Monitoring Strategies Research Articles

Ayla Oasis Lagoons: A Model for Ecological Sustainability and Marine Conservation in Aqaba, Jordan

The Ayla Oasis in Aqaba, Jordan, is a major tourism and residential development project in Aqaba, Jordan, containing three artificial lagoons. This study explores the ecological sustainable development of Ayla Lagoons, focusing on the seawater and bottom sediment quality, and the bottom habitat, in addition to coral conservation and restoration initiatives. The flushing time, averaging 3.7 days for the Upper Lagoon and 2.4 days for the Middle Lagoon, plays a crucial role in maintaining water quality. These measures secure the well-being of all visitors and residents, while also preserving the marine biodiversity. The Upper, Middle, and Tidal Lagoons exhibit physiochemical properties in alignment with seawater characteristics of the Gulf of Aqaba. Sediment quality analysis shows organic carbon levels and grain size distribution vary among lagoons, indicating expected different energy conditions and a healthy environment. The lagoons support a diverse range of species, with a total of 2343 fish individuals belonging to 22 species across 17 families recorded. The comprehensive analysis of the Ayla Oasis lagoons’ seawater and sediment quality revealed a dynamic and resilient ecosystem. Ayla’s coral conservation and restoration initiative within its lagoons feature 166 reef balls, 5 coral nurseries, and 2 metal structures, all designed to foster marine biodiversity. The project demonstrates the effectiveness of Ayla Oasis’ environmental resilience and monitoring strategies, showcasing a commitment to sustainable management and environmental stewardship. These efforts reflect Ayla’s ongoing dedication to protecting and preserving the marine ecosystem, ensuring the long-term health of its coral reefs and surrounding marine life.

First records of Anthidium florentinum (Hymenoptera, Megachilidae) in the Canary Islands: insights on citizen science and exotic bee species

In recent years, the development of biodiversity inventorying platforms has contributed to the detection of exotic species, bringing awareness to the general public about their impact on native habitats. This is important in the Canary Islands and other oceanic archipelagos, where invasive species pose a great risk to the conservation of ecosystems and biodiversity monitoring strategies may not be completely adequate in their detection. Here we report for the first time the occurrence of the Florentine wool carder bee, Anthidium florentinum, in the Canary Islands and address its current distribution in the islands of Tenerife and Gran Canaria with the help of citizen science. Other bee species recently reported as new to the archipelago through the use of iNaturalist are summarized. The possible effects of A. florentinum on native bee communities in the archipelago, along with the role of cities in hosting biological invasions are also discussed.

Safety of Hydroxychloroquine: What a Dermatologist Should Know.

The unique immunomodulatory properties of hydroxychloroquine (HCQ) have attracted considerable interest beyond its use for malaria and rheumatological diseases, including a variety of dermatological conditions. Over recent years, especially after the coronavirus disease 2019 (COVID-19) pandemic, the prescription of HCQ has also significantly expanded, sometimes inappropriately, thus posing additional challenges on its optimal use, due to emerging safety issues. In this review, we provide dermatologists with the latest advancements on selected clinically relevant toxicities, namely retinopathy, pro-arrhythmia, cutaneous reactions, and neuropsychiatric effects. It is hoped this update can assist dermatologists to identify high-risk patients for tailored monitoring, screening, and risk minimization strategies, thus supporting safer HCQ prescribing.

New record of Orientus ishidae (Matsumura, 1902) (Hemiptera: Cicadellidae) in Bulgaria with notes on the distribution of Acanalonia conica (Say, 1830) (Hemiptera: Acanaloniidae)

Orientus ishidae (Matsumura, 1902), a leafhopper species native to East Asia, has been increasingly reported in Europe due to its potential role as a vector of phytoplasmas affecting agricultural crops. In this study, we present the first confirmed record of O. ishidae in Bulgaria, collected from Varna town during field surveys in 2024. The occurrence of O. ishidae in Bulgaria raises concerns about its potential impact on the country’s agriculture, particularly grapevines and fruit crops, which are vulnerable to the phytoplasma diseases vectored by this species. A new distribution records of Acanalonia conica (Say, 1830), previously known only from the most southeastern parts of the country, is indicating that the species established in the north-east and west parts. These records expand the known distribution of both species, O. ishidae and A. conica in Europe, highlighting the need for continued monitoring and management strategies.

