Team situation awareness is a critical cognitive skill that significantly contributes to the optimal performance of healthcare providers. It fosters a positive understanding among team members, thereby facilitating the delivery of professional and high-quality care. This study aims to elucidate the concept of team situation awareness and its dimensions as perceived by staff working in operating rooms. This study utilizes qualitative, directed content analysis to examine the perspectives of operating room staff in Iran. Participants were selected from various centers through purposive sampling, ensuring maximum variation in demographic characteristics. Data were gathered through in-depth, semi-structured interviews and analyzed using a deductive approach. To ensure comprehensive reporting of the study, the Consolidated Criteria for Reporting Qualitative Research checklist (COREQ) was employed. The results indicate that the concept of team situation awareness in operating rooms includes perceiving environmental elements (Identifying equipment and tools, Awareness of the members of the surgical team, Physical condition of the environment), conducting real-time situation analysis (Patient condition assessment, Recognition of potential challenges and risks, Collaborative team decision-making), and projecting future scenarios (Prediction of consequences and assessment the impacts, Crisis management and rapid response). These components are derived from three main categories, eight general categories, and eighteen specific subcategories. The dimensions of team situation awareness in operating room staff encompass procedures that, when effectively promoted, can enhance patient safety, reduce intraoperative risks, and optimize the allocation of clinical resources. Assessing the status of these dimensions within operating rooms can provide a purposeful direction for improving intraoperative safety and informing policy decisions.

Seroma is the most common postoperative complication following mastectomy and may result in additional postoperative interventions and increased treatment burden. However, its etiology and predictive factors remain insufficiently understood. This study aimed to identify predictors of postoperative seroma formation.

We conducted a retrospective analysis of 245 patients (301 breasts) who underwent conventional mastectomy or skin-/nipple-sparing mastectomy, with or without immediate implant reconstruction and axillary surgery, at the University Hospital Leipzig between 2019 and 2023. Variables analyzed included epidemiological characteristics, neoadjuvant chemotherapy, tumor status, perioperative factors, and wound drainage output. Seroma formation was assessed via drains placed in the breast and axilla. Statistical analyses included univariable and multivariable regression and random forest modeling.

In univariable analyses, higher body mass index (BMI), longer surgical duration, diabetes mellitus, hypertension, advanced tumor stage, and elevated C-reactive protein levels were associated with increased breast seroma formation. Random forest analysis identified BMI, number of resected lymph nodes, surgical duration, hypertension, and diabetes as key predictors, all of which remained significant in multivariable models. For axillary seroma, BMI, number of resected lymph nodes, and tumor stage were significant in univariable analyses, while BMI and number of resected lymph nodes remained significant in multivariable models.

Seroma formation is primarily influenced by BMI, extent of lymph node removal, and surgical duration, with hypertension and diabetes as additional risk factors for breast seroma.

The co-administration of Dapagliflozin and Sitagliptin has attracted considerable interest in the management of type 2 diabetes mellitus due to their complementary therapeutic effects. However, their simultaneous determination is analytically challenging because of the significant overlap in their native fluorescence spectra. In this study, a selective and sensitive first-derivative synchronous spectrofluorimetric method was developed for the simultaneous determination of both drugs without prior separation. The proposed approach enabled efficient spectral resolution through zero-crossing points at 348 nm and 289 nm for dapagliflozin and sitagliptin, respectively, using a constant wavelength difference (Δλ = 30 nm). The method exhibited excellent linearity over the concentration ranges of 50-1000 ng/mL and 100-2000 ng/mL for dapagliflozin and sitagliptin, respectively, covering concentration levels relevant to their reported maximum plasma concentrations (Cmax), with low limits of detection (16.02 and 31.07 ng/mL, respectively), indicating high sensitivity. The proposed method demonstrated satisfactory accuracy (mean recoveries of 100.67% and 99.86%) and precision (%RSD < 2%). The method was successfully applied to the analysis of pharmaceutical dosage forms and spiked human plasma, showing reliable recoveries. To the best of our knowledge, this is the first validated spectrofluorimetric method for the simultaneous determination of these co-administered drugs, offering a simple, cost-effective, and efficient alternative to conventional analytical techniques.

This review aimed to highlight the relevance of telehealth in improving glycaemic control among older adults living with diabetes. Articles published between 2015 and 2025 across Ovid MEDLINE database, Cumulative Index to Nursing and Allied Health Literature (CINAHL) database, Scopus Cochrane Library and Ovid Excerpta Medica Database (EMBASE) were reviewed by two authors. The methodological quality of the studies was appraised using the Critical Appraisal Skill Programme (CASP) framework. In total, nine articles were reviewed and analysed to answer two research questions (3.5 and 3.7). The effectiveness of telehealth and digital interventions in supporting older adults with diabetes were highlighted and grouped into four themes: Digital self-monitoring and telehealth in diabetes management, technology-enabled exercise and lifestyle interventions, telehealth-based psychosocial interventions and effectiveness of telemedicine and remote care. Barriers such as limited digital literacy, privacy concerns, and insufficient technical skills continue to restrict widespread adoption of telehealth for the management of older people living with diabetes. Telehealth and digital tools can complement traditional diabetes care for older adults who have limited access to in-person diabetes services. However, optimising outcomes for older people require a focus on digital literacy, equitable access, and age-friendly diabetes telehealth services.

