Enhancing dynamic flood risk assessment and zoning using a coupled hydrological-hydrodynamic model and spatiotemporal information weighting method.

Climate change and intensified human activities are exacerbating the frequency and severity of extreme precipitation events, necessitating more precise and timely flood risk assessments. Traditional models often fail to dynamically and accurately assess flood risks due to their static nature and limited handling of spatiotemporal variations. This study confronts these challenges head-on by developing a novel coupled hydrological-hydrodynamic model integrated with a Block-wise use of the TOPMODEL (BTOP) and the Rainfall-Runoff-Inundation (RRI) model. This integrated approach enables the rapid acquisition of high-precision flood inundation simulation results across large-scale basins, addressing a significant gap in dynamic flood risk assessment and zoning. A critical original achievement of this research lies in developing and implementing a comprehensive vertical-horizontal combined weighting method that incorporates spatiotemporal information for dynamic evaluation indicators, significantly enhancing the accuracy and rationality of flood risk assessments. This innovative method successfully addresses the challenges posed by objective and subjective weighting methods, presenting a balanced and robust framework for flood risk evaluation. The findings from the Min River Basin in China, as a case study, demonstrate the effectiveness of the BTOP-RRI model in capturing the complex variations in runoff and the detailed simulations of flood processes. The model accurately identifies the timing of these peaks, offering insights into the dynamic evolution of flood risks and providing a more precise and timely assessment tool for policymakers and disaster management authorities. The flood risk assessment results demonstrate good consistency with the actual regional conditions. In particular, high-risk areas exhibit distinct characteristics along the river channel, with the distribution area significantly increasing with a sudden surge in runoff. Intense precipitation events expand areas classified as moderate and high risk, gradually shrinking as precipitation levels decrease. This study significantly advances flood risk assessment methodologies by integrating cutting-edge modeling techniques with comprehensive weighting strategies. This is essential for improving the scientific foundation and decision-making processes in regional flood control efforts.

A study of land use changes and its impacts on flood inundation in the Konkoure River Basin, Republic of Guinea.

Due to rising land development, mitigating the negative effects of land use change is becoming a problem. Understanding how land development affects flood inundation is critical for long-term water resource management. This study evaluates the land use change in the Konkoure River Basin and its impact on flood inundation. The land use changes were assessed using Landsat image (level 1) in August 2006 and August 2021. In addition, we used GIS and remote sensing applications to assess the degree of changes that took place in the Konkoure watershed. According to the findings, 32.16% of the total area became built-up areas, and 35.51% was converted to other land uses in Konkoure watershed. Konkoure's most significant change is that 29.50% of forest area transformed into built-up areas and other land uses. The rainfall-runoff-inundation model (RRI) based inundation of the Konkoure River Basin was compared to the MODIS extent between 31 August 2006 and 30 August 2021 flood events. Flood inundation variations in the Konkoure watershed were studied in terms of inundation area, peak inundation depth, runoff volume, and the infiltration rate. As a result, the flood inundation area increased from 139.98 to 198.72 km2 and the infiltration rate decrease from 7 to 5 mm/h. Moreover, we used flow duration curves (FDCs) to fully comprehend the streamflow processes. The result indicates that the Konkoure watershed has experienced flooding partly due to land use change.

The clinical significance of renal resistance index (RRI) and renal oxygen saturation (RrSO2) in critically ill children with AKI: a prospective cohort study.

