, effectively converting non-band-limited signals into band-limited signals that preserve the major frequency components while ignoring smaller-value frequency components. By sampling band-limited signal, we identify sampling nodes that perfectly recover the signal. These sampling nodes act as monitoring nodes that can perform a comprehensive inspection of the WDN and accurately locate leaks. The accuracy of our method in recovering the signal and locating the leak is demonstrated by comparing it with two existing sensor placement optimization methods.

B-333 Optimizing AFP Cutoffs for Hepatocellular Carcinoma Screening: Insights from the National Cancer Screening Program in Korea

Abstract Background The incidence rate and mortality rate of liver cancer were 11.6 (ranked 8th among cancers) and 10.7 (4th) per 100,000 individuals respectively globally in 2020, whereas in Korea, they were higher at 29.5 (7th) and 20.6 (2nd) per 100,000 individuals. The National Cancer Screening Program (NCSP) in Korea conducts biannual concurrent liver ultrasound and serum alpha-fetoprotein (AFP) measurement for hepatocellular carcinoma (HCC) surveillance in high-risk groups, including those with chronic hepatitis B and C, and liver cirrhosis. The effectiveness of surveillance is impacted by varying AFP cutoffs; however, within the NCSP, different cutoffs are being used, and it is not clear which cutoffs are being employed. Harmonization of AFP test results by major reagent manufacturers have been achieved, enabling the adoption of a uniform threshold. This study aims to assess the variation of AFP cutoffs among institutions within the NCSP and suggest a unified and optimal AFP threshold. Methods This study examined HCC screening results from the NCSP between 2018 and 2020, investigating unit and cutoff usage for AFP test across institutions each year (number of institutions were 4452 for 2018, 4754 for 2019, and 4847 for 2020). To determine the optimal AFP cutoff for HCC screening, datasets comprised unique patient results from 2018 to 2020 (number of patients = 819,644). Receiver operating characteristic (ROC) curve analyses were conducted for determine best AFP cutoffs. Cancer diagnosis was defined by billing records indicating HCC within one year post-screening. Results More than 96% of institutions used ng/mL as a unit of AFP test. Among institutions using ng/mL, the most frequently used AFP cutoff was 7 ng/mL, with frequency percentages of 75.7%, 72.2%, and 62.2% in 2018, 2019, 2020, respectively. The percentiles (1st, 10th, 90th, 99th) of AFP cutoff usage for the years 2018, 2019, and 2020 were (7, 7, 8.8, 15), (7, 7, 8.9, 15), and (7, 7, 9, 15) respectively. The AUC of ROC was 0.824 and some cut-off points with their sensitivity and specificity values were as follows: 5 ng/mL (0.648, 0.874); 10 (0.457, 0.976); 20 (0.327, 0.993); 40 (0.246, 0.997); 100 (0.169, 0.998); 200 (0.123, 0.999); 400 (0.084, 1). Conclusions Different cutoffs observed across institutions in NCSP. Our study cautiously suggests that the optimal AFP value for screening HCC in NCSP may range from 10 to 20 ng/mL, considering sensitivity and specificity when AFP is combined with ultrasound in regions with a high prevalence of HCC. For a more suitable AFP cutoff recommendation, additional analyses based on ultrasound findings and underlying diseases should be considered.

Identification and Validation of a Threshold for Early Posttransplant Bronchoalveolar Fluid Hyaluronan that Distinguishes Lung Recipients at Risk for CLAD

BackgroundFew tools exist for early identification of patients at risk for chronic lung allograft dysfunction (CLAD). We previously showed hyaluronan (HA), a matrix molecule that regulates lung inflammation and fibrosis, accumulates in bronchoalveolar lavage fluid (BALF) and blood in CLAD. We aimed to determine if early posttransplant HA elevations inform CLAD risk. MethodsHA was quantified in 3080 BALF and 1323 blood samples collected over the first posttransplant year in 743 adult lung recipients at 5 centers. The relationship between BALF or blood HA and CLAD was assessed using Cox models with a time-dependent binary covariate for “elevated” HA. Potential thresholds for elevated HA were examined using a grid search between the 50th and 85th percentile. The optimal threshold was identified using fit statistics, and the association between the selected threshold and CLAD was internally validated through iterative resampling. A multivariable Cox model using the selected threshold was performed to evaluate the association of elevated HA with CLAD considering other factors that may influence CLAD risk. ResultsBALF HA levels >19.1ng/mL (65th percentile), had the largest hazard ratio for CLAD (HR 1.70, 95% CI 1.25–1.31; p<0.001), optimized fit statistics, and demonstrated robust reproducibility. In a multivariable model, the occurrence of BALF HA >19.1 ng/mL in the first posttransplant year conferred a 66% increase in the hazards for CLAD (adjusted HR 1.66, 95% CI 1.19–2.32; p=0.003). Blood HA was not significantly associated with CLAD. ConclusionsWe identified and validated a precise threshold for BALF HA in the first posttransplant year that distinguishes patients at increased CLAD risk.

