Zoonotic diseases are common threats to global health. A large number of infectious diseases are transmitted from animals to humans. The current study aimed to assess the community's knowledge, attitudes, and practices (KAP) regarding common zoonotic diseases in the Arbaminch district. A cross-sectional survey was carried out between November 2024 and June 2025. A total of 384 participants were interviewed in the study. Participants residing in these areas were randomly chosen. Data were collected using a structured questionnaire. The collected data were analyzed using Stata 17, and the results were reported using descriptive statistics and the chi-square test. The findings of this study revealed that a majority (55%) of participants had good knowledge about zoonotic diseases. Respondents know several modes of transmission for zoonotic diseases, with animal bites (32.5%) being the most recognized, followed by direct contact (15.5%), ingestion of raw products (10%), and inhalation (10%). Regarding attitudes, 63.2% of respondents exhibited a positive attitude towards the importance of zoonotic disease prevention and control, and 67.4% of respondents followed relatively good hygiene and preventive behaviors. However, risky practices were still common. Knowledge score showed a significant association with age. Attitudes of participants were significantly associated with education, age, occupation, and income. Similarly, practices were significantly associated with gender, education level, occupation, and income, with all associations being statistically significant (p < 0.05). The overall community knowledge, attitudes, and practices regarding zoonotic diseases were relatively good.
Fast-track and outpatient surgery have significantly reduced postoperative hospital stays across many surgical specialties. As a result, patients are increasingly discharged with strong opioid prescriptions, contributing to the global opioid crisis. Careful follow-up and opioid tapering are essential. While multidisciplinary Transitional Pain Services (TPS), involving pain specialists, psychologists, and physiotherapists, have shown promise, their widespread implementation is limited by costs and complexity. To address these barriers, we implemented a nurse-led TPS, supervised by a pain specialist and embedded within a multidisciplinary pain clinic. The aim of this study was to evaluate its effectiveness in clinical practice, including a mechanism-based treatment approach to postsurgical pain aimed at opioid tapering and optimizing the use of adjuvant analgesics. This observational cohort study included postoperative patients discharged with >20 mg oral oxycodone equivalents and/or those experiencing or at risk for neuropathic pain. Referred patients received telephone consultations by a nurse practitioner (NP) one to two weeks post-discharge. Each consultation included assessment of pain severity, neuropathic characteristics (using the first two items of the DN4 questionnaire), current analgesic use, and willingness to taper opioids. Patient education and motivational interviewing techniques were employed to support opioid tapering. Descriptive statistics and paired t-tests were used to analyze the data. Between June 2019 and July 2025, 243 patients were enrolled in the TPS. Following nurse-led counseling, 73 % of patients discontinued opioid use entirely, 23 % significantly tapered their dosage (from mean 101-43 mg oral oxycodone equivalent), and 4 % continued at the same dose. Anti-neuropathic medications were initiated in 22 % of patients. A nurse-led Transitional Pain Service is a feasible and effective approach to support opioid tapering in postoperative patients. In addition, early screening for neuropathic pain allows for targeted treatment. This model offers a scalable alternative to traditional multidisciplinary TPS programs.
To evaluate the prevalence of degenerative bony changes of the mandibular condyle and their associations with age, gender, and joint laterality. CBCT scans of 112 temporomandibular joints of 56 clinically symptomatic patients were included based on predefined inclusion and exclusion criteria. Degenerative changes, including erosion, flattening, osteophytes, subchondral sclerosis, and subcortical pseudocysts, were assessed for their presence, frequency, and demographic associations using the Chi-square test, McNemar test, Spearman's correlation analysis, and Cohen's kappa statistics. Erosion was the most prevalent finding (84.8%) and frequently coexisted with flattening. Subcortical pseudocyst showed a positive association with increasing age (p < 0.05), osteophytes were more commonly observed in males (p < 0.01), and subchondral sclerosis occurred more frequently on the left side (p < 0.05). Symptomatic TMJs demonstrated at least one degenerative change, where Erosion was the most prevalent, and subcortical pseudocyst was the least common degenerative change in the mandibular condyle. Age, gender, and joint side showed associations with specific changes.
