External quality assurance program for diagnostic complement laboratories: evaluation of the results of the past seven years.

Introduction: The complement external quality assurance (EQA) program was first organized in 2010 by a group of researchers working in diagnostic complement laboratories. Starting in 2016, INSTAND e.V., a German, non-profit interdisciplinary scientific medical society dedicated to providing expert EQA programs for medical laboratories, started organizing the EQAs for complement diagnostic laboratories together with the same group of experienced scientists and doctors who also work as EQA experts. The aim of the current work is to provide descriptive analysis of the past seven years' complement EQA results and evaluate timeline changes in proficiency testing. Methods: Each year, in March and October, blinded samples (normal, pathological) were sent to the participating diagnostic laboratories, where complement parameters were evaluated exactly as in daily routine samples. Since no reference method/target values exist for these parameters, and participants used different units for measurement, the reported results were compared to the stable mean (Algorithm A) of the participants using the same method/measurement units. A reported result was qualified as "passed" if it fell into the 30-50% evaluation/target range around the mean of reported results (depending on the given parameter). Results: While the number of participating laboratories has increased in the past years (from around 120 to 347), the number of complement laboratories providing multiple determinations remained mostly unchanged (around 30 worldwide). C3, C4, C1-inhibitor antigen and activity determinations provided the best proficiency results, with >90% passing quotas in the past years, independent of the applied method. Determination of the functional activity of the three activation pathways was good in general, but results showed large variance, especially with the pathological samples. Complement factor C1q and regulators FH and FI are determined by only a few laboratories, with variable outcomes (in general in the 85-90% pass range). Activation products sC5b-9 and Bb were determined in 30 and 10 laboratories, respectively, with typical passing quotas in the 70-90% range, without a clear tendency over the past years. Conclusion: With these accumulated data from the past seven years, it is now possible to assess sample-, method-, and evaluation related aspects to further improve proficiency testing and protocolize diagnostic complement determinations.

Evaluation of quality and quantity of randomized controlled trials in hepatobiliary surgery: A scoping/mapping review.

AIM: To evaluate the quantity and quality of randomized controlled trials (RCTs) in hepatobiliary surgery and for identifying gaps in current evidences. METHODS: A systematic search was conducted in MEDLINE (via PubMed), Web of Science, and Cochrane Controlled Register of Trials (CENTRAL) for RCTs of hepatobiliary surgery published from inception until the end of 2023. The quality of each study was assessed using the Cochrane risk-of-bias (RoB) tool. The associations between risk of bias and the region and publication date were also assessed. Evidence mapping was performed to identify research gaps in the field. RESULTS: The study included 1187 records. The number and proportion of published randomized controlled trials (RCTs) in hepatobiliary surgery increased over time, from 13 RCTs (.0005% of publications) in 1970-1979 to 201 RCTs (.003% of publications) in 2020-2023. There was a significant increase in the number of studies with a low risk of bias in RoB domains (p < .01). The proportion of RCTs with low risk of bias improved significantly after the introduction of CONSORT guidelines (p < .001). The evidence mapping revealed a significant research focus on major and minor hepatectomy and cholecystectomy. However, gaps were identified in liver cyst surgery and hepatobiliary vascular surgery. Additionally, there are gaps in the field of perioperative management and nutrition intervention. CONCLUSION: The quantity and quality of RCTs in hepatobiliary surgery have increased over time, but there is still room for improvement. We have identified gaps in current research that can be addressed in future studies.

Automated Web-based Software for CT Quality Control Testing of Low-contrast Detectability using Model Observers.

The Channelized Hotelling observer (CHO) is well correlated with human observer performance in many CT detection/classification tasks but has not been widely adopted in routine CT quality control and performance evaluation, mainly because of the lack of an easily available, efficient, and validated software tool. We developed a highly automated solution - CT image quality evaluation and Protocol Optimization (CTPro), a web-based software platform that includes CHO and other traditional image quality assessment tools such as modulation transfer function and noise power spectrum. This tool can allow easy access to the CHO for both the research and clinical community and enable efficient, accurate image quality evaluation without the need of installing additional software. Its application was demonstrated by comparing the low-contrast detectability on a clinical photon-counting-detector (PCD)-CT with a traditional energy-integrating-detector (EID)-CT, which showed UHR-T3D had 6.2% higher d' than EID-CT with IR (p = 0.047) and 4.1% lower d' without IR (p = 0.122).

