Bivariate Model Research Articles

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

Abstract Introduction 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. Methods 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. Results 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. Conclusion 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.

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 < .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 >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.

Mind wandering is associated with worsening attentional vigilance.

The tendency for our minds to wander is a pervasive and disruptive influence on continued task performance. Models of sustained attention have implicated mind wandering, moments when attention has turned inwards toward task-unrelated thought, in characteristic patterns of worsening performance with greater time-on-task, known as the vigilance decrement. Despite their theoretical connection, associations between mind wandering and the vigilance decrement have not been investigated systematically. Across two studies (N = 730), we evaluated covariance between within-task change in rates of probe-caught mind wandering and patterns of worsening behavioral task performance that characterize the vigilance decrement. Bivariate growth curve models characterized patterns of intraindividual linear change in mind wandering alongside concomitant changes in task accuracy, response time (RT), and RT variability. Importantly, models assessing the covariance between intraindividual change in mind wandering and behavioral outcome measures confirmed that increases in mind wandering are associated with patterns of worsening behavioral performance with greater time-on-task. In addition, we investigated the role of several moderating factors associated with patterns of within-task change: self-reported task interest and motivation, and individuals' propensity for mind wandering, and mindfulness in their daily lives. These factors moderated either the overall level or rate of within-task change in mind wandering. Our results provide support for models of sustained attention that directly implicate mind wandering in worsening behavioral performance with greater time-on-task in continuous performance tasks requiring sustained attention. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Mechanical properties of diamond-type triply periodic minimal surface structures fabricated by photo-curing 3D printing

Triply periodic minimal surface (TPMS) structures have attracted significant attention owing to their smooth surface configuration and parametric modeling properties. In this study, photo-curing 3D printing was employed to generate diamond-type TPMS structures, and micro-CT scanning revealed the presence of internal defects within the 3D printed TPMS structures. Two key design variables were explored: volume fraction and unit cell size. Quasi-static compression experiments were conducted to delve into the compression properties and energy absorption capabilities of the 3D printed TPMS structures. The findings reveal that increasing the volume fraction significantly enhances the compressive modulus, ultimate strength, and energy absorption capacity of TPMS structures. Additionally, increasing the cell size improves compression properties and energy absorption per unit volume. To predict the coupling effect of volume fraction and unit cell size on the compression performance of TPMS structures, a bivariate quadratic regression model was established. In addition, TPMS structures were subjected to load-unload cyclic experiments, shedding light on the evolution patterns of residual strain and hysteresis energy during cyclic loading. It provides insights into the design of reusable and fatigue-resistant diamond-type TPMS structures for various engineering applications.

An experimental and numerical study on chloride transport in concrete under single bending load and coastal soft soil environment

This paper presents an experimental and numerical simulation study on the corrosion of chloride ions in concrete components, using a single pre-applied bending load to represent an additional bending moment caused by an external one-off disturbance. Besides, a novel correlation testing method, the Pearson-Mutual Information (PMI) method, is proposed based on Pearson correlation coefficients and mutual information theory. The findings indicate that a significant effect on chloride ion transport is only observed when the ratio of the applied bending load to the ultimate bending load (λ) exceeds 0.3. There is a distinctly positive and nonlinear relationship between λ and free chloride concentration (CCl), the apparent chloride diffusion coefficient (Da), as well as apparent surface chloride concentration (Cs). The bivariate time-varying model developed in this study demonstrates high fitting accuracy, with simulation results that closely correspond to actual measured data, achieving a coefficient of determination (R²) of 0.98 or higher. Furthermore, a sensitivity analysis of the model input parameters indicates that Cs is more sensitive than Da, and λ is identified as the key parameter. The impacts of the interfacial transition zone (ITZ) and its diffusion coefficient (Ditz) were found to be minimal on the output of the model.

