Quality Index Research Articles

Dynamic Changes and Correlation Analysis of Pumpkin Quality and Physiological Indicators during Postharvest Storage

Pumpkin (Cucurbita moschata Duch.) is a versatile crop with strong stress resistance and promising growth potential. Widely cultivated in various regions of China, it ranks among the top crops globally in terms of both planting area and consumption. Known for its pleasant taste and high nutritional value, pumpkin pulp is rich in essential trace elements for the human body. Even after harvest, pumpkin fruit remains metabolically active, requiring its own nutrients to complete the postripening process. Failure to provide proper postharvest storage conditions can lead to excessive water loss and rapid nutrient depletion, resulting in rough, shriveled, and even rotten peel, ultimately diminishing the economic value of the pumpkin. This study aimed to investigate the changes in pumpkin quality and physiological indicators during storage to provide insights to determine optimal consumption and processing periods of pumpkins. The pumpkins were stored at a temperature of 16 ± 2 °C and 60% to 80% humidity during the experiment. The dynamic changes in fruit quality, hardness, respiration rate, malondialdehyde content, level of antioxidant enzymes, and other indicators of two pumpkin cultivars (BM5 and JQ) were assessed during storage, and the correlation among these indicators was evaluated. The results indicated a decrease in the vitamin C content and pulp hardness, whereas the superoxide dismutase and catalase contents initially increased and then decreased, and malondialdehyde and weight loss rates increased over the storage period. The weight loss rate exhibited significant positive and negative correlations with the malondialdehyde content (P < 0.01) of the two cultivars, whereas the vitamin C content showed a significant positive correlation with pulp hardness (P < 0.01). The findings indicate that optimal fruit quality was maintained within 40 days of postharvest storage. This study provides valuable insights into the selection of storable pumpkin cultivars.

Quality indicators in enteral nutritional therapy in critically ill patients: Results at a Public Hospital in Northeastern Brazil

Quality indicators in enteral nutritional therapy in critically ill patients: Results at a Public Hospital in Northeastern Brazil

Quality indicators in enteral nutrition in chronic patients at nutritional risk: A 3-month follow-up study at a transition hospital in Brazil

Quality indicators in enteral nutrition in chronic patients at nutritional risk: A 3-month follow-up study at a transition hospital in Brazil

Enhancing readmission prediction models by integrating insights from home healthcare notes: Retrospective cohort study

BackgroundHospital readmission is an important indicator of inpatient care quality and a significant driver of increasing medical costs. Therefore, it is important to explore the effects of postdischarge information, particularly from home healthcare notes, on enhancing readmission prediction models. Despite the use of natural language processing (NLP) and machine learning in prediction model development, current studies often overlook insights from home healthcare notes. ObjectiveThis study aimed to develop prediction models for 30-day readmissions using home healthcare notes and structured data. In addition, it explored the development of 14- and 180-day prediction models using variables in the 30-day model. DesignA retrospective observational cohort study. Setting(s)This study was conducted at Ajou University School of Medicine in South Korea. ParticipantsData from electronic health records, encompassing demographic characteristics of 1819 participants, along with information on conditions, drug, and home healthcare, were utilized. MethodsTwo distinct models were developed for each prediction window (30-, 14-, 180-day): the traditional model, which utilized structured variables alone, and the common data model (CDM)-NLP model, which incorporated structured and topic variables extracted from home healthcare notes. BERTopic facilitated topic generation and risk probability, representing the likelihood of documents being assigned to specific topics. Feature selection involved experimenting with various algorithms. The best-performing algorithm, determined using the area under the receiver operating characteristic curve (AUROC), was used for model development. Model performance was assessed using various learning metrics including AUROC. ResultsAmong 1819 patients, 251 (13.80 %) experienced 30-day readmission. The least absolute shrinkage and selection operator was used for feature extraction and model development. The 15 structured features were used in the traditional model. Moreover, five additional topic variables from the home healthcare notes were applied in the CDM-NLP model. The AUROC of the traditional model was 0.739 (95 % CI: 0.672–0.807). The AUROC of the CDM-NLP model was high at 0.824 (95 % CI: 0.768–0.880), which indicated an outstanding performance. The topics in the CDM-NLP model included emotional distress, daily living functions, nutrition, postoperative status, and cardiorespiratory issues. In extended prediction model development for 14- and 180-day readmissions, the CDM-NLP consistently outperformed the traditional model. ConclusionsThis study developed effective prediction models using both structured and unstructured data, thereby emphasizing the significance of postdischarge information from home healthcare notes in readmission prediction.

