Search Results (4,306)

Background: Intrahepatic cholangiocarcinoma (ihCC) is a rare aggressive liver malignancy with rising incidence. For resectable cases, surgery is the only curative approach, but recurrence rates remain high. These challenges highlight the need for personalized, evidence-based clinical decision-making to improve patient outcomes. To address this, we developed the Multiphasic Evidential Decision-making Matrix (MedMax) to support systematic, individualized therapeutic strategies for ihCC. Methods: In this retrospective single-center study, between 2010 and 2020, we assessed the ability of the MedMax matrix to make treatment decisions in 489 consecutive patients with ihCC or suspected ihCC. Patients were divided into two cohorts depending on whether their tumor was operable (surgical cohort, n = 335) or non-operable (non-surgical cohort, n = 154). We assessed the accuracy of diagnostic confirmation and treatment allocation by MedMax and evaluated how the model’s recommendations corresponded to those made by the tumor board. Results: In the surgical cohort, MedMax achieved 100% accuracy in diagnostic confirmation and 97.9% accuracy in treatment allocation. There was 74.3% concordance between the resection type proposed by MedMax and actual extent of resection. This discrepancy was caused by deviations from the preoperative plan based on intraoperative findings, which could not have been predicted preoperatively. In the non-surgical cohort, MedMax again achieved 100% accuracy in diagnostic confirmation and 98.7% accuracy in treatment allocation. All discrepancies between the decisions made by MedMax and those made by the tumor board were attributed complex, high-risk patient profiles. MedMax reliably identified risk factors (such as advanced comorbidities and multifocal disease) in both cohorts. Conclusions: The MedMax matrix can make accurate, reliable and transparent decisions about the diagnosis and treatment of patients with ihCC thanks to its modular, evidence-based approach. It can also stratify and document risks in both surgical and non-surgical settings. Full article

Background/Objectives: Atrial fibrillation (AF) is highly prevalent among older adults and is associated with increased thromboembolic risk. Although anticoagulant therapy (AC) is strongly recommended, its use in elderly and multimorbid patients remains suboptimal. This study aimed to describe long-term trends in AC prescribing patterns among hospitalized older patients with AF. Methods: We conducted a retrospective observational analysis using data from the Italian REPOSI registry, including patients aged ≥65 years hospitalized with AF between 2010 and 2023. AC at admission and discharge was analyzed, including vitamin K antagonists (VKAs), direct oral anticoagulants (DOACs), and antiplatelet agents. Temporal trends, admission-to-discharge treatment changes, and patient characteristics associated with therapy modification were assessed descriptively. Results: The study included 2061 AF patients, characterized by multimorbidity and high thromboembolic risk. A marked shift from VKAs to DOACs was observed over time. However, a substantial proportion of cases remained without AC or received only antiplatelet therapy at both admission and discharge, with untreated individuals being generally older and more clinically complex. DOAC use increased steadily but showed a slight decline at discharge after 2020. Clinical variables available in the registry only partially explained AC changes during hospitalization. Conclusions: Despite increasing adoption of DOACs, AC underuse remains frequent among elderly hospitalized patients with AF. These real-world data highlight persistent challenges in AC management in complex older adults and underscore the need for more comprehensive clinical information and data-driven tools to support individualized therapeutic decision-making. Full article

Antimicrobial resistance (AMR) is an increasing concern in veterinary medicine and may compromise empirical treatment of feline urinary tract infections (UTIs). This retrospective observational study evaluated antimicrobial resistance patterns and their association with multidrug resistance (MDR) in bacterial isolates obtained from urine cultures of cats presented to a feline referral practice in Lisbon, Portugal, between January 2023 and December 2025. A total of 174 cats with positive urine cultures were included, yielding 178 bacterial isolates. Escherichia coli was the most frequent pathogen (57.30%), followed by Enterococcus spp. (16.98%) and Staphylococcus spp. (14.61%). Antimicrobial resistance was detected in 107/178 isolates (60.11%), and 76/178 (42.70%) were classified as multidrug-resistant. Extended-spectrum beta-lactamase-producing Escherichia coli and methicillin-resistant Staphylococcus strains were also identified. Resistance to penicillins and fluoroquinolones was significantly associated with MDR (p < 0.001). These findings highlight the high burden of antimicrobial resistance in feline urinary isolates in this clinical setting and support routine urine culture and susceptibility testing to guide therapeutic decision-making, particularly in recurrent, complicated, or high-risk cases. Full article