Comprehensive comparison of two models evaluating eco-environmental quality in Fangshan.

It is crucial to employ scientifically sound models for assessing the quality of the ecological environment and revealing the strengths and weaknesses of ecosystems. This process is vital for identifying regional ecological and environmental issues and devising relevant protective measures. Among the widely acknowledged models for evaluating ecological quality, the ecological index (EI) and remote sensing ecological index (RSEI) stand out; however, there is a notable gap in the literature discussing their differences, characteristics, and reasons for selecting either model. In this study, we focused on Fangshan District, Beijing, China, to examine the differences between the two models from 2017 to 2021. We summarized the variations in evaluation indices, importance, quantitative methods, and data acquisition times, proposing application scenarios for both models. The results indicate that the ecological environment quality in Fangshan District, Beijing, remained favorable from 2017 to 2021. There was a discernible trend of initially declining quality followed by subsequent improvement. The variation in the calculation results is evident in the overall correlation between the RSEI and EI. Particularly noteworthy is the significantly smaller correlation between EI and the RSEI in 2021 than in the other two years. This discrepancy is attributed to shifts in the contribution of the evaluation indices within the RSEI model. The use of diverse quantitative methods for evaluating indicators has resulted in several variations. Notably, the evaluation outcomes of the EI model exhibit a stronger correlation with land cover types. This correlation contributes to a more pronounced fluctuation in RSEI levels from 2017 to 2021, with the EI model's evaluation results in 2019 notably surpassing those of the RSEI model. Ultimately, the most prominent disparities lie in the calculation results for water areas and construction land. The substantial difference in water areas is attributed to the distinct importance assigned to evaluation indicators between the two models. Moreover, the notable difference in construction land arises from the use of different quantification methods for evaluation indicators. In general, the EI model has suggested to be more comprehensive and effectively captures the annual comprehensive status of the ecological environment and the multiyear change characteristics of the administrative region. On the other hand, RSEI models exhibit greater flexibility and ease of implementation, independent of spatial and temporal scales. These findings contribute to a clearer understanding of the models' advantages and limitations, offering guidance for decision makers and valuable insights for the improvement and development of ecological environmental quality evaluation models.

The "hidden noise" problem in MR image reconstruction.

PURPOSE: The performance of modern image reconstruction methods is commonly judged using quantitative error metrics like root mean squared-error and the structural similarity index, which are calculated by comparing reconstructed images against fully sampled reference data. In practice, the reference data will contain noise and is not a true gold standard. In this work, we demonstrate that the "hidden noise" present in reference data can substantially confound standard approaches for ranking different image reconstruction results. METHODS: Using both experimental and simulated k-space data and several different image reconstruction techniques, we examined whether there was correlation between performance metrics obtained with typical noisy reference data versus those obtained with higher-quality reference data. RESULTS: For conventional performance metrics, the reconstructions that matched best with the higher-quality reference data were substantially different from the reconstructions that matched best with typical noisy reference data. This leads to suboptimal reconstruction results if the performance with respect to noisy reference data is used to select which reconstruction methods/parameters to employ. These issues were reduced when employing alternative error metrics that better account for noise. CONCLUSION: Reference data containing hidden noise can substantially mislead the ranking of image reconstruction methods when using conventional error metrics, but this issue can be mitigated with alternative error metrics.

The European Organisation of External Quality Assurance Providers in Laboratory Medicine (EQALM) Statement: guidelines for publishing about interlaboratory comparison studies (PubILC).

