Univariate Analysis Research Articles

Factors Associated With Adverse Outcomes Among Patients Undergoing Endovascular Revascularization for Iliac Artery Lesions TASC II A and B: A Single-Center Study.

This prospective study from October 2016 to September 2020 aimed to identify the factors associated with non-revascularization and mortality rates in patients who underwent endovascular interventions for Trans-Atlantic Inter-Society Consensus (TASC) II A/B iliac artery occlusions at the Department of Vascular Surgery. Patients with TASC II A/B iliac artery occlusions who underwent endovascular intervention, including balloon angioplasty and stent placement, were included. The primary outcomes were factors associated with non-revascularization and mortality rate. A total of 133 patients were enrolled in this study. Univariable analysis revealed significant associations between non-revascularization and diabetes (hazard ratio [HR]=2.61, 95% confidence interval [CI], p=0.03), chronic kidney disease (HR=16.2, 95% CI, p=0.01), and severe calcifications (HR=8.56, 95% CI, p<0.001). Subsequent multivariable analysis confirmed the significance of these factors, showing HRs of 3.04 (95% CI, p=0.02), 13.12 (95% CI, p=0.03), and 8.62 (95% CI, p<0.001), respectively. The overall mortality rate observed was 20.3%. Severe calcifications emerged as a significant risk factor for mortality in both univariable (HR=2.47, 95% CI, p=0.02) and multivariable (HR=3.01, 95% CI, p<0.001) analyses. Severe calcifications correlate with non-revascularization and mortality, while comorbidities like diabetes mellitus and chronic kidney disease are also associated with non-revascularization. Recognizing these identified factors holds substantial promise in enhancing patient selection and procedural approaches, potentially bolstering the success rates of endovascular interventions. However, further research aimed at comprehending the underlying mechanisms and devising strategies to mitigate these risks is imperative for continued improvement in patient outcomes. The study provides valuable insights into patient selection and procedural planning for endovascular interventions in TASC II A/B iliac artery occlusions. Identifying severe calcifications, diabetes, and chronic kidney disease as key risk factors for non-revascularization and mortality equips clinicians with essential predictive tools, potentially improving outcomes by tailoring treatment approaches. The innovation lies in highlighting the impact of comorbidities and calcification severity, offering a pathway to refine patient eligibility criteria and optimize procedural decisions. This underscores the importance of further research to develop strategies that mitigate these risk factors and enhance intervention success rates.

Novel perspectives on early diagnosis of acute compartment syndrome: the role of admission blood tests.

The role of admission blood indicators in patients with acute compartment syndrome (ACS) remains debated. Our primary purpose was to observe variations of admission blood indicators in patients with ACS, while our secondary goal was to explore potential biomarkers related to ACS. We collected information on patients with tibial fracture between January 2013 and July 2023, and divided them into ACS and non-ACS groups. Propensity score matching (PSM) analysis was performed to lower the impact of potential confounding variables such as demographics and comorbidities. Admission blood indicators were analyzed using univariate, logistic regression, and receiver operating characteristic (ROC) curve analyses. Then, we established a nomogram prediction model by using R language software. After propensity PSM analysis, 127 patients were included in each group. Although numerous blood indicators were found to be relevant to ACS on univariate analysis, logistic regression analysis showed that monocytes (MON, p = 0.015), systemic immune-inflammation index(SII, p = 0.011), and creatine kinase myocardial band (CKMB, p < 0.0001) were risk factorsfor ACS. Furthermore, ROC curve analysis identified 0.79×109/L, 1082.55, and 20.99U/L as the cut-off values to differentiate ACS patients from patients with tibial fracture. We also found that this combination had the highest diagnostic accuracy. Then, we constructed a nomogram prediction model with AUC of 0.869 for the prediction model, with good consistency in the correction curve and good clinical practicality by decision curve analysis. We found that the levels of MON, SII, and CKMB were related to ACS and may be potential biomarkers. We also identified their cut-off values to separate patients with ACS from those with tibial fracture, helping orthopedists promptly evaluate and take early measures. We established a nomogram prediction model that can efficiently predict ACS in patients with tibial fracture.

