Maximum Likelihood Model Research Articles

Semiparametric Inference for Two-Phase Studies with Ordinal Outcomes

Background: The two-phase design is an increasingly used approach in health research. In Phase 1, broad data are collected on a large sample size, and in Phase 2, the correlation of auxiliary variables with an expensive variable is used to select a small but more informative sample. Objectives: Previous research on two-phase design has primarily focused on binary, continuous, and time-to-event outcomes. Recognizing the lack of research on ordinal outcomes, we propose a novel approach for three logit models with proportional odds: cumulative logit (CL), adjacent category (AC), and stopping ratio (SR). Additionally, we examine the validity of our method through four simulation scenarios with various outcome distributions. Methods: We have developed a semiparametric maximum likelihood model to incorporate Phase 1 data. An expectation-maximization (EM) algorithm was used to obtain the estimates while the Louis method was employed to calculate the covariance matrix. We compare the results estimated by our method with those obtained using only Phase 2 data under both simple random sampling and balanced outcome-dependent sampling (ODS). Results: In all experiments, balanced ODS led to reduced bias and higher relative efficiency, and the advantage was more noticeable with higher variability in sampling probability between the outcome categories. The EM method led to improved results in balanced ODS for the CL and SR models, but it was not as effective for the AC model. Conclusions: These findings suggest the efficacy of our method in incorporating Phase 1 data to enhance the quality of statistical estimates when used with balanced ODS.

Abstract 4136009: Adherence and Persistence to Guideline-Directed Medical Therapy in Patients with Heart Failure: A Systematic Review and Meta-Analysis

Introduction: Since individual adherence/persistence studies for heart failure (HF) guideline-directed medical therapy (GDMT) have mainly focused on single classes or had limited sample sizes, providing inconclusive estimates, a comprehensive analysis is needed to understand the magnitude of the problem. Hypothesis: Adherence and persistence to HF GDMT are suboptimal and are associated with increased risks of HF admission and mortality. Aims: To generate estimates of real-world HF medication adherence and persistence and associated clinical outcomes. Methods: We conducted a systematic review and meta-analysis, searching PubMed, EMBASE, and CINAHL for observational studies on adherence and persistence in HF GDMT from inception to 9/25/23. We evaluated bias using the Newcastle-Ottawa Scale. Primary outcomes were adherence and persistence rates using a restricted maximum-likelihood model. Adherence was summarized as the mean proportion of days covered (PDC) and medication possession ratio (MPR), proportion of patients with good adherence (PDC/MPR≥80%), and persistence. Secondary outcomes were all-cause mortality and HF readmission with summary hazard ratios (HRs) and 95% confidence intervals (CI) estimated. Heterogeneity and publication bias were assessed using Cochran’s Q, I squared statistics, funnel plots, and Egger's tests, while subgroup analyses explored variations across studies. Results: The 48 studies included comprised 1,614,985 patients (mean age 71; 57% men). The overall mean PDC/MPR was 76%, with good adherence of 54%, and persistence rates of 60%. Renin-angiotensin-aldosterone system inhibitors had the highest mean PDC/MPR of 78%, good adherence of 56%, and persistence of 64%, while mineralocorticoid receptor antagonists (MRAs) had the lowest at 71%, 47%, and 49% respectively. Nonadherence/nonpersistence to GDMT was associated with a higher rate of mortality (HR 1.27 [95% CI 1.19–1.35]) and HF admission (HR 1.25 [95% CI 1.14-1.37]). Conclusions: Suboptimal adherence/persistence to HF GDMT is common, with only half of patients showing good adherence. Given the association with worse clinical outcomes, clinicians should prioritize identifying barriers to and addressing nonadherence/nonpersistence to HF GDMT, particularly with MRAs.