Data and results from interlaboratory comparison (ILC) studies, external quality assessment (EQA) and proficiency testing (PT) activities are important and valuable contributions both to the further development of all disciplines of medical laboratory diagnostics, and to the evaluation and comparison of in vitro diagnostic assays. So far, however, there are no recommendations as to which essential items should be addressed in publications on interlaboratory comparisons. The European Organization of External Quality Assurance Providers in Laboratory Medicine (EQALM) recognized the need for such recommendations, and these were developed by a group of experts. The result of this endeavor is the EQALM Statement on items recommended to be addressed in publications on interlaboratory comparison activities (PubILC), in conjunction with a user-friendly checklist. Once adopted by authors and journals, the EQALM Statement will ensure essential information and/or study-related facts are included within publications on EQA/PT activities.

Innovating Online Otolaryngology: The Development of the ENT Content Engagement and Quality Index for Audiovisual Material.

Introduction The advent of social media platforms, notably TikTok, has significantly transformed the landscape of health information dissemination, offering both opportunities and challenges for public health communication. This study focuses on TikTok's influence on sinus health information, addressing the dual challenge of widespread engagement and the risk of misinformation in otolaryngology, or ENT (ear-nose-throat), information online. We introduce the ENT Content Engagement and Quality Index (ENT-CEQI), a pioneering tool designed to assess the quality and engagement of ENT-related content on TikTok, aiming to improve public understanding of sinus health. Materials and methods Our methodology involved a systematic analysis of sinus health-related content on TikTok. We collected data on the top 100 most popular videos using the hashtag #sinus at two different points in time, analyzing engagement metrics and content quality. The ENT-CEQI was developed to evaluate content, incorporating both quantitative engagement metrics (views, likes, comments, shares, favorites) and qualitative assessments (accuracy, clarity, relevance, practicality, engagement). The study employed statistical analyses, including trend analysis, correlation analysis, principal component analysis (PCA), KMeans clustering, regression analysis, and the Kruskal-Wallis test, to understand the dynamics of content engagement and quality. Results Initial findings revealed significant disparities in engagement metrics and quality scores among different content creator categories, with physician-generated content showing the highest engagement and quality. The trend analysis indicated shifts in content popularity and quality over time, with a notable increase in views and likes for private company content. The PCA and clustering analyses identified distinct content clusters, offering insights into viewer engagement patterns. Regression analysis and the Kruskal-Wallis test, however, did not find significant predictors (p-value: 0.3916) of content quality or differences in likes across content types, suggesting complex factors influencing content engagement and quality perception. Discussion The study highlights TikTok's potential and pitfalls in disseminating sinus health information. The introduction of the ENT-CEQI represents a major step toward enhancing the evaluation of health content on social media, emphasizing the importance of accuracy, clarity, and relevance in public health communication. The analysis underscores the complexity of social media engagement and the need for robust tools to assess content quality. It also points to the critical role of healthcare professionals in engaging with the public through social media to combat misinformation. Conclusions TikTok serves as a potent platform for sinus health education, capable of reaching wide and diverse audiences. The ENT-CEQI emerges as a vital tool for assessing the quality and engagement of ENT-related content, guiding content creators toward producing more reliable and informative content. This study contributes to the understanding of social media's role in health communication, advocating for the strategic use of innovative tools such as the ENT-CEQI to enhance public health outcomes through improved online health education and misinformation management.

Understanding the limitations of your assay using EQA data with serum creatinine as an example.

OBJECTIVES: Laboratories need to take into consideration the specificity and imprecision of assays not only in verification, but also of quality assessment. This study investigates the composition of serum used in EQA materials by comparing material from a single and multiple donors (pooled material), across multiple methods, using creatinine as an example. METHODS: Sixteen different serum matrices were distributed as 36 specimens through the UK NEQAS for Acute and Chronic Kidney Disease Scheme from March 2022 to March 2023. Male-only and female-only serum was used as single donations, pooled donations, unmanipulated or with added exogenous creatinine. Specimens were distributed to primarily UK participants (approximately n=500) for creatinine analysis. Data has been reviewed by method compared to the enzymatic creatinine method principle mean. RESULTS: From the 16 different matrices, only the enzymatic creatinine assay systems from Roche Cobas and Siemens Atellica met the minimum acceptable bias goal, from biological data, of 5.6 %, in all specimens. Pooled material showed less variation in bias across all methods. CONCLUSIONS: Since Laboratories invest a lot of time and money in quality management, they need to know the limitations of their assays so that they are not investigating 'apparent' EQA/IQC problems which are purely due to non-specific, imprecise assay, rather than an analytical issue in their laboratory. When large numbers of individual donations are combined, interferents are essentially diluted out. Therefore, if EQA material is of this type it will be very difficult to determine the actual assay's bias and variability.