The prognostic values of lymph node ratio for gynecological cancer: a systematic review and meta-analysis.

The aim of this study was to determine the relationship between the lymph node ratio (LNR) and the prognostic values of gynecological cancer. PubMed, Web of Science, Embase, and the Central Cochrane Library were used to search for studies on LNR and gynecological cancer published before 18 April 2024. The effect measure for meta-analysis of primary outcomes was the hazard ratio (HR) for overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS). Pooled HRs and 95% confidence intervals (CIs) were calculated using random- or fixed-effects models. Sensitivity analysis was applied to evaluate the robustness of the results. The I 2 statistic was used to measure heterogeneity. Subgroup analysis and meta-regression were chosen to illustrate the potential heterogeneity of the risk factors for outcomes. Publication bias was assessed using Egger's test and Begg's funnel plots. A total of 34 studies with 23,202 cases were included in this meta-analysis. A meta-analysis found that higher LNR was associated with worse OS (HR = 2.42, 95% CI: 2.07-2.83; I 2 = 77.4%, p < 0.05), PFS (HR = 1.97, 95% CI: 1.66-2.32; I 2 = 0.00%, p > 0.05), and DFS (HR = 3.18, 95% CI: 2.12-4.76; I 2 = 64.3%, p < 0.05). Moreover, meta-analysis revealed significant differences in the association between LNR and OS of cervical cancer (CC) (HR = 2.53, 95% CI: 1.94-3.31; I 2 = 72.6%, p < 0.05), ovarian cancer (OC) (HR = 2.05, 95% CI: 1.66-2.54; I 2 = 76.7%, p < 0.05), endometrial cancer (EC) (HR = 2.16, 95% CI: 1.48-3.16; I 2 = 53.6%, p < 0.05), and vulvar cancer (VC) (HR = 8.13, 95% CI: 3.41-19.43; I 2 = 57.2%, p < 0.05). We observed a clear association between higher LNR and poorer prognosis in our study of patients with gynecological cancer. Further prospective studies are warranted to determine the optimal LNR and whether LNR can guide adjuvant therapy use in gynecological cancer. It is essential to conduct further prospective studies to establish the optimal LNR threshold, determine the minimum threshold of lymph node removal, and investigate whether LNR can serve as a reliable marker for guiding adjuvant therapy choices in gynecological cancer. https://www.crd.york.ac.uk/PROSPERO/#recordDetails, CRD42024541187.

Prognostic value of the duke activity Status Index Questionnaire in predicting mortality in patients with chronic heart failure: 36-month follow-up study

BackgroundThe Duke Activity Status Index (DASI) questionnaire has been the focus of numerous investigations - its discriminative and prognostic capacity has been continuously explored, supporting its use in the clinical setting, specifically during rehabilitation in patients with chronic heart failure (CHF).However, studies exploring optimal DASI questionnaire threshold scores are limited.ObjectiveTo investigate optimal DASI questionnaire thresholds values in predicting mortality in a CHF cohort and assess mortality rates based on the DASI questionnaire using a thresholds values obtained.MethodologyThis is a prospective cohort study with a 36-month follow-up in patients with CHF. All patients completed a clinical assessment, followed by DASI questionnaire, pulmonary function, and echocardiography. The Receiver Operating Characteristic (ROC) curve analysis was used to discriminate the DASI questionnaire score in determining the risk of mortality. For survival analysis, the Kaplan-Meier model was used to explore the impact of ≤/>23 points on mortality occurring during the 36-month follow-up.ResultsOne hundred and twenty-four patients were included, the majority being elderly men. Kaplan Meier analysis revealed that ≤/> 23 was a strong predictor of CHF mortality over a 36-month follow-up.ConclusionA score of ≤/>23 presents good discriminatory capacity to predict mortality risk in 36 months in patients with CHF, especially in those with reduced or mildly reduced ejection fraction. Age, ejection fraction, DASI questionnaire score and use of digoxin are risk factors that influence mortality in this population.