The Main Soil Constraint Factors and Its Improvement Methods Based on Sustainable Development of Agricultural Economy in Tobacco Planting Area in Chenzhou City, Hunan Province of China

Farmland soil is the basis for agricultural production and a fundamental resource. It is beneficial to the sustainable development of agricultural economy to adopt different conservation measures for different soil types which exist various obstacles. In order to provide scientific guidance for accurate soil improvement for the fields under tobacco-rice rotation in Chenzhou City, Hunan Province of China, soil obstacle combination types were analyzed by sampling and determined based on the data of pH, organic matter (OM), available nitrogen (AN), phosphorous (AP) and potassium (AK) in the plough horizons (0–20 cm) of 1008 typical fields, and according soil obstacle combination types, different measures were adopted to improve the soil fertility and tobacco yield and quality. The results showed that based on the five soil quality indices, 61.31%–81.85% of the fields were in the high levels, 26.79%–33.83% of the fields were in the suitable levels, while only 9.66% on average the fields were in the low levels. In total 89 soil obstacle combination types were found in the fields, among which, 22 types (75.3%) with the field numbers were more than 1% of the total fields. The main ones were the types of Reducing pH, OM and NPK (17.76%), followed by the types of Reducing pH, OM and NP (8.43%), Reducing OM and NPK (5.26%), reducing pH, OM and PK (4.66%), and reducing pH, OM and N (4.07%). In conclusion, the comprehensive countermeasures (organic fertilizer and straw mulching) should be considered and taken for the accurate improvement of soil quality according to the actual situation in soil obstacle combinations, and reducing pH, OM and NPK should be considered first for most fields under tobacco-rice rotation.

SUBJECTIVE SLEEP PARAMETERS: A MARKER TO PTSD SYMPTOMS EVOLUTION? A 4-YEAR LONGITUGINAL STUDY

Disturbed sleep is a common feature after exposure to a traumatic event, especially when PTSD develops. However, although there is evidence suggesting a potential role of sleep disturbance in the progression of PTSD symptoms, the interrelationship between sleep and PTSD symptoms has yet to be determined. In order to address this knowledge gap, we have investigated the influence of initial sleep characteristics on the evolution of post-traumatic stress disorder (PTSD) symptoms over 4 years of follow-up among individuals exposed to the Brazilian Kiss nightclub fire. Participants were individuals exposed to the 2013 Kiss nightclub fire in Brazil. Sleep characteristics and PTSD symptoms were measured within the 4 years following the fire by self-report questionnaires, such as The Pittsburgh Sleep Quality Index (PSQI), and PTSD Checklist - Civilian version (PCL-C). Generalized estimating equations (GEE) models were used to examine the longitudinal associations (by estimating the relative effects of initial sleep problems on PTSD symptoms after adjusting for covariates). Comprehensive information concerning socio-demographic factors, health status, and sleep complaints were obtained. A total of 232 individuals were included. In GEE models, no significant interactions were observed between sociodemographic variables and PTSD symptoms in the follow-up period, however, associations were found between PTSD at baseline and the following factors: the female gender, the victim individuals and the existence of prior psychiatric disease. Initial subjective sleep parameters were strongly associated with PTSD symptoms over 4 years, mainly the presence of disturbed dreams (p=0.012), increased sleep latency (p=0.029), and reduced sleep duration (p=0.012). Sleep complaints and PTSD symptoms were common among individuals after the disaster. The current study has found that the presence of sleep complaints, especially increased sleep latency, presence of disturbed dreams and short sleep duration, in the initial presentation after the fire was consistently associated with the perpetration of PTSD symptoms in the next 4 years of follow-up. These findings suggest that interventions addressing these sleep complaints have the potential to reduce the persistence and/or severity of PTSD symptoms.