Biofilm formation and antibiogram profile of bacteria from infected wounds in a general hospital in southern Ethiopia

Biofilm-producing bacteria associated with wound infections exhibit exceptional drug resistance, leading to an escalation in morbidity, worse clinical outcomes (including delay in the healing process), and an increase in health care cost, burdening the whole system. This study is an attempt to estimate the prevalence and the relationship between the biofilm-forming capacity and multi-drug resistance of wound bacterial isolates. The findings intended to help clinicians, healthcare providers and program planners and to formulate an evidence-based decision-making process, especially in resource-limited healthcare settings. This study was done to assess the prevalence of bacterial infections in wounds and the antibiogram and biofilm-forming capacity of those bacteria in patients with clinical signs and symptoms, attending a General Hospital in southern Ethiopia. A cross-sectional study was performed in Arba Minch General Hospital from June to November 2021. The study participants comprised 201 patients with clinically infected wounds. Demographic and clinical data were gathered via a structured questionnaire. Specimens from wounds were taken from each participant and inoculated onto a series of culture media, namely MacConkey agar, mannitol salt agar, and blood agar, and different species were identified using a number of biochemical tests. Antimicrobial susceptibility tests were performed by means of the Kirby-Bauer disc diffusion technique following the guidelines of the Clinical and Laboratory Standards Institute. A micro-titer plate method was employed to detect the extent of biofilm formation. Bivariable and multivariable logistic regression models were applied to analyse the association between dependent and independent variables, and P values ≤ 0.05 were considered as statistically significant. Data analyses were done with Statistical Package for the Social Sciences version 25. Out of the 201 clinically infected wounds, 165 were found culture-positive with an overall prevalence of 82% (95% CI: 75.9–86.9). In total, 188 bacteria were recovered; 53.1% of them were Gram-positive cocci. The often-isolated bacterial species were Staphylococcus aureus, 38.3% (n = 72), and Pseudomonas aeruginosa, 16.4% (n = 31). The Gram-positive isolates showed considerable resistance against penicillin, 70%, and somewhat strong resistance against tetracycline, 57.7%. Gram-negative isolates showed severe resistance to ampicillin, 80.68%. The overall multi-drug resistance (MDR) among isolates was 48.4%. Extended beta-lactamase (ESBL)-producing Gram-negatives and methicillin-resistant Staphylococcus aureus (MRSA) accounted for 49 and 41.67%, respectively; 62.2% of the isolates were biofilm formers and were correlated statistically with MDR, ESBL producers, and MRSA (P < 0.005). The extent of biofilm formation and the prevalence of MDR bacteria associated with infected wounds hint at a public health threat that needs immediate attention. Thus, a more balanced and comprehensive wound management approach and antimicrobial stewardship program are essential in the study setting.

Diagnostic performance of deep learning for infectious keratitis: a systematic review and meta-analysis

Infectious keratitis (IK) is the leading cause of corneal blindness globally. Deep learning (DL) is an emerging tool for medical diagnosis, though its value in IK is unclear. We aimed to assess the diagnostic accuracy of DL for IK and its comparative accuracy with ophthalmologists. In this systematic review and meta-analysis, we searched EMBASE, MEDLINE, and clinical registries for studies related to DL for IK published between 1974 and July 16, 2024. We performed meta-analyses using bivariate models to estimate summary sensitivities and specificities. This systematic review was registered with PROSPERO (CRD42022348596). Of 963 studies identified, 35 studies (136,401 corneal images from >56,011 patients) were included. Most studies had low risk of bias (68.6%) and low applicability concern (91.4%) in all domains of QUADAS-2, except the index test domain. Against the reference standard of expert consensus and/or microbiological results (seven external validation studies; 10,675 images), the summary estimates (95% CI) for sensitivity and specificity of DL for IK were 86.2% (71.6-93.9) and 96.3% (91.5-98.5). From 28 internal validation studies (16,059 images), summary estimates for sensitivity and specificity were 91.6% (86.8-94.8) and 90.7% (84.8-94.5). Based on seven studies (4007 images), DL and ophthalmologists had comparable summary sensitivity [89.2% (82.2-93.6) versus 82.2% (71.5-89.5); P=0.20] and specificity [(93.2% (85.5-97.0) versus 89.6% (78.8-95.2); P=0.45]. DL models may have good diagnostic accuracy for IK and comparable performance to ophthalmologists. These findings should be interpreted with caution due to the image-based analysis that did not account for potential correlation within individuals, relatively homogeneous population studies, lack of pre-specification of DL thresholds, and limited external validation. Future studies should improve their reporting, data diversity, external validation, transparency, and explainability to increase the reliability and generalisability of DL models for clinical deployment. NIH, Wellcome Trust, MRC, Fight for Sight, BHP, and ESCRS.

