Search Results (2,229)

Glioblastoma (GBM) is an aggressive tumor type known to recur after maximal safe surgical resection followed by concurrent radiation therapy (RT) and chemotherapy (temozolomide—TMZ), and adjuvant TMZ maintenance chemotherapy. It exhibits high intratumor heterogeneity within a single specimen, and thus clinical management remains a challenge due to its rapid progression and high recurrence rate. Machine learning algorithms are currently being implemented in biomarker discovery to develop accurate predictive models that can guide clinical decision making. Emerging evidence identifies metabolomics as a critical player in understanding tumor metabolism and progression. Machine learning computation models have been instrumental in GBM classification and biomarker discovery, as well as the evaluation of tumor staging. Metabolomic profiling of biogenic amines in the setting of surgery, chemoradiation, and understanding relapse also suggests a coordination between metabolic pathways and tumor stage. Many challenges in machine learning and metabolomics-based approaches for disease classification remain due to the dimensionality of datasets, as well as identifying more streamlined panels of metabolite biomarkers. The purpose of this review is to showcase the recent developments in the applications of machine learning in metabolomics as a promising approach to enhancing the biomarker discovery process for future classification and interpretation of patient response to therapies for GBM management in the clinical setting. It also presents the major challenges of implementing machine learning approaches in GBM management and its future directions. Full article

Introduction: The management of resectable non-small cell lung cancer has long relied on a relatively limited set of determinants, primarily anatomical resectability and pathological stage. Although these parameters remain central to therapeutic planning, accumulating clinical and translational evidence indicates that they do not fully explain variability in outcomes observed after lung cancer surgery. The primary aim of this review is to evaluate whether current evidence supports the need for a novel heuristic framework in resectable NSCLC. Secondary aims are to examine how host-related, clinical, and data-driven factors contribute to prognosis and treatment selection beyond conventional staging systems. Methods: This review integrates evidence from clinical studies, national registries, and translational analyses to examine how these dimensions contribute to prognosis and treatment selection. Results: Over the past two decades, advances in surgical techniques, perioperative management, systemic therapies, and large-scale clinical databases have revealed additional determinants of prognosis beyond tumor burden, including physiological reserve, nutritional condition, systemic inflammatory state, comorbidities, and socioeconomic environment. Developments in multimodal strategies and minimally invasive surgery have reshaped the therapeutic landscape. Data-driven approaches have identified clinically meaningful subgroups not captured by conventional staging systems. Conclusions: A heuristic framework integrating tumor biology, patient characteristics, and treatment context may better reflect the complexity of contemporary thoracic oncology practice. Full article

Aortic valve stenosis (AS) is assessed by echocardiography in clinical practice. Conventionally, the aortic valve area, peak transaortic valve velocity/gradient and the mean transvalvular gradient determine if the AS is categorized as mild, moderate or severe. Recently, the entity of paradoxical low-flow, low-gradient AS despite normal left ventricular ejection fraction (LVEF) was described and flow (as determined by stroke volume indexed to body surface area) was used to further categorize AS. The new European Society of Cardiology (ESC) and the European Association for Cardio-Thoracic Surgery (EACTS) guidelines in 2025 recommended a new phenotype-based classification, which improved the prognostication of AS. There are now five phenotypes: (1) concordant high-gradient AS; (2) low-flow, low-gradient AS with reduced LVEF; (3) low-flow, low-gradient AS with preserved LVEF; (4) normal-flow, low-gradient AS with preserved LVEF; and (5) discordant high-gradient AS. These appear to have different underlying pathophysiology, and hence prognostication and therapy. In addition, categories of AS in the setting of reduced LVEF are further divided based on their responses to dobutamine or exercise stress, which may result in different therapeutic strategies. In the transaortic valvular replacement (TAVR) versus the surgical aortic valve replacement (SAVR) era, the classification of these AS groups may have differing implications on the appropriate interventions. Furthermore, there are investigations on the effect of AS on the left ventricle and other chambers and stages of AS based on the extent of cardiac damage, which may have important prognostic value post-AVR. On the other spectrum, there are new developments in imaging analysis, such as using artificial intelligence. This state-of-the-art paper will comprehensively review the important updates in AS and its clinical implications. Full article