The Classification of Land Quality Index Using Minimum Data Set – Study in a Tropical Agroecosystem of East Java

The Classification of Land Quality Index Using Minimum Data Set – Study in a Tropical Agroecosystem of East Java

Patient needs in women of childbearing age with psoriasis: retrospective analysis from the German PsoBest registry.

Women of childbearing age (WoCBA) with psoriasis face additional burden related to contraindications of systemic treatments during pregnancy/lactation and to the physical and psychosocial impact of psoriasis on their intimate/sexual relationships. Within a people-centered health care model, this study aimed to identify specific patient needs and their correlates in WoCBA (18-45 years), in comparison to same-age men and women above 45 years. Baseline data from the German PsoBest registry, including patients with moderate/severe plaque-type psoriasis with the indication for systemic therapy, were retrospectively analyzed. Psoriasis severity was assessed with the Psoriasis Area and Severity Index and patient-reported outcomes included EuroQoL Visual Analogue Scale, Dermatology Life Quality Index (DLQI), and Patient Needs Questionnaire. The participants were 2308 WoCBA, 3634 men between 18 and 45 years of age, and 3401 women older than 45 years. In comparison to both control groups, WoCBA reported more DLQI impairments and higher needs to reduce social impairments (eg, "to be able to lead a normal working life"; "to be less burdened in your partnership"; "to be able to have a normal sex life"). These patient needs were associated with having psoriasis arthritis, previous systemic therapy, worse general health, and more DLQI impairments. Retrospective analysis of an established dataset limited the examination of specific developmental, sexual, and reproductive variables. The specific needs of WoCBA with psoriasis were particularly related to the work context/financial stability and intimate relationships, which are crucial aspects in family planning. These results claim for a sex/age-sensitive approach in the psoriasis health care, by considering these needs as qualifiers in the clinical decision for systemic treatment.

Effects of Conventional versus Virtual Reality-simulated Treadmill Exercise on Fatigue, Cognitive Function, and Participant Satisfaction in Post-COVID-19 Subjects. A Randomized Trial

Background/ObjectivePost-COVID-19 subjects typically experience symptoms of fatigue, cognitive impairment, and sleep difficulty, which can be relieved by conventional aerobic exercise. Virtual Reality (VR) technology to support conventional exercise has recently gained much attention. Therefore, this study aimed to assess the effects of traditional treadmill exercise compared to virtual reality-simulated treadmill exercise on fatigue, cognitive function, sleep quality, and participant satisfaction with the exercise program in post-COVID-19 subjects. MethodsThis single-centered, randomized, parallel-group intervention study was conducted between December 2021 and March 2022. Sixteen of twenty post-COVID-19 subjects completed this study (n1=8, n2=8). Inclusion criteria were persistent dyspnea/fatigue, mild cognitive problems, and age 30–60 years. Exclusion criteria were previous severe COVID-19 infection and ICU admission, concomitant respiratory or cardiovascular disease, and musculoskeletal or neurological disease. Eligible subjects were assigned randomly to two groups: a non-VR group that received traditional treadmill aerobic exercise only and a VR group that received treadmill exercise with non-immersive VR. Both groups received moderate-intensity exercise on a treadmill at [50–60% (peak HR－resting HR) + resting HR] for 30–45 min, three times per week, and for four weeks. The outcome measures were the Chalder Fatigue Scale, Montreal Cognitive Assessment (MoCA) questionnaire, Pittsburgh Sleep Quality Index (PSQI), and participant satisfaction with the exercise program rated on a 5-point Likert scale. ResultsBoth groups showed significant improvements in the Chalder Fatigue Scale, the MoCA questionnaire, and the PSQI scores after training compared to baseline (p<0.05), without significant differences between them (p>0.05). However, participant satisfaction with the exercise program was significantly higher in the VR group than in the non-VR group (p=0.037). ConclusionA moderate-intensity 4-week treadmill exercise program with and without non-immersive VR may improve fatigue, cognitive function, and sleep quality to the same extent in COVID-19 survivors. However, participant satisfaction with the exercise program could be greater after conventional treadmill training assisted by non-immersive VR than after conventional treadmill training alone in this cohort. Trial registrationPan African Clinical Trials Registry, PACTR202311561948428, retrospectively registered

