Bivariate Model Research Articles

Unveiling Groundwater Potential in Hangu District, Pakistan: A GIS-Driven Bivariate Modeling and Remote Sensing Approach for Achieving SDGs

Sustainable groundwater development stands out as a contemporary concern for growing global populations, particularly in stressed riverine arid and semi-arid regions. This study integrated satellite-based (Sentinel-2, ALOS-DEM, and CHIRPS rainfall) data with ancillary lithology and infrastructure datasets using Weight of Evidence (WoE) and Frequency Ratio (FR) models to delineate Groundwater Potential Zones (GWPZs) in the Hangu District, a hydrologically stressed riverine region in northern Pakistan, to support the Sustainable Development Goals (SDGs). Ten key variables, including elevation, slope, aspect, distance to drainage (DD), rainfall, land use/land cover, Normalized Difference Vegetation Index, lithology, and road proximity, were incorporated into the Geographic information system (GIS) environment. The FR model outperformed the WoE model, achieving success and prediction rates of 89% and 93%, compared to 82% and 86%. The GWPZs-FR model identified 23% (317 km2) as high potential, located in highly fractured pediment fans below 550 m, with gentle slopes (<5 degrees), DD (within 200 m), and high rainfall in areas of natural trees and vegetation on valley terrace deposits. The research findings significantly support multiple SDGs, with estimated achievement potentials of 37.5% for SDG 6 (Clean Water and Sanitation), 20% for SDG 13 (Climate Action), 15% for SDG 8 (Decent Work and Economic Growth), 12.5% for SDG 9 (Industry, Innovation, and Infrastructure), and notable contributions of 10% for SDG 2 and 5% for SDG 3. This approach provides valuable insights for policymakers, offering a framework for managing groundwater resources and advancing sustainable practices in similar hydrologically stressed regions.

Exploring Reciprocal Associations Between Self-Reported Anxiety and Eating Disorder Symptoms Longitudinally: ABivariate Latent Change Score Approach.

Consistent data support an association between anxiety and eating disorders (EDs), and theoretical models of EDs suggest that anxiety may be involved in the etiology and maintenance of ED symptoms over time. However, the directionality of relations between these variables remains under-characterized, particularly within treatment settings. We used bivariate latent change score models to explore longitudinal associations between anxiety and ED symptoms in a sample of ED patients (N = 548, 93.2% female, Mage = 21.16, 78.8% White, 79.6% Non-Hispanic/Latinx) throughout intensive treatment and at 6- and 12-month follow-up. Best-fitting models exploring change in each variable independently (i.e., univariate models) suggested that changes in ED and anxiety symptoms decreased over time, but that change was influenced by an individual's symptom severity at the previous timepoint. Models exploring associations between changes in both variables over time (i.e., bivariate latent change score models) suggested the best fit for a model where both anxiety and ED symptoms at one timepoint were associated with later change in the other. Specifically, parameters within these models suggested that higher levels of anxiety were associated with increased subsequent reductions in ED symptoms, whereas elevations in ED symptoms were associated with decreased later reductions in anxiety. Our findings suggest that anxiety and ED symptoms are intricately related both within and outside of intensive treatment. Future multi-modal research exploring real-time links between anxiety and ED symptoms throughout treatment is critical to extend this work and inform improvements in targeted, mechanistic interventions for this population.

Modelling and Forecasting of Exchange Rate Pairs Using the Kalman Filter

ABSTRACTDeveloping and employing practically useful and easy to calibrate models for prediction of exchange rates remains a challenging task, especially for highly volatile emerging market currencies. In this paper, we propose a novel approach for joint prediction of correlated exchange rates for two different currencies with respect to the same base currency. For this purpose, we reformulate a generalized version of a bivariate ARMA model into a state space model and use the Kalman filter for estimation and forecasting of the underlying exchange rates as latent variables. With extensive numerical experiments spanning 18 different exchange rates (across both emerging markets, developing and developed economies), we demonstrate that our approach consistently outperforms univariate ARMA models as well as the random walk model in short term out‐of‐sample prediction for various exchange rate pairs. Our study fills a gap in the empirical finance literature in terms of robust, explainable, accurate, and easy to calibrate models for forecasting correlated exchange rates. The proposed methodology has applications in exchange rate risk management as well as pricing of financial derivatives based on two exchange rates.