EPID-34. THE EFFECT OF ANTIDEPRESSANT THERAPY ON GLIOBLASTOMA SURVIVAL: A SYSTEMATIC REVIEW AND META-ANALYSIS

Abstract BACKGROUND Symptoms of depression are highly prevalent among patients with glioblastoma (GBM) and have been associated with poor outcomes. In addition to managing depression symptoms, preclinical and clinical studies suggest that antidepressants may inhibit GBM progression and may be associated with improved outcomes. However, the effect of antidepressants on survival is unknown and results from existing studies are conflicting. OBJECTIVE We conducted a systematic review and meta-analysis to investigate the effect of antidepressant therapy on GBM survival. METHODS We searched PubMed, Embase, Scopus, PsycINFO, and Web of Science from inception to March 2024 for studies assessing the overall survival of patients with GBM treated with antidepressants. Prespecified Hazard ratios (HR), 95% confidence interval (CIs), median overall survival, and patient characteristics were extracted. Results were combined using a restricted maximum-likelihood estimation random-effects model. RESULTS We identified 6 observational studies meeting inclusion criteria with 8269 patients. Of these, 1093 (13%) were treated with antidepressant therapy at some point after their GBM diagnosis. Antidepressant therapy was not significantly associated with overall survival (HR 1.27, 95% CI 0.90-1.79, p=0.17). In a sub-analysis of studies that specified whether SSRIs were utilized, SSRI usage specifically was also not associated with overall survival (HR 1.08, 95% CI 0.58-2.03, p=0.81) We observed considerable heterogeneity (I2 = 92.7%, p<.001). CONCLUSIONS Antidepressants were not significantly associated with overall survival in patients with GBM. However, our meta-analysis was limited by significant heterogeneity observed across studies. The effect of antidepressants on outcomes in patients with GBM remains uncertain. We observed conflicting results in the literature, with some studies suggesting decreased survival. Therefore, the role of antidepressants in patients with GBM warrants further investigation.

A meta-analysis of the effects of sacubitril-valsartan on surrogate markers of systemic right ventricular dysfunction in congenital heart disease

Abstract Introduction Dysfunction of systemic right ventricle (sRV) in adult congenital heart disease (ACHD) patients is expectable and often associated with heart failure and other dismal cardiovascular events. Despite limited evidence, several neurohormonal modulators approved for heart failure with reduced ejection fraction (HFrEF) have been used off-label in patients with RV dysfunction1. Sacubitril-valsartan (ARNI) effects on sRV remains poorly studied, with current evidence being limited to small cohorts. Purpose Review and summarize current evidence about the effects of ARNI in ACHD patients with sRV. Methods We performed a systematic review on MEDLINE, EMBASE, COCHRANE, and SCOPUS for articles that included "systemic right ventricle" and "sacubitril valsartan" until January 2024. Two investigators screened the literature and extracted data. Treatment effects were measured by Cohen's d effect-size (EZ) pre and post-ARNI, with a 95% confidence interval (CI), using a restricted maximum likelihood model. Results From 197 publications screened, five studies fulfilled our criteria, comprising a total of 135 patients. Follow-up after ARNI therapy ranged from 12 to 27 months. No randomized clinical trials were found, and only two studies had a prospective design. Dextro-transposition of the great arteries (D-TGA) after atrial switch operation was the most common type of congenital heart disease with sRV (n=95; 70%). Meta-analysis demonstrates that ARNI reduced NT-proBNP levels during follow-up (EZ= -0.34, CI -0.59 to 0.08; p=0.01; I2=4.0%). Regarding RV function, ARNI improved RV fractional area change (RVFAC) (EZ= 0.75, CI 0.01 to 1.50; p= 0.048; I2=85.0%). A trend for RV global longitudinal strain improvement was also observed with ARNI (EZ= 1.74, CI -0.05 to 3.54; p=0.06; I2=95.9%) but not for tricuspid annular plane systolic excursion (EZ= -0.07, CI -0.33 to 0.20; p=0.62; I2=0.0%). RV diastolic diameter did not change significantly with ARNI (EZ= 0.07, CI -0.43 to 0.56; p=0.79; I2=68.2%). A trend for improvement on the 6-minute walk test was observed (EZ= 1.89, CI -0.13 to 3.91; p=0.07; I2=96.3%), but no effect on exercise oxygen consumption (VO2) (EZ= -0.09, CI -1.32 to 1.15; p=0.89; I2=91.4%). During follow-up ARNI did not change significantly systolic blood pressure (EZ= -0.32, CI -0.74 to 0.11; p=0.15; I2=58.4%) or serum creatinine (EZ= 0.23, CI -0.04 to 0.49; p=0.09; I2=0.0%). Conclusions Despite heterogeneity among these studies, this meta-analysis demonstrates that ARNI might improve NT-proBNP levels and RV function. ARNI seems safe and well tolerated, with no significant effect on blood pressure and renal function. More well-powered studies are needed to confirm the beneficial effects of ARNI in ACHD with sRV.