Identification of Molecular Subtypes and Prognostic Traits Based on Chromosomal Instability Phenotype-Related Genes in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) exhibits significant molecular heterogeneity; however, previous studies have not fully explored its classification into distinct molecular subtypes. Here, we identified LUAD-significant chromosomal instability (CIN) phenotype genes (n = 24) using a TCGA-LUAD cohort (n = 592) and evaluated their ability to predict pathologic grade. Unsupervised clustering and principal component analysis revealed that LUAD patients could be classified into CIN phenotype-related subtypes (GroupLow, GroupModerate, and GroupHigh), each exhibiting distinct transcriptomic patterns. Notably, the GroupHigh showed significantly poor overall survival [OS; hazard ratio (HR) = 1.43, p-value &lt; 10−3] and disease-free survival (DFS; HR = 1.27, p-value &lt; 10−3). Univariate and multivariate analysis confirmed that its expression status was an independent prognostic predictor (p-value &lt; 10−3, HR = 2.18, 95% C.I = 1.26–3.76) of the clinical outcomes, outperforming pathologic grade (p-value &lt; 10−3, HR = 1.2, 95% C.I = 1.08–1.33). Moreover, analysis of surfactant metabolism-related genes revealed higher expression in the GroupLow, which was associated with a favorable prognosis. By integrating multiple independent cohorts (n = 779), we validated these findings and confirmed that CIN phenotype gene status serves as a critical prognostic marker in LUAD. Furthermore, genomic profiling showed that the GroupHigh exhibited frequent mutations in key genes such as KEAP1, LYST, SETD2, and TP53, with oncogenes in this group preferentially showing copy number gains. Our study highlights the significance of CIN phenotype gene status as a predictor of LUAD prognosis and its association with transcriptomic and genomic alterations, paving the way for further clinical validation and potential therapeutic interventions.

Investigation on the mechanical uncertainty of resistance spot weldings and its effect on structure crashworthiness of automotive B-pillars under side impacts

Resistance spot welding (RSW) is the main connection method for the white body structure of automobiles. Understanding the mechanical uncertainty of RSWs and its effect on structure crashworthiness design is of great significance for vehicle safety and lightweight design. In this work, the mechanical uncertainty of RSW was experimentally investigated and its effect on automotive B-pillar crashworthiness under side impacts was numerically analyzed based on a hybrid response surface model (HRSM). Firstly, the mechanical uncertainty of RSWs and associated failure mechanism were investigated and the fluctuation range of RSW strength under different loading conditions were quantified according to experimental results. Then, a reasonable RSW modeling method and subsystem collision simulation approach were demonstrated and the univariate sensitivity analysis was carried out to reveal the effect of RSWs’ mechanical property on B-pillar crashworthiness. Finally, a HRSM integrating Kriging polynomial and deep neural network (DNN) were proposed as surrogate model, based on which the multi-factor analysis was conducted to explore effects of RSW strength uncertainty on structure crashworthiness design.

Radio-pathomic estimates of cellular growth kinetics predict survival in recurrent glioblastoma.

Aim: A radio-pathomic machine learning (ML) model has been developed to estimate tumor cell density, cytoplasm density (Cyt) and extracellular fluid density (ECF) from multimodal MR images and autopsy pathology. In this multicenter study, we implemented this model to test its ability to predict survival in patients with recurrent glioblastoma (rGBM) treated with chemotherapy.Methods: Pre- and post-contrast T1-weighted, FLAIR and ADC images were used to generate radio-pathomic maps for 51 patients with longitudinal pre- and post-treatment scans. Univariate and multivariate Cox regression analyses were used to test the influence of contrast-enhancing tumor volume, total cellularity, mean Cyt and mean ECF at baseline, immediately post-treatment and the pre- and post-treatment rate of change in volume and cellularity on overall survival (OS).Results: Smaller Cyt and larger ECF after treatment were significant predictors of OS, independent of tumor volume and other clinical prognostic factors (HR=3.23×10-6, p<0.001 and HR=2.39×105, p<0.001, respectively). Both post-treatment volumetric growth rate and the rate of change in cellularity were significantly correlated with OS (HR=1.17, p=0.003 and HR=1.14, p=0.01, respectively).Conclusion: Changes in histological characteristics estimated from a radio-pathomic ML model are a promising tool for evaluating treatment response and predicting outcome in rGBM.

Establishment and validation of a nomogram for predicting postoperative intestinal adhesion in children with acute appendicitis.