Delineation of Groundwater Potential Using the Bivariate Statistical Models and Hybridized Multi-Criteria Decision-Making Models

Identifying groundwater potential zones in a basin and developing a sustainable management plan is becoming more important, especially where surface water is scarce. The main aim of the study is to prepare the groundwater potential maps (GWPMs) considering the bivariate statistical models of frequency ratio (FR), weight of evidence (WoE), and the multi-criteria decision-making (MCDM) model of Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) hybridized with FR and WoE. Two distance measures, Euclidean and Manhattan, were used in TOPSIS to evaluate their effect on GWPMs. The research focused on the Burdur Lake catchment located in the southwest of Türkiye. In total, 74 wells with high yields were chosen randomly for the analysis, 52 (70%) for training, and 22 (30%) for testing processes. Sixteen groundwater conditioning factors were selected. The area under the receiver operating characteristic (AUROC) and true skill statistics (TSS) were utilized to examine the goodness-of-fit and prediction accuracy of approaches. The TOPSIS-WoE-Manhattan model and the FR and WoE models gave the best AUROC values of 0.915 and 0.944 for the training and testing processes, respectively. The best TSS values of 0.827 and 0.864 were obtained by the TOPSIS-FR-Euclidean and WoE models for the training and testing processes, respectively.

Dropout from Maternity Continuum of Care and Associated Factors Among Mothers Who Gave Birth After War in Adigrat Town, Tigray, Northern Ethiopia 2024

<i>Background: </i>Maternity continuum of care is the continuity of maternal health care services given to mothers during antenatal period, child birth and post natal period. It is one of the strategic programs meant to lower the death rates of mothers, newborns, and children. In spite of this, a large number of moms discontinue their participation in maternal continuum care. Dropout from the maternity continuum of care is prevalent public health issue in underdeveloped nations, such as Ethiopia. <i>Methods: </i>Community based quantitative cross-sectional study was carried out among 357 mothers who gave birth in the 12 months in Adigrat town. Systematic sampling method was used to obtain study participants. Data was collected using pretested, semi- structured and face to face interviewer administered questioner. Bivariable and multivariable logistic regression model was fitted. Variables having p-value less than 0.2 in bivariable analysis was entered to multivariable logistic regression model. In multivariable logistic regression adjusted odds ratio with 95% confidence interval was used to determine strength and direction of the association between dependent and independent variables. <i>Results:</i> The overall magnitude of drop out from the maternity continuum of care was 237 (66.4%) [95%CI (61.3-70.9)], 60.6% drop out from ANC visit, 5.6% drop out from skill birth attendant and 58.9% drop out from PNC. Mothers never heard on maternal health care service (AOR=4.179 (1.107, 15.783), service out of health facility (AOR =5.136 (1.988, 13.267) noabortionhistory (AOR=1.424 (1.113, 12.133), unplannedpregnancy (AOR=5.478 (1.902, 15.777), less than 4 ANC visit (AOR= 5.583 (2.598, 11. 997) and mothers attitude (AOR=15.049 (2.489, 32.997) were statically significant factors associated with drop out from maternity continuum of care. <i>Conclusion and discussion: </i>This study showed that magnitude of drop out from maternity continuum of care was high as compared to WHO recommendations. As a result concerned stakeholders and policy makers should initiate more than four ANC visit, create awareness on harmful traditional practice, bad pregnancy history, support mothers to use family planning to prevent unplanned pregnancy, and work on attitude change of the community.

Diagnostic accuracy of radiomics and artificial intelligence models in diagnosing lymph node metastasis in head and neck cancers: a systematic review and meta-analysis.

Head and neck cancers are the seventh most common globally, with lymph node metastasis (LNM) being a critical prognostic factor, significantly reducing survival rates. Traditional imaging methods have limitations in accurately diagnosing LNM. This meta-analysis aims to estimate the diagnostic accuracy of Artificial Intelligence (AI) models in detecting LNM in head and neck cancers. A systematic search was performed on four databases, looking for studies reporting the diagnostic accuracy of AI models in detecting LNM in head and neck cancers. Methodological quality was assessed using the METRICS tool and meta-analysis was performed using bivariate model in R environment. 23 articles met the inclusion criteria. Due to the absence of external validation in most studies, all analyses were confined to internal validation sets. The meta-analysis revealed a pooled AUC of 91% for CT-based radiomics, 84% for MRI-based radiomics, and 92% for PET/CT-based radiomics. Sensitivity and specificity were highest for PET/CT-based models. The pooled AUC was 92% for deep learning models and 91% for hand-crafted radiomics models. Models based on lymph node features had a pooled AUC of 92%, while those based on primary tumor features had an AUC of 89%. No significant differences were found between deep learning and hand-crafted radiomics models or between lymph node and primary tumor feature-based models. Radiomics and deep learning models exhibit promising accuracy in diagnosing LNM in head and neck cancers, particularly with PET/CT. Future research should prioritize multicenter studies with external validation to confirm these results and enhance clinical applicability.