Real-World Data on Brodalumab Treatment in Patients with Moderate-to-Severe Plaque Psoriasis: An Observational Study from the Czech Republic BIOREP Registry.

The aim of this observational, multicenter study was to assess the real-world use of brodalumab for the treatment of moderate-to-severe plaque psoriasis in patients in the Czech Republic, using data from the BIOREP registry. The study included 273 patients aged≥18years with moderate-to-severe psoriasis who received brodalumab. Endpoints were drug survival (time from treatment initiation to discontinuation), effectiveness [Psoriasis Area and Severity Index (PASI)], and health-related quality-of-life [Dermatology Life Quality Index (DLQI)]. Predicted drug survival probability was 92.4% [95% confidence interval (CI): 89.1, 95.7%] at 6months and 84.2% (95% CI 79.5, 89.1%) at 12months; this was maintained at 24months [80.4% (95% CI 74.5, 86.8%)]. Younger age, higher body mass index, and no previous biologic treatment were significantly associated with longer drug survival. Absolute PASI≤3 after 3months was achieved by 89.8% of patients; 92.4%, 77.8%, and 59.1% reached PASI 75, PASI 90, and PASI 100, respectively. After 12months, 96.5% of 141 patients had an absolute PASI≤3. The proportion of patients achieving DLQI 0/1 was 87.3% at 12months. This study demonstrated high and sustained drug survival with high rates of skin clearance and improved quality of life in patients with relatively severe disease treated with brodalumab. Improvements were observed as early as 3months post-treatment initiation and were sustained for up to 24months in a real-life setting.

Clinical Cutoff Scores For The Pittsburgh Sleep Quality Index In Adolescents With Concussion

Clinical Cutoff Scores For The Pittsburgh Sleep Quality Index In Adolescents With Concussion

How to implement quality indicators in nutritional therapy in a nutrology service

How to implement quality indicators in nutritional therapy in a nutrology service

Less Is More: Dissecting Trauma Centers by Procedural Volume.

This study aims to examine the relationship between procedural volume and annual trauma volume (ATV) of ACS Level I trauma centers (TC). Although ATV is a hard criterion for TC verification, importance of procedural interventions as a potential quality indicator is understudied. Patients managed at ACS level I TCs were identified from ACS-TQIP 2017-2021. TCs were identified using facility keys and stratified into quartiles based on ATV into low, low-medium, medium-high, and high volume. TCs were also stratified into tertiles [low (LV), medium (MV), high (HV)] based on procedural volume by assessing annual number of laparotomies, thoracotomies, craniotomies/craniectomies, angioembolizations, vascular repairs, and long bone fixations performed at each center. The Cohen κ statistic was used to assess concordance between ATV and procedural volume. A total of 182 Level I TCs were identified: 76 low, 47 low-medium, 35 high-medium, and 24 high volume. Long bone fixation, laparotomy, and craniotomy/craniectomy were the most performed procedures with a median of 65, 59, and 46 cases/center/year, respectively. Overall, 31% of HV laparotomy centers, 31% of HV thoracotomy centers, 22% of HV craniotomy/craniectomy centers, 22% of HV vascular repair centers, 32% of HV long bone fixation centers, and 33% of HV angioembolization centers contributed to the overall number of low-medium and low-volume TCs. The Cohen κ statistic demonstrated poor concordance between ATV and procedural volumes for all procedures (overall procedural volume-κ=0.378, laparotomy-κ=0.270, thoracotomy-κ=0.202, craniotomy/craniectomy-κ=0.394, vascular repair-κ=0.298, long bone fixation-κ=0.277, angioembolization-κ=0.286). ATV does not reflect the procedural interventions performed. Combination of procedural and ATV may provide a more accurate picture of the clinical experience at any given TC. Level III.