Prevalence of anemia among coronavirus disease 2019 patients in Ethiopia: A meta-analysis

Coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2, impacting various systems in the human body, including the hematological and reticuloendothelial systems, which can alter blood production. Consequently, severe anemia-associated complications could occur in COVID-19 patients. At present, there is a lack of pooled prevalence data on anemia among COVID-19 patients in Ethiopia. This systematic review and meta-analysis aimed to determine the overall prevalence of anemia in this population. Following PRISMA guidelines, we conducted a literature search across PubMed/MEDLINE, Cochrane Library, Google Scholar, HINARI, and the Ethiopian Journal of Health Development for articles published before 2024. Additional manual searches were performed to identify relevant studies. Study selection, data extraction, and quality assessment were conducted independently by the authors. The I2 test statistics were used to assess heterogeneity among studies, and the overall prevalence was calculated using a random-effect restricted maximum likelihood model. Out of 860 studies obtained, 11 articles were included in the meta-analysis. The pooled prevalence of anemia among COVID-19 patients in Ethiopia was found to be 22.81% (95% CI [confidence interval]: 14.76 – 30.85%). Specifically, the prevalence of anemia in Addis Ababa and Amhara was 27.13% (95% CI: 14.59 – 39.66%) and 22.50% (95% CI: 11.04 – 33.96%), respectively. This study indicates that anemia is a moderate public health problem among COVID-19 patients in Ethiopia. Consequently, it is imperative to implement preventative interventions and management strategies for anemia in this population.

Oral anticoagulants or antiplatelets for cryptogenic stroke: a systematic review and meta-analysis

Abstract Background Cryptogenic strokes comprise 20 to 30% of ischemic strokes and include a substantial proportion classified as embolic stroke of undetermined source (ESUS). However, the optimal antithrombotic strategy for cryptogenic stroke remains contentious. Purpose We conducted a systematic review and meta-analysis to compare the efficacy and safety of oral anticoagulants (OAC) versus antiplatelets in patients with cryptogenic stroke. Methods Six electronic databases of PubMed, Embase, Web of Science, the Cochrane Library, Google Scholar and ClinicalTrials.gov were searched from inception to Feb 15, 2024 to identify relevant randomized controlled trials (RCTs) comparing stroke recurrence and major bleeding rates between OAC and antiplatelets in cryptogenic stroke patients. We included trials adhering to a stringent diagnostic work-up for cryptogenic stroke, defined as cerebral infarction not attributed to definite sources of cardioembolism, large artery atherosclerosis, or small artery disease despite undergoing comprehensive investigations. The primary outcome was recurrent ischemic stroke, and the secondary outcome was major bleeding based on International Society of Thrombosis and Hemostasis criteria. Subgroup analysis was conducted for ESUS patients with an increased risk of cardiac emboli, such as patent foramen ovale (PFO) and atrial cardiopathy, defined as lead V1 terminal P-wave > 5000 μV × ms in electrocardiogram, serum N-terminal pro-B-type natriuretic peptide level > 250 pg/mL, and left atrial diameter (LAE) > 4 cm, or LAE index ≥ 3 cm/m2 on echocardiogram. Hazard ratio (HR) with 95% confidence (CI) was used as a measure of the effect estimates for aforementioned outcomes. Random-effects meta-analysis was performed using a restricted maximum likelihood model given between-study variance is inevitable. Results Our meta-analysis included 9 RCTs with a total of 15,139 patients (OAC = 7,343; antiplatelets = 7,796). ARCADIA, RE-SPECT ESUS, and NAVIGATE ESUS Trial investigated apixaban, dabigatran, and rivaroxaban, respectively, while warfarin was primarily used as OAC in the remaining six trials. Aspirin was predominantly utilized for antiplatelet therapy. There was no significant difference in recurrent ischemic stroke between OAC and antiplatelets (HR, 0.90; 95% CI, 0.78 to 1.04; I2 = 0%). However, OAC use was associated with a significantly higher risk of major bleeding (HR, 1.66; 95% CI, 1.07 to 2.56; I2 = 36%). Subgroup analysis in ESUS patients revealed comparable rates of recurrent ischemic stroke in those with atrial cardiopathy (HR, 0.91; 95% CI, 0.65 to 1.29; I2 = 0%) and PFO (HR, 0.72; 95% CI, 0.49 to 1.07; I2 = 0%). Conclusions Our meta-analysis suggests that OAC use does not decrease the risk of recurrent ischemic stroke compared with antiplatelet use but is associated with a significantly higher risk of major bleeding in patients with cryptogenic stroke.Primary (A) and secondary (B) outcomesSubgroup analysis for recurrent stroke

Knowledge, Attitudes, and Practices of Pregnant Women and Hospital Staff Regarding Umbilical Cord Blood Banking: Systematic Review and Meta-Analysis.