OBJECTIVE: The purpose of this study was to look into the clinical significance of the renal resistance index (RRI) and renal oxygen saturation (RrSO2) in predicting the development of acute kidney injury (AKI) in critically ill children. A new non-invasive method for the early detection and prediction of AKI needs to develop. METHODS: Patients admitted to the pediatric intensive care unit (PICU) affiliated with the capital institute of pediatrics from December 2020 to March 2021 were enrolled consecutively. Data of clinical information, renal Doppler ultrasound, RrSO2, and hemodynamic index within 24 h of admission were prospectively collected. Patients were divided into two groups: the study group was AKI occurred within 72 h, while the control group did not. SPSS (version 25.0) was used to analyze the data, and P < 0.05 was considered a statistical difference. RESULTS: 1) A total of 66 patients were included in this study, and the incidence of AKI was 19.70% (13/66). The presence of risk factors (shock, tumor, severe infection) increased the incidence of AKI by three times. 2) Univariate analysis showed significant differences in length of hospitalization, white blood cells (WBC), C-reactive protein (CRP), renal resistance index (RRI), and ejection fraction (EF) between the study and control groups (P < 0.05). There were no significant differences in renal perfusion semi-quantitative score (P = 0.053), pulsatility index (P = 0.051), pediatric critical illness score (PCIS), and peripheral vascular resistance index (P > 0.05). 3) Receiver operating characteristic (ROC) curve showed that if RRI > 0.635, the sensitivity, specificity, and AUC for predicting AKI were 0.889, 0.552, and 0.751, respectively; if RrSO2 < 43.95%, the values were 0.615, 0.719 and 0.609, respectively; if RRI and RrSO2 were united, they were 0.889, 0.552, and 0.766, respectively. CONCLUSIONS: The incidence of AKI is high in PICU patients. And infection, RRI, and EF are risk factors for AKI in PICU patients. RRI and RrSO2 have certain clinical significance in the early prediction of AKI and may provide a new non-invasive method for early diagnosis and prediction of AKI.

Novel AI-based HRV analysis (NAIHA) in healthcare automation and related applications.

BACKGROUND: Heart rate variability (HRV) analysis computed on R-R interval series of ECG records with heavy burden of ectopic beats or non-sinus rhythm can significantly distort HRV parameters and hence clinically ineligible for HRV analysis. Yet, existing algorithmic methods of HRV analysis do not check such eligibility and require manual identification of eligible window (portion of ECG record) to ensure reliability. OBJECTIVE: We aimed to propose a robust algorithm with a sliding window feature to automate the identification of an eligible window, if available, which compute HRV parameters within that window obviating manual input. METHODS: The proposed algorithm classifies each window as either eligible or ineligible. With a window classified eligible, we stop sliding through the record, otherwise we move to the next window and repeat the eligibility identification process, until either an eligible window is found, or all windows are exhausted. RESULTS: When evaluated on random subset of 100 records from MIMIC-III waveform database, the proposed algorithm excluded every ineligible record, and missed only 1.25% of eligible ones. The HRV parameters computed using proposed method closely approximated the standard HRV analysis with Pearson correlation coefficients (ideally one) and fractions of variance unexplained (ideally zero) ranging from 96.3% to 99.8% and 0.34% to 7.43%, respectively. CONCLUSIONS: When translated into practice, proposed algorithm will reduce clinicians'' burden without compromising the accuracy of HRV analysis, potentially leading to its wider adoption.

Signal Quality Analysis of Single-Arm Electrocardiography.

The number of people experiencing mental stress or emotional dysfunction has increased since the onset of the COVID-19 pandemic, as many individuals have had to adapt their daily lives. Numerous studies have demonstrated that mental health disorders can pose a risk for certain diseases, and they are also closely associated with the problem of mental workload. Now, wearable devices and mobile health applications are being utilized to monitor and assess individuals' mental health conditions on a daily basis using heart rate variability (HRV), typically measured by the R-to-R wave interval (RRI) of an electrocardiogram (ECG). However, portable or wearable ECG devices generally require two electrodes to perform bipolar limb leads, such as the Einthoven triangle. This study aims to develop a single-arm ECG measurement method, with lead I ECG serving as the gold standard. We conducted static and dynamic experiments to analyze the morphological performance and signal-to-noise ratio (SNR) of the single-arm ECG. Three morphological features were defined, RRI, the duration of the QRS complex wave, and the amplitude of the R wave. Thirty subjects participated in this study. The results indicated that RRI exhibited the highest cross-correlation (R = 0.9942) between the single-arm ECG and lead I ECG, while the duration of the QRS complex wave showed the weakest cross-correlation (R = 0.2201). The best SNR obtained was 26.1 ± 5.9 dB during the resting experiment, whereas the worst SNR was 12.5 ± 5.1 dB during the raising and lowering of the arm along the z-axis. This single-arm ECG measurement method offers easier operation compared to traditional ECG measurement techniques, making it applicable for HRV measurement and the detection of an irregular RRI.