Hydrochemical characterization and assessment of health risks of trace elements in the Huai River Basin of China.

Basin water pollution is a global problem, especially in the densely populated areas. The Huai River Basin (abbreviated as HRB), including the Huai River system and the Yishu River system, is the sixth-largest and most densely populated watershed in China. However, there is a lack of comprehensive studies of river and well water throughout the Huai River basin, including hydrochemistry characterization and assessment of health risks. This study investigated water quality and pollution sources of river and well water in the HRB based on the hydrochemistry analysis and different water quality indices. The water body in the HRB showed weak alkalinity (pH = 8.4 ± 0.7) and had high TDS values (TDS = 339 ± 186 mg/L) with water types of HCO3-Ca-Mg and SO4-Cl-Ca-Mg in the Huai River system, and SO4-Cl-Ca-Mg in the Yishu River system. Atmospheric input and evaporation had less impact on hydrochemistry. Evaporite dissolution and carbonate weathering had a greater impact on hydrochemistry. Carbonate precipitation and cation exchange also influenced the dissolved solutes, especially Ca2+ and Na+. Samples had low to medium salinity hazards and sodium absorption ratios and were suitable for irrigation. For drinking purposes, samples were fresh water and have good or excellent according to the Water Quality Index (WQI). Land use types influenced water quality with the worst river water quality from cropland. Combining different assessment indices, the water quality of the Yishu River system performed better than the Huai River system. Absolute principal component analysis-multiple linear regression and the positive matrix factorization models identified the main pollutants as As, Ba, Cr, Ni, and Mn, with natural sources of As, Ba, and Ni and anthropogenic inputs of Cr, and Mn. Although the water quality of the HRB has improved in recent years, high potential risk from As, Cr, Mn, Ba, and Ni should be noted. This study provided vital information for basin hydrochemistry analysis and water quality assessment.

Longitudinal stream synoptic (LSS) monitoring to evaluate water quality in restored streams.

Impervious surface cover increases peak flows and degrades stream health, contributing to a variety of hydrologic, water quality, and ecological symptoms, collectively known as the urban stream syndrome. Strategies to combat the urban stream syndrome often employ engineering approaches to enhance stream-floodplain reconnection, dissipate erosive forces from urban runoff, and enhance contaminant retention, but it is not always clear how effective such practices are or how to monitor for their effectiveness. In this study, we explore applications of longitudinal stream synoptic (LSS) monitoring (an approach where multiple samples are collected along stream flowpaths across both space and time) to narrow this knowledge gap. Specifically, we investigate (1) whether LSS monitoring can be used to detect changes in water chemistry along longitudinal flowpaths in response to stream-floodplain reconnection and (2) what is the scale over which restoration efforts improve stream quality. We present results for four different classes of water quality constituents (carbon, nutrients, salt ions, and metals) across five watersheds with varying degrees of stream-floodplain reconnection. Our work suggests that LSS monitoring can be used to evaluate stream restoration strategies when implemented at meter to kilometer scales. As streams flow through restoration features, concentrations of nutrients, salts, and metals significantly decline (p < 0.05) or remain unchanged. This same pattern is not evident in unrestored streams, where salt ion concentrations (e.g., Na+, Ca2+, K+) significantly increase with increasing impervious cover. When used in concert with statistical approaches like principal component analysis, we find that LSS monitoring reveals changes in entire chemical mixtures (e.g., salts, metals, and nutrients), not just individual water quality constituents. These chemical mixtures are locally responsive to restoration projects, but can be obscured at the watershed scale and overwhelmed during storm events.

[Synthetic indicator of compliance with standards for Quality Units of health centers and multicenter prospective pilot study]. / Indicador sintético de cumplimiento de estándares para Unidades de Calidad de centros sanitarios y estudio de pilotaje prospectivo multicéntrico.