The aim of this study is to assess the knowledge, attitudes, and practices of pregnant women and hospital staff regarding umbilical cord blood (UCB) donation and storage to understand its limitations in clinical practice. MEDLINE, Scopus, LILACS, EMBASE, Scielo.br, and PROSPERO were searched from inception to 30 November 2023 with no geographic or language restrictions. The study eligibility criteria included cross-sectional studies that interviewed pregnant women and/or hospital staff about their knowledge, attitudes, and practices regarding private or public storage. A random-effects restricted maximum-likelihood model with Freeman-Tukey Double arcsine transformation meta-analysis was carried out to calculate the pooled estimates. MOOSE guidelines were followed. STATA 14.1 was used for statistical analysis. The Newcastle-Ottawa Scale and ROBINS-I tool were used for quality and risk of bias assessments. In total, 19 studies providing data for 19,904 pregnant women and 1245 hospital staff members were included. Pooled pregnant women awareness was 61% ((95% CI 0.60 to 0.62), I2 = 0%, τ2 = 0.00, Q = 11.0 (p = 0.950)), and 61% for hospital staff (95% CI 0.58 to 0.64), I2 = 0%, τ2 = 0.00, Q = 4.00 (p = 0.310)). In total, 57% ((95% CI 0.56 to 0.58), I2 = 0, τ2 = 0.00, Q = 4.00 (p = 0.320)) of pregnant women had a positive attitude about UCB, while 34% ((95% CI 0.32 to 0.36), I2 = 0%, τ2 = 0.00, Q = 4.00 (p = 0.310)) were in favor of donating UCB for research and 65% ((95% CI 0.63 to 0.66), I2 = 0%, τ2 = 0.00, Q = 4.0 (p = 0.350)) were planning UCB storage. A significant (p < 0.001) preference for public relative to private banking (51% ([95% CI 0.49 to 0.54], I2 = 0%, τ2 = 0.00, Q = 4.0 (p = 0.310)) vs. 12% ([95% CI 0.10 to 0.13], I2 = 0%, τ2 = 0.00, Q = 4.0 (p = 0.300))) was noted for pregnant women. The same was retrievable for professionals (84% ([95% CI 0.79 to 0.88], I2 = 0%, τ2 = 0.00, Q = 2.0 (p = 0.110)) vs. 6% ([95% CI 0.03 to 0.09], I2 = 0%, τ2 = 0.00, Q = 1.0 (p = 0.070); p < 0.001)). Despite these efforts, lack of knowledge and positive attitudes about UCB banking remain, emphasizing the need for increasing educational programs on the subject.

Correlations and Variations Between the Major Biochemical Parameters of the Blood of Hybrid Swine.

In modern animal husbandry, increasing attention is given to mathematical modeling and statistical methods, especially for evaluating commercial hybrids. Our aim was to evaluate the phenotypic and genetic variability of biochemical parameters of blood serum of the 56 hybrid boars (Large White × Landrace × Duroc) raised in feeding stations (Russia) through mathematical modeling. The particular variances and covariances of traits were calculated using the limited maximum likelihood model and the REMLF90 programs. A narrow range of variability was found for major biochemical parameters in relationship with the "FFG-factor" ("fattening period × final live weight × gain"), including the majority of the metabolites (p ≤ 0.05). The highest values of the genetic correlations were observed for the "total protein" parameter with albumins (0.78), globulins (0.94), creatinine (0.99), and enzymes: AST (0.98), ALT (0.80), etc. Phenotypic and genetic relationships showed fairly high correlation coefficients (0.5-0.8). It is important to emphasize that most of the studied amino acids (alanine, arginine, aspartic acid and asparagine, glutamic acid and glutamine, glycine, isoleucine, leucine, serine, threonine, tyrosine, valine) were significantly associated with the "FFG-factor" (p ≤ 0.05). The proposed approach provides reliable data on metabolite variability and correlations.

Genetic variability and diversity analysis for some agronomic traits of a sweet potato (Ipomoea batatas L.) collection: Insights for breeding superior genotypes