A Model and Data Dual-Driven Framework for Lithium-Ion Battery Cycle Life Prediction Integrating Uncertainty Model

Abstract To address the shortcomings of single model-based or data-driven methods in battery life prediction, this paper proposes a model and data dual-driven framework for lithium-ion battery (LIB) cycle life prediction integrating uncertainty model. First, a cloud model is used to quantify the uncertainty inherent in the empirical model and construct a capacity degradation uncertainty model. Next, health features highly correlated with capacity are extracted from historical data to train a convolutional neural network, forming an online estimation model that guides subsequent parameter correction. Then, based on the prediction discrepancy between the two models, the error-feedback gate recurrent unit with improved attention model is developed for the online dynamic correction of empirical model parameters, realizing a closed-loop prediction framework. Finally, a rolling correction strategy based on statistical error is proposed to dynamically adjust the cloud model parameters, with the corrections fed back to the capacity degradation uncertainty model to further refine prediction uncertainty and accuracy. Experimental results indicate that the proposed method achieves high accuracy across various battery datasets, with relative error remaining below 2%, and provides uncertainty-quantified remaining useful life prediction, which effectively supports the online health monitoring and maintenance strategy formulation of LIBs in diverse scenarios.

Possibilities of using telemedical interventions in the framework of providing specialized endocrinological care to the population

Telemedicine is the use of telecommunication systems to provide medical care to the population at a distance. It has the potential to improve patient outcomes, access to care, and reduce health care costs. As telemedicine consultation applications continue to evolve, it is important to understand in which clinical situations and settings of care a telemedicine intervention is appropriate and can ensure that patients receive quality care. Objective: to assess the acceptability, effectiveness and safety of using TMC in the provision of specialized endocrinological care to patients. Search strategy: review of the most relevant studies published in the electronic databases Medscape, PubMed, PubMed Central, MEDLINE, Scopus, eLibrary, CyberLeninka. The selection criterion was scientific articles published up to March 2024 inclusive. Search keywords: telemedicine, virtual care, endocrinology, diabetes. Conclusions. The results of currently published studies have shown that telemedicine interventions can have a beneficial effect on the outpatient management of patients with chronic non-communicable diseases, in particular diabetes mellitus, and improve the self-management of glycemic parameters in patients. However, many questions remain unresolved regarding the choice of the optimal strategy for monitoring, treating and providing quality medical care to patients with endocrine pathology. Findings to date indicate significant promise for implementing telemedicine interventions within health care delivery. The advisability of their use in each specific case must be approached individually and solely as another, additional tool for improving the quality and accessibility of medical care.

Distributed Backface Strain Sensing of Composite Adhesively Bonded Joints under Mode II Fatigue Loading

When investigating the fracture behaviour of adhesive joints, accurate crack tip localization is under mode II loading is particularly challenging due to the absence of crack opening. The crack front often has a curved shape, so methods that inspect the side of the specimen cannot capture the crack length throughout its width. In this study, distributed backface strain sensing using Optical Backscatter Reflectometry fibre sensors is used to monitor fatigue crack growth in adhesively bonded composite End Notched Flexure Specimens. The obtained backface strain profiles were compared with analytical and Finite Element solutions to understand their relationship with the crack length. Results show that the crack tip position can be found by a local extremum in the first derivative of the strain profile. The proposed monitoring technique was compared with more established techniques for crack length measurement, such as Visual Testing, Compliance Monitoring, and Phased Array Ultrasonic Testing, and was shown to provide good accuracy. The evaluation of these techniques not only plays a crucial role in ensuring accurate testing, but can also contribute to the development of effective strategies for inspection and monitoring of adhesive joints.