Relevance of DNA preservation for future botany and ecology.

The use of molecular methods in plant systematics and taxonomy has increased during the last decades; however, the accessibility of curated genetic samples and their metadata is a bottleneck for DNA-based genetic studies in botany. Plant biodiversity DNA banks and DNA-friendly collections could be critical suppliers of curated genetic material for researchers in the current context of plant biodiversity loss. Here, we aimed to understand the potential of plant DNA banks and DNA-friendly collections to enhance the growth and openness of scientific knowledge. The preservation of genetic material should become part of a natural collection's process for the generation of extended specimens enabling the preservation of both the phenotype and genotype and contributing to the generation of data networks which cross-fertilize other fields. These curated collections are advantageous in endangered species research, detecting processes related to extinction, giving a genetic dimension to IUCN assessments or completing the Leipzig Catalogue of Vascular Plants. Therefore, DNA collections are fundamental in producing FAIR data, responsible research and innovation (RRI) and meeting the goals of international conservation programmes. The completion of natural collections is important for current research efforts and furthermore vital to support future research in an era of ongoing plant biodiversity loss.

Responsible Research and Innovation Framework, the Nagoya Protocol and Other European Blue Biotechnology Strategies and Regulations: Gaps Analysis and Recommendations for Increased Knowledge in the Marine Biotechnology Community.

As the quest for marine-derived compounds with pharmacological and biotechnological potential upsurges, the importance of following regulations and applying Responsible Research and Innovation (RRI) also increases. This article aims at: (1) presenting an overview of regulations and policies at the international and EU level, while demonstrating a variability in their implementation; (2) highlighting the importance of RRI in biodiscovery; and (3) identifying gaps and providing recommendations on how to improve the market acceptability and compliance of novel Blue Biotechnology compounds. This article is the result of the work of the Working Group 4 "Legal aspects, IPR and Ethics" of the COST Action CA18238 Ocean4Biotech, a network of more than 130 Marine Biotechnology scientists and practitioners from 37 countries. Three qualitative surveys ("Understanding of the Responsible Research and Innovation concept", "Application of the Nagoya Protocol in Your Research", and "Brief Survey about the experiences regarding the Nagoya Protocol") indicate awareness and application gaps of RRI, the Nagoya Protocol, and the current status of EU policies relating to Blue Biotechnology. The article categorises the identified gaps into five main categories (awareness, understanding, education, implementation, and enforcement of the Nagoya Protocol) and provides recommendations for mitigating them at the European, national, and organisational level.

Pursuing impact in research: towards an ethical approach.

BACKGROUND: Research proactively and deliberately aims to bring about specific changes to how societies function and individual lives fare. However, in the ever-expanding field of ethical regulations and guidance for researchers, one ethical consideration seems to have passed under the radar: How should researchers act when pursuing actual, societal changes based on their academic work? MAIN TEXT: When researchers engage in the process of bringing about societal impact to tackle local or global challenges important concerns arise: cultural, social and political values and institutions can be put at risk, transformed or even hampered if researchers lack awareness of how their 'acting to impact' influences the social world. With today's strong focus on research impacts, addressing such ethical challenges has become urgent within in all fields of research involved in finding solutions to the challenges societies are facing. Due to the overall goal of doing something good that is often inherent in ethical approaches, boundaries to researchers' impact of something good is neither obvious, nor easy to detect. We suggest that it is time for the field of bioethics to explore normative boundaries for researchers' pursuit of impact and to consider, in detail, the ethical obligations that ought to shape this process, and we provide a four-step framework of fair conditions for such an approach. Our suggested approach within this field can be useful for other fields of research as well. CONCLUSION: With this paper, we draw attention to how the transition from pursuing impact within the Academy to trying to initiate and achieve impact beyond the Academy ought to be configured, and the ethical challenges inherent in this transition. We suggest a stepwise strategy to identify, discuss and constitute consensus-based boundaries to this academic activity. This strategy calls for efforts from a multi-disciplinary team of researchers, advisors from the humanities and social sciences, as well as discussants from funding institutions, ethical committees, politics and the society in general. Such efforts should be able to offer new and useful assistance to researchers, as well as research funding agencies, in choosing ethically acceptable, impact-pursuing projects.