This study aims to explore the value of multiple indicators in the evaluation of risk factors for intestinal adhesion (IA) after appendectomy in children with acute appendicitis (AA). A retrospective study was conducted on 608 patients who underwent appendectomy in the Department of Pediatric Surgery, Children's Medical Center of Jilin Province from January 2017 to April 2023, with a one-year follow-up period to record the occurrence of IA after appendectomy. Univariate and multivariate analysis were used to screen the risk factors of postoperative IA, and a prediction model was established to predict postoperative IA. There were 527 patients in the non-IA group and 81 patients in the IA group. Binary Logistic regression was used to determine the strength of correlation with postoperative intestinal adhesion. The risk factors identified were as follows: DS ≥ 43h (OR = 3.903, 5points), CRP ≥ 65mg/L (OR = 3.424, 4.5points), PCT ≥ 0.9µg/L (OR = 8.683, 8points), Surgical duration ≥ 100min (OR = 6.457, 7points), Appendiceal perforation (OR = 6.073, 6.5points), Postoperative exhaust time ≥ 55h (OR = 14.483, 10points). After test, the nomogram drawn based on binary logistic regression can obtain good prediction efficiency. In the training set, the area under the curve was 0.960, the sensitivity was 0.898, and the specificity was 0.905. In the test set, the area under the curve was 0.957, the sensitivity was 0.864, and the specificity was 0.906. Postoperative exhaust time ≥ 55h has a high risk of IA after appendicitis surgery in children. Early recovery of intestinal peristalsis function is essential. This scoring model is a novel and promising method for predicting postoperative IA.

Lipid metabolism-related gene signature predicts prognosis and unveils novel anti-tumor drugs in specific type of diffuse large B cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is the most common type of lymphoma which possess highly aggressive and heterogeneous. Despite advances in understanding heterogeneity and development of novel targeted agents, the prognosis of DLBCL patients remains unsatisfied. Lipids are crucial components of biological membranes and signal transduction while accumulating evidence has supported the vital roles of abnormal lipid metabolism in tumorigenesis. Furthermore, some related pathways could serve as prognostic biomarkers and potential therapeutic targets. However, the clinical significance of abnormal lipid metabolism reprogramming in DLBCL has not been investigated. In the current study, we developed a prognostic risk model for DLBCL based on the abnormal expressed lipid metabolism genes and moreover based on our risk model we classified patients with DLBCL into novel subtypes and identified potential drugs for DLBCL patients with certain lipid metabolism profiles. We utilized univariate Cox regression analysis to identify the prognosis-related lipid metabolism genes, and then performed LASSO Cox regression to identify prognostic related lipid metabolism related genes. Multivariate cox regression was used to establish the prognostic model. Patients were divided in to high and low risk groups based on the median risk score. Immune cell infiltration and GSEA were used to identify the pathways between high and low risk groups. Oncopredict algorithm was utilized to identify potential drug for high-risk patients. In vitro cell apoptosis and viability analysis were employed to verify the specific tumor inhibition effects of AZD5153. Nineteen survival related lipid metabolism genes TMEM176B, LAYN, RAB6B, MMP9, ATAD3B, SLC2A11, CD3E, SLIT2, SLC2A13, SLC43A3, CD6, SIRPG, NEK6, LCP2, CTTN, CXCL2, SNX22, BCL6 and FABP4 were identified and subjected to build the prognostic model which was further verified in four external microarray cohorts and one RNA seq cohorts. Tumor immune microenvironment analysis and GSEA results showed that the activation of MYC targets genes rather than immunosuppression contribute to the poor survival outcome of patients in the high-risk group. AZD5153, a novel bivalent BET bromodomain inhibitor which could inhibit the transcription of MYC and E2F exhibited specific antitumor function for cells with high-risk score. Our results provide the first lipid metabolism-based gene signature for predicting the survival of patients with DLBCL. Furthermore, by determining novel subtypes with our lipid metabolism prognostic model we illustrated that drugs that compromising MYC target genes rather than immune checkpoint inhibitors may be beneficial to DLBCL patients with certain lipid metabolism profiles.

Development and validation of a risk prediction model for severe postoperative complications in elderly patients with hip fracture.

