Category: Statistics

Br Dent J. 2025 Sep 5. doi: 10.1038/s41415-025-8719-y. Online ahead of print.

ABSTRACT

Purpose The aim of this study was to assess the effectiveness of a PEEK (polyether-ether-ketone) ultrasonic tip in the cleaning around implant-supported restorations and to evaluate the effect of different cement types on the amount of residual cement at the restoration margins.Materials and methods A master model with an implant analogue placed in the upper left first premolar region was used to create 72 cast models and zirconia crowns were fabricated for each model. A total of 72 zirconia crowns were divided into two main groups based on the cleaning method applied after cementation. In the first group, residual cement was cleaned using only a dental explorer, while in the second group, cleaning was enhanced by using a PEEK ultrasonic tip following the initial use of a dental explorer. Each main group was further divided into three subgroups according to the type of cement used: polycarboxylate cement, glass ionomer cement and resin cement. After cementation and cleaning, the zirconia crowns were detached from the models, and cement residue was digitally photographed from the buccal, lingual, mesial and distal surfaces. The percentage of residual cement was then evaluated using Adobe Photoshop via pixel-based digital analysis. Data were analysed using the Shapiro-Wilk test, Robust ANOVA and Bonferroni method test for multiple comparisons.Results Statistical analyses revealed a significant difference between the cleaning methods regardless of cement type (p = 0.002). The results demonstrated that cleaning with a PEEK ultrasonic tip significantly reduced residual cement compared to using a dental explorer alone. Among the tested cements, resin cement left the least residual cement, while glass ionomer and polycarboxylate cements left significantly more residue (p <0.001).Conclusions The findings emphasise the clinical advantages of the PEEK ultrasonic tip cleaning method. Additionally, resin cement demonstrated the lowest amount of residual cement.

PMID:40913142 | DOI:10.1038/s41415-025-8719-y

Br Dent J. 2025 Sep 5. doi: 10.1038/s41415-025-8716-1. Online ahead of print.

ABSTRACT

Introduction The COVID-19 pandemic significantly disrupted healthcare systems worldwide, including in Germany. This study investigated the impact of the pandemic on the management of dental abscesses and examined the implications for the upcoming German healthcare reform.Aims To assess how the COVID-19 pandemic affected hospitalisation, intensive care unit (ICU) admissions and treatment outcomes for dental abscesses, and to analyse the relationships between these findings and the German healthcare reform.Design Retrospective cohort study.Setting A major metropolitan hospital in Munich.Materials and methods In total, 200 patients (93 in 2019, 107 in 2020) with dental abscesses were studied. Data collected included demographics, pre-hospitalisation antibiotic use, ICU admissions, and length of stay (LOS). Statistical analysis compared the outcomes between the two years.Results ICU LOS significantly decreased in 2020 (3.3 days versus 13.7 days in 2019; p = 0.022). More patients in 2020 received antibiotics before hospitalisation and fewer required surgeries. Overall, hospital resource usage was more efficient in 2020.Discussion The pandemic emphasised the importance of preventive dental care. It highlighted how local dental offices can play a more significant role in managing dental emergencies, with potential implications for the German healthcare system’s future structure and resource allocation.Conclusion The COVID-19 pandemic reshaped dental emergency care and hospital resource usage. This shift has significant implications for the future organisation of healthcare, especially in the context of the German hospital reform.

PMID:40913141 | DOI:10.1038/s41415-025-8716-1

Obes Surg. 2025 Sep 6. doi: 10.1007/s11695-025-08210-y. Online ahead of print.

ABSTRACT

BACKGROUND: Bariatric surgery (BS) is the most effective treatment for severe obesity, but a significant proportion of patients experience insufficient weight loss (IWL) or weight regain. Glucagon-like peptide-1 receptor agonists (arGLP-1) have emerged as a promising adjunctive therapy for managing these suboptimal outcomes. This study evaluates the efficacy and safety of arGLP-1 in patients with IWL or WR after BS.

METHODS: A retrospective analysis was conducted on 100 patients who underwent BS (96 sleeve gastrectomy, 4 gastric bypass) and received arGLP-1 therapy (semaglutide or dulaglutide) for IWL (defined as < 50% excess weight loss (EWL) from baseline), and WR (a ≥ 10 kg increase from the nadir weight post-surgery). Data on weight loss, comorbidities, and adverse events were collected over a median follow-up of 1 year. Statistical analyses included paired t-tests, Wilcoxon signed-rank tests, and chi-squared tests.