A wearable platform for biochemical sweat analysis using photonic crystal hydrogel.

Wearable systems for health monitoring are highly desired in personal diagnostics and precision medicine while challenges remain in constructing such wearable systems with reliability and high performance. Herein, we report a wearable platform for non-invasive monitoring biomarkers in sweat. The device is composed of a butterfly-shaped like microfluidic platform in which responsive photonic crystal hydrogels are embedded in each butterfly wing as sensors. Sweat lactate concentration and pH can be obtained via the color variation of the sensor with naked eyes. Accurate quantitative analysis of the two target analytes can be obtained via the image analysis on a mobile phone by integrating the linear range response to analytes within the physiological range. Moreover, the sensor exhibits good reproducibility, excellent selectivity and long-term stability. On-body trials have been conducted by attaching the device on volunteers' body, and the obtained results are consistent with those analyzed through standardized methods, demonstrating its potentiality in real-time and continuous monitoring sweat biomarkers. This non-invasive wearable sensor provides a new strategy for personal health monitoring and sports performance assessment.

Assessment of macrobenthos in evaluating the restoration effects of artificial mangrove planting on tidal flats in Zhejiang, China.

Artificially planted mangroves are widely used for tidal flat restoration, but their effectiveness in restoring these ecosystems remains unclear. Macrobenthos, as key indicators of tidal flat ecosystem health, can reflect changes in environmental conditions and quality resulting from the introduction of artificial mangroves. This study aimed to investigate the ecological restoration effects of artificially planted mangroves in northern China by surveying macrobenthic communities across four regions in June 2023. We compared the macrobenthic community structures in mangrove zones with those in Spartina alterniflora or unvegetated mudflat control zones by estimating habitat quality indices and community structure analyses. Additionally, we explored the relationship between community structures and environmental factors to identify key drivers of community structure changes. Significant differences in species abundance and biomass were observed across the four regions, with mudflat zones exhibiting the highest values, followed by mangrove and Spartina alterniflora zones. Beta diversity was higher in mangrove zones compared to control zones, driven primarily by turnover components. The AMBI index indicated excellent ecological conditions in 18-year-old mangrove zone on Maoyan Island, while poorer conditions were observed in the mangrove zone of Zhoushan City. Environmental factors, such as sand content, organic carbon content, and elevation, significantly influenced macrobenthic community distribution. Overall, our findings suggest that the 18-year-old mangrove zone on Maoyan Island is ecologically stable and demonstrates significant restoration effects. Using macrobenthos to assess the restoration efficacy of mangroves proves to be both effective and feasible. Furthermore, while the mangroves have successfully established and grown, their long-term survival depends on the active involvement of local stakeholders, highlighting the importance of long-term monitoring and adaptive management strategies.

Integrated Utilization of Functional Nanomaterials for COVID-19 Monitoring, Prevention, and Diagnostic Strategies

Integrated Utilization of Functional Nanomaterials for COVID-19 Monitoring, Prevention, and Diagnostic Strategies

Environmental DNA/RNA metabarcoding for noninvasive and comprehensive monitoring and assessment of marine fishes.

Marine fisheries resources are under increasing threat, necessitating the development of new effective monitoring and management strategies. Environmental DNA (eDNA) and RNA (eRNA) metabarcoding has emerged as a non-invasive and sensitive alternative method for monitoring fish biodiversity and fisheries resources and assessing the fisheries impact of anthropogenic activities. Here, we summarize crucial technical details about eDNA metabarcoding for marine fish monitoring and provide meta-analytical trends in primer selection and sample size, assessment standards, fish and fisheries databases, reference fish genomic databases, and other relevant metrics. The pressing need for better reference databases and standardization methods is discussed. We further highlight the potency of emerging eDNA metabarcoding studies for monitoring global fish diversity and revealed regional study hotspots in South China, Atlantic and Mediterranean Seas. The innovative advances in using eDNA/eRNA metabarcoding for fish diversity monitoring and assessment from the detection of rare or invasive species to branching applications in biomass estimation, population genetics, food web analysis, fish migration and feeding studies were reviewed. We also explore the potential of eRNA metabarcoding as an upcoming extension of eDNA metabarcoding in marine fish monitoring and assessment with improved functional relevance. We envision the integration of eDNA/eRNA metabarcoding-based fish monitoring methods with traditional monitoring approaches to significantly improve marine fish surveillance, ecological research, and conservation efforts.