This study aimed to investigate risk factors associated with severe postoperative complications following hip fracture surgery in elderly patients and to develop a nomogram-based risk prediction model for these complications. A total of 627 elderly patients with hip fractures treated at Yongchuan Hospital of Chongqing Medical University from January 2015 to April 2024 were collected. 439 patients were assigned to the training cohort for model development, and 188 to the validation cohort for model assessment. The training cohort was stratified based on the presence or absence of severe complications. We employed LASSO regression, as well as univariate and multivariate logistic regression analyses, to identify significant factors. A nomogram was constructed based on the outcomes of the multivariate regression. The model's discriminative ability was assessed using the area under the receiver operating characteristic curve (AUC), while calibration plots and decision curve analysis (DCA) evaluated its calibration and stability. Internal validation was performed using the validation cohort. Out of the 627 patients, 118 (18.82%) experienced severe postoperative complications. Both LASSO regression and multivariate logistic analysis identified the modified 5-item frailty index (mFI-5) and the preoperative C-reactive protein to albumin ratio (CAR) as significant predictors of severe complications. The nomogram model, derived from the multivariate analysis, exhibited strong discriminative ability, with an AUC of 0.963 (95% CI: 0.946-0.980) for the training cohort and 0.963 (95% CI: 0.938-0.988) for the validation cohort. Calibration plots demonstrated excellent agreement between the nomogram's predictions and actual outcomes. Decision curve analysis (DCA) indicated that the model provided clinical utility across all patient scenarios. These findings were consistent in the validation cohort. Both the mFI-5 and CAR are predictive factors for severe postoperative complications in elderly patients undergoing hip fracture surgery.

Real-world predictors of dupilumab prescription in patients with chronic rhinosinusitis with nasal polyps.

Despite increasing dupilumab use for chronic rhinosinusitis with nasal polyps (CRSwNP), little is known about the factors influencing its use in real-world practice. We aimed to identify factors that may predict dupilumab prescription in CRSwNP patients who have undergone endoscopic sinus surgery (ESS). A single-institution, retrospective cohort study of patients who underwent ESS for CRSwNP between 2015 and 2023 was conducted. Demographics, comorbidities, 22-item sinonasal outcome test (SNOT-22) scores, and dupilumab prescription date were extracted from patient records. Intraoperative nasal mucus cytokine levels were measured using a multiplex bead assay. Univariate logistic regression analysis was performed to identify factors associated with dupilumab prescription, and multivariate logistic regression was used to adjust for surgery date. A total of 299 CRSwNP patients were included, including seventy (23.4%) who were prescribed dupilumab postoperatively. Patients were more likely to be prescribed dupilumab if they had asthma (odds ratio [OR] 2.304), aspirin-exacerbated respiratory disease (AERD, OR 3.375), elevated tissue eosinophils (OR 1.005), and higher 3-month postoperative SNOT-22 scores (OR 1.027). Patients prescribed dupilumab also had greater odds of having elevated mucus interleukin (IL)-5 (OR 1.128) and IL-13 (OR 1.213). When adjusting for surgery date, associated factors included: asthma (OR 2.444), AERD (OR 3.750), allergic rhinitis (OR 1.833), higher tissue eosinophils (OR 1.005), elevated 3-month SNOT-22 scores (OR 1.028), and higher IL-5 (OR 1.123) and IL-13 (OR 1.202) levels. Asthma, AERD, allergic rhinitis, and elevated tissue eosinophil, IL-5, and IL-13 levels are predictive of dupilumab prescription in CRSwNP patients. These may serve as clinical and inflammatory biomarkers and can aid in counseling patients about expected disease trajectory.

Prevalence and Antibiotic Resistance of Streptococcus agalactiae in Women of Childbearing Age Presenting Urinary Tract Infections from Western Romania

Urinary tract infections (UTIs) are a common bacterial infection in women of childbearing age. Streptococcus agalactiae (Group B Streptococcus—GBS), a rare causative pathogen of UTIs in this population, is particularly important due to the potential risk during pregnancy, when it can lead to life-threatening neonatal infections. The current study analyzed 17,273 urine samples collected from consecutive women aged 18–45 years from Arad County, Western Romania. A total of 2772 samples tested positive for UTIs. In 130 cases, GBS was identified as the causative agent. Univariate logistic regression analysis revealed that women aged 25–34 years were more likely to test positive for GBS than those aged 18–24 years (cOR = 1.91, 95% CI: 1.07–3.43, p = 0.03). Antibiotic sensitivity testing revealed that all GBS strains were fully sensitive to penicillin, ampicillin, and vancomycin. High resistance was observed for clindamycin (77.34%) and tetracycline (88.46%). While GBS was found to be a rare pathogen in UTIs, our results underscore the importance of monitoring GBS in women of childbearing age, especially due to its risks during pregnancy, and emphasize the need for appropriate antibiotic management.