Incidence of acute kidney injury and its predictors among neonates admitted at neonatal intensive care unit of, Northwest Ethiopia comprehensive specialized hospitals, 2023.

Acute kidney injury is an acute and reversible increment in serum creatinine (SCr) levels with a reduction in urine output oliguria, or anuria. Acute kidney injury is a major cause of neonatal morbidity and mortality worldwide; it is a serious problem in low and middle-income countries, particularly in sub-Saharan Africa such as Ethiopia. Moreover, there are few studies in developing countries. This study aimed to investigate the incidence and predictors of acute kidney injury in neonates admitted to the neonatal intensive care unit of some specialized hospitals in the Amhara region of northwestern Ethiopia. A facility-based retrospective follow-up study was conducted in the Northwest Amhara Region's comprehensive specialized hospitals with 634 neonates from January 2020 to December 2022. Data were collected by reviewing patient charts using simple random sampling with a pretested checklist, entered using Epi-data 4.6, and analyzed using STATA 14. Median survival time, Kaplan-Meier survival curve, and log-rank test were calculated. Bivariable and multivariable Cox hazard models were used to determine the determinants of acute kidney injury. A hazard ratio with a 95% confidence interval was calculated. Variables with p-values less than 0.05 were considered statistically significant. The incidence of Acute Kidney Injury among Neonates admitted to Neonatal IntensiveCare Unit was 14.9 per 1000 (95% CI: 12.5-17.7) with the proportion of acute kidney injury (20.19%) (95% CI: 17.23-23.50) neonates with sepsis (AHR: 2.59; 95%CI: 1.21-5.56), neonates with perinatal asphyxia [(AHR: 2.70; 95%CI: 1.29-5.65) were taking gentamicin drugs [(AHR = 1.74; 95%CI: 1.03-2.94], neonates were preterm [(AHR; 1.77: 95%CI: 1.05 -2.98], and neonatal-hyponatremia [(AHR: 2.14; 95%CI: (1.00 -4.9)] and hyperkalemia [(AHR: 2.64; 95 CI: (1.11- 6.2)] were statistically found to be significant predictors of acute kidney injury. The incidence of acute kidney injury in neonates was high. Premature infants, neonates with sepsis, who suffered perinatal asphyxia, who received gentamicin drugs, whose sodium levels decreased and potassium levels increased were at higher risk of developing acute kidney injury. All concerned agencies should work to prevent acute kidney injury and pay special attention to multifactorial causes. Therefore, strategies need to be developed and/or strengthened to prevent the occurrence of acute kidney injury in infants with sepsis, neonates who suffered perinatal asphyxia, and preterm infants whose sodium levels decreased and potassium levels increased.

Discontinuation of family planning use among women of reproductive age in Rwanda: analysis from three Rwandan Demographic Health Survey (RDHS) 2010-2020.