Management of post-injury anticoagulation in the traumatic brain injury patient: A scoping review.

Traumatic brain injury (TBI) remains a leading cause of morbidity and mortality among trauma patients. The care of these patients continues to be a complex endeavor with prevention of associated complications, often requiring as much attention as that of the treatment of the primary injury. Paramount among these are venous thromboembolic events (VTE) due to their high incidence, additive effect on the risk of morbidity and mortality, and the careful balance that must be utilized in their diagnosis and treatment to prevent progression of the brain injury itself. In this review, we have synthesized the most recent major studies detailing the ideal choice of chemoprophylactic agent, the timing of initiation, and continued monitoring and management strategies through the hospital course and beyond. Additional discussion is provided for subpopulations in which management can vary significantly, including the elderly, critically ill, and obese. Ultimately, current literature supports the use and safety of low molecular weight heparin over unfractionated heparin, especially when dosed using newer assays including anti-Xa levels. The timing of prophylaxis remains important, as the risk of VTE increases with each day that prophylaxis is held. Consensus findings favor initiation within 24-72 h, in the absence of documented progression, life threatening bleeding, or need for major surgical intervention. Despite available data, there continues to be significant variability in practice patterns which we hope to address with this review.

EWMA control chart framework for efficient Maxwell quality characteristic monitoring: An application to the aerospace industry

The Maxwell distribution is extensively employed in statistical modeling to analyze data, notably in the fields of chemistry, astrophysics, demography, actuarial sciences, economics, industry, and engineering. Recently, the application of the Maxwell data generating process (DGP) has focused extensively on the domain of statistical control charts. The V chart and VSQ chart are often used to identify unexpected changes in the distributional shift of the Maxwell process. The VSQ chart offers considerably better performance than the V chart for detecting moderate to large shifts in the scale parameter. However, the VSQ chart adopts the fundamental structure of the Shewhart monitoring scheme and is insensitive to small alterations in the target parameter. We propose a new control chart, namely, the Maxwell exponentially weighted moving average (MXEWMA) chart, for improved monitoring of quality attributes that are assumed to conform to Maxwell data generation. The factors used to design the parameters of the proposed chart are computed at different false alarm probabilities and across various sample sizes. The effectiveness of the suggested scheme is considered in terms of the different features of the run length (RL) distribution, including the average, median and standard deviation. A comparative study of the MXEWMA chart with the existing VSQ chart was performed across various sample sizes. The comparative analysis showed that the MXEWMA chart is an effective alternative and performs well in detecting reasonably small shifts in the parameter. Simulated data are employed to describe the computational procedure of the MXEWMA scheme. The simulation analysis demonstrated that the MXEWMA chart outperforms the existing method in identifying slight changes in the studied parameters. A real dataset is also considered to support the theoretical part of the work.

Attraction of Lygus lineolaris (Hemiptera: Miridae) to a ubiquitous floral volatile in the field.

