bluuebunny/crossref_metadata_2025_split huggingface dataset:
18F-FDG PET/CT parameters for prediction of response to neoadjuvant therapy and prognosis in rectal cancer
Authors: Ebinç Senar , Güzel Yunus , Oruç Zeynep , Kömek Halil , Kalkan Ziya , Can Canan , Taşdemir Bekir , Urakçi Zuhat , Kaplan Muhammet Ali , Küçüköner Mehmet , Işikdoğan Abdurrahman 
Published: November 2022

Objective
This study aims to investigate the role of F-18 fluorodeoxyglucose PET/computed tomography (18F-FDG PET/CT) parameters in the prediction of treatment response and the prognosis in locally advanced rectal cancer.

Methods
We investigated the relationship of 18F-FDG PET/CT parameters [rectal metabolic tumor volume (MTV), rectal total lesion glycolysis (TLG), rectal standard uptake value (SUV) max, rectal highest peak SUV, lymph node MTV, lymph node TLG, lymph node highest peak SUV] with the pathological response and disease-free survival (DFS) in 60 patients who received neoadjuvant therapy for a diagnosis of locally advanced rectal cancer. Patients with a total score of 0 were assigned to the low-risk group, patients with a score of 1 were assigned to the intermediate-risk group and patients with a score of 2 were assigned to the high-risk group.

Results
The multivariate analysis revealed that, from baseline PET CT parameters, lymph node highest peak SUV strongly predicted the pathological response at a cutoff value of 2.23. DFS was predicted by the lymph node highest peak SUV at a cutoff value of 3.13 and by the MTV value at a cutoff value of 27 cm3. The risk scoring performed with regard to rectal MTV and lymph node highest peak SUV values determined a median DFS of 19 months in patients with a risk score of 2, whereas the median DFS was not reached in patients with risk scores of 0 and 1 (P < 0.001).

Conclusion
This study determined that rectal MTV and lymph node highest peak SUV predicted the response to neoadjuvant therapy and DFS.
The combined tumor-nodal glycolytic entropy improves survival stratification in nonsmall cell lung cancer with locoregional disease
Authors: Chen Yu-Hung , Lue Kun-Han , Chu Sung-Chao , Chang Bee-Song , Lin Chih-Bin 
Published: November 2022

Objective
To investigate whether combining primary tumor and metastatic nodal glycolytic heterogeneity on 18F-fluorodeoxyglucose PET (18F-FDG PET) improves prognostic prediction in nonsmall cell lung cancer (NSCLC) with locoregional disease.

Methods
We retrospectively analyzed 18F-FDG PET-derived features from 94 patients who had undergone curative treatments for regional nodal metastatic NSCLC. Overall survival (OS) and progression-free survival (PFS) were analyzed using univariate and multivariate Cox regression models. We used the independent prognosticators to construct models to predict survival.

Results
Combined entropy (entropy derived from the combination of the primary tumor and metastatic nodes) and age independently predicted OS (both P = 0.008) and PFS (P = 0.007 and 0.050, respectively). At the same time, the Eastern Cooperative Oncology Group status was another independent risk factor for unfavorable OS (P = 0.026). Our combined entropy-based models outperformed the traditional staging system (c-index = 0.725 vs. 0.540, P < 0.001 for OS; c-index = 0.638 vs. 0.511, P = 0.003 for PFS) and still showed prognostic value in subgroups according to sex, histopathology, and different initial curative treatment strategies.

Conclusion
Combined primary tumor-nodal glycolytic heterogeneity independently predicted survival outcomes. In combination with clinical risk factors, our models provide better survival predictions and may enable tailored treatment strategies for NSCLC with locoregional disease.
Cost Effectiveness of Universal Screening for Blunt Cerebrovascular Injury: A Markov Analysis
Authors: Ali Ayman , Broome Jacob M , Tatum Danielle , Abdullah Youssef , Black Jonathan , Simpson John Tyler , Salim Ali , Duchesne Juan , Taghavi Sharven 
Published: November 2022

Background:
Blunt cerebrovascular injury (BCVI) is a significant cause of morbidity and mortality following blunt trauma. Numerous screening strategies exist, although which is used is institution and physician dependent. We sought to identify the most cost-effective screening strategy for BCVI, hypothesizing that universal screening would be optimal among the screening strategies studied.