Family planning (FP) is fundamental in addressing unwanted pregnancies, unplanned pregnancies, unsafe abortions, maternal and child mortalities. It plays a crucial role in achieving the Sustainable Development Goals (SDGs), especial Goal 3. However, despite a high FP discontinuation percentage of 30% in Rwanda, there is limited studies on the contributing factors. Thus, the purpose of this study was to assess the discontinuation of FP use and associated factors among women aged 15-49 years in Rwanda. A pooled data analysis of three consecutive Rwandan Demographic and Health Surveys (RDHS) for the years 2010-11, 2014-15, and 2019-20 was performed using Stata Version 17.0. A multistage stratified sampling method was used to select study participants, and weighted analysis was conducted. Both bivariate and multivariate logistic regression models were used to identify factors associated with FP discontinuation. A statistical significance was determined at p < 0.05. The findings showed that 17%, 28%, and 29% of Rwandan women of reproductive age discontinued using FP in 2010-11, 2014-15, and 2019-20, respectively. Pooled multivariate analysis indicated that FP discontinuation rates was more than double folds higher in 2014-15 (AOR: 2.17; 95% CI: 2.01 to 2.35) and 2019-20 (AOR: 2.71; 95% CI: 2.49 to 2.93) compared to 2010-11. The odds of FP discontinuation were higher among women aged 20-34 years (AOR: 7.71; 95% CI: 5.87 to 10.13) and women aged 35-49 years (AOR: 3.43; 95% CI: 2.59 to 4.55); those with four or more children (AOR: 1.38; 95% CI: 1.28 to 1.49); women from poor households (AOR: 5.19; 95% CI: 1.85 to 14.57); those who attending a health facility in the last year (AOR: 1.56; 95% CI: 1.46 to 1.66); women with a history of pregnancy termination (AOR: 1.17; 95% CI: 1.09 to 1.26); those with no education (AOR: 1.39; 95% CI: 1.28 to 1.51) and currently married women (AOR: 11.57; 95% CI: 10.21 to 13.10). Additionally, the most common reasons for FP discontinuation were fear of side effects (31.2%) and the desire to become pregnant (27.5%). The trend of FP discontinuation among reproductive-age women in Rwanda has significantly increased from 200 - 11 to 2019-20. Key contributing factors include region, older age, higher parity, poor household status, health facility attendance, history of pregnancy termination, lack of education, being married and fear of side effects. Therefore, interventions should focus on addressing these factors to reduce FP discontinuation rates.

Onsite training-mentoring intervention improves data quality: an implementation research.

The quality of health data is not satisfactory in Low and Middle Income Countries (LMICs). Haramaya University, in collaboration with Ministry of Health and Regional Health Bureau, conducted an implementation research in selected public health facilities and administrative units. This research was aimed to test the onsite training-mentoring (OTM) intervention and adaptation of the implementation strategy to improve the routine health information system (RHIS) data quality in the context of public health sector. An interrupted time series design with an onsite training-mentoring intervention was used to improve data quality in public health sector of Jigjiga Woreda, eastern Ethiopia from July 2021 to June 2022. Both the pre and post intervention assessments data were collected by experienced and trained public health professionals using interviewer guided self-administered interview, record review and observation data collection techniques. Data were analyzed using descriptive, bivariate, and multivariate logistic models to identify predictors of data quality. The overall data accuracy was increased from 88.12% before to 95.0% after intervention; and it was above 90% in all the facilities. The overall data content completeness was increased from 75.75% to 89.9%, though it varied among the facilities. The timeliness and report completeness were 100% in all the facilities. The odds of those health workers who had poor knowledge were less likely to ensure data quality (AOR = 0.39; 95%CI: 0.19, 0.83) than their counterparts. The intervention was brought substantial changes of data quality in the study setting. Knowledge of the workers towards data quality is a crucial factor to ensure data quality in the sector. Thus, collective efforts is required to continue this tested intervention to ensure the quality of the routine health information system in the lower levels of the sector.

Genetic variants for Alzheimer's disease and comorbid conditions.

Alzheimer's disease and related dementias (ADRD) frequently co-occur with comorbidities such as diabetes and cardiovascular diseases in elderly populations. Utilize a life-course approach to identify genetic variants that are associated with the co-occurrence of ADRD and another comorbid condition. Research data from African American participants of the Indianapolis-Ibadan Dementia Project (IIDP) linked with electronic medical record (EMR) data and genome-wide association study (GWAS) data were utilized. The age of onset for ADRD was obtained from longitudinal follow-up of the IIDP study. Age of onset for comorbid conditions was obtained from EMR. The analysis included 1177 African Americans, among whom 174 were diagnosed with ADRD. A semi-parametric marginal bivariate survival model was used to examine the influence of single nucleotide polymorphisms (SNPs) on dual time-to-event outcomes while adjusting for sex, years of education, and the first principal component of GWAS data. Targeted analysis of 20 SNPs that were reported to be associated with ADRD revealed that six were significantly associated with dual-disease outcomes, specifically congestive heart failure and cancer. In addition, eight novel SNPs were identified for associations with both ADRD and a comorbid condition. Using a bivariate survival model approach, we identified genetic variants associated not only with ADRD, but also with comorbid conditions. Our utilization of dual-disease models represents a novel analytic strategy for uncovering shared genetic variants for multiple disease phenotypes.

Diagnostic Accuracy of Optic Nerve Sheath Diameter Measurement by Ultrasonography for Noninvasive Estimation of Intracranial Hypertension in Traumatic Brain Injury: A Systematic Review and Meta-Analysis.