Herbivorous insects utilize olfactory and visual cues to orient on suitable host plants, and such cues can be employed to facilitate insect monitoring. Lygus lineolaris Palisot de Beauvois is a polyphagous pest throughout North America. Monitoring this pest as it moves between crop and non-crop hosts remains challenging, and a lack of effective monitoring tools complicates management of this insect. In this study, we examined the electrophysiological and behavioral responses of L. lineolaris to the volatile emissions of 2 crop hosts: alfalfa and strawberry. Gas chromatography with electroantennographic detection was applied to identify antennally active compounds in headspace extracts of flowering host plants, before responses to individual compounds were examined in the field. Five compounds consistently elicited antennal depolarizations in adults of L. lineolaris and, of these, (±)-linalool increased the capture rate of L. lineolaris females in the field. Subsequent experiments examined the influence of visual cues and stereochemistry on capture rate, revealing that lures containing (±)-linalool and (S)-(+)-linalool significantly increased the capture rate of L. lineolaris females compared with traps baited with (R)-(-)-linalool and controls, indicating that L. lineolaris is attracted to (S)-(+)-linalool. While lures increased capture on red traps, this was not the case for white traps, emphasizing the importance of visual cues in the movements and monitoring of L. lineolaris. This study demonstrates that L. lineolaris is attracted to (S)-(+)-linalool in the field, and that attraction depends on trap color. This knowledge is expected to improve monitoring strategies for L. lineolaris in agricultural systems.

Intrinsic dual-emitting Si dots for high-precision and broad-range pH detection.

High-precision and broad-range pH detection is critical for health status assessment, such as signal transduction, enzyme activity, endocytosis, and cell proliferation and apoptosis. Although pH-responsive ratiometric fluorescent probes offer an effective pH monitoring strategy, their preparation often requires multi-step modification and decreases fluorescence efficiency and stability. Herein, we developed a simple method to prepare fluorescent Si dots with dual emission centers for high-precision and broad-range pH monitoring, and the detection of urease based on pH-responsive Si dots and pH monitoring in living cell was further explored. The dual-emitting Si dots had two emission centers at 427nm and 500nm. The emission at 427nm showed a fluorescence enhancement and effective quenching in the pH ranges of 3.0-10.0 and 10.0-12.0, respectively. While the emission at 500nm increased gradually with increasing pH from 3.0 to 12.0. Two linear relationships were obtained between the synchronous fluorescence intensity ratio and pH in the ranges of 7.0-9.5 and 10.0-12.0 with a △pH of 0.1, indicating a broad detection range and high precision. Then the Si dots were used to detect urease activity via urea hydrolysis-mediated pH changes. A linear range of 1-80 U/L was established with a detection limit of 0.28 U/L. Furthermore, the Si dots were used for pH imaging in living HeLa cells. The cells changed from green to blue when the pH of HeLa cells increased from 6.0 to 10.0. These findings collectively suggest that the intrinsic dual-emitting Si dots may offer a simple and versatile platform for developing pH-relevant biosensors and bioimaging applications. Additionally, this approach provides reliable methods for preparing intrinsic dual-emitting probe and constructing fluorescence ratiometrics, which widely used in health status assessment.

Abstract TMP102: Title: Prediction of Post-Stroke AF in ESUS Patients is Enhanced by Combining Expert-Derived Predictors and Embedding of Full Diagnostic Codes using Pre-Trained Hypergraph Neural Networks