Maturity-onset diabetes of the young (MODY) is a clinically and genetically heterogeneous group of monogenic diabetes subtypes that is frequently misdiagnosed as type 1 or type 2 diabetes, and accurate genetic diagnosis enables a precision-medicine treatment approach. Regional Turkish data are limited, and previous Turkish series have been pediatric only. We characterized the genetic spectrum and therapeutic consequences of next-generation sequencing (NGS)-based MODY testing in a combined adult-and-pediatric cohort from the eastern Black Sea region of Türkiye.

We retrospectively analyzed 296 consecutive patients with clinically suspected MODY referred between January 2022 and June 2025. A targeted NGS panel covering 14 MODY genes was applied, variants were classified per 2015 ACMG/AMP criteria, and treatment changes attributable to the genetic diagnosis were extracted from medical records. Pathogenic or likely pathogenic (P/LP) variants were identified in 43 of 296 patients (14.5%); diagnostic yield rose to 26.0% with variants of uncertain significance included. GCK-MODY accounted for 72.1% of P/LP findings, with a recurrent frameshift c.1256del p.(Phe419SerfsTer12) across nine apparently unrelated families consistent with a regional founder allele. Rare subtypes included MODY4 (PDX1), MODY6 (NEUROD1), MODY8 (CEL), MODY10 (INS), MODY12 (ABCC8) and MODY13 (KCNJ11). The genetic diagnosis directly modified pharmacological therapy in 14 patients, including insulin discontinuation in three KATP-channel MODY and one INS-MODY case.

NGS-based MODY testing yields actionable findings in approximately one in seven clinically selected patients in this region and supports inclusion of MODY testing in routine endocrinology practice.

We previously found that urinary n-terminal osteopontin (ntOPN) performed well for predicting diabetic kidney disease (DKD). This study is aimed at screening potential biomarkers for improving ntOPN-based models in DKD detection and prediction.

We performed a cross-sectional and then prospective cohort study. The novel biomarkers for DKD development were selected by the SOMAscan platform. The selected biomarkers were further validated by the SHapley Additive exPlanations (SHAP) algorithm, Pearson correlation, and logistic regression. The ntOPN-based models for DKD prediction were established, evaluated, and utilized by machine learning.

The baseline growth differentiation factor 15 (GDF15) was selected by SOMAscan assays, and urinary GDF15 was validated as an independent predictor for DKD occurrence (adjusted OR 1.43, 95% CI 1.20-1.75) and progression (adjusted OR 1.39, 95% CI 1.15-1.75) by multivariate logistic regression. The receiver operating characteristic (ROC) analysis showed that the multibiomarker panel consisting of urinary ntOPN-to-creatinine ratio (UntOCR) and urinary GDF15-to-creatinine ratio (UGCR) had stronger abilities in forecasting the 2-year risk of DKD occurrence (AUC 0.838 vs. 0.818) and DKD progression (AUC 0.867 vs. 0.834) than the combination of estimated glomerular filtration rate (eGFR_cr-cys) and urinary albumin-to-creatinine ratio (UACR). A nomogram was further built with a high C-index (0.8433).

Compared with eGFR_cr-cys combined with UACR, the models based on urinary ntOPN and GDF15 could provide more accurate tools for DKD prediction. Our attempt might provide a feasible approach for searching promising biomarkers for clinical applications.

Ventilator-associated pneumonia (VAP) represents a complication occurring in patients undergoing mechanical ventilation. This study aimed to develop a Bayesian network model to identify factors associated with the occurrence of VAP.

A retrospective cohort analysis was conducted using data from patients aged ≥ 60 years who underwent mechanical ventilation in the Department of Intensive care unit at the Second Hospital of Shanxi Medical University between June 2018 and June 2022. Collected variables included demographic characteristics, clinical conditions, medication use, catheterization-related data, laboratory findings, nursing-related and mechanical ventilation-related data. The chi-square test and logistic regression analysis were applied to determine factors associated with VAP. A Bayesian network model was subsequently constructed using the max-min hill-climbing algorithm.

A total of 502 patients were included, comprising 332 males and 170 females, with a median age of 72 years (range: 60-100 years). The prevalence of VAP was 9.6% (48/502 patients). The constructed Bayesian network included 10 nodes and 17 directed edges. Direct associations with VAP were identified for antibiotic use exceeding three agents, reintubation, mechanical ventilation methods, and an Acute Physiology and Chronic Health Evaluation II (APACHE II) score ≥ 15. Indirect associations were observed for disease category, diabetes mellitus, presence of an indwelling central venous catheter, transfusion, and corticosteroid administration. The area under the receiver operating characteristic curve for the Bayesian network model was 0.84 (95% CI: 0.79-0.90).