Slaughter Performance, Meat Quality and Organoleptic Indices of Crossbred Progenies from Meat-Type Chicken and Nigerian Indigenous Chicken Breeds

Slaughter Performance, Meat Quality and Organoleptic Indices of Crossbred Progenies from Meat-Type Chicken and Nigerian Indigenous Chicken Breeds

Bibliometric analysis of Indian research trends in air quality forecasting research using machine learning from 2007–2023 using Scopus database

Machine-learning air pollution prediction studies are widespread worldwide. This study examines the use of machine learning to predict air pollution, its current state, and its expected growth in India. Scopus was used to search 326 documents by 984 academics published in 231 journals between 2007 and 2023. Biblioshiny and Vosviewer were used to discover and visualise prominent authors, journals, research papers, and trends on these issues. In 2018, interest in this topic began to grow at a rate of 32.1 percent every year. Atmospheric Environment (263 citations), Procedia Computer Science (251), Atmospheric Pollution Research (233) and Air Quality, Atmosphere, and Health (93 citations) are the top four sources, according to the Total Citation Index. These journals are among those leading studies on using machine learning to forecast air pollution. Jadavpur University (12 articles) and IIT Delhi (10 articles) are the most esteemed institutions. Singh Kp's 2013 "Atmospheric Environment" article tops the list with 134 citations. The Ministry of Electronics and Information Technology and the Department of Science and Technology are top Indian funding agency receive five units apiece, demonstrating their commitment to technology. The authors' keyword co-occurrence network mappings suggest that machine learning (127 occurrences), air pollution (78 occurrences), and air quality index (41) are the most frequent keywords. This study predicts air pollution using machine learning. These terms largely mirror our Scopus database searches for "machine learning," "air pollution," and "air quality," showing that these are among the most often discussed issues in machine learning research on air pollution prediction. This study helps academics, professionals, and global policymakers understand "air pollution prediction using machine learning" research and recommend key areas for further research.

Assessment of the Water Quality of WWTPs’ Effluents through the Use of Wastewater Quality Index

Assessment of the Water Quality of WWTPs’ Effluents through the Use of Wastewater Quality Index

Carbohydrate quality index and risk of non-alcoholic fatty liver disease in Iranian adults

Background/aimIn the current study, we aimed to assess the association of carbohydrate quality index (CQI) with the risk of non-alcoholic fatty liver disease (NAFLD) in Iranian adults.MethodsThis case-control study was conducted on 225 newly diagnosed NAFLD patients and 450 controls, aged 20–60 years. A food frequency questionnaire was used to calculate the CQI and its components, including fiber intake, glycemic index, whole grains: total grains ratio, and solid carbohydrates: total carbohydrates ratio. Multivariable logistic regression was used to estimate the odds ratio (OR) of NAFLD across the tertile of CQI and its components.ResultsThe participant’s mean ± SD of body mass index and age were 26.8 ± 4.3 kg/m2 and 38.1 ± 8.8 years, respectively. The median (interquartile) CQI score in participants of the case and control groups was 20 (15–25) and 23 (18–28), respectively. In the multivariable-adjusted model, the risk of NAFLD decreased significantly across the tertiles of the CQI [(OR: 0.20; %95CI: 0.11–0.39), Ptrend <0.001)]. Also, the odds of NAFLD decreased across tertiles of solid carbohydrates to total carbohydrates ratio [(OR: 0.39; 95%CI: 0.22–0.69), Ptrend <0.001)]. However, a high dietary glycemic index (GI) was associated with increased odds of NAFLD [(OR:7.47; 95%CI: 3.89–14.33, Ptrend<0.001)]. There was no significant relationship between other CQI components, including fiber intake and whole grain/total grains and the risk of NAFLD.ConclusionsOur results revealed that a diet with a high quality of carbohydrates, characterized by higher intakes of solid carbohydrates, whole grain, and low GI carbohydrates, can be related to a reduced risk of NAFLD.

