Quality Database Research Articles

Biologics Used for Psoriasis: A Drug Utilization Study Based on Two Nationwide Danish Data Sources.

Biological treatment has been a game changer in the management of moderate-to-severe psoriasis. In Denmark, biological treatment for psoriasis is registered in two data sources. We aimed to describe the utilization of biologics for psoriasis in Denmark using data from both data sources separately. We used data from two different nationwide Danish data sources: The healthcare registries and the clinical quality database, Dermbio. Utilization patterns were described by three different parameters: (1) distribution of drugs used in the first treatment episodes, (2) treatment cascade on a population level, and (3) drug survival using Kaplan Meier (KM) analysis and the proportion of patients covered (PPC) method. From January 1, 2011, to December 31, 2018, we found 1878 users of biologics in the healthcare registries and 2264 in Dermbio. Adalimumab, ustekinumab, and secukinumab were the most common first-choice treatments throughout the study period. According to the healthcare registries, it was most common to have more than one treatment episode with the same drug. In Dermbio, most were registered to have only one observable treatment episode overall in the study period. Ustekinumab showed the longest drug survival in both databases. Drug survival was longer for all biologics in Dermbio than in the healthcare registries. Adalimumab, ustekinumab, and secukinumab were the most common first-choice treatments in Denmark. Overall, ustekinumab showed the longest drug survival. We observed important differences in treatment cascades and drug survival between Dermbio and the healthcare registries, which should be considered when using these data sources to perform drug utilization studies on biologics.

Insurance and Structural Access Quality and Effects on AAA Mortality: A National Healthcare Quality and Disparities Report Analysis.

The National Health care Quality and Disparities Report (NHDQR) presents trends for measures related to access to care, affordable care, care coordination, effective treatment, healthy living, patient safety, and person-centered care. This study aims to determine the significance of insurance quality and access to care on AAA repair outcomes. Data was obtained through the Agency for Health care Research and Quality database from 2016-2020. AAA repair mortality rates per 1000 persons, insurance quality, and structural access were compared between the 31 reportable U.S. states in which data was analyzed using linear regression models and ANOVA. Insurance quality and structural access groups were categorized as weak, average, and strong, based on NHDQR Reports measures. No association was found between access to care and AAA mortality at specific time points (2016 and 2020; P-value = .90 and .29 respectively) and when comparing states that showed improvement from 2016 to 2020 (weak categorization to strong; P value = .27). An association was found between private insurance quality and AAA repair mortality at baseline (2016; P-value = .022) and in those that showed improvement or worsening in private insurance quality over the study period (P-value = .042). Our findings suggest that there is no association between structural access quality and AAA mortality although an association exists between AAA mortality and private insurance quality.

Characteristics and outcomes of emergency department patients across health care systems: an international multicenter cohort study

BackgroundA wide variation of emergency medical system configurations across countries has limited the value of comparison of quality and performance measures in the past. Furthermore, lack of quantitative data on EDs prevents definition of the problems and possibilities for data driven improvement of quality of care. Therefore, the objective is to describe and compare Emergency Department (ED) populations and characteristics, and their outcomes in the Netherlands, Denmark and Australia, using a recently developed template for uniform reporting of standardized measuring and describing of care provided in the ED (structure, staffing and governance, population, process times and outcomes).MethodsThis international multicenter cohort included all consecutive ED visits from National Quality Registries or Databases from participating sites from three countries. Patient and ED characteristics (using the template for uniform reporting) and relevant clinical outcomes were described and compared per country.ResultsWe included 212,515 ED visits in the Netherlands, 408,673 in Denmark and 556,652 in Australia. Patient characteristics differed markedly, with Australian ED patients being younger, less often triaged as “immediate”, and less often triaged with the high-risk chief complaints “feeling unwell” compared to Danish and Dutch patients. ED characteristics mainly differed with respect to the mean annual census per ED (Netherlands 26,738 (SD 2630), Denmark 36,675 (SD 12974), Australia 50,712 (4884)), median (IQR) lengths of stay of patients discharged home (Netherlands 2.1 (1.4–3.1); Denmark 2.8 (1.7–5.0); Australia 3.3 (2.0–5.0) hrs) and proportion of hospitalizations (ranging from 30.6 to 39.8%).In-hospital mortality was 4.0% in Australia, higher compared to the Netherlands and Denmark (both 1.6%). Not all indicators of the framework were available in all registries.ConclusionsPatient and ED characteristics and outcomes varied largely across countries. Meaningful interpretation of outcome differences across countries could be improved if quality registries would more consistently register the measures of the recently developed template for uniform reporting.