RESULTS: At 1 year, patients achieved significant weight loss with a median total weight loss (%TWL) of 25.5% and a median excess weight loss (%EWL) of 66.3% compared to 16.6% and 40.8%, respectively, at treatment initiation with BMI reduction of 3.7 kg/m². Significant improvements were observed in comorbidities, including reductions in obstructive sleep apnea (- 30%), hypertension (- 40%), and arthralgia (- 56.5%). Glycated hemoglobin levels decreased by 0.8 points. Treatment was well-tolerated, with nausea being the most common side effect (5% discontinuation rate).

CONCLUSION: arGLP-1 are effective and safe for managing IWL or WR after BS, leading to significant weight loss, comorbidity improvement, and sustained %TWL. These findings support their use as a valuable adjunctive obesity management medication (OMMs) in post-bariatric care, though long-term adherence and cost-effectiveness require further investigation.

PMID:40913138 | DOI:10.1007/s11695-025-08210-y

Eur J Appl Physiol. 2025 Sep 6. doi: 10.1007/s00421-025-05969-x. Online ahead of print.

ABSTRACT

BACKGROUND: Musculoskeletal disease (MSD), including osteoarthritis, rheumatoid arthritis, osteoporosis, and sarcopenia, poses a serious social burden. While physical activity (PA) benefits musculoskeletal health, the optimal PA level for MSD prevention remains unclear. Clarifying risk factors and biological mechanisms is essential.

METHODS: This study included 9,113 adults aged 20-60 years from NHANES 2013-2018. Blood and urine specimens were used to analyze metabolic and inflammatory markers. PA was assessed using the Global Physical Activity Questionnaire. Multivariate logistic regression, generalized additive models and mediation analysis were used to evaluate the relationships among PA, biomarkers and MSD.

RESULTS: Among 9113 participants, 2685 (29.5%) had MSD. PA levels of 600-1200 MET-min/week were associated with the greatest MSD risk reduction (24%; 95% CI 0.62-0.93) compared with inactivity after full adjustment. Participants with MSD showed higher levels of metabolic and inflammatory markers and lower PA levels (P < 0.05). Mediation analysis revealed that atherogenic index of plasma (AIP), triglycerides (TG), neutrophils (NEU), total cholesterol (TC), and triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) acted as complementary mediators at the highly active PA level only, with mediation proportions of 12.4%, 7.6%, 6.1%, 6.0%, and 5.7%. While, lymphocytes (LYM) served as an indirect-only mediator across both active and highly active PA levels, accounting for 21.8% of the total effect.

CONCLUSION: In individuals aged 20-60 years, 600-1200 MET-min/week most effectively reduces MSD risk, with these associations likely mediated by metabolic and inflammatory markers. This study elucidates underlying biological mechanisms linking PA and MSD, highlighting potential metabolic and inflammatory pathways for prevention strategies.

PMID:40913129 | DOI:10.1007/s00421-025-05969-x

Eur J Hum Genet. 2025 Sep 6. doi: 10.1038/s41431-025-01929-3. Online ahead of print.

ABSTRACT

Congenital Anomalies of Kidney and Urinary Tract (CAKUT) can occur in isolation or in conjunction with one or more non-CAKUT associated congenital anomalies or neurodevelopmental disorders (CAKUT+). A molecular cause is not identified in most individuals with CAKUT+. This is due, in part, to uncertainty regarding the efficacy of genetic testing and an incomplete understanding of the genes that cause CAKUT+. Here, we use data from 515 individuals with CAKUT+ (n = 500) or isolated CAKUT (n = 15) to determine the efficacy of clinical exome sequencing (cES) and to identify new phenotype expansions that involve CAKUT. We determined that cES established a molecular diagnosis in 27.4% (141/515) of individuals in this cohort. No statistically significant difference in efficacy was seen with regards to age, sex, CAKUT phenotype, or associated organ system abnormality. Only 3.5% (5/144) to 14.6% (21/144) of the individual diagnoses made in our cohort could have been identified using one of four clinically available CAKUT gene panels. We then used a machine-learning approach to confirm that PHIP is a CAKUT gene and to implicate ADNP and SETD5 genes associated with an increased risk of CAKUT. These findings lead us to conclude that cES should be considered in individuals with CAKUT+ for whom a molecular diagnosis has not been identified, that cES has the potential to identify many diagnoses in individuals with CAKUT+ that would be missed using a CAKUT gene panel, and that individuals with ADNP-, PHIP-, and SETD5-related disorders may present with CAKUT phenotypes.

PMID:40913078 | DOI:10.1038/s41431-025-01929-3

Sci Rep. 2025 Sep 5;15(1):28716. doi: 10.1038/s41598-025-11890-2.