Early identification and initiation of therapy for life-threatening hemorrhage is essential to minimize patient morbidity and mortality. In primary hemostasis, platelet function is integral to reach this goal, but major hemorrhage leads to impaired platelet mechanical activation and aggregation. Current devices for measuring platelet function are cumbersome or not promptly available for clinical decision making in this setting. Within this manuscript we prospectively evaluate a novel, rapid assay utilizing measures of platelet aggregation to predict hemorrhage. In this prospective cohort study at an academic regional Level I trauma center, we included adult (> 16 years old) participants who were triaged as level I or II trauma activations. The primary exposure studied was platelet aggregation analyzed on a prototype device. The primary and secondary outcomes measured were life-threatening hemorrhage (death from hemorrhage or need for hemorrhage control procedure) and transfusion requirements of > 2 units of blood components, respectively. Standard descriptive statistics were used to characterize the cohort. Predictive outcomes were analyzed using multivariable regression to compare: (1) the platelet aggregation assay; (2) clinical parameters (systolic blood pressure, heart rate, and injury mechanism); and (3) a combined model. Of 761 patients, 482 patients met inclusion criteria for our study, 36 (7.5%) had life-threatening hemorrhage and 43 (8.9%) patients required > 2 units of blood transfusion. For life-threatening hemorrhage, platelet aggregation had an area under the curve (AUC): 0.61 (95% confidence interval [CI] 0.53-0.69); clinical parameters AUC: 0.83 (CI 0.75-0.91); and the combined model AUC: 0.85 (CI 0.79-0.92) which was not significantly improved when compared to clinical parameters alone (p = 0.32). For transfusion of > 2 units, the platelet aggregation model had AUC: 0.68 (CI 0.61-0.76); clinical parameters AUC: 0.84 (CI 0.79-0.90); and combined model AUC: 0.88 (CI 0.83-0.93), improving transfusion prediction over clinical parameters alone (p = 0.013). In a cohort of traumatically injured patients, a novel, rapid measure of platelet aggregation enhanced well-established clinical parameters to predict the need for blood transfusion but not life-threatening hemorrhage. Future work should validate the clinical utility of this technology in a larger cohort and patients with significant non-traumatic hemorrhage.
Proper air quality forecasting is essential in developing countries such as India, where climate variability, industrialization, and increasing urbanization play a major role in degrading air quality and posing health risks. This research introduces an integrated machine learning (ML) architecture for the prediction of the Air Quality Index (AQI) in two Andhra Pradesh urban cities, Visakhapatnam and Vijayawada, and one city in Telangana, Hyderabad based on five years of pollutant and meteorological data. This approach combines a deep feedforward neural network (FNN) with residual blocks and several traditional regression techniques, viz., Random Forest, Lasso, and Gradient Boosting, to both predict AQI directly and impute it through pollutant-wise modeling in accordance with CPCB standards. Imposing a large amount of feature engineering like temporal lags, rolling statistics, and pollutant interactions was used to identify spatiotemporal dynamics. The unified advanced FNN model attained [Formula: see text] values of 0.965, 0.97, and 0.96, and Root Mean Square Errors (RMSE) of 10.0, 11.25, and 13.17 for Vijayawada, Hyderabad, and Visakhapatnam respectively. Furthermore, predictions for pollutant-specific values in 2025 showed close conformity with real AQI values ([Formula: see text], RMSE = 2.68, 5.84, 5.30 for Random Forest for Vijayawada, Hyderabad, Visakhapatnam respectively) when predicted from estimated pollutant concentrations. This research illustrates a scalable method for AQI forecasting that is capable of informing real-time policy and public health intervention in data-scarce settings.