A Note on the Determinants of IFRS Policy Choice When Accounting for Non‐controlling Interest and Goodwill

This paper provides evidence on the choices made by European firms when measuring non‐controlling interest (NCI) and goodwill. Since 2009, IFRS 3 allows measurement of NCI either at fair value (full goodwill method) or at the proportionate share of net assets (partial goodwill method). IFRS 3 allows this policy choice on a per transaction basis. Our data comprise 188 hand‐collected firm choices in connection with business combinations with remaining NCI, between 2010 and 2016. We use the theoretical framework developed by Stadler and Nobes (2014) explaining differences in firms’ choices of overt accounting options by country, industry, and firm‐specific topic factors. Based on univariate and multivariate analyses, we find that transaction‐specific and firm‐specific topic factors influence accounting policy choice, whereas country and industry factors do not. The choice has different effects on financial leverage and operating returns, which inform firm‐level preferences. Regarding choices made at the transaction level, we find acquirers with an intention to buy additional shares from non‐controlling shareholders tend to prefer the full goodwill method. Thus, the choice of accounting method conveys information to users about future additional acquisitions and has implications for standard setters, indicating that offering choices at transaction level may increase the forward‐looking content of financial statements.

Development and validation of survival nomograms for patients with anaplastic thyroid carcinoma: a SEER program-based study.

We aimed to study the prognostic risk factors affecting patients with anaplastic thyroid carcinoma (ATC), develop a clinical prognostic model, and assess patient survival outcomes. Patients with anaplastic thyroid carcinoma from 2000 to 2019 were selected from the Surveillance, Epidemiology, and End Results (SEER) Program to extract the clinical variables used for analysis. The dataset was divided into training (70%) and validation (30%) sets based on a 7:3 ratio. Univariate and LASSO regression analyses were performed on clinical variables from the training set to identify independent prognostic factors. Independent prognostic factors were determined by Univariate and lasso regression according to the clinical variables of the training set, and a nomogram model was established to construct a prognostic model based on the contribution degree of the predictors. The prognostic model was evaluated and internally verified by C-index, ROC curve and calibration curve. A total of 713 ATC patients were included in the SEER database. LASSO regression results indicated that age, marital status, race, tumor size, whether the primary lesion was limited to the thyroid gland, surgery, radiotherapy and chemotherapy, were associated with overall survival(OS) prognosis of ATC, and were used to construct nomograms. In the training cohort, the OS nomogram's C-index was 0.708 (95% CI 0.672-0.745); in the internal validation cohort, the C-index was 0.677 (95% CI 0.620-0.735). ROC curves demonstrated that the OS nomogram exhibits excellent predictive accuracy and discriminative ability. Calibration curves indicated strong consistency between the OS nomogram's predicted survival rates and actual survival rates. We established a survival prediction model for ATC, which can assist clinicians in assessing patient prognosis and making personalized treatment decisions.

Double Materiality Approach and Sustainable Business Model Paradigm: A Three-Fold Analysis

Adopting the United Nations 2030 Agenda for Sustainable Development, governments commit to the 17 goals and 169 associated targets in areas of critical importance for humanity and planet, while companies manifest a growing interest in playing a significant role to SDGs prioritisation. Researchers, policymakers, stakeholders, and analysts are all preoccupied about responsible ways of redesigning the business model to mitigate the growing concerns, such as companies’ failures, global multidimensional crisis, and sustainability-related issues. Under the light of institutional theory, legitimacy theory, stakeholder theory, the aim of this research is to investigate how environmental, social and governance (ESG) policies and practices included in a sustainable business model may respond to the double materiality approach in order to contribute to a balance among divergent interests of managers, investors, and other stakeholders. The financial materiality is conceptualized using ESG data, that mainly targets investor’s needs. Stakeholder materiality, is concerned with external impact of companies, embodied in societal-level outcomes measured as the number of SDGs addressed in corporate reporting. In this study, company-year data are collected from Refinitiv Eikon database, starting with 2015, until current reporting period and analysed using frequency, univariate and correlation analyses. Based on Levene homogeneity, the ANOVA parametric t-test results are validated by Mann-Whitney Wilcoxon and Krushkal Wallis non-parametric tests. Three main research questions are responded. First, the findings examine and discuss the evolution of sustainability reporting measured with ESG scores, decomposed by the three pillars and ten categories, along with the SDGs prioritisation. Second, statistically significant differences in ESG and SDGs variables reported by various groups clustered on industry-related corporate characteristics are discussed. Third, the significant associations between ESG measures and SDGs are analysed from the double materiality perspective. The study contributes to the academic and practical understanding of the evolving business model under normative dimension of institutional theory, incorporating the decision to engage in current sustainability frameworks and policies.

Evaluating the causal association between circulating plasma proteins, 731 immune cell phenotypes, and atopic dermatitis: A mediation Mendelian randomization study.