ABSTRACT

The processing-transportation composite robots, with their dual functions of processing and transportation, as well as comprehensive robot-machine interactions, have been widely and efficiently applied in the manufacturing industry, leading to a continuous increase in energy consumption. Hence, this work focuses on investigating robot-machine integrated energy-efficient scheduling in flexible job shop environments. To address the new problem, an innovative mixed-integer linear programming model and a novel dual-self-learning co-evolutionary algorithm are proposed, aimed at minimizing the total energy consumption and makespan. In the proposed algorithm, a three-dimensional vector is first used to comprehensively express the solution, and then a greedy decoding strategy is designed to reduce the idle time and energy consumption simultaneously. A hybrid initialization method with adaptive random selection and chaos mapping is developed to ensure the diversity and high quality of the initial solutions. A dual-self-learning mechanism, including a self-learning evolutionary mechanism and a self-learning cooperation mechanism, is designed to select suitable evolutionary operators and enhance interactions between populations, respectively. Finally, multiple sets of experiments are conducted to demonstrate the effectiveness of the proposed mathematical model, improved components and algorithm through numerical, statistical, and differential analyses.

PMID:40913072 | DOI:10.1038/s41598-025-11890-2

Br J Cancer. 2025 Sep 5. doi: 10.1038/s41416-025-03169-0. Online ahead of print.

ABSTRACT

BACKGROUND: Locally advanced nasopharyngeal carcinoma (LA-NPC) has a heterogeneous prognosis, with approximately one-fourth of patients experiencing poor outcomes. Studies have explored the application of induction chemoimmunotherapy followed by chemoradiotherapy, but its efficacy was controversial.

METHODS: The protocol was registered in the Prospective Register of Systematic Reviews (PROSPERO, CRD42024619387). The primary outcome measures were objective response rate (ORR), complete response rate (CRR), and the incidence of treatment-related adverse events (TRAEs). Meta-analysis was performed using Cochrane Collaboration Review Manager 5.4.1 and Meta-Analyst Beta 3.13 statistical software.

RESULTS: The meta-analysis involving 1680 patients with LA-NPC from 7 studies showed that the induction chemoimmunotherapy group had significantly better ORR (odds ratio[OR] = 2.03, 95% confidence interval [CI]:1.44-2.86, P < 0.01), and CRR (OR = 2.61, 95% CI:1.55-4.38, P < 0.01) than the induction chemotherapy group. The pooled ORR and CRR of induction chemoimmunotherapy were 92.7% (95% CI: 90.7-94.7%) and 24.3% (95% CI: 15.2-33.6%), respectively. There was no significant difference of TRAEs between induction chemotherapy group and induction chemoimmunotherapy group (OR = 1.13; 95% CI: 0.92-1.39, P = 0.23).

CONCLUSIONS: Induction chemoimmunotherapy could be a promising induction treatment option for LA-NPC patients, improving ORR and CRR with an acceptable safety profile. However, due to limitations in this meta-analysis, further large-scale, well-designed clinical trials are required to validate these results and optimise treatment strategies.

PMID:40913058 | DOI:10.1038/s41416-025-03169-0

Sci Rep. 2025 Sep 5;15(1):32368. doi: 10.1038/s41598-025-16070-w.

ABSTRACT

In radiomics, feature selection methods are primarily used to eliminate redundant features and identify relevant ones. Feature projection methods, such as principal component analysis (PCA), are often avoided due to concerns that recombining features may compromise interpretability. However, since most radiomic features lack inherent semantic meaning, prioritizing interpretability over predictive performance may not be justified. This study investigates whether feature projection methods can improve predictive performance compared to feature selection, as measured by the area under the receiver operating characteristic curve (AUC), the area under the precision-recall curve (AUPRC), and the F1, F0.5 and F2 scores. Models were trained on a large collection of 50 binary classification radiomic datasets derived from CT and MRI of various organs and representing different clinical outcomes. Evaluation was performed using nested, stratified 5-fold cross-validation with 10 repeats. Nine feature projection methods, including PCA, Kernel PCA, and Non-Negative Matrix Factorization (NMF), were compared to nine selection methods, such as Minimum Redundancy Maximum Relevance (MRMRe), Extremely Randomized Trees (ET), and LASSO, using four classifiers. The results showed that selection methods, particularly ET, MRMRe, Boruta, and LASSO, achieved the highest overall performance. Importantly, performance varied considerably across datasets, and some projection methods, such as NMF, occasionally outperformed all selection methods on individual datasets, indicating their potential utility. However, the average difference between selection methods and projection methods across all datasets was negligible and statistically insignificant, suggesting that both perform similarly based solely on methodological considerations. These findings support the notion that, in a typical radiomics study, selection methods should remain the primary approach but also emphasize the importance of considering projection methods in order to achieve the highest performance.

PMID:40913054 | DOI:10.1038/s41598-025-16070-w

ESMO Open. 2025 Sep 4;10(9):105573. doi: 10.1016/j.esmoop.2025.105573. Online ahead of print.