BACKGROUND AND OBJECTIVE: In Spain, Quality Units play a key and unique role in advising healthcare centers on the methodology of healthcare quality. The objectives of the study were to develop computer algorithms to obtain a synthetic indicator of standard compliance for Quality Units and to pilot its functioning in these units. MATERIALS AND METHODS: The Excel program was used to establish evaluation algorithms, and quantitatively interrelate and weight various categories of standards, as a computer evaluation tool, to build a continuous improvement cycle system, and offer a global synthetic indicator of compliance. The tool was tested in a prospective multicenter pilot study, in which coordinators of Quality Units from different health centers and care settings participated, to evaluate the usefulness of the tool and compliance with the standards, in addition to analyzing the content validity of each standard. RESULTS: The formulas for the structured computer algorithms were developed, consecutively, in a «PLAN-DO-CHECK-ACT¼ improvement cycle for the 9 categories of standards, resulting in a single synthetic indicator of compliance. Twenty-one Quality Units participated in the piloting. The overall average compliance rate for the synthetic indicator was 55.63% with differences between centers (P=.002) and between categories (P<.0001), but not by autonomous communities (P=.86) or by areas (P=.97). Content validity was ensured through the variable of «understanding¼ of the standards (P<.001), and through their «justification¼ with documentary evidence (P<.001). CONCLUSIONS: The computer tool with the synthetic indicator have allowed for the evaluation of standard compliance in Quality Units of healthcare centers.

Assessing paraspinal muscle atrophy with electrical impedance myography: Limitations and insights.

Paraspinal muscle atrophy is gaining attention in spine surgery due to its link to back pain, spinal degeneration and worse postoperative outcomes. Electrical impedance myography (EIM) is a noninvasive diagnostic tool for muscle quality assessment, primarily utilized for patients with neuromuscular diseases. However, EIM's accuracy for paraspinal muscle assessment remains understudied. In this study, we investigated the correlation between EIM readings and MRI-derived muscle parameters, as well as the influence of dermal and subcutaneous parameters on these readings. We retrospectively analyzed patients with lumbar spinal degeneration who underwent paraspinal EIM assessment between May 2023 to July 2023. Paraspinal muscle fatty infiltration (FI) and functional cross-sectional area (fCSA), as well as the subcutaneous thickness were assessed on MRI scans. Skin ultrasound imaging was assessed for dermal thickness and the echogenicities of the dermal and subcutaneous layers. All measurements were performed on the bilaterally. The correlation between EIM readings were compared with ultrasound and MRI parameters using Spearman's correlation analyses. A total of 20 patients (65.0% female) with a median age of 69.5 years (IQR, 61.3-73.8) were analyzed. The fCSA and FI did not significantly correlate with the EIM readings, regardless of frequency. All EIM readings across frequencies correlated with subcutaneous thickness, echogenicity, or dermal thickness. With the current methodology, paraspinal EIM is not a valid alternative to MRI assessment of muscle quality, as it is strongly influenced by the dermal and subcutaneous layers. Further studies are required for refining the methodology and confirming our results.

Reproductive toxicity assessment of cellulose nanofibers, citric acid, and branched polyethylenimine in sea urchins: eco-design of nanostructured cellulose sponge framework (Part B).

In the framework of a safe-by-design approach, we previously assessed the eco-safety of nanostructured cellulose sponge (CNS) leachate on sea urchin reproduction. It impaired gamete quality, gamete fertilization competence, and embryo development possibly due to the leaching of chemical additives deriving from their chemical synthesis. To extend this observation and identify the component(s) that contribute to CNS ecotoxicity, in the present study, we individually screened the cytotoxic effects on sea urchin Arbacia lixula and Paracentrotus lividus gametes and embryos of the three main constituents of CNS, namely cellulose nanofibers, citric acid, and branched polyethylenimine. The study aimed to minimize any potential safety risk of these components and to obtain an eco-safe CNS. Among the three CNS constituents, branched polyethylenimine resulted in the most toxic agent. Indeed, it affected the physiology and fertilization competence of male and female gametes as well as embryo development in both sea urchin species. These results are consistent with those previously reported for CNS leachate. Moreover, the characterisation of CNS leachate confirmed the presence of detectable branched polyethylenimine in the conditioned seawater even though in a very limited amount. Altogether, these data indicate that the presence of branched polyethylenimine is a cause-effect associated with a significant risk in CNS formulations due to its leaching upon contact with seawater. Nevertheless, the suggested safety protocol consisting of consecutive leaching treatments and conditioning of CNS in seawater can successfully ameliorate the CNS ecotoxicity while maintaining the efficacy of its sorbent properties supporting potential environmental applications.