Atopic dermatitis (AD) is a chronic inflammatory skin disease characterized by eczematous lesions and severe itching. However, its pathogenesis has not yet been fully elucidated. The aim of this study was to investigate the causal relationship between plasma proteins and AD, as well as to identify and quantify the potential roles of immune cell phenotypes as mediators. We utilized summary-level data from genome-wide association studies and conducted a two-sample Mendelian randomization (MR) analysis involving 4907 circulating plasma proteins, 731 immune cell phenotypes, and AD. Initially, we conducted bidirectional univariate MR analyses to forecast causal effects linking circulating plasma proteins and AD. Subsequently, we employed a two-step MR analysis to scrutinize the immune cell phenotypes that could mediate these effects. The inverse variance weighted was the main method employed for MR analysis, while the Cochran's Q test and MR-Egger intercept test were used to assess the presence of heterogeneity and pleiotropy, respectively. We then determined whether our results could be influenced by individual single-nucleotide polymorphisms using the "leave-one-out" test. Positive correlations were observed between KRT1, IL18R1, and SEMA6A and the risk of AD, whereas BDH2, ADAMTS3, ANKRD1, TIAM1, MID2, and IFNA16 all showed negative correlations with the risk of AD. Mediation analysis indicated that CD8 on CM CD8br cells acted as a mediator between IFNA16 and AD, with a mediation effect proportion of 11.2%. In addition, sensitivity analyses did not reveal significant heterogeneity or level pleiotropy. Our findings indicated the presence of a one-way causal relationship between the circulating plasma protein IFNA16 and AD. This study also explored immune cell phenotypes that may serve as mediators, offering novel insights into the etiology, pathogenesis, and potential clinical interventions in AD. Nevertheless, these findings need to be validated by clinical and laboratory studies.

Cost-effectiveness of diagnostic technologies for mycobacterium tuberculosis infection in India and Brazil.

The economic value of new skin-based tests and blood-based interferon-γ release assays (IGRAs) for tuberculosis (TB) infection is not yet well-established. This study evaluates the cost and cost-effectiveness in two high-burden countries by comparing:(a) new skin-based tests(Diaskintest and Cy-Tb) with the purified protein derivative (PPD)-tuberculin test (TST);(b) IGRAs (Standard E TB-Feron ELISA (TBF))with approved IGRAs (QuantiFERON-TB Gold Plus (QFT-GP)and TSPOT.TB); and (c) the best performing skin-based test with the best performing IGRA) based on cost effectiveness. In this paper, we developed a decision tree model for India and Brazil from a health system perspective. To quantify the effect of parameter variability and uncertainty, we performed both univariate and probabilistic sensitivity analysis. The study findings reveal that among skin-based tests, the Diaskintest is more cost-effective compared to TST-PPD at 22.6 USD and 41.0 USD per correctly diagnosed case of TB infection for Brazil and India, respectively. For blood-based assays, TSPOT.TB outperforms QFT-GP and TBF due to its lower cost and higher effectiveness. When compared with Diaskintest, TSPOT.TB has an incremental cost of approximately 8 USD and 6 USD for India and Brazil respectively but is more effective. The incremental cost-effectiveness ratio (ICER) was 74 USD and 55 USD for India and Brazil, respectively. In summary, while Diaskintest is potentially cost-saving when compared to TSPOT.TB in these two high-burden TB countries but the TSPOT.TB demonstrates higher effectiveness.

Risk factors for surgical site infection after general surgery in HIV-infected patients: a retrospective study.

As the number of HIV-infected patients increased, the number of patients requiring general surgery has subsequently increased. However, impairment of immune function due to HIV infection increases the risk of postoperative surgical-site infection and significant harm to patient health. This study aimed to examine the risk factors for surgical-site infection after general surgery. The patients' data were from Zunyi fourth hospital medical information system. Machine learning based Boruta algorithm were used for variable screening. Univariable and multivariable logistic regression and restricted cubic spline analysis were performed to examine the relationship between significant variables and surgical-site infection. A total of 125 general surgery postoperative HIV-infected patients participated in the study. Surgical-site pathogen culture identified Escherichia coli, Klebsiella pneumoniae, and mixed bacteria as the three most common pathogens causing Surgical-site infection. Univariable and multivariable logistic regression analysis to adjust for risk factors identified type III surgical incision (OR = 9.92, 95% CI = 1.28-76.75) and elevated preoperative white blood cell (WBC) count (OR = 1.30, 95% CI = 1.12-1.51) as independent risk factors for postoperative surgical-site infection, whereas CD4 + T lymphocyte count greater than 400 cells/µL was identified as a protective factor (OR = 0.23, 95% CI = 0.09-0.60) while. The restricted cubic spline analysis results directly reflected the dose-response relationship between continuous variables and postoperative surgical-site infection. Type III incision and an elevated WBC count pose a higher risk of postoperative surgical-site infection. A CD4 + T lymphocyte counts greater than 400 cells/µL provided a protective effect of lower risk of surgical site infection. Preoperative serum neutrophil percentage, albumin level, red blood cell count, and serum urea level within a specific range were beneficial in reducing the risk of incisional infections. Our research provides a theoretical basis for clinical practice.