A study was conducted during the 2017 cropping season to assess the genetic variability of selected agronomic traits in sweet potato. A total of 355 sweet potato genotypes (351 from different countries of the world and four check varieties) were evaluated at Tuber Crops Research Sub Centre, Bangladesh Agricultural Research Institution, Bogura, Bangladesh. The experiment was conducted using an augmented randomized complete block design. Findings revealed positive correlations among five agronomic traits, namely the weight of marketable storage root per plant (MRW), weight of storage root per plant (RW), fresh weight of foliage per plant (FW), number of marketable storage root per plant (MRN) and number of storage root per plant (RN) suggesting their suitability for phenotypic selection. There was a positive skewness in most studied traits (FW, MRW, MRW and RW), indicating the presence of a few genotypes with exceptionally high values for those traits. By employing principal component analysis, the most influential traits in sweet potato genotypes were identified for first two components (Dim) showing significant contributions to Dim-1 and Dim-2 collectively accounting for 84.7 % of the total variance. Through cluster analysis, two main clusters (Cluster I and Cluster II) were identified among the studied genotypes, each characterized by distinct trait patterns. Cluster I demonstrated superior performance in all traits, while Cluster II exhibited lower values for all traits. Further sub-clustering within Cluster II (sub-clusters IIA and IIB) revealed additional variations of the collection. The Euclidean distance for inter-cluster (ranging from 7.94 to 11.39) and intra-cluster (ranging from 3.17 to 10.38) were determined utilizing the complete distance method. In restricted maximum likelihood (REML) model, all the traits were significantly influenced by genetic effects, with broad-sense heritability ranging from 32 % to 70 %. The REML displayed high selection accuracy, with values exceeding 91 % for studied traits. The Multi-Trait Genotype-Ideotype Distance Index (MGIDI) identified 18 genotypes, with Moz1.15 emerging as the best-performing genotype under a 5 % selection pressure. Among the selected genotypes, trait uniqueness was highest for FW (54 %), followed by RN (50 %), MRN (18 %), MRW (14 %), and RW (5 %). The selection gain for these top-ranked genotypes varied between 23.2 % and 69.2 %. Findings established the existence of useful genetic variability for selected agronomic traits of sweet potato that could be exploited for breeding, genetics study and conservation.

Systematic Review and Meta-Analysis: Iron Deficiency and Iron Deficiency Anemia Among Military Recruits Undergoing Basic Combat Training

ABSTRACT Introduction The first period of military service consists of a physically and mentally challenging basic combat training (BCT) program. Factors like demanding physical exercise, limited recovery time, and restricted diet choice and food intake may challenge iron intake and homeostasis in recruits undergoing BCT. Iron-deficient individuals may experience reduced work capacity, fatigue, weakness, frequent infections, and increased injury risk. Limited knowledge is available on the extent of this potential health risk among military recruits. The aim of the present study was to systematically review published studies on the prevalence and change in prevalence of anemia, iron deficiency (ID), and ID anemia (IDA) among recruits undergoing BCT. Materials and Methods Electronic searches were conducted in the databases Medline (Ovid), Embase (Embase.com), and Web of Science (Clarivate Analytics) from database inception up until April 16, 2024. Inclusion criteria were observational studies with both cross-sectional and observational longitudinal designs that examined the effects of BCT (intervention) on iron status (outcome) in military recruits (population). Extracted data were the number of participants (n), age, sex, country/population, BCT duration, and relevant measures of prevalence and changes in prevalence of anemia, ID, and IDA (primary outcome) and physical performance, mood state, stress fractures, attrition rate, and nutritional supplements (secondary outcomes). The study quality and risk of bias were assessed using the JBI Critical Appraisal Checklist for Studies Reporting Prevalence Data and The National Institutes of Health Quality Assessment Tool for Before-After (Pre-Post) Studies With No Control Group. Meta-analyses were performed using restricted maximum-likelihood models, and the effect size was calculated as Cohen’s h with 95% CI. Results Twenty-two articles were systematically reviewed (n = 111,764 men and 12,650 women), and six of these papers (n = 388 men and 773 women) were included in the meta-analysis. There was a varying prevalence of anemia, ID, and IDA among military recruits at the start of BCT. Results from meta-analyses showed negligible and nonsignificant effects of BCT on the prevalence of anemia, ID, and IDA. The quality of the included cross-sectional studies ranging from fair to good, whereas a large proportion of the included longitudinal studies were classified as poor. No sign of publication bias was found. Conclusions The prevalence of anemia, ID, and IDA in military recruits seems not to be affected by the completion of BCT shorter than 16 weeks, whereas the effects of longer BCT durations remain unclear. Even though body iron homeostasis seems unaffected, adequate energy and nutritional intake should remain a priority. Future research could focus on dietary interventions to determine the optimal diet among female recruits in specifically exposed populations.