Background/Objectives: Early detection through minimally invasive approaches is critical for timely patient stratification and optimal therapeutic decision-making in colorectal cancer (CRC). Liquid biopsy, based on the analysis of tumor-derived components in blood and other body fluids, has emerged as a promising strategy to overcome current limitations in CRC diagnosis and follow-up. This review evaluates the current landscape of liquid biopsy clinical trials in CRC, focusing on predictive biomarker detection, prognostic assessment, and disease monitoring. Methods: ClinicalTrials.gov was searched using the terms “colorectal cancer” and “liquid biopsy” yielding 153 registered trials. After manual screening, 44 trials were excluded for not using liquid biopsy for CRC management, leaving 109 trials for analysis. Of these, 25 were completed, and 13 had publicly available results related to liquid biopsy. Results: The included trials were conducted across 27 countries on four continents. Overall, 119 biomolecules assessments and 167 different endpoints were reported across 109 clinical trials. Because individual trials could evaluate multiple biomolecules and endpoints, counts exceed the total number of trials. Cell-free DNA (cfDNA) was evaluated in 92/109 trials (84%) and accounting for 77% of all biomolecule assessments. Circulatingtumor cells (CTCs) were analyzed in 9/109 trials (8%, representing 8% of all the biomolecules analyzed), and microRNAs (miRNAs) in 8/109 (7%, representing 7% of all the biomolecules analyzed). Treatment sensitivity was the most common endpoint (57/109, 52% of the clinical trials; representing 34% of all the 167 different endpoints analyzed), followed by disease progression (28/109, 26%; representing 17% of all the different endpoints analyzed) and diagnostic applications (21/109, 19%; representing 12% of all the different endpoints analyzed). Among the 25 completed studies, 10/25 (40%) were interventional and 15/25 (60%) observational, spanning 14 countries. The majority of completed trials (21/25, 84%) used cfDNA. Interventional studies were predominantly phase II (5/10), with fewer phase III trials (2/10), primarily evaluating treatment response, particularly in relation to EGFR inhibitors and RAS/BRAF mutation status. Four observational studies (4/15) investigated emerging biomarkers, including long noncoding RNAs and miRNAs. Conclusions: Current clinical trials highlight cfDNA as the dominant and most clinically advanced liquid biopsy biomarker in CRC, primarily used for treatment guidance and disease monitoring. In contrast, CTCs and RNA-based biomarkers remain underrepresented. The limited number of randomized late-phase trials, heterogeneity in study design, and technical challenges associated with emerging biomarkers underscore the need for standardized methodologies and robust validation before routine clinical implementation. Full article