Study Design:
A Markov decision analysis model was used to compare the following screening strategies for identification of BCVI: (1) no screening (NS); (2) Denver criteria (DC); (3) extended Denver criteria (eDC); (4) Memphis criteria (MC); and (5) universal screening. The base-case scenario modeled 50-year-old patients with blunt traumatic injury excluding isolated extremity injures. Patients with BCVI detected on imaging were assumed to be treated with antithrombotic therapy, subsequently decreasing risk of stroke and mortality. One-way sensitivity analyses were performed on key model inputs. A single year horizon was utilized with an incremental cost-effectiveness ratio (ICER) threshold of $100,000 per quality-adjusted life-year (QALY).

Results:
The most cost-effective screening strategy for patients with blunt trauma among the strategies analyzed was universal screening. This method resulted in the lowest stroke rate, mortality, cost, and highest QALY. An estimated 3,506 strokes would be prevented annually as compared to eDC (ICER of $71,949 for universal screening vs. ICER of $12,736 for eDC per QALY gained) if universal screening were implemented in the United States. In one-way sensitivity analyses, universal screening was the optimal strategy when the incidence of BCVI was >6%.

Conclusion:
This model suggests universal screening may be the cost-effective strategy for BCVI screening in blunt trauma for certain trauma centers. Trauma centers should develop institutional protocols that take into account individual BCVI rates.
Population pharmacokinetics and exposure-response analysis of sotrovimab in the early treatment of COVID-19
Authors: Sager Jennifer E. , El-Zailik Asma , Passarell Julie , Roepcke Stefan , Li Xiaobin , Aldinger Melissa , Nader Ahmed , Skingsley Andrew , Alexander Elizabeth L. , Yeh Wendy W. , Mogalian Erik , Garner Chad , Peppercorn Amanda , Shapiro Adrienne E. , Reyes Maribel 
Published: November 2022

AbstractSotrovimab is a recombinant human monoclonal antibody that has been shown to prevent progression to hospitalization or death from severe disease in non-hospitalized high-risk patients with mild-to-moderate COVID-19 following either intravenous (IV) or intramuscular (IM) administration. Population pharmacokinetic (popPK) and exposure-response (ER) analyses were performed to characterize sotrovimab PK and the relationship between exposure and response (probability of progression), as well as covariates that may contribute to between-participant variability in sotrovimab PK and efficacy following IV or IM administration. Sotrovimab PK was described by a two-compartment model with linear elimination; IM absorption was characterized by a sigmoid absorption model. PopPK covariate analysis led to the addition of the effect of body weight on systemic clearance and peripheral volume of distribution, sex on IM bioavailability and first-order absorption rate (KA), and body mass index on KA. However, the magnitude of covariate effect was not pronounced and was therefore not expected to be clinically relevant based on available data to date. For ER analysis, sotrovimab exposure measures were predicted using the final popPK model. An ER model was developed using the exposure measure of sotrovimab concentration at 168 hours that described the relationship between exposure and probability of progression within the ER dataset for COMET-TAIL. The number of risk factors (≤1 vs >1) was incorporated as an additive shift on the model-estimated placebo response but had no impact on overall drug response. Limitations in the ER model may prevent generalization of these results to describe the sotrovimab exposure-progression relationship across SARS-COV-2 variants.
Comparison of AI-integrated pathways with human-AI interaction for population mammographic screening
Authors: Frazer Helen ML , Peña-Solorzano Carlos A , Kwok Chun Fung , Elliott Michael S , Chen Yuanhong , Wang Chong ,   the BRAIx team, Lippey Jocelyn , Hopper John , Brotchie Peter , Carneiro Gustavo , McCarthy Davis J 
Published: November 2022