Lessons learned during a 12-year monitoring project with the endangered Magdalena River turtle (Podocnemis lewyana): hunting pressure, habitat degradation, and methodological considerations

Turtle species in the Family Podocnemididae, including the Colombian endemic and critically endangered Magdalena River Turtle Podocnemis lewyana, characteristically present low recapture rates that preclude estimation of population parameters using maximum likelihood modeling. In our 12-year monitoring project with this species, we evaluated changes in relative abundances, proportions of sex/size classes, and individual body sizes and body conditions in a population in four channels in the middle Magdalena River drainage. We also inspected for associations between trends in changes in these variables and differences in hunting pressure and habitat degradation. To inspect for temporal and spatial demographic dynamics, we estimated variation in relative abundances using the Catch Per Unit Effort index, the total number of turtles captured over an entire 5-day sampling period using ten baited funnel traps. Relative abundances and the proportions of sex/size classes were different between sites and years. We found a significant decline in the proportion of females and juveniles over time, along with evidence that the females still present were smaller in body size. Our results support the hypothesis that hunting eliminates adult females from these sites, perhaps also translating into a reduction in recruitment. The lack of evidence of generalized declines in body condition of all size classes suggests that habitat degradation might contribute less to the population declines in this region. Our results also illustrate that even when recapture rates are low, monitoring turtles via standardized trapping may yield insights into the population’s conservation status that other relative abundance indices cannot.

The interdependence of caring, safety, and health in correctional settings: Analysis of a survey of security staff in a large county jail system

The health of incarcerated populations is intertwined with the health of security staff, but the social mechanisms, and especially the specific interventions, that might mitigate these health harms are underexplored. We examine one possible mechanism of interrelated health harms: whether and how jail security staff are willing and able to care for mentally ill detainees. We hypothesize that the attitudes of security staff towards care affect the well-being of everyone in a jail setting—staff, as well as detainees. Analyzing 539 anonymous respondent surveys administered to a stratified cluster sample of security staff working in a large U.S. county jail system, we (1) describe the prevalence of a perceived duty to care and availability of caring resources among security staff and (2) analyze whether variations in a duty to care and caring resources predict outcomes associated with staff and detainee well-being. Across five maximum likelihood models estimated, both perceived duty to care and availability of caring resources are significantly associated with collaborative relationships with medical staff, increased perceptions of personal safety, decreased frequency of hostile encounters, and better self-reported health outcomes. Our models explain 20 percent of the variation in self-reported health outcomes (R2 = .20), a meaningful effect of care on security personnel's well-being. Our findings suggest security staff have an often-overlooked duty to care akin to that experienced by healthcare staff. Among healthcare staff, dual loyalty trainings have successfully amplified caring duties relative to security duties; similar trainings for security staff might better leverage their caring duties to improve both staff and detainee well-being.

Immediate or delayed trial without catheter in acute urinary retention in males: A systematic review.

To compare the success of establishing spontaneous micturition following immediate trial without catheter (TWOC) to delayed TWOC in males catheterized for acute urinary retention. In this systematic review, we included studies reporting success rates of immediate TWOC or delayed TWOC (≤30 days) among males ≥18 years of age catheterized for acute urinary retention. We excluded studies on suprapubic catheterization, postoperative/perioperative catheterization and urinary retention related to trauma. We searched the following databases: MEDLINE, Embase, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Open Grey and Clinicaltrials.gov. The search was concluded on 30 November 2022. There were no restrictions on language or publication date. Risk of bias was assessed using the ROB 2.0 and ROBINS-I tools. We did random-effects restricted maximum likelihood model meta-analyses. Certainty of evidence was assessed using GRADE. We included 61 studies. In two randomized controlled trials (RCTs), both with some concerns for risk of bias, including in total 174 participants, the relative success rate was 1.22 (95% CI 0.84-1.76) favouring delayed TWOC. In two comparative cohort studies, both with serious risk of bias, including 642 participants, the relative success rate was 1.18 (0.94-1.47) favouring delayed TWOC. One study was excluded from this meta-analysis because of critically low quality. Four studies reporting success rates for cohorts with immediate TWOC, all with serious risk of bias, including 409 participants, had an overall success rate of 47% (29-66). Fifty-two studies reporting success rates for cohorts with delayed TWOC, all with serious risk of bias, including 12 489 participants, had an overall success rate of 53% (49-56). The certainty of the evidence was considered low for the RCTs and very low for the rest. There was a limited number of appropriately designed studies addressing the research question directly. The evidence favours neither approach.