Tooth structure anomalies, though not frequently described, can be observed in the external appearance not only of humans but also of dogs. The emergence of an oversized set of teeth is not solely an esthetic and health problem, but often also leads to behavioral issues. In the commonly available medical literature, there are many cases describing the occurrence and treatment of double teeth, both in the incisors and in the cheek teeth. In this article, the authors describe a clinical case of a one-year-old female Golden Retriever dog diagnosed with a double tooth in her permanent dentition. The complex morphology of the affected tooth posed a considerable diagnostic and therapeutic challenge. Surgical separation of the tooth was performed, requiring an individualized treatment approach and the adaptation of protocols derived primarily from human dentistry. This case highlights the diagnostic and clinical decision-making difficulties associated with such anomalies. It also emphasizes the importance of tailored therapeutic strategies for managing rare dental developmental abnormalities in dogs. The teeth were successfully surgically separated, and thus the present report contributes to the limited body of literature on double teeth in veterinary patients and provides practical insight into their management. This description of the first case of this type in veterinary dentistry aims to encourage readers to explore the topic of double teeth and demonstrates a non-standard way of thinking and dealing with such a tooth. The presented case is unique from both a diagnostic and therapeutic perspective. Previous publications have focused on these abnormalities as separate entities, failing to consider their simultaneous occurrence within a single tooth. The therapeutic approach employed also deserves particular attention. The most commonly recommended approach involves extraction of the affected teeth; however, in this case, an attempt was made to separate and preserve them, representing a novel clinical approach. Full article

Breast reconstruction represents an integral component of contemporary breast cancer management, with substantial impact on patients’ psychological well-being, body image, and overall quality of life. Given the profound symbolic and personal significance of the breast, mastectomy—whether total or partial—extends beyond oncologic resection and may result in considerable aesthetic, functional, and psychosocial consequences. For this reason, reconstructive planning should be incorporated into the initial multidisciplinary treatment strategy while ensuring that oncologic safety and adjuvant therapies are never compromised. Breast reconstruction may be achieved using autologous tissue, implant-based techniques, or a combination of both approaches. Each method carries specific advantages, limitations, and potential complications and must be tailored to the individual patient’s oncologic status, anatomy, and expectations. This article provides a historical overview of the evolution of breast cancer treatment and reconstructive techniques. It further examines the principles, benefits, and challenges associated with different reconstructive modalities, highlighting key considerations in clinical decision-making and long-term outcomes. Full article

Background/Objectives: Efficient management of intensive care unit (ICU) resources is a critical challenge for modern healthcare systems, which must balance high-quality patient care with operational and financial performance. ICU length of stay (LOS) is a key metric of clinical complexity and hospital efficiency. However, traditional methods for predicting LOS often fail to capture the complex, nonlinear interactions among physiological, demographic, and treatment-related variables. Machine learning (ML) and deep learning (DL) models have emerged as promising tools for enhancing predictive accuracy and supporting data-driven decision-making. Methods: This study presents a systematic review and meta-analysis of ML and DL approaches for predicting ICU LOS in adult patients. Following PRISMA guidelines, eight scientific databases were searched, yielding 33 eligible studies published between 2015 and 2025. Results: Mixed medical–surgical ICUs were the most common setting (51.5%), and 45.5% of datasets were sourced from public repositories. Most studies (19/33) focused on binary classification of prolonged stays, although thresholds ranged from >48 h to ≥14 days. The pooled results from ten studies yielded an AUROC of 0.9005 (95% CI: 0.8890–0.9121), indicating strong predictive capability across diverse clinical contexts. Subgroup analyses showed comparable performance between specialized surgical and general ICUs. Conclusions: These findings suggest that AI-driven LOS prediction models exhibit strong discriminatory power for ICU LOS prediction, supporting hospital capacity planning. However, to translate this into reliable clinical support, the methodological heterogeneity, scarcity of external validation, and near absence of calibration reporting identified in this review need to be addressed. Full article