OGC SO37 - Pyloric drainage interventions for delayed gastric conduit emptying after oesophagectomy: A single centre analysis

Abstract Background Oesophagectomy in combination with perioperative multimodal therapy is the cornerstone of modern curative treatment for resectable oesophageal cancer. Delayed gastric emptying (DGE) is a common postoperative complication that results from the anatomical and physiological changes in the gastric conduit after an oesophageal resection. It is associated with an increased risk of pneumonia, anastomotic leak and prolonged hospital stay. Although several prophylactic pyloric drainage interventions have been postulated to mitigate the risk of DGE, the optimal modality remains debatable. This study aimed to define the incidence, evaluate prognostic factors, and characterise the management of DGE following oesophagectomy. Method Consecutive patients who underwent an oesophagectomy for oesophageal cancer between January 2022 and March 2024 were retrospectively identified from a hospital database. Pyloric drainage procedures consisted of expectant management, endoscopic/open pyloric Botox and pyloroplasty. Univariable and multivariable analyses were performed to define the incidence of DGE after each pyloric drainage modality, evaluate prognostic factors for DGE, and characterise the need for subsequent intervention in the management of DGE. Results The study cohort comprised 137 patients – mean age 66 years, male 78%. The incidence of DGE was 31%. Pyloroplasty had the lowest incidence of DGE (16%) followed by endoscopic botox (21%). Intra-operative pyloric drainage reduced the risk of DGE (p=0.03). The modality of prophylactic pyloric drainage used significantly influenced the risk of developing DGE (p=0.028). No significant differences were identified between patient demographics, operative approach, and oncological variables in the development of DGE. On multivariable analysis, pyloroplasty was associated with a reduced risk of DGE (OR 0.27, 95% CI 0.09 – 0.71). DGE did not influence overall survival. Conclusion DGE is a common postoperative complication which affects up to 39% of patients undergoing oesophagectomy. Patients who did not undergo a prophylactic pyloric drainage procedure during the index oesophagectomy were at an increased risk of developing DGE. Most patients with DGE (71%) require further intervention via endoscopy and botox injection. Pyloroplasty as a prophylactic drainage modality significantly reduced the risk of developing DGE compared to endoscopic botox. Further prospective randomised controlled trials are required to validate these findings.

Indexing status of orthodontic research published in presumed predatory journals: a bibliometric study.

To examine the frequency and features of presumed predatory orthodontic publications. We also aimed to assess the presence of these types of publications in established scientific databases. Six electronic databases were searched to identify orthodontic articles published in 2022 in English. Equal numbers of articles from legitimate (n = 159) and suspect or predatory journals (n = 159) were considered. Data regarding journal, article and author characteristics were obtained. The indexing status of the publications in PubMed, Ovid, Embase, Web of Science, Scopus and EBSCOhost was evaluated. The total number of databases that the article was indexed in, level of evidence, origin of first author and research funding were recorded. Univariable ordinal regression analyses were performed to explore potential association between article legitimacy and indexing status. The majority of studies in predatory journals were found in non-specialized journals (79.6%). Scopus was the most porous database, indexing over half of predatory and suspect articles (56%). In Web of Science (Core collection), the distribution of articles across different indexing categories varied (SCIE; 16.4%, ESCI; 30.2%). In contrast, only 8.2% of these articles appeared in Medline. Articles in legitimate journals tended to have higher level of evidence and were indexed in more databases in comparison to predatory/suspect publications (OR=1.5; 95% CI: 1.37-1.64; p<0.01). The origin of the first author was a significant predictor for journal legitimacy (p<0.001). A high proportion of orthodontic publications appear in presumed predatory and suspect journals which are in turn often indexed in trustworthy databases. Medline was the least susceptible to predatory publications, while Web of Science and Scopus were more prone. Predatory and suspect journals are increasingly prevalent with the penetration of these journals into recognized databases. We were able to identify associated trends.