EstuarySAT Database Development of Harmonized Remote Sensing and Water Quality Data for Tidal and Estuarine Systems.

Researchers and environmental managers need big datasets spanning long time periods to accurately assess current and historical water quality conditions in fresh and estuarine waters. Using remote sensing data, we can survey many water bodies simultaneously and evaluate water quality conditions with greater frequency. The combination of existing and historical water quality data with remote sensing imagery into a unified database allows researchers to improve remote sensing algorithms and improves understanding of mechanisms causing blooms. We report on the development of a water quality database "EstuarySAT" which combines data from the Sentinel-2 multi-spectral instrument (MSI) remote sensing platform and water quality data throughout the coastal USA. EstuarySAT builds upon an existing database and set of methods developed by the creators of AquaSat, whose region of interest is primarily larger freshwater lakes in the USA. Following the same basic methods, EstuarySAT utilizes open-source tools: R v. 3.24+ (statistical software), Python (dynamic programming environment), and Google Earth Engine (GEE) to develop a combined water quality data and remote sensing imagery database (EstuarySAT) for smaller coastal estuarine and freshwater tidal riverine systems. EstuarySAT fills a data gap that exists between freshwater and estuarine water bodies. We are able to evaluate smaller systems due to the higher spatial resolution of Sentinel-2 (10 m pixel image resolution) vs. the Landsat platform used by AquaSat (30 m pixel resolution). Sentinel-2 also has a more frequent revisit (overpass) schedule of every 5 to 10 days vs. Landsat 7 which is every 17 days. EstuarySAT incorporates publicly available water quality data from 23 individual water quality data sources spanning 1984-2021 and spatially matches them with Sentinel-2 imagery from 2015-2021. EstuarySAT currently contains 299,851 matched observations distributed across the coastal USA. EstuarySAT's primary focus is on collecting chlorophyll data; however, it also contains other ancillary water quality data, including temperature, salinity, pH, dissolved oxygen, dissolved organic carbon, and turbidity (where available). As compared to other ocean color databases used for developing predictive chlorophyll algorithms, this coastal database contains spectral profiles more typical of CDOM-dominated systems. This database can assist researchers and managers in evaluating algal bloom causes and predicting the occurrence of future blooms.

Higher rates of recurrence and worse quality of life in obese patients undergoing inguinal hernia repair.

Prior investigations regarding the effect of obesity on inguinal hernia repair have been mixed. The aim of our study was to retrospectively compare perioperative outcomes, recurrence rate, and quality of life between obese and non-obese patients undergoing inguinal hernia repair. Patients who underwent inguinal hernia repair by any approach at a single institution were identified from a prospectively maintained quality database. Patients with a body mass index (BMI) greater than or equal to 30kg/m2 were considered obese. Quality of life was measured with the Surgical Outcomes Measurement System (SOMS) and Carolinas Comfort Scale (CSS) surveys. Differences between obese and non-obese patients were assessed using independent samples t-tests, Wilcoxon rank-sum, and chi-square tests. Between 2010 and 2021, a total of 5575 patients underwent inguinal hernia repair. Fifteen percent of patients were identified as obese (835 patients, mean BMI 33.2 ± 3.3kg/m2). A significantly higher percentage of obese patients were diabetic, and operative time and estimated blood loss were higher in the obese group (all p < 0.001). Rates of hernia recurrence in obese patients was significantly more likely than in non-obese patients (4.2% vs 2.0%, p < 0.001). Up to 2 years postoperatively, a greater percentage of obese patients reported worse quality of life on the SOMS and more bothersome symptoms on the CCS. Inguinal hernia repair in obese patients is a more technically challenging operation. Long-term follow-up revealed a greater risk of hernia recurrence and worse quality of life up to 2 years postoperatively in this patient population.