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

Triple-negative breast cancer (TNBC) has been associated with a poorer prognosis than other subtypes, due to its more aggressive behaviour. Since 2020, significant advances in locoregional and systemic therapy have improved outcomes for patients with TNBC, but the implementation of these treatments remains inconsistent across Canada. There is, therefore, a critical need for evidence-informed, consensus-driven guidance to support the integration of new therapies into practice. Research Excellence, Active Leadership Canadian Breast Cancer Alliance (REAL Alliance), a pan-Canadian group of breast cancer specialists and Breast Cancer Canada, a patient advocacy organization, convened to develop national clinical consensus recommendations for the management of breast cancer. Through a selective literature review and modified Delphi process of national experts in the fields of medical oncology, radiation oncology, surgical oncology and pharmacy, REAL Alliance developed national consensus recommendations for the management of TNBC. The result is a set of 23 recommendations: four overall general recommendations, 11 in early-stage TNBC, and eight in metastatic TNBC. These recommendations are intended for oncology healthcare professionals, and are intended to guide evidence-informed, consistent care across Canada. 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

Background/Objectives: Healthcare facilities are among the most energy-intensive public buildings, yet hospital decision-support models rarely integrate energy-related performance indicators alongside operational metrics. This study aims to address this gap by developing a discrete-event simulation framework capable of jointly evaluating clinical efficiency and energy consumption in elective orthopedic surgical pathways. Methods: A comprehensive discrete-event simulation model was developed to represent the diagnostic imaging and orthopedic surgical process. The model was parameterized using a hybrid data-collection approach that combined clinical activity data, scientific literature, and expert judgment. Energy consumption was modeled by differentiating fixed loads, such as heating, ventilation, and air-conditioning systems and lighting, from activity-dependent loads associated with diagnostic and surgical equipment. Baseline performance was assessed and compared with alternative scenarios for organizational and technological improvements. Results: The analysis showed that fixed infrastructural loads, particularly HVAC systems, were the main drivers of per-patient energy consumption, with inefficient space utilization and prolonged idle times. Scenario analysis demonstrated that organizational interventions, such as increasing operating room throughput and optimizing MRI scheduling, can substantially reduce energy intensity by diluting fixed loads and decreasing idle consumption. Technological interventions, such as replacing conventional surgical lamps with LED systems, produced smaller but still beneficial reductions. The combined implementation of organizational and technological strategies yielded the greatest overall improvement. Conclusions: Integrating energy metrics into discrete-event simulation provides effective support for hospital decision-making by revealing the interaction between workflow design, resource utilization, and environmental performance. The findings indicate that organizational redesign, particularly when combined with technological upgrades, can significantly improve both operational efficiency and sustainability in hospital settings. This study highlights discrete-event simulation as a promising tool for energy-aware healthcare planning. Full article