Intracranial hypertension (IH) is associated with an unfavorable outcome in traumatic brain injury (TBI), and management strategies guided by intracranial pressure monitoring improve prognosis. Owing to the limitations of using invasive devices, measurement of optic nerve sheath diameter (ONSD) by ultrasonography is an alternative noninvasive method. However, its accuracy has not been validated in patients with TBI, so we aim to determine the diagnostic accuracy of measuring ONSD by ultrasonography in patients with TBI to estimate IH, compared with invasive monitoring. Systematic review of electronic databases and manual literature review from inception to June 2023. The analysis included diagnostic accuracy studies of ultrasonographic measurement of ONSD compared with invasive monitoring published in any language and with patients of any age. A qualitative synthesis was performed describing the clinical and methodological characteristics, strengths, limitations, and quality of evidence. In addition, a bivariate random effects model meta-analysis and a hierarchical summary receiver operating characteristics model were performed for the pediatric and adult population separately. Five hundred and forty eight patients of 688 in 16 eligible studies were adults and 120 were children. Pooled sensitivity and specificity of ONSD measurement by ultrasonography were 84% (95% CI, 76%-89%) and 83% (95% CI, 73%-90%), respectively. During the sensitivity analysis, these parameters exhibited consistent values. Pooled area under the curve was 0.91 for adults and 0.76 for children. Optimal threshold for estimating IH was 5.76 mm for adults and 5.78 mm for children. Measurement of ONSD by ultrasonography is a reliable, low-cost, and safe alternative for the estimation of IH with TBI in adults. More robust studies are needed to overcome the high risk of bias and heterogeneity for this analysis.

A comparative study of antenatal depression among urban and rural pregnant women in Gimbi District, Oromia, Ethiopia

BackgroundAntenatal depression (AND) is a form of clinical depression that can be caused by stress and worries that can bring pregnancy to more severe levels. It has negative impacts on women, the family, and the community at large. The comparative study of antenatal depression among rural and urban pregnant women was less studied in Ethiopia and in this study area in particular.ObjectiveThe objective of the study was to compare the prevalence of antenatal depression and its associated factors among pregnant women in Gimbi rural and urban residents in Ethiopia in 2023.MethodsA community-based comparative cross-sectional study design was used from 1 February to 30 March 2023. A systematic random sampling method was used to select study participants. Data were collected using pretested interviewer-administered structured questionnaires. Binary logistic regression analysis was used to identify factors associated with antenatal depression. Variables with a p-value of 0.25 or less in the bi-variable logistic regression model were candidates for a multi-variable logistic regression model.ResultsThe prevalence of antenatal depression was 56 (21.5%), 95% CI: [16.9–25.5] among rural participants and 50 (19.2%) [95%] CI: [14.6–23.8] among urban participants. Having complications during pregnancy (AOR: 4.92, 95% CI: 1.35, 17.88), ever had depression (AOR: 3.20, 95% CI: 1.30, 7.85), consuming alcohol (AOR: 3.78, 95% CI: 1.24, 11.49), and educational status (can read and write) (AOR: 2.14, 95% CI:1.05, 4.67) were factors associated with antenatal depression among urban mothers, while no antenatal care follow-up (AOR: 6.6, 95% CI: 2.63, 16.85), unplanned pregnancy (AOR: 4.51, 95% CI:1.10, 1.86), and having complications during pregnancy (AOR: 2.77, 95% CI: 1.30, 5.92) were factors associated with antenatal depression among rural mothers.ConclusionThe prevalence of antenatal depression among rural mothers was higher than the prevalence of antenatal depression among urban mothers in the Gimbi district. Having complications during pregnancy, ever had depression, consuming alcohol, and educational status were associated factors with antenatal depression among urban mothers; having complications during pregnancy, unplanned pregnancy, and no ANC follow-up were factors associated with antenatal depression among rural mothers. Therefore, quality family planning and ANC services should be provided for the women to reduce unplanned pregnancies and experience complication-free pregnancy periods.