Exploring global remote sensing products for water quality assessment: Lake Nicaragua case study

This study explores the applicability of 13 globally-derived Chlorophyll-a (CHL) products from optical satellite remote sensing to support local water quality management in Lake Nicaragua. The temporal and spatial consistency between the products was analyzed, as well as their agreement with in-situ data collected from 2011 to 2016. The Climate Change Initiative (CCI) CHL product was identified as the most stable and reliable, suggesting its suitability for monitoring Lake Nicaragua. However, the correlation of this product with in-situ measurements was weak, attributed to the sparse and inconsistent nature of the available in-situ water quality data. The hotspots analysis identified critical areas around urban and agricultural zones with high CHL concentrations, providing valuable insights for targeted management interventions. This study emphasizes the need for improved global to local remote sensing strategies, including the selection of the appropriate algorithms for the region, continuous calibration and validation with in-situ data, and the development of a robust, publicly accessible local water quality database that includes both in-situ and remote sensing data, to support effective monitoring for local water management.

Urban mobility and air pollution at the neighbourhood scale in the Megacity of São Paulo, Brazil

Developing countries’ megacities, characterised by dense populations and socioeconomic disparities, often face high levels of pollutants, mainly from vehicle emissions. Poor air quality can lead to a range of public health problems which in turn, need to be addressed by public policies. The main goal of this article is to examine the impact of public policies and the influence of transport modes on air pollution of three districts from the Metropolitan Region of São Paulo, in Brazil: Pinheiros, Parque Dom Pedro II and Taboão da Serra. The method was held through a comparative analysis, which in turn, took into account urban indicators, urban mobility data and pollutants levels (CO and NOx). These data were collected from the 2007 and 2017 São Paulo Metrô Origin and Destination Surveys and the Air Quality Database of the Environmental Company of the State of São Paulo. As key findings, the three study areas’ pollutant concentrations presented a downward trend from 2007 to 2017 as the same time there was an increase in the public transport and non-motorized transport modes. However, it is important to highlight the confluence of the state and federal public policies occuring at the same period such as PRONCOVE, Rodoanel and the Yellow Subway Line. The identified socio-environmental disparities in the urban realm highlight the importance of localised analyses in order to reveal problems and opportunities to get a better response in terms of urban mobility and air quality. Thus, the perpetuation of constant policy’s updates and interdisciplinary collaboration is crucial.

Predictors of Delayed Clinical Benefit Following Surgical Treatment for Low Grade Spondylolisthesis.

Retrospective review of prospectively collected data. To investigate what factors predict delayed improvement after surgical treatment of low grade spondylolisthesis. Lumbar surgery leads to clinical improvement in the majority of patients with low grade spondylolisthesis. Most patients improve rapidly after surgery, but some patients demonstrate a delayed clinical course. The Quality and Outcomes Database (QOD) was queried for grade 1 spondylolisthesis patients who underwent surgery who had patient reported outcome measures (PROMs) collected at baseline, 3-, 6- and 12-months, including back and leg pain numeric rating scale (NRS), Oswestry Disability Index (ODI), and EuroQol-5D (EQ-5D). Patients were stratified as "Early responders" reaching MCID at 3 months and maintaining improvement through 12 months and "Delayed responders" not reaching MCID at 3 months but ultimately reaching MCID at 12 months. These two groups were compared with respect to factors which predicted delayed improvement. Of 608 patients enrolled, 436 (72%) met inclusion criteria for this study. Overall, 317 patients (72.7%) reached MCID for ODI at 12 months following surgery. Of these patients, 249 (78.5%) exhibited a rapid clinical improvement trajectory and had achieved ODI MCID threshold by the 3-month postop follow-up. 68 patients (21.4%) showed a delayed trajectory, and had not achieved ODI MCID threshold at 3 months, but did ultimately reach MCID at 12-month follow-up. Factors associated with delayed improvement included impaired preoperative ambulatory status, better baseline back and leg pain scores, and worse 3-month leg pain scores (P<0.01). The majority of patients undergoing surgery for low grade spondylolisthesis reach ODI MCID threshold rapidly, within the first three months after surgery. Factors associated with a delayed clinical course include impaired preoperative ambulation status, relatively better preoperative back and leg pain, and persistent leg pain at 3 months.