A Novel Adaptive Noise Elimination Algorithm in Long RR Interval Sequences for Heart Rate Variability Analysis.

As heart rate variability (HRV) studies become more and more prevalent in clinical practice, one of the most common and significant causes of errors is associated with distorted RR interval (RRI) data acquisition. The nature of such artifacts can be both mechanical as well as software based. Various currently used noise elimination in RRI sequences methods use filtering algorithms that eliminate artifacts without taking into account the fact that the whole RRI sequence time cannot be shortened or lengthened. Keeping that in mind, we aimed to develop an artifacts elimination algorithm suited to long-term (hours or days) sequences that does not affect the overall structure of the RRI sequence and does not alter the duration of data registration. An original adaptive smart time series step-by-step analysis and statistical verification methods were used. The adaptive algorithm was designed to maximize the reconstruction of the heart-rate structure and is suitable for use, especially in polygraphy. The authors submit the scheme and program for use.

Artificial Intelligence and 3D Scanning Laser Combination for Supervision and Fault Diagnostics.

In this work, we combine some of the most relevant artificial intelligence (AI) techniques with a range-resolved interferometry (RRI) instrument applied to the maintenance of a wind turbine. This method of automatic and autonomous learning can identify, monitor, and detect the electrical and mechanical components of wind turbines to predict, detect, and anticipate their degeneration. A scanner laser is used to detect vibrations in two different failure states. Following each working cycle, RRI in-process measurements agree with in-process hand measurements of on-machine micrometers, as well as laser scanning in-process measurements. As a result, the proposed method should be very useful for supervising and diagnosing wind turbine faults in harsh environments. In addition, it will be able to perform in-process measurements at low costs.

The Societal Readiness Thinking Tool: A Practical Resource for Maturing the Societal Readiness of Research Projects.

In this paper, we introduce the Societal Readiness (SR) Thinking Tool to aid researchers and innovators in developing research projects with greater responsiveness to societal values, needs, and expectations. The need for societally-focused approaches to research and innovation-complementary to Technology Readiness (TR) frameworks-is presented. Insights from responsible research and innovation (RRI) concepts and practice, organized across critical stages of project-life cycles are discussed with reference to the development of the SR Thinking Tool. The tool is designed to complement not only shortfalls in TR approaches, but also improve upon other efforts to integrate RRI, sustainability, and design thinking in research and innovation cycles. Operationalization and early-stage user tests of the Tool are reported, along with discussion of potential future iterations and applications.

A Q methodology study on divergent perspectives on CRISPR-Cas9 in the Netherlands.