Background: Atrial Fibrillation (AF) occurs in about one-fourth of patients with Embolic Stroke of Undetermined Source (ESUS). Accurate prediction of post-stroke AF upon discharge from an index stroke admission informs a personalized post-stroke monitoring strategy of AF and interventions. While clinical risk scores predict AF, machine learning (ML) models have shown superior performance. However, traditional ML approaches only use expert-derived predictors available in an electronic health record (EHR) and thus may miss variables that would potentially increase the accuracy of prediction. Aims: This study aims to enhance AF prediction by augmenting expert-derived predictors with an unbiased selection of full diagnostic codes and medication histories up to index strokes. Through embedding learning with hypergraph neural networks, we generate compact representations of high-dimensional data to improve prediction accuracy by capturing complex feature interactions. Methods: We analyzed data from 510 ESUS patients (55.3% female, mean age 61.4 years) from 2015 to 2023 at Emory Healthcare. We focus on experiments using a logistic regression (LR) model to predict AF from different sets of features. At baseline, we use 58 clinically motivated predictors, including comorbidities characterized by 17 ICD codes manually extracted based on literature, and 41 other features extracted from lab results, echocardiographic and ECG. To directly model the full history of comorbidities and medications, another baseline uses the full 1530 ICD codes plus the 41 other features (1571 in total). In contrast, the embedding method uses the full 1530 ICD codes to generate condensed, informative embedding vectors (32-dimensional), eventually getting 32+41=73 features. To generate the embedding, a hypergraph neural network was trained on a larger stroke cohort (n=7956) to model the interactions between the 1530 ICD codes. A nested cross-validation approach was employed within 5-fold splits, and ROC-AUC scores were recorded. Result: Among 510 ESUS patients, 107 (21.0%) developed AF (mean age 67.9 years, 57% female). We compared the performance of LR model with different features from ICD codes (Table 1). The results show that the learned 32-dim embedding vectors improves the prediction of post-ESUS AF. Conclusion: The embedding technique can significantly enhance predictive performance by integrating comprehensive medical information, maximizing the use of available data for improved outcomes.

Zooplankton distribution and its associated hydrology across Indian Sundarbans over the last decade: Insights from current trends and future directions.

Zooplankton play a crucial role in estuarine ecosystems by aiding nutrient cycling through trophic chains and contributing to large-scale water filtration. The present review highlights the zooplankton research conducted over the last decade (2014-2024) in the Indian Sundarbans, with a focus on research trends, species distribution, hydrological associations, and long-term monitoring and conservation strategies. The study reveals a surge in zooplankton research after 2019, with an emphasis on both small- and large-scale studies. However, tidal creek/canals remain less explored compared to rivers. A lack of methodological standardization in zooplankton research is evident across the Indian Sundarbans. The Saptamukhi-Thakuran-Matla river stretch exhibited the highest species diversity, with 70 species recorded. Similarly, the tidal creeks and canals of Sagar Island were identified as species-rich habitats, with 63 species reported. Oithona brevicornis was found in seven riverine stretches, while Paracalanus parvus and Labidocera euchaeta were each recorded from six rivers, but Bestiolina similis was mostly reported as the numerically predominant zooplankton species. Salinity emerged as the most influential hydrological factor for zooplankton distribution, followed by dissolved oxygen and water temperature. However, increasing pollution, climate change-induced cyclones, salinization, and human activities are threatening zooplankton communities of the Indian Sundarbans. Furthermore, the review underscores the need for long-term monitoring strategies in the Sundarbans, by addressing the integration of remote sensing method, automated devices, data repositories, and ecological modeling approaches. Additionally, the present review recommends future policies for zooplankton conservation, emphasizing habitat protection, water quality assessment, stakeholder engagement, and securing funding to implement long-term monitoring initiatives.

Innovations in Wave Energy: A Case Study of TALOS-WEC’s Multi-Axis Technology

The technologically advanced learning ocean system—wave energy converter (TALOS-WEC) project addresses the urgent need for sustainable and efficient energy solutions by leveraging the vast potential of wave energy. This project presents a pioneering approach to wave energy capture through its unique multi-axis and omnidirectional point absorber design. Featuring a fully enclosed power take-off (PTO) system, the TALOS-WEC harnesses energy across six degrees of freedom (DoFs) using an innovative internal reaction mass (IRM) mechanism. This configuration enables efficient energy extraction from the relative motion between the IRM and the hull, aiming for energy conversion efficiencies ranging between 75–80% under optimal conditions, while ensuring enhanced durability in harsh marine environments. The system’s adaptability is reflected in its versatile geometric configurations, including triangular, octagonal, and circular designs, customised for diverse marine conditions. Developed at Lancaster University, UK, and supported by international collaborations, the TALOS-WEC project emphasises cutting-edge advancements in hydrodynamic modelling, geometric optimisation, and control systems. Computational methodologies leverage hybrid frequency-time domain models and advanced panel codes (WAMIT, HAMS, and NEMOH) to address non-linearities in the PTO system, ensuring precise simulations and optimal performance. Structured work packages (WPs) guide the project, addressing critical aspects such as energy capture optimisation, reliability enhancement, and cost-effectiveness through innovative monitoring and control strategies. This paper provides a comprehensive overview of the TALOS-WEC, detailing its conceptual design, development, and validation. Findings demonstrate TALOS’s potential to achieve scalable, efficient, and robust wave energy conversion, contributing to the broader advancement of renewable energy technologies. The results underscore the TALOS-WEC’s role as a cutting-edge solution for harnessing oceanic energy resources, offering perspectives into its commercial viability and future scalability.