Cervical cancer incidence in Denmark: Disentangling determinants of time trend.

Cervical cancer is a preventable disease. Nevertheless, stagnation has been seen in incidence rates also in countries with well-functioning healthcare. On this basis, we investigated associations between control interventions and changes in cervical cancer incidence in Denmark from 2009 to 2022. Data on human papillomavirus (HPV)-vaccination were retrieved from Staten's Serum Institute; on screening recommendations from Danish Health Authority, on screening performance from Danish Quality Database for Cervical Screening; and on cervical cancer incidence from Nordcan and Danish Cancer Register. We reported coverage with HPV vaccination (1+ dose); coverage with cervical cell samples; number of women with primary HPV tests; proportion of non-normal cell samples without timely follow-up; number of conizations; and cervical cancer incidence rates. In 2022, all women aged ≤29 had been offered childhood HPV vaccination with coverage of 80%-90%. By 2020-2022, the cervical cancer incidence rate in women aged 20-29 was 3 per 100,000; at level of disease elimination. In 2017, women aged 70+ were offered a one-time HPV screening, and by 2020-2022, the old-age peak in cervical cancer incidence had largely disappeared. From 2009 to 2022, proportion of non-normal cell samples without timely follow-up decreased from 20% to 10%, and conventional cytology was largely replaced by SurePath liquid-based cytology; these factors could explain the steady decrease in cervical cancer incidence rate. Implementation of primary HPV screening in women aged 30-59 in 2021 was reflected in a, probably temporary, increase in the 2022 cervical cancer incidence rate. In conclusion, combined interventions with childhood HPV vaccination; one-time HPV screening of elderly women; and better management of screening broke previous stagnation in cervical cancer incidence rate.

Blind Quality Assessment of Dense 3D Point Clouds with Structure Guided Resampling

Objective quality assessment of three-dimensional (3D) point clouds is essential for the development of immersive multimedia systems in real-world applications. Despite the success of perceptual quality evaluation for 2D images and videos, blind/no-reference metrics are still scarce for 3D point clouds with large-scale irregularly distributed 3D points. Therefore, in this article, we propose an objective point cloud quality index with Structure Guided Resampling (SGR) to automatically evaluate the perceptually visual quality of dense 3D point clouds. The proposed SGR is a general-purpose blind quality assessment method without the assistance of any reference information. Specifically, considering that the human visual system is highly sensitive to structure information, we first exploit the unique normal vectors of point clouds to execute regional pre-processing that consists of keypoint resampling and local region construction. Then, we extract three groups of quality-related features, including (1) geometry density features, (2) color naturalness features, and (3) angular consistency features. Both the cognitive peculiarities of the human brain and naturalness regularity are involved in the designed quality-aware features that can capture the most vital aspects of distorted 3D point clouds. Extensive experiments on several publicly available subjective point cloud quality databases validate that our proposed SGR can compete with state-of-the-art full-reference, reduced-reference, and no-reference quality assessment algorithms.

Quality and recognizability estimation video encryption database

In literature about selective encryption of image and video content, image quality indices are usually used to gauge the degree of encryption. These methods have frequently been shown not to work well for the evaluation of encryption, mainly due to them being trained on predominantly high quality contents. The problem for creating a proper recognition index or visual encryption strength index is the lack of data to train on. In this paper we present the first database of encrypted video content, ranging from high quality to completely unrecognizable, together with human observer scores for quality and recognizability. We also provide a basic evaluation of visual quality indices on this database, directly and in different combination by fusion, to showcase that currently image and video quality indices are ill fit for the purpose of estimating video encryption strength/recognizably. This inability of quality indices to perform also showcases that this database fills the required blind spot of currently available data.

Dual-stream mutually adaptive quality assessment for authentic distortion image

To address semantic misperception caused by distortion and accurately simulate human perceptual processes, this study proposed a method that utilised dual-stream mutually adaptive feature mapping. To extract complementary features, a dual-stream unsupervised method was used during the training phase. One stream was responsible for the extraction of low-level and global features, whereas the other was dedicated to extracting high-level semantic and positional features. Following the freezing of feature extraction network weights, we proposed a structure that used standard deviation labels to predict the quality distribution. The experimental results obtained from 10 published image quality databases demonstrated the superiority of the proposed algorithm. The algorithm outperformed the majority of mainstream methods when evaluated on authentic distortion databases and exhibited competitive performance on synthetic distortion databases.