AbstractArtificial intelligence (AI) holds promise for improving breast cancer screening, but many challenges remain in implementing AI tools in clinical screening services. AI readers compare favourably against individual human radiologists in detecting breast cancer in population screening programs. However, single AI or human readers cannot perform at the level of multi-reader systems such as those used in Australia, Sweden, the UK, and other countries. The implementation of AI readers in mammographic screening programs therefore demands integration of AI readers in multi-reader systems featuring collaboration between humans and AI. Successful integration of AI readers demands a better understanding of possible models of human-AI collaboration and exploration of the range of possible outcomes engendered by the effects on human readers of interacting with AI readers. Here, we used a large, high-quality retrospective mammography dataset from Victoria, Australia to conduct detailed simulations of five plausible AI-integrated screening pathways. We compared the performance of these AI-integrated pathways against the baseline standard-of-care “two reader plus third arbitration” system used in Australia. We examined the influence of positive, neutral, and negative human-AI interaction effects of varying strength to explore possibilities for upside, automation bias, and downside risk of human-AI collaboration. Replacing the second reader or allowing the AI reader to make high confidence decisions can improve upon the standard of care screening outcomes by 1.9–2.5% in sensitivity and up to 0.6% in specificity (with 4.6–10.9% reduction in the number of assessments and 48–80.7% reduction in the number of reads). Automation bias degrades performance in multi-reader settings but improves it for single-readers. Using an AI reader to triage between single and multi-reader pathways can improve performance given positive human-AI interaction. This study provides insight into feasible approaches for implementing human-AI collaboration in population mammographic screening, incorporating human-AI interaction effects. Our study provides evidence to support the urgent assessment of AI-integrated screening pathways with prospective studies to validate real-world performance and open routes to clinical adoption.
Diabetic control and compliance using HbA1C testing guidelines in public healthcare facilities of Gauteng province, South Africa
Authors: Ngalulawa Kone , Naseem Cassim , Innocent Maposa , Jaya Anna George 
Published: November 2022

ABSTRACTObjectiveThis study aimed at evaluating diabetic control and compliance with testing guidelines, across healthcare facilities of Gauteng Province, South Africa as well as factors associated with time to achieve control. South Africa’s estimated total unmet need for care for patients with type 2 diabetes mellitus is 80%.Research design, methods and findingsThe data of 511781 patients were longitudinally evaluated. Results were reported by year, age category, race, sex, facility and test types. HbA1c of ≤7 was reported as normal, >7 - ≤9 as poor control and >9% as very poor control. The chi-squared test was used to assess the association between a first-ever HbA1c status and variables listed above. The Kaplan Meier analysis was used to assess probability of attaining control among those who started with out-of-control HbA1C. The extended Cox regression model assessed the association between time to attaining HbA1C control from date of treatment initiation and several covariates. We reported hazard ratios, 95% confidence intervals and p-values.Data is reported for 511781 patients with 705 597 laboratory results. Poorly controlled patients constituted 51.5%, with 29.6% classified as very poor control. Most poorly controlled patients had only one test over the entire study period. Amongst those who started with poor control status and had at least two follow-up measurements, the likelihood of achieving good control was higher in males (aHR=1.16; 95% CI:1.12-1.20; p<0.001) and in those attending care at hospitals (aHR=1.99; 95% CI:1.92-2.06; p<0.001).ConclusionThis study highlights poor adherence to guidelines for diabetes monitoring.Author(s) summary-Worldwide, diabetes mellitus is an escalating public health crisis and, the second among the top ten leading natural causes of death in South Africa.-With most patients exhibiting poor control using HbA1C testing, this study undertook an audit to check the percentage of patients who follow testing guidelines for monitoring diabetes in the public healthcare facilities of Gauteng province, South Africa.-Overall, the guidelines for monitoring diabetes are not followed.-The study highlights the need to find innovative ways to improve monitoring of diabetic patients in an effort to curb complications of the disease.
Maternal diabetes and offspring use of dental services – Northern Ireland national cohort study
Authors: Salami Anas , Karim Ikhlas El , Lundy Fionnuala , Loney Tom , Donaldson Michael , O’Neill Ciaran 
Published: November 2022