Integral nursing leadership, based on Wilber's Integral Framework, is vital for fostering positive work environments and aligning staff with organizational goals. This study assessed the status of integral nursing leadership and its association with job satisfaction and turnover intention among nurses in Ardabil, Iran. This cross-sectional correlational study was conducted from November 2024 to January 2025 with 450 nurses from five hospitals affiliated with Ardabil University of Medical Sciences. Data were collected using a demographic form, the Integral Nursing Leadership Scale (INLS), and single-item measures for job satisfaction and turnover intention. Analysis was performed in SPSS-26 using descriptive statistics, Pearson correlation, and linear regression (p < 0.05). Job satisfaction showed a significant, strong negative correlation with turnover intention (r = -0.585, p < 0.01). The mean score for integral nursing leadership was 3.85 out of 6. Only 37.3% of nurses reported job satisfaction, while 62.7% were dissatisfied and intended to leave. Regression analysis indicated that integral nursing leadership was a significant positive predictor of job satisfaction (B = 0.253, p < 0.001) and a significant negative predictor of turnover intention (B = -0.193, p < 0.001). Higher levels of integral nursing leadership are associated with increased job satisfaction and reduced turnover intention among nurses. This highlights the importance of developing integral leadership qualities to improve workplace culture and retention. Future research should investigate longitudinal effects and develop targeted interventions based on these findings.
The timeliness of treatment for out-of-hospital cardiac arrest (OHCA) is critical for patient survival. Automated External Defibrillators (AEDs) are a proven effective intervention, yet China's rapidly developing Public Access Defibrillation (PAD) program may be accompanied by significant spatial inequities in AED distribution. This study developed a comprehensive multi-dimensional evaluation model to assess the spatial equity of AED allocation in four first-tier Chinese cities: Beijing, Shanghai, Guangzhou, and Shenzhen. The model integrated four dimensions: resource allocation (supply-demand ratio), spatial coverage (service coverage index), opportunity accessibility (accessibility index via an enhanced Gaussian two-step floating catchment area method), and spatial distribution (Gini coefficient). These dimensions were aggregated into a Comprehensive Equity Index (CEI) using the Entropy Weight Method (EWM). Leveraging high-resolution gridded population data and precise AED locations, our analysis captures fine-scale spatial variations often obscured in aggregate statistics. Furthermore, to uncover the spatially heterogeneous drivers of equity, we employed an integrated Principal Component Analysis and Geographically Weighted Regression (PCA-GWR) framework to analyze socioeconomic and urban environmental factors. The results indicate that: (1) Overall comprehensive equity was low across all cities (mean CEI < 0.3). Shenzhen exhibited the highest equity (mean CEI: 0.252), followed by Beijing (0.207), with Shanghai and Guangzhou lagging. (2) A significant "core-periphery" disparity was observed in all cities, with core districts showing markedly higher equity than suburban districts, a gap particularly pronounced in Beijing and Shanghai. (3) The PCA-GWR analysis revealed pronounced spatial heterogeneity in the associations between external factors and AED equity. Degree of urbanization showed a generally positive association, which was consistently weaker in urban cores. Public service facility provision exhibited inconsistent (often negative) associations, while the wealth-population density trade-off demonstrated marked city-specific variation. This study provides a systematic, multidimensional assessment of AED allocation equity in major Chinese cities. By employing a spatially nuanced PCA-GWR framework, it reveals that equity is shaped by complex, location-specific interactions of urban development, service provision, and socioeconomic structure. The findings underscore the necessity for spatially differentiated policy interventions within China's PAD program to achieve more equitable and efficient deployment of these lifesaving resources.
Access to large, diverse biomedical datasets is critical for advancing medical research, yet privacy regulations severely restrict data sharing. We present an end-to-end framework for privacy-preserving health data synthesis that integrates advanced deep generative models (DGMs) with robust preprocessing, formal differential privacy (DP) training for select DGMs, empirical privacy risk evaluation, data-sufficiency analysis, domain-guided quality control, and biobank visualization tools. Released as open-source containerized software, the framework ensures reproducible deployment while preserving statistical fidelity, machine learning (ML) utility, and privacy guarantees. Empirical evaluations across diverse biobank datasets demonstrate that TabSyn-a transformer-based diffusion model-combined with our correlation-and distribution-aware CorrDst loss function achieves superior performance balancing fidelity, privacy, and computational efficiency. The tailored preprocessing pipeline effectively handles high missingness rates, substantially improving distributional accuracy and clinical plausibility. Across 26 biobank datasets spanning three regulatory levels, the framework shows that TabSyn with correlation- and distribution-aware loss function consistently achieves superior performance in terms of fidelity, privacy, and computational efficiency.