Geographic Characteristics and Meteorological Factors Dominate the Variation of Chlorophyll‐a in Lakes and Reservoirs With Higher TP Concentrations

AbstractNutrients such as phosphorus and nitrogen lead to extensive growth of harmful algae in lakes and reservoirs, which results in eutrophication. The driving mechanism of primary productivity change in lakes and reservoirs at a wide spatial and temporal scale remains largely unknown. We establish a water quality database using a stacking machine learning model, including monthly chlorophyll‐a (Chl‐a), total nitrogen (TN) and phosphorus (TP) concentrations in 255 lakes and 332 reservoirs from 1980 to 2018. We find an increase in the number of lakes and reservoirs at risk of algal blooms, with approximately 2.66% exhibiting Chl‐a concentrations exceeding 30 μg L−1 by 2018. Variations in Chl‐a concentrations were not entirely synchronized at the individual and regional levels with TN and TP concentrations, or their stoichiometric ratios, as estimated by a hierarchical linear model spanning 1980 to 2018. Further, we discovered unexpected effects of geographical features (i.e., latitude, longitude, and slope) and meteorological factors (i.e., air temperature) on Chl‐a concentrations in the lakes and reservoirs with higher TP concentrations (&gt;0.041 mg L−1 for lakes and &gt;0.027 mg L−1 for reservoirs), through the use of multiple regression trees and structural equation model analysis. Our findings underscore the importance of (a) implementing flexible nutrient pollution control approaches based on nutrient ecoregions that consider geographical variations, and (b) developing mitigation and adaptation strategies to address the uncertain risks posed by climate change in the prevention and control of eutrophication in lakes and reservoirs.

Outcomes of nonemergency cardiac surgery after overnight operative workload: A statewide experience

ObjectiveCardiac surgeons experience unpredictable overnight operative responsibilities, with variable rest before same-day, first-start scheduled cases. This study evaluated the frequency and associated impact of a surgeon's overnight operative workload on the outcomes of their same-day, first-start operations. MethodsA statewide cardiac surgery quality database was queried for adult cardiac surgical operations between July 1, 2011, and March 1, 2021. Nonemergency, first-start, Society of Thoracic Surgeons predicted risk of mortality operations were stratified by whether or not the surgeon performed an overnight operation that ended after midnight. A generalized mixed effect model was used to evaluate the effect of overnight operations on a Society of Thoracic Surgeons composite outcome (5 major morbidities or operative mortality) of the first-start operation. ResultsOf all first-start operations, 0.4% (239/56,272) had a preceding operation ending after midnight. The Society of Thoracic Surgeons predicted risk of morbidity and mortality was similar for first-start operations whether preceded by an overnight operation or not (overnight operation: 11.3%; no overnight operation: 11.7%, P = .42). Unadjusted rates of the primary outcome were not significantly different after an overnight operation (overnight operation: 13.4%; no overnight operation: 12.3%, P = .59). After adjustment, overnight operations did not significantly impact the risk of major morbidity or mortality for first-start operations (adjusted odds ratio, 1.1, P = .70). ConclusionsFirst-start cardiac operations performed after an overnight operation represent a small subset of all first-start Society of Thoracic Surgeons predicted risk operations. Overnight operations do not significantly influence the risk of major morbidity or mortality of first-start operations, which suggests that surgeons exercise proper judgment in determining appropriate workloads.