High-energy Neutrinos from Late-time Jets of Gamma-Ray Bursts Seeded with Cocoon Photons

In gamma-ray bursts (GRBs), ∼100–1000 s after the prompt emission, afterglow observations have consistently shown X-ray excesses detected in the form of flares (in long GRBs) or extended emission (in short GRBs). These observations are interpreted as emissions from jets launched by late central engine activity. However, the characteristics of these late-time jets, particularly the dissipation radius (r diss), Lorentz factor (Γ), and cosmic-ray loading factor (ξ p ), remain unknown despite their importance. Here, in order to understand the properties of the late-time jets with future multimessenger observations, we estimate the detectability of neutrinos associated with late-time emissions for a wide range of r diss and Γ, assuming ξ p = 10. We take into account external seed photons from the cocoon around the jets, which can enhance the neutrino production through photohadronic interaction in the jet dissipation region. Our results are still consistent with the upper limit obtained by IceCube. Our calculations indicate a promising prospect for neutrino detection with IceCube-Gen2 through the stacking of ∼1000–2000 events, for a wide range of r diss and Γ. We found that setting an optimal energy threshold of 10 TeV can significantly reduce noise without negatively affecting neutrino detection. Furthermore, even in the case of nondetection, we show that meaningful constraints on the characteristics of the late-time jets can be obtained.

Precise and Accurate Short-term Forecasting of Solar Energetic Particle Events with Multivariate Time-series Classifiers

Solar energetic particle (SEP) events are one of the most crucial aspects of space weather that require continuous monitoring and forecasting using robust methods. We demonstrate a proof of concept of using a data-driven supervised classification framework on a multivariate time-series data set covering solar cycles 22, 23, and 24. We implement ensemble modeling that merges the results from three proton channels (E ≥ 10 MeV, 50 MeV, and 100 MeV) and the long-band X-ray flux (1–8 Å) channel from the Geostationary Operational Environmental Satellite missions. Our task is binary classification, such that the aim of the model is to distinguish strong SEP events from nonevents. Here, strong SEP events are those crossing the Space Weather Prediction Center’s “S1” threshold of solar radiation storm and proton fluxes below that threshold are weak SEP events. In addition, we consider periods of nonoccurrence of SEPs following a flare with magnitudes ≥C6.0 to maintain a natural imbalance of sample distribution. In our data set, there are 244 strong SEP events comprising the positive class. There are 189 weak events and 2460 “SEP-quiet” periods for the negative class. We experiment with summary statistic, one-nearest neighbor, and supervised time-series forest (STSF) classifiers and compare their performance to validate our methods for prediction windows from 5 minutes up to 60 minutes. We find the STSF model to perform better under all circumstances. For an optimal classification threshold of ≈0.3 and a 60 minutes prediction window, we obtain a true skill statistic TSS = 0.850, Heidke skill score HSS = 0.878, and Gilbert skill score GSS = 0.783.

Intracoronary ECG ST-segment shift remission time during reactive myocardial hyperemia: a new method to assess hemodynamic coronary stenosis severity.

Fractional flow reserve (FFR) measurements are recommended for assessing hemodynamic coronary stenosis severity. Intracoronary ECG (icECG) is easily obtainable and highly sensitive in detecting myocardial ischemia due to its close vicinity to the myocardium. We hypothesized that the remission time of myocardial ischemia on icECG after a controlled coronary occlusion accurately detects hemodynamically relevant coronary stenosis. This retrospective, observational study included patients with chronic coronary syndrome undergoing hemodynamic coronary stenosis assessment immediately following a strictly 1-min proximal coronary artery balloon occlusion with simultaneous icECG recording. icECG was used for a beat-to-beat analysis of the ST-segment shift during reactive hyperemia immediately following balloon deflation. The time from coronary balloon deflation until the ST-segment shift reached 37% of its maximum level, i.e., icECG ST-segment shift remission time (τ-icECG in seconds), was obtained by an automatic algorithm. τ-icECG was tested against the simultaneously obtained reactive hyperemia FFR at a threshold of 0.80 as a reference parameter. From 120 patients, 139 icECGs (age, 68 ± 10 yr old) were analyzed. Receiver operating characteristic (ROC) analysis of τ-icECG for the detection of hemodynamically relevant coronary stenosis at an FFR of ≤0.80 was performed. The area under the ROC curve was equal to 0.621 (P = 0.0363) at an optimal τ-icECG threshold of 8 s (sensitivity, 61%; specificity, 67%). τ-icECG correlated inversely and linearly with FFR (P = 0.0327). This first proof-of-concept study demonstrates that τ-icECG, a measure of icECG ST segment-shift remission after a 1-min coronary artery balloon occlusion accurately detects hemodynamically relevant coronary artery stenosis according to FFR at a threshold of ≥8 s.NEW & NOTEWORTHY Invasive hemodynamic measurements are recommended by the current cardiology guidelines to guide percutaneous coronary interventions in the setting of chronic coronary syndrome. However, those pressure-derived indices demonstrate several theoretical and practical limitations. Thus, this study demonstrates the accuracy of a novel, pathophysiology-driven approach using intracoronary ECG for the identification of hemodynamically relevant coronary lesions by quantitatively assessing myocardial ischemia remission.