AbstractIntroductionA small number of literature has posited a link between prenatal exposure to gestational diabetes mellitus and an increased risk of developmental defects in the enamel of offspring. However, the evidence remains inconclusive.AimsThis study examined the relationship between the diabetes status of mothers and the use of dental services by offspring to that pregnancy.Material and methodsAnonymised data from a cohort of mothers who carried a child to term in Northern Ireland between 2012 and 2017 and service use by the child were taken from administrative databases from March 2015 to September 2021. Descriptive statistics, differences in means and regression analyses were used to examine the relationship between service use and maternal diabetes status, controlling for covariates.ResultsIn multivariate analyses that controlled inter alia for age and deprivation, diabetes status was negatively related to restoration, extraction, prevention, and total service use. In the analysis of the COVID period, pre-COVID prevention was negatively related to extractions, restorations, prevention, and services in general.ConclusionThe relationship between maternal diabetic status and aspects of offspring use of dental services was contrary to that suggested in previous studies and warrants more detailed investigation using this valuable data resource.
Assessing the Causal Effect of Blood Pressure on Renal Cancer in the UK Biobank via Mendelian Randomisation
Authors: Clifton Lei , Liu Xiaonan , Collister Jennifer A , Littlejohns Thomas J , Hunter David J 
Published: November 2022

1.AbstractBackgroundHypertension is associated with increasing risk of renal cancer in observational studies, but there is insufficient evidence on whether hypertension is a causal factor for renal cancer.MethodsWe analysed data from 313,520 individuals of White British ancestry aged 40-69 years at baseline from the UK Biobank prospective cohort. We used polygenic risk scores (PRS) for SBP and DBP, respectively, in Mendelian randomisation analyses to assess the causal effect of blood pressure on renal cancer. Our primary outcome is renal-parenchyma cancer, and we used bladder cancer as a negative control. We conducted additional sensitivity analyses, using individual SNPs from the PRS as instruments, to ensure the MR results are robust.ResultsAmong the study population, 1159 participants developed renal-parenchyma cancer over the median of 12.5 years of follow-up. Every 5 mmHg increase in measured SBP and DBP was significantly associated with increased risk for renal-parenchyma cancer (HR: 1.04; 95% CI: 1.02-1.05; p < 0.001 and HR: 1.07; 95% CI: 1.03-1.10; p < 0.001 respectively). Consistent with observational association analyses, we observed statistically significant associations between each 5 mmHg genetically elevated BP and risk of renal-parenchyma cancer, with DBP (HR: 1.17; 95% CI: 1.07-1.27; p < 0.001) having a stronger association than SBP (HR: 1.09; 95% CI: 1.02-1.17; p = 0.009). These significant associations were maintained in sensitivity analyses. We observed a null association of genetically predicted blood pressure with bladder cancer.ConclusionsThese findings provide evidence that elevated BP is causally associated with renal-parenchyma cancer.
Midwifery care providers’ childbirth and immediate newborn care competencies: a cross-sectional study in Benin, Malawi, Tanzania and Uganda
Authors: Moller Ann-Beth , Welsh Joanne , Agossou Christian , Ayebare Elizabeth , Chipeta Effie , Dossou Jean-Paul , Gross Mechthild M , Houngbo Gisele , Hounkpatin Hashim , Kandeya Bianca , Mwilike Beatrice , Petzold Max , Hanson Claudia 
Published: November 2022

AbstractEvidence-based quality care is essential for reducing the high burden of maternal and newborn mortality and morbidity in sub-Saharan Africa. Provision of quality care results from interaction between several components of the health system including competent midwifery care providers. We assessed midwifery care providers’ childbirth and immediate newborn competencies as part of the Action Leveraging Evidence to Reduce perinatal morTality and morbidity (ALERT) project in Benin, Malawi, Tanzania, and Uganda. We used a self-administered questionnaire assessing knowledge, and skills drills observations assessing skills and behaviours in the 16 ALERT maternity wards. A total of 302 participants took part in the knowledge assessment and 113 skills drills were conducted. The assessments revealed knowledge gaps in frequency of fetal heart rate monitoring and timing of umbilical cord clamping. More than half of the participants scored poorly on aspects related to routine admission tasks, clinical history-taking and rapid and initial assessment of the newborn in the skills drills assessment, while higher scores were achieved in active management of the third stage of labour. The assessment also suggested a lack of involvement of women in decision-making, illustrated by the failure to encourage women to ask questions and failing to report clinical findings back to them. Participants furthermore indicated a lack of support from their managers, supervision and access to education and training resources. Inadequate competency level of the midwifery care providers may be due to gaps in pre-service training but possibly furthermore related to the structural and operational facility characteristics including continuing professional development. Investment and actioning on these findings are needed when developing and designing pre-service and in-service training to ensure women, newborns and families have access to evidence-based and quality midwifery care when needed.Trial registrationPACTR202006793783148—June 17th, 2020.
Predicting Alzheimer’s Disease with Multi-Omic Data: A Systematic Review
Authors: Davis Anthony , Mendoza Wilson , Leach Daniel , Marques Oge 
Published: November 2022