Spatial Distribution Patterns of Phytoplankton and Their Relationship with Environmental Factors in the Jinjiang River, China

Our study aims to investigate the water quality and distribution patterns of phytoplankton communities in the Jinjiang River Basin in Quanzhou, as well as their relationship with environmental factors. We integrated data from the national water quality databases of the two main tributaries of the West and East Jinjiang Rivers between 2020 and 2023, supplemented by field surveys. Redundancy analysis was used to explore the effect of environmental factors on phytoplankton communities. Our findings revealed that the West Jinjiang River experienced a significant influence from excessive fertilizer use in tea cultivation, leading to an increase in TN concentrations compared to the East Jinjiang River. The abundance of phytoplankton in the Jinjiang River Basin was 105 cells·L−1, with phytoplankton being dominated by Chlorophyta, Cyanphyta, and diatoms, accounting for an average of 50%, 20%, and 19% of the total phytoplankton abundance, respectively. Redundancy analysis indicated that temperature, pH, and nutrient concentrations were important factors influencing the phytoplankton communities. With increasing temperature and nutrients concentrations, the abundance of Chlorophyta and Dinophyta significantly increased. This study provides a solid foundation for the regular “health diagnosis” of crucial rivers and lakes in Quanzhou and supports the establishment of a health guarantee system for rivers and lakes.

Brazilian Atmospheric Inventories – BRAIN: a comprehensive database of air quality in Brazil

Abstract. Developing air quality management systems to control the impacts of air pollution requires reliable data. However, current initiatives do not provide datasets with large spatial and temporal resolutions for developing air pollution policies in Brazil. Here, we introduce the Brazilian Atmospheric Inventories (BRAIN), the first comprehensive database of air quality and its drivers in Brazil. BRAIN encompasses hourly datasets of meteorology, emissions, and air quality. The emissions dataset includes vehicular emissions derived from the Brazilian Vehicular Emissions Inventory Software (BRAVES), industrial emissions produced with local data from the Brazilian environmental agencies, biomass burning emissions from FINN – Fire INventory from the National Center for Atmospheric Research (NCAR), and biogenic emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN) (https://doi.org/10.57760/sciencedb.09858, Hoinaski et al., 2023a; https://doi.org/10.57760/sciencedb.09886, Hoinaski et al., 2023b). The meteorology dataset has been derived from the Weather Research and Forecasting Model (WRF) (https://doi.org/10.57760/sciencedb.09857, Hoinaski and Will, 2023a; https://doi.org/10.57760/sciencedb.09885, Hoinaski and Will, 2023c). The air quality dataset contains the surface concentration of 216 air pollutants produced from coupling meteorological and emissions datasets with the Community Multiscale Air Quality Modeling System (CMAQ) (https://doi.org/10.57760/sciencedb.09859, Hoinaski and Will, 2023b; https://doi.org/10.57760/sciencedb.09884, Hoinaski and Will, 2023d). We provide gridded data in two domains, one covering the Brazilian territory with 20×20 km spatial resolution and another covering southern Brazil with 4×4 km spatial resolution. This paper describes how the datasets were produced, their limitations, and their spatiotemporal features. To evaluate the quality of the database, we compare the air quality dataset with 244 air quality monitoring stations, providing the model's performance for each pollutant measured by the monitoring stations. We present a sample of the spatial variability of emissions, meteorology, and air quality in Brazil from 2019, revealing the hotspots of emissions and air pollution issues. By making BRAIN publicly available, we aim to provide the required data for developing air quality policies on municipal and state scales, especially for under-developed and data-scarce municipalities. We also envision that BRAIN has the potential to create new insights into and opportunities for air pollution research in Brazil.​​​​​​​

Development of Soil Quality Databases and Land Potential Assessment Using GIS: A Case Study of Lao Cai Province, Vietnam

The utilization of Geographic Information Systems (GIS), particularly the Mapinfo software, is indispensable in the establishment of a land quality and land potential database encompassing each land parcel within Lao Cai province. Through a multifaceted approach involving data collection techniques, field surveys, data analysis, and the creation of both spatial and attribute databases, the GIS application in Lao Cai province has successfully compiled a comprehensive dataset. This dataset encompasses a range of layers, including boundaries, administrative demarcations, land use statuses, survey points, soil types, slope characteristics, soil depth, irrigation patterns, climatic conditions, soil fertility data, and transportation and hydrological information. The amalgamation of this spatial data with attribute data yields a comprehensive repository featuring information on 405 units of agricultural land quality and potential, in addition to 65 aggregated non-agricultural land parcels. This combined dataset functions as the foundational land quality and potential database for Lao Cai province. Assessment outcomes for land quality and land potential throughout the entire province reveal that 51.42% of the land exhibits low quality, 35.06% demonstrates moderate quality, and 13.52% boasts high quality. In terms of land potential, 29.15% is categorized as having low potential, 44.88% as having moderate potential, and 25.97% as having high potential. Furthermore, the precise delineation of land quality and potential for each land parcel within the database effectively caters to the information retrieval needs of land administrators and stakeholders. This research also seeks to contribute to the standardization of land databases at both the provincial and national levels, thereby bolstering land management efforts within the context of globalization, development, and climate change adaptation.