Mortality and its predictors among patients with Guillain–Barré syndrome in the intensive care unit of a low-income country, Ethiopia: a multicenter retrospective cohort study

BackgroundGuillain–Barré syndrome (GBS) is a rare autoimmune disease that affects the peripheral nervous system. It is characterized by the destruction of nerves involved in movement. This condition can lead to transient pain, changes in temperature and touch sensations, muscle weakness, loss of sensation in the legs and/or arms, and difficulty swallowing or breathing. Published data on the outcomes of critical care for patients with GBS are extremely scarce in Africa, particularly Ethiopia. Therefore, this study aimed to assess mortality and its predictors among patients with GBS in the intensive care unit (ICU) of specialized hospitals in Ethiopia, a low-income country.Materials and methodsThis retrospective cohort study was conducted at the Tibebe Ghion Specialized Hospital and the Felege Hiwot Comprehensive Specialized Hospital in Bahir Dar, Ethiopia, from 1 January 2019 to 30 December 2023. Data were collected in the medical record rooms. Cox regression analysis was performed to identify the predictors of mortality among GBS patients in the ICU. The crude and adjusted hazard ratios (AHRs) and 95% confidence intervals (CIs) were calculated using bivariable and multivariable Cox regression models. A p-value of &amp;lt;0.05 was considered statistically significant.ResultsOf 124 GBS patients admitted to the ICU, 120 were included in the final analysis. During the follow-up, there were 23 (19.17%) deaths. The overall incidence rate of death was 1.96 (95% CI: 1.30, 2.95) per 100 person-days of observation. Traditional medicine (AHR = 3.11, 95%: 1.12, 16.70), COVID-19 infection (AHR = 5.44, 95% CI: 1.45, 73.33), pre-ICU cardiac arrest (AHR = 6.44, 95% CI: 2.04, 84.50), and ICU readmission (AHR = 4.24, 95% CI: 1.03, 69.84) were identified as the independent predictors of mortality.ConclusionThe mortality rate among GBS patients admitted to the ICU was high. Traditional medicine, COVID-19 infection, pre-ICU cardiac arrest, and readmission to the ICU were the significant predictors of mortality. Conducting large-scale studies with a prospective design in the future would yield more robust evidence.

Latent change-on-change between amyloid accumulation and cognitive decline.

While the influence of cross-sectional β-amyloid (Aβ) on longitudinal changes in cognition is well established, longitudinal change-on-change between Aβ and cognition is less explored. A series of bivariate latent change score models (LCSM) examined the relationship between changes in 11C-Pittsburgh Compound-B (PiB) positron emission tomography (PET) and the Preclinical Alzheimer's Cognitive Composite-5 (PACC-5) while adjusting for covariates, including cross-sectional medial temporal lobe (MTL) tau-PET burden. We selected 352 clinically normal older participants with up to 9 years of PiB-PET and PACC-5 data from the Harvard Aging Brain Study (HABS). Aβ accumulation was associated with subsequent cognitive decline beyond the effects of cross-sectional Aβ burden. Within this model including covariates such as age, sex, and apolipoprotein ε4 (APOEε4) status, we found no evidence supporting previously published associations between cross-sectional tau-PET and cognitive intercept/slope. Short-term Aβ changes are significantly associated with cognitive decline in clinically normal older adults and may eclipse the effect of cross-sectional Aβ and MTL tau. Aβ accumulation is associated with subsequent cognitive decline. High Aβ burden is not the sole metric signaling impending cognitive decline. Contrary to prior work, MTL tau-PET and cognition were not associated in our models. Models of bivariate latent Aβ and cognitive change may eclipse theeffects of MTL tau.