Community Structure and Water Quality Assessment of Benthic Macroinvertebrates in Hongze Lake.

This study investigated the species, density, biomass and physicochemical factors of benthic macroinvertebrates in Hongze Lake from 2016 to 2020. Redundancy analysis (RDA) was used to analyze the relationship between physicochemical parameters and the community structure of macroinvertebrates. Macroinvertebrate-based indices were used to evaluate the water quality conditions in Hongze Lake. The results showed that a total of 50 benthic species (10 annelids, 21 arthropods and 19 mollusks) were collected. The community structure of benthic macroinvertebrates varied in time and space. The dominant species were Limnodrilus hoffmeisteri (L.hoffmeisteri), Corbicula fluminea (C.fluminea), Nephtys oligobranchia (N.oligobranchia). In 2016, arthropods such as Grandidierella sp. were the dominant species of benthos in Hongze Lake while annelids and mollusks dominated from 2017 to 2020, such as L.hoffmeisteri, N.oligobranchia, C.fluminea. The benthic fauna of Chengzi Lake and Lihewa District were relatively abundant and showed slight variation, while the benthic macroinvertebrates of the Crossing the water area were few and varied greatly. RDA showed that changes in benthic macroinvertebrate structure were significantly correlated with dissolved oxygen (DO), Pondus Hydrogenii (pH) and transparency (SD). The Shannon Wiener, Pielou, and Margalef indices indicate that Hongze Lake is currently in a moderately polluted state. Future studies should focus on the combined effects of various physicochemical indicators and other environmental factors on benthic communities.

Development and Evaluation of a Quality Assessment Tool for Laparoscopic Sleeve Gastrectomy Videos: A Review and Comparison of Academic and Online Video Resources.

BACKGROUND: Video recording of surgical procedures is increasing in popularity. They are presented in various platforms, many of which are not peer-reviewed. Laparoscopic sleeve gastrectomy (LSG) videos are widely available; however, there is limited evidence supporting the use of reporting guidelines when uploading LSG videos to create a valuable educational video. We aimed to determine the variations and establish the quality of published LSG videos, in both peer-reviewed literature and on YouTube, using a newly designed checklist to improve the quality and enhance the transparency of video reporting. METHODS: A quality assessment tool was designed by using existing research and society guidelines, such as the Bariatric Metabolic Surgery Standardization (BMSS). A systematic review using PRISMA guidelines was performed on MEDLINE and EMBASE databases to identify video case reports (academic videos) and a similar search was performed on the commercial YouTube platform (commercial videos) simultaneously. All videos displaying LSG were reviewed and scored using the quality assessment tool. Academic and commercial videos were subsequently compared and an evidence-based checklist was created. RESULTS: A total of 93 LSG recordings including 26 academic and 67 commercial videos were reviewed. Mean score of the checklist was 5/11 and 4/11 for videos published in articles and YouTube, respectively. Academic videos had higher rates of describing instruments used, such as orogastric tube (P < 0.001) and stapler information (P = 0.04). Fifty-four percent of academic videos described short-term patient outcomes, while not reported in commercial videos (P < 0.001). Sleeve resection status was not universally reported. CONCLUSIONS: Videos published in the academic literature are describing steps in greater detail with more emphasis on specific technical elements and patient outcomes and thus have a higher educational value. A new quality assessment tool has been proposed for video reporting guidelines to improve the reliability and value of published video research.

Patient-derived PixelPrint phantoms for evaluating clinical imaging performance of a deep learning CT reconstruction algorithm.