Background: Posterior spinal fusion (PSF) for adolescent idiopathic scoliosis (AIS) is a standard procedure with recognized long-term complications that may emerge years after surgery. Informed consent requires disclosure of material risks, but it is unclear whether these long-term sequelae are consistently communicated. This study systematically reviewed publicly available consent materials to assess disclosure of evidence-based long-term complications of PSF for AIS. Methods: Official websites of spine, orthopedic, and neurosurgical societies, along with major hospitals across North America, South America, Europe, and Australia, were searched for publicly available informed consent forms and patient information leaflets related to PSF for AIS. Documents were assessed for explicit mention of predefined long-term complications: chronic pain/health-related quality of life, pseudoarthrosis, adjacent segment degeneration, future surgery, pulmonary function impact, late infection, local tissue reaction to metal debris, and pregnancy-related issues. Disclosure frequencies were calculated. Results: Thirty-one documents from ten countries were included. Immediate perioperative risks were almost universally reported, whereas long-term complications were inconsistently disclosed. Reporting frequencies were: pseudoarthrosis, 80.6% (n = 25); future surgery, 67.7% (n = 21); adjacent segment degeneration, 51.6% (n = 16); chronic pain, 48.4% (n = 15); local tissue reaction to metal debris, 38.7% (n = 12); late infection, 25.8% (n = 8); pregnancy-related issues, 22.6% (n = 7); and pulmonary impact, 9.7% (n = 3). Conclusions: Publicly available consent materials for AIS surgery incompletely disclose long-term complications compared with the published evidence. However, written information sheets and consent forms represent only one component of the consent process. Consistently with the patient-centered standard articulated in Montgomery v Lanarkshire Health Board, informed consent should include discussion of material risks, benefits, reasonable alternative treatments including standard care, and the option of no treatment, with disclosure tailored to what matters to the patient and family. Updating written materials to better reflect lifelong risks may strengthen one important component of informed consent and shared decision-making for patients and families. Full article

Quality evaluation in production systems represents a significant challenge in the manufacturing industry, particularly in environments where expert judgment plays a key role in managing the inherent uncertainty of the production system. This study proposes a fuzzy multicriteria decision-making control chart, termed Fuzzy Decision-Making Control Chart based on AHP-Extent and Triangular Fuzzy Numbers (FDMCC-AHPE). The method integrates expert knowledge through triangular fuzzy numbers and a Fuzzy Analytic Hierarchy Process supported by Extent Analysis, to define fuzzy decision intervals for quality assessment and subsequently perform a structured analysis to classify the product within a control chart framework. In this framework, expert judgments expressed through linguistic evaluations are systematically translated into triangular fuzzy numbers and processed using FAHP–Extent Analysis, allowing the aggregation of subjective assessments within a structured mathematical decision model. The proposed method was validated in a tannery company, specifically in the retanning process. The industrial case study considers both qualitative criteria, such as surface defects and color uniformity, and quantitative process variables that include bath pH, treatment duration, and processing temperature. The results were compared with an empirical expert-based evaluation and a structured expert assessment supported by a multicriteria decision-making method. The findings demonstrate that the FDMCC-AHPE exhibits greater sensitivity in discriminating between quality states under uncertain evaluation conditions, particularly when samples involve complex evaluation conditions. Full article

Ankle–foot orthoses (AFOs) are widely used in the rehabilitation of patients with neurological or musculoskeletal disorders. However, treatment outcomes may be influenced by incorrect use of the device or by inappropriate orthosis selection. Since many types of AFOs are available, differing in materials, stiffness, and geometry, an objective evaluation tool can support clinical decision-making. This work presents the design, development, and characterization of an instrumented AFO able to quantify relevant gait parameters in an objective way. The proposed device integrates three measurement modalities in a compact wearable structure. Two longitudinal strain gauges estimate ankle plantar- and dorsiflexion angles. Two force-sensitive elements detect foot–ground contact and allow identification of stance and swing phases of the gait cycle. A single inertial measurement unit (IMU) is used to measure lateral shank inclination. The strain-gauge-based angle estimation was validated against a gold-standard motion capture system, achieving a root mean square error of approximately 1.6 degrees and showing higher accuracy than the IMU for plantar/dorsiflexion measurement, while maintaining a simple electronic architecture. The force sensors were validated using a force platform and demonstrated reliable detection of loading and unloading events. Monitoring lateral inclination through the single IMU provides additional information related to balance and potential fall risk. Data are transmitted via Bluetooth Low Energy (BLE) to a custom Python-based application for real-time visualization and recording. Overall, the results validate the electronic instrumentation and demonstrate reliable system performance, indicating that the proposed instrumented AFO represents a promising platform for objective gait assessment and future clinical applications. Full article