Magnitude and associated factors of prescribing drugs by their brand names among prescribers working at selected hospitals in Addis Ababa, Ethiopia

Background One possible mechanism for lowering expenditure on drugs and increasing their accessibility is by prescribing generic drugs, which are less costly and have equivalent safety and effectiveness profile as brand drugs. However, in Addis Ababa brand-prescribing practice is so common to the extent of making the health department administration of the city to write letters to subcities and hospitals discouraging brand prescribing. This study tried to identify the magnitude and factors affecting brand prescribing in the city. Objective: General objective of this study was to assess magnitude and associated factors of prescribing drugs by brand names at Addis Ababa. Methods An institution based analytical cross-sectional study design was employed from May to August, 2022, using a sample of 485 prescribers. The hospitals were selected by using simple random sampling method and prescribers from different departments were selected by using systematic random sampling method. Data was collected using semistructured, self-administered questionnaire and entered into Statistical Package for Social Sciences version 25 for analysis. The data was described using percentages, graphs and tables. Mean and standard deviations were calculated to identify measures of central tendency and dispersion. Association between dependent and independent variables was checked using bivariate and multivariable logistic regression models. Statistical significance was declared at 95% confidence interval and p &lt; .05. Results The magnitude of prescribing drugs by their brand names was 54.0%. Being trained on good prescribing practice (AOR: 6.81; 95%CI: 2.08-22.28), confidence on Ethiopian Food and Drug Administration Authority (AOR: 18.18; 95%CI: 6.78-48.80), and knowledge about generic drugs (AOR: 11.86; 95%CI: 4.76-29.55) were found to be independent predictors of prescribing drugs by their brand names. Conclusion and recommendation Brand medicine prescribing is positively associated with training on good prescribing practice and knowledge about generic drugs. Hence, training prescribers on good prescribing practice and educating them about generic drugs can minimize brand prescribing.

Outcome Reporting in Studies Investigating Treatment for Caesarean Scar Ectopic Pregnancy: A Systematic Review.

Caesarean scar ectopic pregnancy (CSEP) is associated with significant maternal and foetal morbidity. However, the optimal treatment remains unknown. The aim of this study was to review outcomes reported in studies on CSEP treatment and outcome reporting quality. We reviewed 1270 articles identified through searching PubMed, MEDLINE and Google Scholar from 2014 to 2024 using the search terms 'caesarean scar ectopic pregnancy and caesarean scar pregnancy'. We included all study types evaluating any form of CSEP treatment, with a sample size of ≥ 50, where diagnosis was described, and the article was in English. Two authors independently reviewed studies and assessed outcome reporting and methodological quality. The relationship between outcome reporting quality and publication year and journal type was assessed with univariate and bivariate models. A total of 108 studies, including 17 941 women, were included. 83% of all studies originated from China. Studies reported on 326 outcomes; blood loss (86%), need for additional intervention (77%) and time for serum hCG to normalise post treatment (69%) were the most common outcomes. A primary outcome was clearly defined in 11 (10%) studies. The median quality of outcome reporting was 3 (IQR 3-4). No relationship was demonstrated between outcome reporting quality and publication year (p = 0.116) or journal type (p = 0.503). This review demonstrates that there is a wide variation in outcomes reported in studies on CSEP treatment. Development and implementation of a core outcome set by international stakeholders which includes patients is urgently needed to enable high-quality research that is both useful and relevant to patients.

Factors affecting U.S. adults’ comfort level in sharing social needs information with healthcare providers

ObjectiveThis study examines various factors affecting U.S. adults’ comfort level in sharing information about their social needs with healthcare providers. MethodsWe used data from the 2022 Health Information National Trends Survey (cycle 6), a nationally representative survey of U.S. adults (n = 6252). The outcome variables were participants’ comfort level in sharing information about three social needs (food insecurity, transportation difficulties, and housing instability). Data were analyzed using weighted bivariate and multivariable logistic regression models. ResultsParticipants who faced discrimination when getting medical care based on race/ethnicity were more likely to be uncomfortable in sharing information about food insecurity, housing instability, and transportation difficulties. Those who trusted the healthcare system “a lot” were less likely to be uncomfortable in sharing information about food insecurity and transportation difficulties. Patient-Centered Communication (PCC) and social isolation scores significantly affected participants’ comfort level in sharing information about social needs. ConclusionVarious factors such as trust, discrimination, social isolation, and PCC were found to be significantly affecting US adults’ comfort level in sharing information about social needs. Practice implicationsHealthcare systems and policymakers should focus on developing approaches and strategies to enhance trust, reduce discrimination, improve patient-provider communication, and create supportive social environments.

Node-RADS: a systematic review and meta-analysis of diagnostic performance, category-wise malignancy rates, and inter-observer reliability.