BACKGROUND: CRISPR-Cas9, a technology enabling modification of the human genome, is developing rapidly. There have been calls for public debate to discuss its ethics, societal implications, and governance. So far, however, little is known about public attitudes on CRISPR-Cas9. This study contributes to a better understanding of public perspectives by exploring the various holistic perspectives Dutch citizens have on CRISPR-Cas9. METHODS: This study used Q methodology to identify different perspectives of Dutch citizens (N = 30) on the use of CRISPR-Cas9. The Q-sort method aims at segmenting audiences based on the structural characteristics of their perspectives. Participants individually ranked 32 statements about CRISPR-Cas9 and discussed their rankings in small groups. By-person factor analysis was performed using PQMethod. Participants' contributions to the discussions were used to further make sense of the audience segments identified. RESULTS: Five perspectives on CRISPR-Cas9 were identified: (1) pragmatic optimism (2) concerned scepticism; (3) normative optimism; (4) enthusiastic support; and (5) benevolent generalism. Each perspective represents a unique position motivated by different ranking rationales. Sorting rationales included improving health, preventing negative impacts on society, and fear of a slippery slope. Overall, there is broad, but not universal support for medical uses of CRISPR-Cas9. CONCLUSIONS: Research on CRISPR-Cas9 should prioritise the broadly supported applications of the technology. Research and public debates on CRISPR-Cas9, its uses, its broader implications, and the governance of CRISPR-Cas9 are recommended. A discourse that includes all perspectives can contribute to the embedding of future uses of CRISPR-Cas9 in society. This study shows that Q methodology followed by group discussions enables citizens to contribute meaningfully to discourses about research.

Predicted dominance of variant Delta of SARS-CoV-2 before Tokyo Olympic Games, Japan, July 2021.

Using numbers of SARS-CoV-2 variants detected in Japan as at 13 June 2021, relative instantaneous reproduction numbers (RRI) of the R.1, Alpha, and Delta variants with respect to other strains circulating in Japan were estimated at 1.25, 1.44, and 1.95. Depending on the assumed serial interval distributions, RRI varies from 1.20-1.32 for R.1, 1.34-1.58 for Alpha, and 1.70-2.30 for Delta. The frequency of Delta is expected to take over Alpha in Japan before 23 July 2021.

Autoencoder-Based Extrasystole Detection and Modification of RRI Data for Precise Heart Rate Variability Analysis.

Heart rate variability, which is the fluctuation of the R-R interval (RRI) in electrocardiograms (ECG), has been widely adopted for autonomous evaluation. Since the HRV features that are extracted from RRI data easily fluctuate when arrhythmia occurs, RRI data with arrhythmia need to be modified appropriately before HRV analysis. In this study, we consider two types of extrasystoles-premature ventricular contraction (PVC) and premature atrial contraction (PAC)-which are types of extrasystoles that occur every day, even in healthy persons who have no cardiovascular diseases. A unified framework for ectopic RRI detection and a modification algorithm that utilizes an autoencoder (AE) type of neural network is proposed. The proposed framework consists of extrasystole occurrence detection from the RRI data and modification, whose targets are PVC and PAC. The RRI data are monitored by means of the AE in real time in the detection phase, and a denoising autoencoder (DAE) modifies the ectopic RRI caused by the detected extrasystole. These are referred to as AE-based extrasystole detection (AED) and DAE-based extrasystole modification (DAEM), respectively. The proposed framework was applied to real RRI data with PVC and PAC. The result showed that AED achieved a sensitivity of 93% and a false positive rate of 0.08 times per hour. The root mean squared error of the modified RRI decreased to 31% in PVC and 73% in PAC from the original RRI data by DAEM. In addition, the proposed framework was validated through application to a clinical epileptic seizure problem, which showed that it correctly suppressed the false positives caused by PVC. Thus, the proposed framework can contribute to realizing accurate HRV-based health monitoring and medical sensing systems.

Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running.

Recent advances in wearable technologies integrating multi-modal sensors have enabled the in-field monitoring of several physiological metrics. In sport applications, wearable devices have been widely used to improve performance while minimizing the risk of injuries and illness. The objective of this project is to estimate breathing rate (BR) from respiratory sinus arrhythmia (RSA) using heart rate (HR) recorded with a chest belt during physical activities, yielding additional physiological insight without the need of an additional sensor. Thirty-one healthy adults performed a run at increasing speed until exhaustion on an instrumented treadmill. RR intervals were measured using the Polar H10 HR monitoring system attached to a chest belt. A metabolic measurement system was used as a reference to evaluate the accuracy of the BR estimation. The evaluation of the algorithms consisted of exploring two pre-processing methods (band-pass filters and relative RR intervals transformation) with different instantaneous frequency tracking algorithms (short-term Fourier transform, single frequency tracking, harmonic frequency tracking and peak detection). The two most accurate BR estimations were achieved by combining band-pass filters with short-term Fourier transform, and relative RR intervals transformation with harmonic frequency tracking, showing 5.5% and 7.6% errors, respectively. These two methods were found to provide reasonably accurate BR estimation over a wide range of breathing frequency. Future challenges consist in applying/validating our approaches during in-field endurance running in the context of fatigue assessment.