AbstractBackground and PurposeAlzheimer’s Disease (AD) is a complex neurodegenerative disease that has been becoming increasingly prevalent in recent decades. Efforts to identify predictive biomarkers of the disease have proven difficult. Advances in the collection of multi-omic data and deep learning algorithms have opened the possibility of integrating these various data together to identify robust biomarkers for predicting the onset of the disease prior to the onset of symptoms. This study performs a systematic review of recent methods used to predict AD using multi-omic and multi-modal data.MethodsWe systematically reviewed studies from Google Scholar, Pubmed, and Semantic Scholar published after 2018 in relation to predicting AD using multi-omic data. Three reviewers independently identified eligible articles and came to a consensus of papers to review. The Quality in Prognosis Studies (QUIP) tool was used for the risk of bias assessment.Results22 studies which use multi-omic data to either predict AD or develop AD biomarkers were identified. Those studies which aimed to directly classify AD or predict the progression of AD achieved area under the receiver operating characteristic curve (AUC) between .70 - .98 using varying types of patient data, most commonly extracted from blood. Hundreds of new genes, single nucleotide polymorphisms (SNPs), RNA molecules, DNA methylation sites, proteins, metabolites, lipids, imaging features, and clinical data have been identified as successful biomarkers of AD. The most successful techniques to predict AD have integrated multi-omic data together in a single analysis.ConclusionThis review has identified many successful biomarkers and biosignatures that are less invasive than cerebral spinal fluid. Together with the appropriate prediction models, highly accurate classifications and prognostications can be made for those who are at risk of developing AD. These early detection of risk factors may help prevent the further development of cognitive impairment and improve patient outcomes.
Calculating functional diversity metrics using neighbor-joining trees
Authors: Cardoso Pedro , Guillerme Thomas , Mammola Stefano , Matthews Thomas J. , Rigal Francois , Graco-Roza Caio , Stahls Gunilla , Carvalho Jose Carlos 
Published: November 2022

AbstractThe study of functional diversity (FD) provides ways to understand phenomena as complex as community assembly or the dynamics of biodiversity change under multiple pressures. Different frameworks are used to quantify FD, either based on dissimilarity matrices (e.g., Rao entropy, functional dendrograms) or multidimensional spaces (e.g. convex hulls, kernel-density hypervolumes). While the first does not enable the measurement of FD within a richness/divergence/regularity framework, or results in the distortion of the functional space, the latter does not allow for comparisons with phylogenetic diversity (PD) measures and can be extremely sensitive to outliers.We propose the use of neighbor-joining trees (NJ) to represent and quantify functional diversity in a way that combines the strengths of current FD frameworks without many of their weaknesses. Our proposal is also uniquely suited for studies that compare FD with PD, as both share the use of trees (NJ or others) and the same mathematical principles.We test the ability of this novel framework to represent the initial functional distances between species with minimal functional space distortion and sensitivity to outliers. The results using NJ are compared with conventional functional dendrograms, convex hulls, and kernel-density hypervolumes using both simulated and empirical datasets.Using NJ we demonstrate that it is possible to combine much of the flexibility provided by multidimensional spaces with the simplicity of tree-based representations. Moreover, the method is directly comparable with PD measures, and enables quantification of the richness, divergence and regularity of the functional space.