Glucosylsphingosine (lyso-Gb1) serves as a biomarker for evaluating disease activity in Gaucher disease (GD). While treatment-related changes are documented, the dynamics of lyso-Gb1 during untreated states remain poorly understood. This retrospective, longitudinal cohort study utilized a large GD database comprising 701 patients and over 6200 visits with lyso-Gb1 measurements. Patients with at least two untreated visits were included in the analysis (n = 272). A significant change was defined as ≥50 ng/mL for lyso-Gb1, ≥1 g/dL for hemoglobin, and ≥50 × 10⁹/L for platelet count. Multivariable logistic regression analyses identified clinical factors associated with lyso-Gb1 decline or an increase. During untreated states, 35 patients (12.9%; 95% CI 9.4–17.5%) exhibited a decline in lyso-Gb1, with a median decrease of 96.3 ng/mL. This decline was more common in females (OR 3.50, p = 0.032) and associated with higher initial lyso-Gb1 levels (p < 0.001) and baseline hemoglobin (p = 0.032). An increase in lyso-Gb1 was observed in 98 patients (36.0%; 95% CI 30.5–41.9%), with a median rise of 135.1 ng/mL. This increase correlated with lower baseline platelet counts (p = 0.003), lower baseline hemoglobin (p = 0.002), and longer follow-up duration (p = 0.001). In many cases, lyso-Gb1 increases were observed without a preceding change in hemoglobin or platelet count. In summary, declines in lyso-Gb1 in untreated states are rare but possible. The association with female sex may reflect inflammatory effects. Although increases in lyso-Gb1 were expected without treatment, they occurred mainly in patients with higher disease severity markers. Nevertheless, most patients in the untreated states remained stable within ±50 ng/mL. These findings demonstrate a heterogeneous trajectory of lyso-Gb1 across untreated states and highlight the importance of interpreting lyso-Gb1 changes within the clinical context when making treatment decisions. Full article

Background/Objectives: The purpose of this study was to examine the sex-specific distribution of traumatic spinal fractures and potential predictive clinical factors for a more well-founded treatment evaluation. Methods: This study is a retrospective cohort study. Data from electronic medical records were analyzed and compiled in a database. Demographic information, trauma-specific characteristics, and radiological measurements, as well as laboratory values and surgical treatments, were collected. Only surgical cases were included in this study. Statistical analyses were performed using the IBM SPSS Statistics program. Chi-square tests, effect sizes, and 95 confidence intervals were used for comparison of categorical variables, and means and standard deviations were calculated, as well as Levene’s test for equality and t-tests for analyzing continuous variables. The statistical significance was set at a two-tailed p < 0.05. Results: A total of 164 patients were included, with a mean age of 58.03 years. Statistically significant differences between sexes were found in age (p = 0.04), GCS (p = 0.03), hemoglobin (p = 0.03), hematocrit (p = 0.007), and the one-year post-surgical intervertebral angle (p = 0.004). AIS score showed statistically significant differences in the cervical and lumbar sections (p < 0.015; p = 0.022) and the overall spine (p = 0.049). No statistically significant difference in the HU values in the vertebra above the fracture was found between men and women. Women showed significantly larger one-year postoperative intervertebral angles than men. Conclusion: Vertebrae with lower HU values tend to collapse despite stable surgical treatment; therefore, additional bone quality assessment should be contemplated. These findings highlight sex-specific considerations for future clinical decision-making. Full article