To perform a systematic review and meta-analysis to estimate diagnostic performance, category-wise malignancy rates, and inter-observer reliability of Node Reporting and Data System 1.0 (Node-RADS). Five electronic databases were systematically searched for primary studies on the use of Node-RADS to report the possibility of cancer involvement of lymph nodes on CT and MRI from January 1, 2021, until April 15, 2024. The study quality was assessed by modified Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and Quality Appraisal of Diagnostic Reliability (QAREL) tools. The diagnostic accuracy was estimated with bivariate random-effects model, while the pooled category-wise malignancy rates were obtained with random-effects model. Six Node-RADS-CT studies and three Node-RADS-MRI studies covering nine types of cancer were included. The study quality was mainly damaged by inappropriate index test and unknown timing according to QUADAS-2, and unclear blindness during the rating process according to QAREL. The area under hierarchical summary receiver operating characteristic curve (95% conventional interval) was 0.92 (0.89-0.94) for Node-RADS ≥ 3 as positive and 0.91 (0.88-0.93) for Node-RADS ≥ 4 as positive, respectively. The pooled malignancy rates (95% CIs) of Node-RADS 1 to 5 were 4% (0-10%), 31% (9-58%), 55% (34-75%), 89% (73-99%), and 100% (97-100%), respectively. The inter-observer reliability of five studies was interpreted as fair to substantial. Node-RADS presented a promising diagnostic performance with an increasing probability of malignancy along higher category. However, the evidence for inter-observer reliability of Node-RADS is insufficient, and may hinder its implementation in clinical practice for lymph node assessment. Question Node-RADS is designed for structured reporting of the possibility of cancer involvement of lymph nodes, but the evidence supporting its application has not been summarized. Findings Node-RADS presented diagnostic performance with AUC of 0.92, and malignancy rates for categories 1-5 ranged from 4% to 100%, while the inter-observer reliability was unclear. Clinical relevance Node-RADS is a useful tool for structured reporting of the possibility of cancer involvement of lymph nodes with high diagnostic performance and appropriate malignancy rate for each category, but unclear inter-observer reliability may hinder its implementation in clinical practice.

The diagnostic performance of dual-energy CT imaging in cervical lymph node metastasis of papillary thyroid cancer: a meta-analysis

PurposeThis meta-analysis aimed to evaluate the diagnostic efficacy of dual-energy computed tomography (DECT) in detecting cervical lymph node metastasis among papillary thyroid cancer (PTC) patients.MethodsA comprehensive search across PubMed, Embase, and Web of Science databases was conducted to identify pertinent publications up to May 2024. This search focused on studies examining the diagnostic accuracy of DECT in detecting cervical lymph node metastases in PTC patients. We employed a bivariate random-effects model to calculate pooled sensitivity and specificity of DECT. The degree of heterogeneity in the studies was quantified using the I2 statistic. Furthermore, the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was utilized to evaluate the methodological quality of the included studies.ResultsThis meta-analysis encompassed 14 articles, collectively involving 1,615 patients. The pooled sensitivity, specificity, and AUC for DECT in detecting cervical lymph node metastases in PTC patients were 0.81 (95% CI: 0.76–0.85), 0.86 (95% CI: 0.80–0.91), and 0.89 (95% CI: 0.86–0.92), respectively. According to Fagan’s nomogram, for DECT, with a pre-test probability of 50%, the post-test probability was calculated as 85% for a positive result and 18% for a negative result. Deeks’ funnel plot asymmetry test showed no significant publication bias was observed for DECT (p = 0.28).ConclusionOur meta-analysis indicates that DECT demonstrates superior sensitivity and specificity in cervical lymph node metastasis among PTC patients. To corroborate these findings and evaluate their clinical applicability, further prospective studies are necessary.

Genetic variation in surface temperature measured using infra-red thermography and genetic associations with production traits in grazing dairy cattle

ABSTRACT Increasing global temperatures and the incidence of extreme weather conditions will result in heat stress becoming a greater issue in production animals. Genetic selection and breeding for heat-tolerant animals have been promoted as a possible mitigation strategy in dairy cattle. The objectives of this study were to obtain in-field skin temperature measurements of the eye, muzzle and udder using infra-red thermography to examine the genetic variation in skin temperature within cows of a dairy herd and to estimate the genetic correlations between skin temperature and production traits. Thermal images and herd test records were obtained for the dairy herd at Massey University’s dairy farm 1. Estimates of (co)variances were obtained using the JWAS program with univariate and bivariate animal models. The heritability estimates for the eye, muzzle and udder temperature were low to moderate at 0.20, 0.24 and 0.39, respectively. All genetic correlations between production and temperature traits were positive except for eye temperature with milk yield and protein yield which was negative and weak. These results indicate that it may be possible to select for a greater skin temperature, however, these results need to be validated using a larger sample size.