ABSTRACT

BACKGROUND: Antibody-drug conjugates (ADCs) combine targeted monoclonal antibodies with cytotoxic payloads and are an emerging modality in systemic cancer therapy. Thirteen ADCs are Food and Drug Administration approved, with many more in development. However, design and use remain challenging, with issues including on/off-target toxicity, resistance from prior exposure to payload classes, and optimal target/payload selection.

PATIENTS AND METHODS: This pooled analysis included patients treated on 19 clinical trials (9 phase I, 10 phase II/III) of 14 novel ADCs at Sarah Cannon Research Institute, London (2012-2025). Patients who received one or more doses of the study drug were analyzed. Descriptive statistics and Cox regression were used to evaluate demographics, tumor characteristics, toxicity and outcomes, overall and in subgroups.

RESULTS: A total of 163 patients [median age 61 years (range 31-82 years); 46.8% male] were included. Most had breast (n = 53, 32.5%) or gynecological cancers (n = 36, 22.1%), with a median of 4 prior treatments (range 1-20). Payloads included alkylating agents (n = 3), microtubule inhibitors (n = 8), and topoisomerase inhibitors (n = 3). Four ADCs targeted an oncogene (HER2); others targeted tumor-associated antigens (TAAs). Treatment-emergent adverse events (TEAEs) occurred in 84% (grade 3-4 in 29%). Rates of any-grade colitis, interstitial lung disease (ILD), neuropathy, ocular toxicity, and hepatotoxicity were 2.4%, 6.0%, 25.1%, 18.0% and 22.8%, respectively. Most toxicities emerged within 6 weeks, except colitis (median 18.2 weeks), ILD (13.1 weeks), neuropathy (11.6 weeks) and thrombocytopenia (23.2 weeks). No significant difference in grade ≥3 AEs was seen across payload classes (P = 0.50), although HER2 targeting was associated with higher rates (P = 0.04). Overall objective response rate was 16%, higher with topoisomerase payloads (43%), HER2 targeting (49% versus 6% for TAAs), in breast cancer (39%), and at recommended phase II dosing (25%).

CONCLUSIONS: ADCs show activity across tumor types, with greater efficacy when targeting oncogenes. Toxicities are frequent and often early. Anticipating timing of toxicities is key to effective clinical management.

PMID:40912047 | DOI:10.1016/j.esmoop.2025.105573

J Clin Neurosci. 2025 Sep 3;141:111603. doi: 10.1016/j.jocn.2025.111603. Online ahead of print.

ABSTRACT

BACKGROUND: Meningiomas exhibit considerable phenotypic variation within each WHO grade, thus additional markers are needed to identify prognostically relevant subgroups and optimize long-term management. Among biomarkers, genetic signatures correlate with prognoses. High Ki-67 proliferation indices and TERT promotor mutations and loss of CDKNA are known prognostic markers. Yet, such markers were mainly established by correlative analyses between biomarker expression and retrospective clinical data.

METHODS: Our group has reported on expression of a panel of markers in 176 meningiomas from 170 meningioma patients who underwent surgery from 2005 to 2008 in a previous publication. The markers were growth hormone receptor, insulin-like growth factor 1 receptor, progesterone receptor (PR), CD34, androgen receptor, epidermal growth factor receptor E30, caspase 3, and vascular endothelial growth factor (VEGF). Of the 176 meningiomas, 159 were classified as WHO grade 1, 16 were WHO grade 2 and one was WHO grade 3. We have now surveyed outcome after >10 years. We analyzed possible correlations between marker expression and clinical data such as recurrence, tumor location and patient death.

RESULTS: 27 of 155 WHO grade 1 and 5 of 15 WHO grade 2 meningiomas recurred. No statistically significant correlations between marker expression and recurrence were observed. The 10-year mortality was 10,8% and 53,4% for WHO grade 1 and 2, respectively, with 47 % and 50 % being disease specific for meningioma. A statistically significant negative correlation was observed between PR expression and death related to the tumor (50 % PR expression vs. 89 % in those not dying from the tumor; p = 0.001). Additionally, Ki-67 values showed to be higher in tumors of patients dying from the tumor (8 % vs. 4 %, p = 0.001). A statistically significant relationship was observed between PR and central/skull base (70 % expression in central/skull base vs. 39 % in other locations, p = 0,0002).

CONCLUSIONS: During 10-year follow-up, tumor recurrence was an important cause of death, accounting for approximately half of follow-up mortality despite the benign grading of meningiomas. This ambitious, prospective observational study failed to identify expression of GHr, Igf1r, CD34, EGFR, caspase 3 and VEGF as clinically relevant biomarkers.

PMID:40912009 | DOI:10.1016/j.jocn.2025.111603