In the digital age, university students' sustained academic engagement and strong learning resilience in the face of increasing academic pressure and complex campus challenges are essential to the attainment of substantial academic achievement. At present, how to enhance students' academic engagement and foster learning resilience has become a pressing issue for educational administrators. Although previous studies have examined multiple factors influencing academic engagement and resilience, they have largely emphasized the isolated effects of psychological traits on individual learning performance while overlooking the complex possibility that perceived external contexts, such as the learning environment, learning climate, and social relationships, may jointly shape learning resilience through psychological and emotional regulatory mechanisms. Therefore, this study focuses on the interaction among external contexts, internal affective drivers (academic self-efficacy and perceived campus belonging), and learning resilience. Using questionnaire survey data and structural equation modeling, this study examines the extent to which external contexts are associated with academic self-efficacy and perceived campus belonging, explores whether these internal affective drivers are statistically associated with learning resilience through mediating pathways, and constructs an "external context-affective drivers-learning resilience" model to identify potential explanatory pathways and provide evidence-based implications for educational management.
The association between preoperative peripheral nerve block (PNB), major adverse cardiovascular events (MACE), and postoperative length of hospital stay (LOS) in elderly patients who underwent major thoracic and abdominal surgery remains unclear. This study aims to explore the potential mediating effect of MACE on the association between preoperative PNB and postoperative LOS using a statistical mediation framework. In this retrospective cohort study, perioperative data were collected from elderly patients (aged over 65 years) who underwent major thoracic and abdominal surgery. Mediation analysis was employed to examine the relationships between PNB, MACE, and postoperative LOS. A total of 1915 patients were included in the analysis, with 68.7% (1316/1915) receiving preoperative PNB. Compared to patients who did not receive PNB, those who did had a significantly lower incidence of MACE (P < 0.001) and a shorter postoperative LOS (P < 0.001). The adjusted total and direct associations of PNB with postoperative LOS were - 0.809 days (95% confidence interval [CI], -1.236 to -0.390; P < 0.001) and - 0.661 days (95% CI, -1.077 to -0.250; P = 0.003), respectively. A statistically significant indirect association via MACE was observed (adjusted β=-0.149 days; 95% CI, -0.271 to -0.060; P < 0.001), indicating that 18.1% (95% CI, 6.7% to 41.0%) of the total association was statistically attributable to the indirect pathway through MACE under the model assumptions. A sensitivity analysis excluding postoperative covariates yielded consistent results (proportion mediated: 25.3%). Our findings suggest that the observed association between preoperative PNB and reduced postoperative LOS in elderly patients following major thoracic and abdominal surgery may be partly explained by a statistically significant indirect pathway through a reduction in MACE, potentially accounting for approximately 18% of the total effect. These findings are hypothesis-generating and represent statistical associations rather than demonstrated causal mechanisms. ChiCTR2400087610; https://www.chictr.org.cn.
This study examined the prevalence of post-traumatic stress disorder (PTSD) diagnoses among pregnant women who delivered in hospitals in the United States between 2016 and 2020, and explored associations with adverse pregnancy outcomes, hospital length of stay, and hospital costs. This cross-sectional study utilised survey-weighted data from the Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS) to estimate sample characteristics and prevalence trends. Logistic regression models were used to analyse associations between PTSD and adverse pregnancy outcomes. Length of hospital stay and hospital costs were examined using negative binomial and generalised linear models with log link and gamma distribution, respectively. PTSD prevalence increased from 236.3 to 545.8 per 100,000 delivery hospitalisations between 2016 and 2020 (p < 0.001; average annual percentage change [AAPC] 23.0%). PTSD was associated with a higher prevalence of comorbidity, increased odds of preterm delivery (adjusted odds ratio [aOR] 1.13; 95% CI 1.08-1.18), and increased odds of fetal growth restriction (aOR 1.09; 95% CI 1.01-1.17, p = 0.03). Longer hospital stays and higher costs were also observed among women with PTSD. These findings highlight a rising prevalence of PTSD among pregnant women who delivered in hospitals in the United States over the study period. PTSD was associated with higher prevalence of comorbidity, and increased length of stay and hospital cost. Further research is warranted to investigate the reasons behind the trend, and to clarify the temporal relationship between prenatal PTSD and adverse pregnancy outcomes.