PilotCareTrans Net: an EEG data-driven transformer for pilot health monitoring

IntroductionIn high-stakes environments such as aviation, monitoring cognitive, and mental health is crucial, with electroencephalogram (EEG) data emerging as a keytool for this purpose. However traditional methods like linear models Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) architectures often struggle to capture the complex, non-linear temporal dependencies in EEG signals. These approaches typically fail to integrate multi-scale features effectively, resulting in suboptimal health intervention decisions, especially in dynamic, high-pressure environments like pilot training.MethodsTo overcome these challenges, this study introduces PilotCareTrans Net, a novel Transformer-based model designed for health intervention decision-making in aviation students. The model incorporates dynamic attention mechanisms, temporal convolutional layers, and multi-scale feature integration, enabling it to capture intricate temporal dynamics in EEG data more effectively. PilotCareTrans Net was evaluated on multiple public EEG datasets, including MODA, STEW, SJTUEmotion EEG, and Sleep-EDF, where it outperformed state-of-the-art models in key metrics.Results and discussionThe experimental results demonstrate the model's ability to not only enhance prediction accuracy but also reduce computational complexity, making it suitable for real-time applications in resource-constrained settings. These findings indicate that PilotCareTrans Net holds significant potential for improving cognitive health monitoring and intervention strategies in aviation, thereby contributing to enhanced safety and performance in critical environments.

Early detection of CTRCD by echocardiography among patients with breast cancer treated with anthracycline and trastuzumab stratified by HFA-ICOS risk classes

Abstract Background Cancer therapy-related cardiac dysfunction (CTRCD), particularly with anthracyclines and trastuzumab, can be seen frequently among patients with breast cancer. Early detection of CTRCD is crucial to prevent irreversible myocardial damage and heart failure. Echocardiography measurements including left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS) have a vital role in early detection of CTRCD. Purpose To detect subclinical left ventricular systolic dysfunction by using 2D-GLS in patient with breast cancer on Anthracycline -Trastuzumab stratified by Heart Failure Association - International Cardio-Oncology Society (HFA-ICOS) risk stratification. Methods A cross-sectional study conducted at the cardio-oncology service in Iraq from August 2022 to June 2023 enrolled women with breast cancer referred for echocardiography. The sample included females with more than 18 years old, treated with Anthracycline and/or Trastuzumab, with normal baseline left ventricular function (LVEF 54%). Results were considered abnormal if LVEF < 52% and/or GLS < -18%. Results Among 100 patients included in the study, 30 were treated with Anthracycline, 20 with Trastuzumab, and 50 with a combination of both treatments. The mean age was 48.14 ± 8.64 years. Of 65 patients with known HFA-ICOS risk stratification, GLS impairment was found in 3 patients with high HFA-ICOS risk class. There was no right ventricular dysfunction (normal TAPSE). Results are shown in Table 1. Conclusions Subclinical LV systolic dysfunction (GLS impairment) was found in all of the patients with high HFA-ICOS risk class in addition to some of the patients with medium HFA-ICOS risk. Early risk stratification helps identify high-risk patients, enabling close monitoring and cardioprotection strategies. Early detection of subclinical LV dysfunction can improve standard of care of the patients.