The Bayesian network model elucidates the interrelationships among multiple factors associated with VAP. The model may provide ancillary information to help clinicians identify patient profiles associated with higher VAP risk and facilitate the implementation of early during mechanical ventilation.

To evaluate the association between glucagon-like peptide-1 receptor agonist (GLP-1RA) use and perioperative, postoperative and fusion-related outcomes following spine surgery.

A systematic search of PubMed/ MEDLINE, Scopus, Web of Science, and the Cochrane Library was conducted from inception through December 2025 in accordance with PRISMA 2020 guidelines. Comparative studies evaluating outcomes of spine surgery in patients exposed to GLP-1RAs versus non-users were included. Random-effects meta-analyses were performed for perioperative outcomes, medical and surgical complications, reoperation and fusion-related outcomes. Subgroup analyses were conducted based on diabetes status, fusion levels and duration of follow-up.

Twenty comparative studies with 546,668 patients were included in the analysis. GLP-1RA use was not associated with significant differences in perioperative or postoperative outcomes, including transfusion [log odds ratio (OR)=-0.25,95% CI:-0.67,0.17), operative time [mean difference (MD)=-5.3 min,95% CI:-23.9,13.3)], length of stay (MD=-0.19days,95% CI:-1.35,0.96), surgical site infection (logOR = 0.29,95% CI:-0.08,0.66), venous thromboembolism (logOR = 0.19,95% CI:-0.25,0.63), readmission (logOR = 0.31,95% CI:-0.07,0.69), reoperation (logOR = 0.12,95% CI:-0.17,0.42), or implant failure. In contrast, GLP-1RA use was associated with higher fusion success (logOR = 0.42,95% CI:0.33,0.51;p < 0.001), consistent across follow-up intervals.

In the available observational literature, GLP-1RA use is not associated with increased perioperative complications following spine surgery and may be related to improved fusion outcomes. These findings provide reassurance regarding perioperative safety and suggest a potential long-term benefit in arthrodesis, although prospective studies are needed to confirm causality and define optimal perioperative management strategies.

III.

Fentanyl and morphine are commonly prescribed opioids for cancer-related pain; however, the comparative associations between these agents and clinical outcomes in critically ill patients with malignancies remain unclear. This study aims to examine the associations of fentanyl versus morphine with delirium, length of stay (LOS) in the intensive care unit (ICU), and short-term mortality in this population. Clinical data from critically ill adults with malignancies admitted to the ICU for the first time were derived from the Medical Information Mart for Intensive Care-IV v3.1. The primary outcome was delirium. Secondary outcomes comprised 14- and 30-day all-cause mortality and the LOS in the ICU. Logistic regression models were adopted to evaluate the association of fentanyl versus morphine with delirium; linear regression models were applied to examine the association with the LOS in the ICU; Cox proportional hazards models were adopted to analyze associations with 14- and 30-day all-cause mortality. Subgroup analyses stratified by sex, age, hypertension, diabetes mellitus, and sepsis were performed to explore the stability of the findings. Propensity score matching was conducted for sensitivity analysis. Data from 2074 critically ill patients with malignancy (1051 fentanyl users and 1023 morphine users) were analyzed. Compared with those receiving fentanyl, patients receiving morphine demonstrated a significantly diminished risk of delirium (odds ratio = 0.273, 95% confidence interval [CI]: [0.200, 0.371], p < 0.001). Morphine was linked to a shorter LOS in the ICU relative to fentanyl (β = - 0.870, 95% CI: - 1.496 to - 0.243, p = 0.007). Nonetheless, compared to fentanyl users, those receiving morphine were linked to a 114.60% elevated risk of 14-day all-cause mortality (hazard ratio [HR] = 2.146, 95% CI: [1.503, 3.066], p < 0.001) and a 70.60% heightened risk of 30-day all-cause mortality (HR = 1.706, 95% CI [1.254, 2.320], p < 0.001). In conclusion, morphine is associated with a diminished risk of delirium and a shorter LOS in the ICU among critically ill patients with malignancy, yet concurrently linked to elevated short-term mortality. These findings indicate potentially divergent outcome associations within this population and may offer a point of reference for individualized analgesic management in critically ill patients with malignancy.

In four patients with diabetes and end-stage kidney disease, glycated hemoglobin A1c (HbA1c) showed marked, time-varying discordance with continuous glucose monitoring (CGM)-derived glucose management indicator, ranging from - 2.1% to + 6.2%. Anemia, erythropoiesis-stimulating therapy, iron disturbances, hemoglobinopathy, transfusion and glycemic variability contributed, supporting CGM metrics for safer assessment and treatment adjustment.