Early diagnosis of plant leaf diseases plays an important role in protecting crop yields and supporting sustainable agriculture. This paper proposes an improved DeepFusionNet model optimized through a hybrid Flower Pollination Algorithm and Butterfly Optimization Algorithm, balancing global exploration with local refinement for faster and more stable convergence. The model combines DenseNet201 and MobileNetV2 by compressing their final convolutional feature maps with 1×1 convolutions and fusing them along the channel dimension to form a compact and discriminative representation. This fused representation is then classified using a Random Forest classifier. This framework consistently achieves high accuracy on all eight datasets, with performance ranging between 97.07% and 99.66%. Extensive experiments are performed that include statistical validation, convergence studies, and reliability tests to prove the robustness of the approach. Furthermore, to make it practically useful, the whole system is embedded into a mobile application capable of real-time disease detection and providing actionable recommendations to farmers for the effective treatment and prevention of diseases.
Metacognitive theory suggests that maladaptive beliefs about thinking are associated with the cognitive attentional syndrome (CAS), which is characterized by repetitive negative thinking and heightened threat monitoring. This study examined a dual-mediation model in which rumination and anxiety sensitivity were tested simultaneously as mediators of the relationship between metacognitive beliefs and sleep quality in a nonclinical sample. A total of 346 Iranian adults (18-60 years) completed validated self-report measures of metacognitive beliefs, rumination, anxiety sensitivity, and sleep quality. Structural equation modeling (SEM) with bias-corrected bootstrapping (2,000 resamples) was used to test the hypothesized model. The model demonstrated acceptable fit to the data (CFI = 0.96, RMSEA = 0.074). Metacognitive beliefs were not significantly associated with sleep quality after including the mediators. However, significant indirect effects were observed through rumination (β = 0.32, 95% CI [0.20, 0.40]) and anxiety sensitivity (β = 0.28, 95% CI [0.17, 0.37]). The model explained 50% of the variance in sleep quality. The findings indicate that metacognitive beliefs are statistically associated with poorer sleep quality indirectly through rumination and anxiety sensitivity in a community sample. These results support the value of examining transdiagnostic cognitive-emotional processes in sleep research. Due to the cross-sectional design and reliance on self-report measures, causal inferences cannot be drawn. Future longitudinal and experimental studies are needed to clarify the temporal relationships and clinical utility of these pathways.
Heavy metal (HM) contamination in agricultural soils adjacent to bauxite mining poses a significant risk to the ecological and human health. This study provides a comprehensive assessment of the degree of contamination, the spatial distribution, source apportionment, and probabilistic health risks assessment in bauxite mining-affected agricultural ecosystems in Eastern India. Soil samples (n = 120) were collected from the Rayagada district (Zone 1 = 60) and Koraput district (Zone 2 = 60) regions of Eastern India. Soils in both zones were found to acidic (Zone 1pH: 5.65 ± 0.45 and Zone 2pH: 5.62 ± 0.64) and low electrical conductivity (EC) values of (Zone 1 = 0.04 ± 0.01 and Zone 2 = 0.03 ± 0.01 mS/cm). In Zone 1, average values of Cr (249.05 ± 74.51 mg/kg), Cd (4.73 ± 0.98 mg/kg) and Fe (53,284.20 ± 12,889.27 mg/kg) were significantly greater than Zone 2. Spatial distribution suggested high levels of HMs were associated close to the mining activities. Positive Matrix Factorization (PMF) revealed the four major pollution sources identified in this study, namely industrial, natural/geological, traffic-related, and agricultural inputs. Pollution indices revealed significant pollution (PLI: 1.56 in Zone 1; 1.08 in Zone 2), while ecological risk index values for Cr exceeding 600 in both zones. Although non-carcinogenic risk (HI < 1) was within acceptable limits, carcinogenic risks-primarily attributed to Cr and Pb-were elevated for children (TCR = 1.01E-02). The Sobol sensitivity analysis found chromium, lead, and nickel as important contributors to carcinogenic risk. Overall, the findings emphasize the need for focused management, monitoring and long-term restoration in agricultural land affected by mining.