Detecting Clinically Significant Prostate Cancer in PI-RADS 3 Lesions Using T2w-Derived Radiomics Feature Maps in 3T Prostate MRI

Prostate Imaging Reporting and Data System version 2.1 (PI-RADS) category 3 lesions are a challenge in the clinical workflow. A better detection of the infrequently occurring clinically significant prostate cancer (csPCa) in PI-RADS 3 lesions is an important objective. The purpose of this study was to evaluate if feature maps calculated from T2-weighted (T2w) 3 Tesla (3T) MRI can help detect csPCa in PI-RADS category 3 lesions. In-house biparametric 3T prostate MRI examinations acquired between January 2019 and June 2023 because of elevated prostate-specific antigen (PSA) levels were retrospectively screened. Inclusion criteria were a PI-RADS 3 lesion and available results of an ultrasound-guided targeted and systematic biopsy. Exclusion criteria were a simultaneous PI-RADS category 4 or 5 lesion and hip replacement. Target lesions with the International Society of Urological Pathology (ISUP) grade group 1 were rated clinically insignificant PCa (ciPCa) and ≥2 csPCa. This resulted in 52 patients being included in the final analysis, of whom 11 (21.1%), 8 (15.4%), and 33 (63.5%) patients had csPCa, ciPCa, and no PCa, respectively, with the latter two groups being combined as non-csPCa. Eight of the csPCas were located in the peripheral zone (PZ) and three in the transition zone (TZ). In the non-csPCa group, 29 were located in the PZ and 12 in the TZ. Target lesions were marked with volumes of interest (VOIs) on axial T2w images. Axial T2w images were then converted to 93 feature maps. VOIs were copied into the maps, and feature quantity was retrieved directly. Features were tested for significant differences with the Mann–Whitney U-test. Univariate models for single feature performance and bivariate models implementing PSA density (PSAD) were calculated. Ten map-derived features differed significantly between the csPCa and non-csPCa groups (AUCs: 0.70–0.84). The diagnostic performance for TZ lesions (AUC: 0.83–1.00) was superior to PZ lesions (AUC: 0.74–0.85). In the bivariate models, performance in the PZ improved with AUCs &gt;0.90 throughout. Parametric feature maps alone and as bivariate models with PSAD can (?) noninvasively identify csPCa in PI-RADS 3 lesions and could serve as a quantitative tool reducing ambiguity in PI-RADS 3 lesions.

Cross-country comparison of depressive symptoms and social-emotional aspects in university students from Brazil and Germany during the COVID-19 pandemic: results from two cross-sectional surveys.

The COVID-19 pandemic negatively affected students' mental health, increasing pre-existing psychosocial vulnerabilities. University students worldwide have presented differences in their mental health status; however, cross-country studies comparing students' mental health during the pandemic are lacking. To investigate potential differences between university students from Brazil and those from Germany with respect to (a) depressive symptoms and alcohol and drug consumption, (b) social and emotional aspects (loneliness, self-efficacy, perceived stress, social support and resilience) and (c) attitudes towards vaccination. Two online cross-sectional studies were conducted with university students during the COVID-19 pandemic in Brazil (November 2021 to March 2022) and in Germany (April to May 2022). Depressive symptoms, alcohol consumption, loneliness, self-efficacy, perceived stress, social support, resilience, sociodemographic information and attitudes towards vaccination were assessed. Data were analysed using univariate and bivariate models. The total sample comprised N = 7911 university students, with n = 2437 from Brazil and n = 5474 from Germany. Brazilian students presented significantly more depressive symptoms and suicidal thoughts, higher levels of perceived stress, higher frequency of drug or substance consumption, and lower levels of perceived social support and resilience than German students, whereas German students presented higher levels of loneliness than Brazilian students. A more favourable opinion towards vaccinations in general was found among Brazilian students compared with German students. In both countries, low-threshold (online) counselling targeting university students is needed. The differences between the samples could indicate country and/or cultural differences which justify further research in this area.