In-silico mechanistic analysis of adsorption of Iodinated Contrast Media agents on graphene surface

The study aims at assessing the potential of graphene-based adsorbents to reduce environmental impacts of Iodinated Contrast Media Agents (ICMs). We analyze an extensive collection of ICMs. A modeling approach resting on molecular docking and Density Functional Theory simulations is employed to examine the adsorption process at the molecular level. The study also relies on a Quantitative Structure-Activity Relationship (QSAR) modeling framework to correlate molecular properties with the adsorption energy (Ead) of ICMs, thus enabling identification of the key mechanisms underpinning adsorption and of the key factors contributing to it. A collection of distinct QSAR-based models is developed upon relying on Multiple Linear Regression and a standard genetic algorithm method. Having at our disposal multiple models enables us to take into account the uncertainty associated with model formulation. Maximum Likelihood and formal model identification/discrimination criteria (such as Bayesian and/or information theoretic criteria) are then employed to complement the traditional QSAR modeling phase. This has the advantage of (a) providing a rigorous ranking of the alternative models included in the selected set and (b) quantifying the relative degree of likelihood of each of these models through a weight or posterior probability. The resulting workflow of analysis enables one to seamlessly embed DFT and QSAR studies within a theoretical framework of analysis that explicitly takes into account model and parameter uncertainty. Our results suggest that graphene-based surfaces constitute a promising adsorbent for ICMs removal, π-π stacking being the primary mechanism behind ICM adsorption. Furthermore, our findings offer valuable insights into the potential of graphene-based adsorbent materials for effectively removing ICMs from water systems. They contribute to ascertain the significance of various factors (such as, e.g., the distribution of atomic van der Waals volumes, overall molecular complexity, the presence and arrangement of Iodine atoms, and the presence of polar functional groups) on the adsorption process.

Diatom cell-size composition as a novel tool for quantitative estimates of the water table in peatlands.

Diatom cell-size composition is an indicator of aquatic environmental changes but has been rarely investigated, especially in semi-terrestrial peatlands. In this study, both taxonomic composition and cell-size composition of diatoms were analysed in 41 samples from two montane peatlands, northeastern China. Redundancy analyses revealed that diatom taxonomic composition was significantly related to the depth to the water table (DWT) and Ca2+, while cell-size composition was significantly associated with DWT and Si. DWT was the most important factor and its sole effect explained 26.2% and 17.9% of the total variance in taxonomic composition and cell-size composition, respectively. Accordingly, diatom-based water-table transfer functions were developed based on taxonomic composition and cell-size composition, respectively. The maximum-likelihood (ML) model based on diatom taxonomic composition had the best performance, with a correlation coefficient value (R2) of 0.78 and the root mean squared error of prediction (RMSEP) of 6.66 cm. The ML model based on cell-size composition had similar performance, with an R2 of 0.78 and the RMSEP of 6.87 cm, suggesting that diatom cell-size composition can be a new quantitative means to track past water-table changes. This method requires further appraisal with palaeoecological data but offers a new option that deserves exploration.

Banking sector and economic growth in the digital transformation era: insights from maximum likelihood and Bayesian structural equation modeling

PurposeIn the digital era, the banking sector has transformed into a powerful intermediary, effectively connecting surplus and deficit units. This dynamic landscape empowers savers to secure their finances and generate returns, while simultaneously enabling businesses and individuals to access capital for investment and promoting economic growth. This study explores the relationships among banking development dimensions – represented by primary assets and liabilities, bank capital (core capital and required reserves) and economic growth as measured by components of gross domestic product (GDP).Design/methodology/approachThe study consolidated monthly balance sheets from digital banks over a 20-year period, resulting in an aggregate monthly balance sheet that reflects the financial position of all digital banks in the Palestinian economy. The research employs both maximum likelihood and Bayesian structural equation modeling to measure the causal pathways of the consolidated balance sheet with the individual components of GDP.FindingsThe results revealed that bank main assets (investments and loans) and liabilities (deposits) collectively explain for 97% of bank capital. Investments and loans demonstrate significant negative correlations with bank capital, while deposits exhibit a positive impact. This leads to a fundamental conclusion that a substantial proportion of retained earnings within the banking sector is reinvested, fueling expansion and growth. Additionally, the results showed a significant relationship between bank capital and various GDP components, including private consumption, gross investment and net exports (p = 0.000). However, while the relationship between bank capital and government spending was insignificant in the maximum likelihood estimation, Bayesian estimation revealed a slight yet positive impact of bank capital on government spending.Originality/valueThis research stands out due to its unique exploration of the intricate relationship between bank sector development dimensions, primary assets and liabilities and their impact on bank capital in the digital era. It offers fresh insights by dividing this connection into specific dimensions and constructs, utilizing a comprehensive two-decade dataset covering the digital banks records.