Corporate bankruptcy prediction is essential for assessing companies' capacity to maintain sustainable customer relationships and service quality. This study proposes a novel CNN-based hybrid approach that transforms correlation-filtered financial features into 64 × 64 grayscale images, enabling reliable identification of firms at financial risk whose deteriorating conditions could compromise their ability to maintain quality customer service and sustain long-term business relationships. The research explicitly examines the linkage between financial health indicators and customer relationship sustainability by categorizing financial features based on their operational impact on service delivery, relationship management capabilities, and long-term customer commitment fulfillment. The methodology was evaluated on a comprehensive dataset of 43,405 Polish companies (2,091 bankrupt, 41,314 healthy) using two resampling strategies: random downsampling and Synthetic Minority Oversampling Technique (SMOTE). Following correlation-based feature selection that reduced multicollinearity by eliminating features with absolute correlation coefficients exceeding 0.8, retained financial features were normalized and transformed into spatial image representations. Six classification models were implemented: Deep Neural Network (DNN), Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), Gradient Boosting (GB), and Logistic Regression (LR), alongside five CNN-hybrid variants, evaluated using 5-fold cross-validation. SMOTE-balanced datasets demonstrated superior performance across all models. Ensemble methods achieved exceptional accuracy, with Random Forest reaching 99.99% and Gradient Boosting 99.97%. The innovative CNN-SVM hybrid model attained 99.77% accuracy with perfect ROC-AUC (1.000), providing reliable indicators for assessing firms' financial stability and their ability to invest in customer experience initiatives. Statistical analysis identified company size and working capital as the most discriminative financial indicators directly impacting customer service delivery capabilities. Customer-related metrics such as receivables turnover and collection period indicators emerged as critical predictors of relationship management effectiveness. The study contributes a novel spatial feature representation methodology enabling precise identification of companies whose financial deterioration could compromise customer service quality and relationship sustainability. These findings provide significant implications for stakeholders seeking enhanced risk assessment capabilities that consider both internal financial health and external customer relationship dynamics in bankruptcy prediction.
Sleep disorders include a range of common problems that affect the quality of sleep at night and, as a result, impact an individual's daily functioning. Treatment protocols vary from over-the-counter products to regulated pharmaceuticals. Melatonin and Tasimelteon are two compounds utilized for severe to moderate sleeping disorders. This study developed and validated a sensitive, simple bioanalytical LC-MS/MS method for the measurement of Melatonin and Tasimelteon in spiked rat brain tissue. Chromatographic analyses were conducted in isocratic mode, with Citalopram selected as an appropriate internal standard. The Supelco Ascentis® Express Phenyl-Hexyl column was used for the stationary phase, and the mobile phase comprised 0.2% formic acid in a mixture of acetonitrile and water (65:35, v/v). A response surface methodology is applied. The Box-Behnken design was used to optimize the influence of three independent factors (acetonitrile%, formic acid%, and flow rate (mL/min)) on the response. The study focused on finding the most significant factors influencing chromatographic separation, namely the resolution between Tasimelteon and Melatonin, as well as the tailing factors of both. Statistical analysis of variance provided the optimal conditions for separating the substances as well as the most influential factors. Validation of the analytical method was conducted in accordance with the International Council for Harmonization guideline M10 related to bioanalytical method validation. The method validated was precise and linear in 55.00-1650 (ng/mL) and 20-600 (ng/mL) for the Melatonin and Tasimelteon, respectively. The validated method's lower limit of quantification values was 55 and 20 ng/mL for Melatonin and Tasimelteon, respectively. For Melatonin, intraday accuracy (recovery, %) ranged from 96.53% to 102.68%, and precision (expressed as relative standard deviation) ranged from 0.26% to 0.96%. And inter-day accuracy ranged from 96.58% to 103.08%, and inter-day precision ranged from 0.33% to 3.55%. Intraday accuracy results for Tasimelteon 99.61%-103. 75% precision results were in the range 0.23%-0.93%; additionally, inter-day accuracy was 99.37-103.87%, and the precision range was 1.04-2.11%. The total run time was 3 min, with retention time for Melatonin and Tasimelteon at 1.9 and 2.5 min, respectively, achieving effective chromatographic separation under optimum conditions. The Red Green Blue 12 score for whiteness was determined to be 79.2%.