Filling up the water quality database to assess the water quality levels and self-cleaning capacities

The one of water resource’s functions is the self-renewable capacity about quality, quantity and energy. To assess the level or fluctuat trend of water resource functions, a complete set of continuous and representative data is needed. The water quality monitoring of environment management is implementing continuous in Ho Chi Minh City. Because of many causes, the water quality data set is asynchronous by years and observation locations. It causes the many difficulties to researches, studies as the assessment of water’s self-cleaning capacity. With the support of two interpolations equations (the Highest order polynomial fitting Curve Function (HopCEF) and Multivariable Regression Correlative Function (MrCEF)) and GIS tool, the water quality and self-cleaning capacity distributions are zoned/mapped with the fully and continuously data set. The research of water quality and self-cleaning capacity is implemented with the filled quality data set period 2012 – 2022 for urban inner canal system in HCMC. Based on the assessment’s results and the mapped distribution of levels, the fluctuations the quality and self-cleaning capacity of inner canal system are made high visualization. And they are a valuable basis for planning and decision making on the solutions of management agencies in HCMC.

Youth mentoring: A new holistic intervention targeting the needs of young persons with acquired brain injury

Introduction: Holistic rehabilitation approaches addressing the numerous complex challenges in young persons with acquired brain injury are required. The purpose of this study was to describe and evaluate the holistic person-centered youth mentoring intervention program, which is based on occupational therapy. Methods: Prospectively collected data were extracted from a national clinical quality database ( n = 59). Proportions of young persons receiving different aspects of support and proportions rating the intervention as meaningful were calculated. One-year changes in occupation, work ability, and social interactions were calculated. Results: The young persons most frequently received support for energy management (75%) and structuring of everyday life (61%). Seventy-three percent rated the intervention as meaningful. One year post-inclusion, occupation and work ability had increased by 35% and 58%, respectively, and it had declined by 10% and 26%, respectively. The 1-year increase and decrease in social interactions were less clear (15% and 25%, respectively). One-year changes did not differ between those who entered the program early or late after injury indicating the potential beneficial effect of the program. Conclusion: The findings could indicate that the program has a unique value in supporting young persons with acquired brain injury to create a meaningful everyday life through occupation, work ability, and social interaction.

Does type of bone graft matter? A retrospective review of the use of biological bone grafts in patients undergoing elective 1-3 level spinal interbody fusion.

There is a lack of strong evidence for use of expensive bone substitutes. This study compares perioperative data and patient reported quality-of-life outcomes across the varied types of bone graft extenders. The study analyzes the existing Quality and Outcomes Database and evaluates patient reported outcomes for 1-3 level lumbar fusion procedures comparing across different types of biologics bone graft. We retrospectively analyzed a prospectively collected data registry. Bone graft implant data were collected and grouped into the following categories: (1) Autograft with basic allograft (2) Enhanced, synthetic, or cellular allograft (3) Use of BMP. Preoperative and 1year patient reported outcomes and perioperative data from the prospective collected registry were analyzed. There were 384 patients included in this study. There were 168 (43.8%) patients in group 1, 133 (34.6%) patients in group 2, and 83 (21.6%) in group 3. There were no group differences in baseline or 1year back pain, leg pain, ODI, or EQ-5D. The GLM Repeated Measures results indicate a significant difference within each of the three groups between the preoperative and postoperative measures for back pain, leg pain, ODI, and EQ-5D. The change over time was not significantly different between the groups. Bone graft extenders are a significant contributor to the cost of lumbar fusion. This study demonstrates no difference in preoperative, and 1year patient reported outcomes between the three groups. There was no significant difference in rate of reoperations across the three groups.