Background: Excessive gingival display is frequently associated with upper lip hypermobility and represents a common aesthetic concern. Several therapeutic approaches have been proposed, including botulinum toxin type A injections, lip repositioning surgery (LRS), and combined techniques; however, no clear consensus exists regarding the most effective and stable treatment option. Methods: A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PRISMA) guidelines. A comprehensive search of multiple electronic databases was performed, leading to the inclusion of 17 human studies that met predefined PICOS criteria. The review protocol was registered in PROSPERO (CRD420261281920). Results: Most included studies reported favorable outcomes in terms of reduction in gingival display, improvement in smile aesthetics, and patient satisfaction. No major adverse effects were reported, suggesting acceptable safety profiles for all therapeutic modalities. Outcomes varied depending on the type of intervention, surgical technique, botulinum toxin dosage and injection protocol, and the initial severity of upper lip hypermobility. Conclusions: Both botulinum toxin injections and LRS demonstrated effectiveness in reducing excessive gingival display. Botulinum toxin provided a rapid but temporary improvement, whereas modified LRS showed greater stability over time. Combined approaches appeared to offer the most consistent long-term results by limiting postoperative relapse. Further standardized protocols and long-term clinical studies are needed to confirm these findings and support evidence-based clinical decision-making. Full article

Rotator cuff injuries are among the most common musculoskeletal conditions that affect shoulder function and can ultimately impact quality of life. While physical therapy is essential in the care of rotator cuff injuries, the ideal dose of therapeutic exercises continues to be a significant clinical dilemma because of the generalized nature of rehabilitation protocols. This pilot study proposes a machine learning approach to personalize rehabilitation using surface electromyography (sEMG) data collected from eight healthy individuals by testing four key shoulder movements: scaption, internal rotation, external rotation, and external rotation at 90° abduction. In this research, the XGBoost algorithm was used to model muscle activation patterns by achieving a high predictive accuracy (R² = 0.5325; MSE = 0.0084 μV²). Because sEMG reliably measures superficial muscle activity, a linear programming model was used to divide a 60 min therapy session in a way that increases activation of superficial muscles (such as deltoid and trapezius) while reducing strain on deep muscles (such as supraspinatus and infraspinatus). Three optimization scenarios were tested by reflecting a different clinical goal: prioritizing superficial muscles, minimizing deep muscle strain, or balancing both. Optimized time allocations assigned more time to external rotation at 90° abduction and scaption. This research demonstrates the potential for data-driven methods to transform rotator cuff rehabilitation through personalized and evidence-based treatment plans. The results enhance clinical practice by enabling adaptive rehabilitation planning and show that machine learning can support decision-making in complex muscle activation analysis with strong performance and low latency. Full article

Background: This article provides a comprehensive overview of recent advancements in artificial intelligence (AI) and deep-learning technologies for breast cancer (BC) diagnosis across various imaging modalities. Methods: A systematic review was conducted in strict adherence to the PRISMA guidelines, incorporating a comparative analysis of 65 peer-reviewed studies published between 2018 and 2024. The evaluation focused on diagnostic performance, architectural developments, and clinical integration strategies. Results: The review synthesizes primary findings on convolutional neural networks (CNNs), emerging architectures including graph neural networks, and hybrid models, with diagnostic accuracy, risk prediction, and personalized screening strategies identified as the leading research domains. Notable achievements include CNNs attaining up to 98.5% accuracy in mammography and Vision Transformers reaching 96% in histopathological analysis. Furthermore, the implementation of explainable AI methodologies, such as SHAP, LIME, and Grad-CAM, is emphasized for maintaining transparency, trust, and accountability in clinical decision-making. Conclusions: AI constitutes a pivotal factor in facilitating early BC diagnosis and optimizing treatment outcomes. Nevertheless, significant challenges persist, including dataset heterogeneity, model generalizability, standardization of imaging protocols, computational resource limitations, and the seamless integration of these technologies into established clinical workflows. Future research must prioritize robust multi-dataset validation and standardized implementation frameworks to overcome existing limitations and advance successful BC diagnostic practices. Full article