Contextualizing Security Innovation: Responsible Research and Innovation at the Smart Border?

Current European innovation and security policies are increasingly channeled into efforts to address the assumed challenges that threaten European societies. A field in which this has become particularly salient is digitized EU border management. Here, the framework of responsible research and innovation (RRI) has recently been used to point to the alleged sensitivity of political actors towards the contingent dimensions of emerging security technologies. RRI, in general, is concerned with societal needs and the engagement and inclusion of various stakeholder groups in the research and innovation processes, aiming to anticipate undesired consequences of and identifying socially acceptable alternatives for emerging technologies. However, RRI has also been criticized as an industry-driven attempt to gain societal legitimacy for new technologies. In this article, we argue that while RRI evokes a space where different actors enter co-creative dialogues, it lays bare the specific challenges of governing security innovation in socially responsible ways. Empirically, we draw on the case study of BODEGA, the first EU funded research project to apply the RRI framework to the field of border security. We show how stakeholders involved in the project represent their work in relation to RRI and the resulting benefits and challenges they face. The paper argues that applying the framework to the field of (border) security lays bare its limitations, namely that RRI itself embodies a political agenda, conceals alternative experiences by those on whom security is enacted upon and that its key propositions of openness and transparency are hardly met in practice due to confidentiality agreements. Our hope is to contribute to work on RRI and emerging debates about how the concept can (or cannot) be contextualized for the field of security-a field that might be more in need than any other to consider the ethical dimension of its activities.

Differential Impact of the Renal Resistive Index on Future Cardiovascular Events in Hospitalized Atherosclerotic Cardiovascular Patients According to Left Ventricular Ejection Fraction　- The Jichi Vascular Hemodynamics in Hospitalized Cardiovascular Patients (J-VAS) Study.

BACKGROUND: Determinants of poor outcome in atherosclerotic cardiovascular disease (ASCVD) according to left ventricular ejection fraction (LVEF) are unclear. The renal resistive index (RRI) correlates well with atherosclerotic vascular damage, which, in turn, is correlated with cardiovascular outcomes. This study investigated whether high RRI is associated with poor cardiovascular outcomes in ASCVD patients classified by LVEF.Methods and Results:Records of 1,598 acute coronary syndromes (ACS) and acute decompensated heart failure (ADHF) patients, categorized into preserved (p), mid-range (mr), and reduced (r) ejection fraction (EF) groups (EF ≥50% [n=1,130], 40-50% [n=223], and <40% [n=245], respectively), were analyzed retrospectively. The primary endpoint was any cardiovascular-related event: fatal and non-fatal ACS, ADHF, stroke, and sudden cardiac death. Over 1.9-years follow-up (3,030 person-years), 233 events occurred: 122, 37, and 74 in the pEF, mrEF, and rEF groups, respectively. Adjusted Cox regression analysis revealed RRI ≥0.8 was associated with the primary endpoint in the pEF group (hazard ratio [HR] 1.67; 95% confidence interval [CI] 1.09-2.56), but not in the mrEF or rEF groups. The primary endpoint risk of pEF patients with an RRI ≥0.8 was comparable to that of mrEF patients using the pEF+RRI <0.8 group as the reference (HR 1.89 [95% CI 1.26-2.83] and 1.77 [95% CI 1.19-2.63], respectively). CONCLUSIONS: RRI was associated with the risk of cardiovascular events in ASCVD patients with pEF.