The purpose of this study was to retrospectively compare the prognostic outcomes of patients with colorectal cancer (CRC) who achieved a clinical complete response (CCR) after neoadjuvant immunotherapy (NI) and those who achieved a CCR after surgery. A literature review of publications was conducted in the PubMed database. This study included 70 patients who were diagnosed with mismatch repair deficiency/microsatellite instability high (dMMR/MSI-H) colorectal cancer and who were treated with NI between 2018 and 2024. CCR patients were grouped into the "watch and wait" (W&W) method group or the radical surgery group. Afterwards, the oncological and clinical outcomes of patients who achieved a clinical complete response (CCR) were compared to those of patients who were classified as tumour free. We also conducted a literature review of publications in the PubMed database of clinical studies that compared clinical outcomes between W&W and surgery for CCR dMMR/MSI-H patients. Among the 70 NI-treated dMMR/MSI-H CRC patients, 44 (62.86%) achieved a CCR. Of these, 25 patients were managed with a watch-and-wait (W&W) strategy, while 19 underwent curative-intent surgery. In the surgery group, 16 patients (84.21%) achieved a pathological complete response (pCR). During follow-up, 2 patients (10.53%) in the surgery group developed recurrence, and both subsequently died, while the remaining 17 patients were alive at the last follow-up. No statistically significant differences were observed between the W&W and surgery groups in terms of recurrence or survival outcomes. A literature review including nine studies further demonstrated comparable oncological outcomes between W&W and surgical management in patients who achieved a CCR. Patients in the W&W group presented similar oncological outcomes to those who underwent surgery. Surgery may not be necessary for patients with dMMR/MSI-H colorectal cancer who achieve a clinical complete response after neoadjuvant immunotherapy. However, large sample sizes and multicentre investigations are needed to validate these findings.
To evaluate finerenone-associated adverse events (AEs) and to investigate the association between finerenone use and renal injury via data mining of the Food and Drug Administration Adverse Event Reporting System (FAERS). To minimize statistical bias, the data extraction period was set from database inception (2004) to provide a stable background for disproportionality analysis. Four disproportionality algorithms (ROR, PRR, BCPNN, and MGPS) and stricter case-screening methods were employed to improve analytical precision. Additionally, a clinical priority evaluation was conducted to rank clinical risks and surveillance levels for these AEs. Supplementary analysis was performed to assess the relationship between finerenone and renal injury, as well as associated risk factors. A total of 1316 finerenone-related reports were identified. 30 AEs were detected as significantly positive signals, with most being related to renal function (15 PTs, 50%), blood pressure (5 PTs, 16.67%), and blood potassium (4 PTs, 13.33%). Among them, blood glucose increased, blood creatine increased, and flank pain were new potential AEs. Acute kidney injury, hyperkalemia, renal impairment, glomerular filtration rate decreased, blood creatinineincreased, blood potassium increased, and hyponatremia exhibited moderate clinical priority levels and warrant further study. Signals reflecting renal injury were detected in patients regardless of baseline nephropathy. Male sex, taking more than 3 drugs, and using amlodipine may be risk factors for finerenone-related nephrotoxicity. These results highlight new finerenone-related AEs, provide ranked guidance for pharmacovigilance through clinical priority evaluation, and clarify factors that influence renal injury, providing guidance for individualized treatment and improved drug safety.