Pemodelan Pengaruh Sektor Keuangan Terhadap Pertumbuhan Ekonomi Di Indonesia

The financial sector has a major influence on economic growth in Indonesia. Good modeling influences the accuracy of economic growth predictions and has an impact on the financial sector. Several models have been introduced to analyze the relationship between the two, but it is necessary to test which of these models is most appropriate. This research aims to find the best model of the financial sector's influence on economic growth in Indonesia. Three models were compared so that the best model was selected, namely the Bayesian Vector Autocorrelation (BVAR), Linear Regression, and Pseudo Poisson Maximum Likelihood (PPML) models. The comparison method was carried out to determine the best model from the third model using various criteria, and then an in-depth study of the best model was carried out by considering various diagnostic tests and stability tests. The analysis results show that the BVAR (2) model is the best model among the three existing models. However, some specific analysis results in the regression analysis model (such as the negative impact on CPS) and the PPML model (such as the high R-square) can be taken into consideration by policyholders in the financial sector in determining policies related to these areas for economic growth.

Mixture models for simultaneous classification and reduction of three-way data

AbstractFinite mixture of Gaussians are often used to classify two- (units and variables) or three- (units, variables and occasions) way data. However, two issues arise: model complexity and capturing the true cluster structure. Indeed, a large number of variables and/or occasions implies a large number of model parameters; while the existence of noise variables (and/or occasions) could mask the true cluster structure. The approach adopted in the present paper is to reduce the number of model parameters by identifying a sub-space containing the information needed to classify the observations. This should also help in identifying noise variables and/or occasions. The maximum likelihood model estimation is carried out through an EM-like algorithm. The effectiveness of the proposal is assessed through a simulation study and an application to real data.

Linear Mixed-Effects Models for Dependent Data: Power and Accuracy in Parameter Estimation

Linear mixed-effects models have been increasingly used to analyze dependent data in psychological research. Despite their many advantages over ANOVA, critical issues in their analyses remain. Due to increasing random effects and model complexity, estimation computation is demanding, and convergence becomes challenging. Applied users need help choosing appropriate methods to estimate random effects. The present Monte Carlo simulation study investigated the impacts when the restricted maximum likelihood (REML) and Bayesian estimation models were misspecified in the estimation. We also compared the performance of Akaike information criterion (AIC) and deviance information criterion (DIC) in model selection. Results showed that models neglecting the existing random effects had inflated Type I errors, unacceptable coverage, and inaccurate R-squared measures of fixed and random effects variation. Furthermore, models with redundant random effects had convergence problems, lower statistical power, and inaccurate R-squared measures for Bayesian estimation. The convergence problem is more severe for REML, while reduced power and inaccurate R-squared measures were more severe for Bayesian estimation. Notably, DIC was better than AIC in identifying the true models (especially for models including person random intercept only), improving convergence rates, and providing more accurate effect size estimates, despite AIC having higher power than DIC with 10 items and the most complicated true model.

Phylogenetic placement and comparative analysis of the mitochondrial genomes of Idiostoloidea (Hemiptera: Heteroptera).

The classification system and the higher level phylogenetic relationships of Pentatomomorpha, the second largest infraorder of Heteroptera (Insecta: Hemiptera), have been debated and remain controversial over decades. In particular, the placement and phylogenetic relationship of Idiostoloidea are not well resolved, which hampers a better understanding of the evolutionary history of Pentatomomorpha. In this study, for the first time, we reported the complete mitochondrial genome for two narrowly distributed families of Idiostoloidea (including Idiostolidae and Henicocoridae), respectively. The length of the mitochondrial genome of Monteithocoris hirsutus and Henicocoris sp. is 16,632 and 16,013 bp, respectively. The content of AT is ranging from 75.15% to 80.48%. The mitogenomic structure of Idiostoloidea is highly conservative and there are no gene arrangements. By using the Bayesian inference, maximum likelihood, and Bayesian site-heterogeneous mixture model, we inferred the phylogenetic relationships within Pentatomomorpha and estimated their divergence times based on concatenated mitogenomes and nuclear ribosomal genes. Our results support the classification system of six superfamilies within Pentatomomorpha and confirm the monophyletic groups of each superfamily, with the following phylogenetic relationships: (Aradoidea + (Pentatomoidea + (Idiostoloidea + (Coreoidea + (Pyrrhocoroidea + Lygaeoidea))))). Furthermore, estimated divergence times revealed that most pentatomomorphan superfamilies and families diverged during the Late Jurassic to Early Cretaceous, which coincides with the explosive radiation of angiosperms.