AMICAI: A Method Based on Risk Analysis to Integrate Responsible Research and Innovation into the Work of Research and Innovation Practitioners.

The integration of ethics into the day-to-day work of research and innovation (R&I) is an important but difficult challenge. However, with the Aachen method for identification, classification and risk analysis of innovation-based problems (AMICAI) an approach from an engineering perspective is presented that enables the integration of ethical, legal and social implications into the day-to-day work of R&I practitioners. AMICAI appears in particular capable of providing a procedural guidance for R&I practitioners based on a method established in engineering science, breaking down the object of consideration into partial aspects and prioritizing the innovation-based problems in dependence of potential risk. This enables the user to apply AMICAI continuously during all stages of the research and development (R&D) process and to analyze and choose between certain sociotechnical alternatives. In this way, problems that affect ethical, legal, and social aspects can be understood, reflected and considered in the mostly technically focused R&D process. The paper gives a general guidance about AMICAI by describing principles and assumptions, providing the steps of analysis and application aids, giving an example application, explaining the necessary adjustments of AMICAI compared to the methodical basis of failure mode, effects, and criticality analysis and discussing the advantages and limits. AMICAI's simple applications can stimulate interdisciplinary cooperation in the R&D process and be a starting point for the development of an "open RRI risk analysis platform" allowing society to evaluate innovation-based problems.

Practices of Responsible Research and Innovation: A Review.

This paper presents results of a systematic literature review of RRI practices which aimed to gather insights to further both the theoretical and practical development of RRI. Analysing practices of RRI and mapping out main approaches as well as the values, dimensions or characteristics pursued with those practices, can add to understanding of the more conceptual discussions of RRI and enhance the academic debate. The results, based on a corpus of 52 articles, show that practices already reflect the rich variety of values, dimensions and characteristics provided in the main definitions in use, although not all are addressed yet. In fact, articles dealing with uptake of RRI practices may be improved by including more methodological information. RRI practices may further the conceptual debate by including more reflection, and these may foster mutual responsiveness between theory and practice by early anticipating impacts.

The predictive value of the renal resistive index for contrast-induced nephropathy in patients with acute coronary syndrome.

BACKGROUND: Percutaneous coronary intervention (PCI) has been associated with contrast-induced nephropathy (CIN) at a rate that varies depending on the patient's risk factors. This study was conducted to evaluate the predictive value of the renal resistive index (RRI) for CIN in patients with acute coronary syndrome (ACS) undergoing PCI. METHODS: This prospective study enrolled 146 consecutive patients with ACS. Renal Doppler ultrasound examinations to measure RRI were performed pre-PCI and at 1 h and 24 h after PCI. The primary endpoint was CIN, defined as a relative (≥25%) or absolute (≥0.5 mg/dL; 44 µmol/L) increase in serum creatinine from baseline within 48 h after contrast exposure. RESULTS: CIN was identified in 31 patients (21.2%); however, none of the patients required haemodialysis. Compared to patients without CIN, higher RRIs were observed at 1 h (0.71 ± 0.05 vs. 0.65 ± 0.06, p < 0.05) and 24 h (0.70 ± 0.05 vs. 0.66 ± 0.06, p < 0.05) post-procedure in patients with CIN. The RRI rose transiently from baseline (0.68 ± 0.05) to 1 h (0.71 ± 0.05) and then tended to decline at 24 h (0.70 ± 0.05). A receiver operating characteristic curve analysis showed that the pre-procedure RRI was a powerful predictive indicator of CIN (area under the curve = 0.661, p = 0.006). The best cutoff value was 0.69 with 67.7% sensitivity and 67% specificity. Besides hyperuricemia and chronic kidney disease, the multivariate logistic regression analysis revealed that a high baseline RRI (≥0.69) was a significant predictor of CIN (odds ratio = 4.445; 95% confidence interval: 1.806-10.937; p = 0.001). CONCLUSIONS: A high pre-procedural RRI appears to be independently predictive of CIN in patients with ACS undergoing PCI.