Pembangunan Sistem Informasi Pelaporan Masalah Lingkungan Berbasis Web di Universitas Kristen Satya Wacana

Meeting environmental challenges necessitates the exploration of new and inventive solutions. The Environmental Quality Index (IKLH) report revealed an uptick in Indonesia's index to 72.42 in 2022 from 71.45 in 2021, despite a worsening air quality trend. Acknowledging the importance of Human Resource Management and "Go Green" education in promoting environmental consciousness, this paper proposes the adoption of Laravel for expeditious handling of environmental issues at UKSW. Through the utilization of the Waterfall model and UML methodology, the system integrates MVC architecture, streamlining the process of environmental problem reporting for students. Rigorous Black Box Testing ensures the seamless functionality of the system. Ultimately, this initiative seeks to fortify the university's environmental stewardship while advancing the Go Green campaign, thereby fostering a campus environment that is both pristine and sustainable.

Effects of Organic Manure on Wheat Yield and Accumulation of Heavy Metals in a Soil—Wheat System

The application of organic manure is an effective way to develop sustainable agriculture. However, the application of organic manure may be associated with a potential risk of heavy metal pollution for soil and crops. In this study, the effects of organic cow manure (T1) (as base fertilizer), organic pig manure (T2) (as base fertilizer) and chemical fertilizer (T3) on winter wheat grain yields, grain quality, heavy metal concentrations and heavy metal bioconcentration factors (BCFs) in a soil–wheat system were studied from November 2021 to June 2023. The results showed that the winter wheat grain yields in the T1 and T2 treatments were lower than those in the T3 treatment by 2.57–38.0% and 10.5–25%, respectively. There were no significant differences in quality indexes of winter wheat grain among different fertilizer treatments. The concentrations of heavy metals in topsoil and winter wheat were 0.12–76.11 μg/g and 0.01–43.25 μg/g, respectively. The BCFs of heavy mental in the soil–wheat grain system was 0–2.92. In general, there were no significant differences in heavy metals’ concentrations in topsoil and wheat grain among different fertilizer treatments. In summary, compared with chemical fertilizer, the short-term application of organic manures had no significant effect on heavy metals concentrations in topsoil and wheat.

Burnout Professional Fulfilment and Sleep Quality in Indian Healthcare Workers in Times of the Covid-19 Pandemic

Aim and Background: With more than 210 nations affected, the SARS-COV-2 became the most widespread worldwide pandemic. As of 14 April 2022, over 500 million cases were confirmed globally Given these numbers, it was hardly surprising that the Covid-19 epidemic significantly strained healthcare systems worldwide. This study aimed to evaluate the degree of Burnout, Professional fulfilment, and Sleep quality across various groups of healthcare professionals working during the Covid-19 pandemic and looked for any correlation between these three variables. Methods: This study employed a cross-sectional observational research design and gathered data from respondents across various regions of India through an anonymous online or paper-based questionnaire tailored to the preferences of each participating Healthcare Worker (HCW). The assessment of professional fulfilment was conducted by employing the Stanford Professional Fulfillment Index and the sleep quality of healthcare workers was determined via the use of the Pittsburgh Sleep Quality Index. The variables were analyzed using statistical tools; Chi-square test, Fisher’s Exact test,Kruskal-Wallis One Way Analysis of Variance and Spearman’s rank correlation Results: Burnout was notably higher among the HCWs with poorer Sleep quality and lower in HCWs with higher Professional Fulfilment. Correlations further revealed that Burnout scores positively correlated with Work exhaustion and Interpersonal Disengagement Conclusion: This illustrates that HCWs with poorer sleep quality and lesser professional fulfilment experienced greater burnout at work during the COVID-19 pandemic Clinical significance: These insights guide healthcare providers and policy markers to optimize the well being of Healthcare Workers and foster informed preparedness in case of future pandemics. Keywords: COVID-19, PSQI, HCW, SPFI, Burnout, Professional Fulfilment, Sleep Quality.