BACKGROUND This retrospective study aimed to radiographically compare injectable platelet-rich fibrin (I-PRF)-enriched bone graft matrix (sticky bone) with conventional particulate grafting during lateral sinus lift procedures performed simultaneously with implant placement in patients exhibiting insufficient posterior maxillary residual bone height. MATERIAL AND METHODS Twenty-four systemically healthy, non-smoking patients who underwent lateral sinus lift surgery between January 2014 and June 2023 were included. Patients were retrospectively allocated into groups according to grafting material: conventional particulate bone graft (group 1, n=12) and I-PRF-enriched bone graft matrix (sticky bone) (group 2, n=12). Radiographic bone height measurements were obtained using panoramic radiographs acquired preoperatively, immediately postoperatively, and at 6 months postoperatively. Measurements were conducted using calibrated digital software. Inter- and intragroup comparisons were analyzed via paired and independent samples t-tests, using a statistical significance threshold of P<0.05. RESULTS Immediate postoperative bone gain was significantly higher in group 1 than in group 2 (11.94 mm vs 10.15 mm; P<0.05). However, bone resorption at 6 months was significantly greater in group 1 than in group 2 (2.61 mm vs 1.07 mm; P<0.05). Bone loss percentage also was significantly higher in group 1 than in group 2 (16.50% vs 7.74%; P<0.05), indicating superior bone preservation in group 2. CONCLUSIONS Although conventional grafting resulted in greater initial bone gain, I-PRF-enriched bone graft matrix demonstrated significantly reduced bone resorption at 6 months. Sticky bone may provide a clinical advantage in bone preservation after sinus lift procedures.
Swallowing and diaphragmatic functions share neural regulatory pathways and require synchronous assessment. Patients who have had a stroke are susceptible to many complications, of which dysphagia and diaphragmatic dysfunction are particularly common. To compare the distribution and severity of swallowing function in stroke patients with and without diaphragmatic dysfunction, and to explore the correlation between swallowing and diaphragmatic functions. This cross-sectional observational study among 102 Chinese stroke patients with hemiplegia was conducted in August 2022 to December 2024. Data collection was completed in the first 48 h following admission, including sex, age, post-stroke duration, stroke type, stroke region, hemiplegia side, nasogastric feeding, and pneumonia. The patients were stratified into two groups by the presence or absence of diaphragmatic dysfunction, which was assessed by diaphragmatic ultrasound with a threshold of diaphragm thickening fraction (TFdi) < 20%. We compared the distribution and severity of different swallowing functions using the Modified Barium Swallow Study Impairment Profile (MBSImP) and the Penetration-Aspiration Scale (PAS) by Videofluoroscopic Swallowing Study (VFSS) between the two groups. Significant differences were found between the two groups in the oral and pharyngeal phases of the MBSImP (p < 0.003), including hold position/tongue control, bolus preparation/mastication, bolus transport/lingual motion, oral residue, initiation of the pharyngeal swallow, anterior hyoid motion, pharyngeal stripping wave, and pharyngeal residue (p < 0.003). In contrast, there were no significant differences between the two groups in some components of the MBSImP including lip closure, soft palate elevation, laryngeal elevation, epiglottic movement, laryngeal closure, pharyngeal contraction, and tongue base retraction (p > 0.003). The severity of swallowing physiological impairment by MBSImP between the two groups, including the oral phase, pharyngeal phase and total MBSImP scores showed significant differences (p < 0.003). By contrast, the distribution and severity of penetration and aspiration risk by PAS showed no statistically significant difference between the two groups (p > 0.003). TFdi was negatively correlated with grades of Water Swallowing Test, the oral phase, pharyngeal phase and total MBSImP scores (rs = -0.327 to -0.300, p < 0.003). Whereas no significant correlations were found between TFdi and pneumonia, nasogastric feeding and the PAS scores (p > 0.003). Patients with diaphragmatic dysfunction exhibited a higher proportion of swallowing physiological impairment in the oral and pharyngeal phases, along with greater severity of such impairments. Diaphragmatic function was correlated with swallowing function, but the correlation was weak and of uncertain clinical significance.