Objective Deep learning reconstruction (DLR) algorithms exhibit object-dependent resolution and noise performance. Thus, traditional geometric CT phantoms cannot fully capture the clinical imaging performance of DLR. This study uses a patient-derived 3D-printed PixelPrint lung phantom to evaluate a commercial DLR algorithm across a wide range of radiation dose levels. Method The lung phantom used in this study is based on a patient chest CT scan containing ground glass opacities and was fabricated using PixelPrint 3D-printing technology. The phantom was placed inside two different size extension rings to mimic a small- and medium-sized patient and was scanned on a conventional CT scanner at exposures between 0.5 and 20 mGy. Each scan was reconstructed using filtered back projection (FBP), iterative reconstruction, and DLR at five levels of denoising. Image noise, contrast to noise ratio (CNR), root mean squared error (RMSE), structural similarity index (SSIM), and multi-scale SSIM (MS SSIM) were calculated for each image. Results DLR demonstrated superior performance compared to FBP and iterative reconstruction for all measured metrics in both phantom sizes, with better performance for more aggressive denoising levels. DLR was estimated to reduce dose by 25-83% in the small phantom and by 50-83% in the medium phantom without decreasing image quality for any of the metrics measured in this study. These dose reduction estimates are more conservative compared to the estimates obtained when only considering noise and CNR. Conclusion DLR has the capability of producing diagnostic image quality at up to 83% lower radiation dose, which can improve the clinical utility and viability of lower dose CT scans. Furthermore, the PixelPrint phantom used in this study offers an improved testing environment with more realistic tissue structures compared to traditional CT phantoms, allowing for structure-based image quality evaluation beyond noise and contrast-based assessments.

Evaluation of imprecision in the different detection methods of Zn based on 5 years of data from an external quality assessment program in China.

BACKGROUND: This study examines the imprecision of zinc (Zn) measurements across various clinical detection methods by analyzing the external quality assessment (EQA) data from 2018 to 2022. The findings of this study aim to offer recommendations for enhancing Zn measurements. METHODS: Participating laboratories were grouped into peer categories based on the detection methods. The robust mean and coefficient of variation (CV) of the samples were calculated following ISO 13528 guidelines. The evaluation criteria for optimal, desirable, and minimum allowable imprecision in Zn estimation are 2.50%, 5.05%, and 7.55%, respectively, based on biological variation. Furthermore, the study examined inter-lab CVs, inter-method bias, and the passing rate. The impact of sample concentration on CVs and the pass rate was also investigated. RESULTS: Over the past five years, 4283 laboratories participated in the EQA program, showing a high pass rate that improved as sample concentration increased. Differential pulse polarography (DPP) demonstrated stable and low CVs (0.61-1.86%). Although differential pulse stripping (DPS) was less stable than DPP, it still exhibited a low CV (0.71-3.10%). Graphite furnace atomic absorption spectrometry (GFAAS) and flame atomic absorption spectrometry (FAAS) performed similarly and displayed stable CVs (2.39-4.42%) within the acceptable range of desirable imprecision (5.05%). However, the CVs for ICP-MS were unacceptable in three out of the five years (5.28-6.20%). In 2022, the number of participating laboratories for DDP, DPS, GFAAS, FAAS and ICP-MS is 131, 35, 35, 820 and 72, respectively. CONCLUSION: This study provides reliable insights into the imprecision of Zn measurements in clinical laboratories. The findings indicate that additional efforts are required to reduce the imprecision of ICP-MS in Zn measurements.

Hybrid WT-CNN-GRU-based model for the estimation of reservoir water quality variables considering spatio-temporal features.