Quality of newborn care and associated factors: An analysis of the 2022 Kenya demographic and health survey.

Kenya one of the African countries has pledged to reduce neonatal death as per the 2030 World Health Organization target. Providing high-quality newborn care is critical in minimizing neonatal mortality. This study aimed to determine the factors that influence the quality of newborn care in Kenya. Secondary data from 11,863 participants of the 2022 Kenya Demographic and Health Survey (KDHS) were analyzed. The participants were chosen using two-stage stratified sampling. The quality of newborn care was operationalized as receiving all components of newborn care after childbirth, as reported by the mother. Using SPSS (version 29), univariate and multivariable logistic regression analyses were used to analyse the data. In this study, 32.7% (95% confidence interval [CI]: 31.0%-34.5%) of the mothers reported that their newborns had received all components of quality neonatal care after childbirth. Mothers who spent an average of one hour accessing the health facilities compared with those who spent less than half an hour were 1.33 (95%CI: 1.01-1.75) times more likely to report that their newborns had received quality newborn care. Mothers who gave birth in a non-government organization health facility were 30.37 (95%CI: 2.69-343.20) times more likely to report that their newborns had received quality newborn care compared with those who delivered from a faith-based organization. On the contrary, in terms of regions, mothers who lived in Nyanza, Eastern, and Rift Valley provinces compared with those who lived in the coastal regions were 0.53 (95%CI: 0.34-0.82), 0.61 (95%CI: 0.39-0.94), and 0.62 (95%CI: 0.41-0.93) times less likely to report that their newborns had received quality newborn care, respectively. Mothers who subscribed to other religions or faith (0.28 (95%CI: 0.10-0.76) compared with those from the Christian faith, were less likely to report that their newborns had received quality newborn care. Finally, mothers who gave birth through cesarean section were 0.44 (95%CI: 0.32-0.61) times less likely to report that their newborns had received quality newborn care than mothers who gave birth through spontaneous vaginal delivery. The study indicates that about a third of the neonates received quality newborn care and that facility-related and parental social factors were associated with receiving quality newborn care. Stakeholders need to pay more attention to newborn babies whose mothers come from certain regions of Kenya where the quality of newborn care was found to be low, minority religious faith denominations, and those who delivered by ceasearen section. Stakeholders also should focus on strengthening collaborations with NGO health facilities and achieving universal health coverage to improve the quality of newborn care provided in health facilities.

The Effect of Compensation on Job Satisfaction of Regional Public Service Agency (BLUD) Nurses and Organizational Citizenship Behavior (OCB) at RSUD Bayu Asih Purwakarta

Introduction: Organizational Citizenship Behavior (OCB) is the behavior of employees that goes beyond their formal obligations, is very important in supporting organizational performance. Good job satisfaction is often associated with increased OCB, while compensation is a key factor in influencing employee job satisfaction. This study was conducted at RSUD Bayu Asih Purwakarta, especially for BLUD nurses, to determine the effect of compensation on job satisfaction and its impact on OCB. Objective: This study aims to analyze the effect of compensation on job satisfaction and Organizational Citizenship Behavior (OCB) in BLUD nurses at RSUD Bayu Asih Purwakarta. Methods: This study used quantitative methods with a cross-sectional approach. The study was conducted from March-September 2024. Data were collected from 76 BLUD nurses at RSUD Bayu Asih Purwakarta through questionnaires. Analysis of research data using univariate analysis explains the characteristics of variables, while bivariate analysis examines the influence between variables using chi-square. This study uses path analysis to test the causal relationship between variables that have been determined bivariate. Data processing was carried out with the SPSS version 25 statistical program. Results: The results showed that there was a significant influence between compensation and nurses' job satisfaction, indicated by a p-value of 0.001 (&lt;0.05). In addition, compensation also has a significant influence on the application of OCB with a p-value of 0.005 (&lt;0.05). The effect of job satisfaction on OCB is also significant with a p-value of 0.000 (&lt;0.05). The contribution of the effect of compensation on job satisfaction and its impact on OCB is 43.9%, indicating the important role of job satisfaction as a mediator in this relationship. Conclusion: Adequate compensation can increase nurses' job satisfaction and Organizational Citizenship Behavior (OCB). Hospital management needs to increase compensation and improve supervisor-subordinate relationships to foster job satisfaction, so that voluntary behaviors such as OCB can develop, improving overall organizational performance.