Water quality indicators (WQIs), such as chlorophyll-a (Chl-a) and dissolved oxygen (DO), are crucial for understanding and assessing the health of aquatic ecosystems. Precise prediction of these indicators is fundamental for the efficient administration of rivers, lakes, and reservoirs. This research utilized two unique DL algorithms-namely, convolutional neural network (CNNs) and gated recurrent units (GRUs)-alongside their amalgamation, CNN-GRU, to precisely gauge the concentration of these indicators within a reservoir. Moreover, to optimize the outcomes of the developed hybrid model, we considered the impact of a decomposition technique, specifically the wavelet transform (WT). In addition to these efforts, we created two distinct machine learning (ML) algorithms-namely, random forest (RF) and support vector regression (SVR)-to demonstrate the superior performance of deep learning algorithms over individual ML ones. We initially gathered WQIs from diverse locations and varying depths within the reservoir using an AAQ-RINKO device in the study area to achieve this. It is important to highlight that, despite utilizing diverse data-driven models in water quality estimation, a significant gap persists in the existing literature regarding implementing a comprehensive hybrid algorithm. This algorithm integrates the wavelet transform, convolutional neural network (CNN), and gated recurrent unit (GRU) methodologies to estimate WQIs accurately within a spatiotemporal framework. Subsequently, the effectiveness of the models that were developed was assessed utilizing various statistical metrics, encompassing the correlation coefficient (r), root mean square error (RMSE), mean absolute error (MAE), and Nash-Sutcliffe efficiency (NSE) throughout both the training and testing phases. The findings demonstrated that the WT-CNN-GRU model exhibited better performance in comparison with the other algorithms by 13% (SVR), 13% (RF), 9% (CNN), and 8% (GRU) when R-squared and DO were considered as evaluation indices and WQIs, respectively.

Performance of direct oral anticoagulant (DOAC) testing by hemostasis laboratories: The Australasian/Asia-Pacific experience.

INTRODUCTION: Direct oral anticoagulants (DOACs) reflect anticoagulation agents given to treat or prevent thrombosis, having largely replaced vitamin K antagonists (VKAs) such as warfarin. DOACs are given in fixed daily doses and generally do not need monitoring. However, there may be a variety of reasons that justify measurement of plasma DOAC levels in individual patients. METHODS: We report updated findings for DOAC testing in our geographic region, using recent data from the RCPAQAP, an international external quality assessment (EQA) program, currently with some 40-60 participants in each of the different DOAC (rivaroxaban, apixaban, dabigatran) modules, to assess laboratory performance in this area. Data has been assessed for the past 5 years (2019-2023 inclusive), with 20 samples each per DOAC. RESULTS: Data shows a limited repertoire of assays in use, and mostly consistency in reported numerical values when assessing proficiency samples. Available assays mostly comprised reagents from four manufacturing suppliers. There was good consistency across what participants identified as 'DOAC detected', but some variability when participants attempted to grade DOAC levels as low vs moderate vs high. Inter-laboratory/method coefficient of variation (CVs) were generally <15% for each DOAC, when present at >100 ng/mL. CONCLUSION: We hope our findings, reflecting on mostly consistent reporting of DOAC levels and interpretation provides reassurance for clinicians requesting these measurements, and helps support their implementation in regions where there is a paucity of test availability.

Spatial-temporal characteristics analysis and ecological environment quality evaluation of forest health care bases in Yunnan, Guizhou and Sichuan provinces.

As the forest health care in China is still in the early stage of development, the construction standards of forest health care base are not unified yet, resulting in large differences in the evaluation criterion for the ecological environment of forest health care bases. So, it is urgent to develop a new forest health care ecological environment quality assessment method. Yunnan, Guizhou and Sichuan provinces of China were selected as the study area, the previous 6 batches of 165 national forest health care pilot construction bases were selected as the main data source. This study explored the spatial and temporal distribution characteristics of forest health care bases in the study area using standard deviation ellipses, kernel density estimation method and cold and hot spot analysis. Furthermore, this study evaluated the ecological environment quality of the forest health care bases with a new ecological environment quality evaluation index model, which assembled Fraction Vegetation Coverage (FVC), Wetness (WET), Evapotranspiration (ET), Land Surface Temperature (LST) and Normalized Difference Bare Soil Index (NDBSI). The results are as follows: (1) the forest health bases in the study area are mainly located by the east of the Hu Line with a northeast-southwest distribution direction characteristics, and gradually expanded into a shape of "high in the east and low in the west, multi-point development". (2) the area with ecological environment quality in excellent, good and medium grade accounts for about 87.73 % in the study area, indicating that most of the study area is suitable for the construction of forest health care base. These results can provide a practical guidance for the further rational layout and balanced development of forest health care bases in the study area.