Background: Kounis syndrome is an allergic acute coronary syndrome precipitated by coronary vasospasm, plaque destabilization, stent thrombosis, or bypass occlusion. Cardiac surgery represents a uniquely high-risk setting due to cardiopulmonary bypass–associated inflammation and exposure to multiple pharmaceutical agents. Importantly, Kounis syndrome remains underrecognized in this context, as classical signs of anaphylaxis may be masked under general anesthesia and cardiopulmonary bypass, while ischemic manifestations may be misattributed to other perioperative conditions. Methods: A narrative review of PubMed-indexed literature was conducted to synthesize current evidence on the pathophysiology, perioperative triggers, clinical presentation, diagnostic strategies, and management of Kounis syndrome in cardiac surgery, with emphasis on intraoperative recognition and surgical decision-making. Published cases were retrieved involving perioperative cardiac surgery patients with a definite diagnosis of Kounis syndrome. Additionally, cases presenting with severe perioperative anaphylaxis and life-threatening cardiovascular involvement (grade III with cardiovascular collapse and grade IV with cardiac arrest) were included as possible Kounis syndrome, reflecting real-world diagnostic uncertainty in the intraoperative setting. Results: The literature review identified five cases of definite Kounis syndrome and ten cases of possible Kounis syndrome, including three cases with cardiovascular collapse and seven cases with cardiac arrest. Recurrent episodes were reported in several patients, particularly due to re-exposure to the triggering agent. In the context of cardiac surgery, Kounis syndrome is most frequently triggered by chlorhexidine, protamine, antibiotic prophylaxis, and anesthetic agents. The clinical presentation is often subtle during cardiopulmonary bypass. Vasoplegia, pulmonary hypertension, ventricular dysfunction, new regional wall-motion abnormalities, and hyperdynamic ventricles on transesophageal echocardiography commonly precede overt electrocardiographic changes. Diagnosis is primarily clinical and relies on intraoperative ultrasound, hemodynamic monitoring, serum tryptase, serum troponin, and, when indicated, coronary angiography. A dual-pathway approach addressing both anaphylaxis and myocardial ischemia is essential; however, one component may predominate, particularly in perioperative patients with limited clinical information, potentially leading to misdiagnosis. A multidisciplinary approach is therefore required for rapid diagnosis and individualized management. In refractory cases, cardiopulmonary bypass or ventricular assist devices may provide lifesaving support. Conclusions: Kounis syndrome remains underrecognized in cardiac surgery but carries significant morbidity. Increased clinical awareness, multidisciplinary collaboration, structured diagnostic approaches, and preventive strategies are essential to improve outcomes and reduce the risk of recurrence during future procedures. 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: Postoperative anemia associated with intertrochanteric hip fracture is a detrimental complication that detrimentally impairs patients’ outcomes. This study is designed to develop an online predictive tool to assist physicians in developing surgical blood preparation strategies to prevent the occurrence of postoperative anemia. Methods: This study included data collected from June 2017 to June 2025 on intertrochanteric hip fracture patients at Tangdu Hospital, including demographic information, comorbidities, vital signs, and laboratory results. LASSO regression was used to select predictive variables, and seven machine learning techniques: Logistic Regression, Support Vector Machine, Decision Tree, LightGBM, XGBoost, Neural Networks, and Random Forest, were compared to identify the best tool for predicting postoperative anemia risk. We created a patient-specific risk prediction tool with SHAP-driven interpretability for clinical decision support. Results: A total of 815 patients were included in the analysis, of whom 208 (25.5%) presented with postoperative anemia. Eight variables were selected to build seven machine learning models. Among these, the SVM model exhibited the best predictive performance in terms of discrimination, calibration, and clinical applicability, with an AUC range of 0.827–0.831. In test sets encompassing diverse population characteristics, SVM achieved the highest sensitivity (72.73%), accuracy (77.78%), and F1 score (57.14%). Conclusions: We established an online prediction platform for clinical practice, enabling clinicians to assess anemia risk in intertrochanteric hip fracture patients and support early prevention of postoperative anemia. 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

Syphilitic panuveitis is a severe and diagnostically highly challenging manifestation of ocular syphilis. Its predominant posterior-segment involvement and its tendency to mimic noninfectious or viral uveitis may delay etiologic recognition and increase the risk of permanent vision loss. Rhegmatogenous retinal detachment (RRD) is a rare but vision-threatening complication that likely reflects advanced, inflammation-induced disruption of the vitreoretinal interface. A narrative literature review was conducted using the PubMed, Scopus, and Web of Science databases (January 2000 to 10 September 2025). Studies addressing the clinical presentation, imaging findings, pathophysiology, and management of syphilitic panuveitis and associated rhegmatogenous retinal detachment were analyzed. Infectious mimickers were also presented, with particular emphasis on West Nile virus (WNV). Evidence was synthesized qualitatively. Posterior uveitis and panuveitis are one of the most common ocular manifestations of syphilis. Posterior segment involvement in ocular syphilis is frequently bilateral, typically presenting with dense vitritis, retinal vasculitis, and optic neuropathy. RRD is a rare presenting complication, most often developing in areas of prior inflammatory retinitis and arising due to retinal necrosis, persistent vitreoretinal traction, and early proliferative vitreoretinopathy, which increases surgical complexity and may limit functional recovery. HIV coinfection often modifies disease severity. In relevant endemic or seasonal settings, WNV-associated ocular inflammation represents an important diagnostic pitfall. Syphilitic panuveitis should be considered early in patients presenting with unexplained posterior uveitis or panuveitis. Routine testing for syphilis and HIV in the uveitic laboratory palette, together with targeted evaluation for infectious mimickers, is essential to reduce diagnostic delay and avoid inappropriate immunosuppression. RRD should be recognized as a marker of advanced, inflammation-induced vitreoretinal interface damage requiring timely antimicrobial therapy and early involvement of vitreoretinal surgery. Full article

Podiatry residents may benefit from addiction medicine rotations due to substantial overlap between podiatric needs and substance use disorders (SUDs), particularly in the hospital setting. In a semi-structured format, we describe the cases of two podiatry residents, perhaps the first ever documented, who rotated with an inpatient addiction medicine consult team at an urban, academic hospital. These two residents joined the addiction consult team in 2023 and 2024 and rated their confidence in twelve learning objectives via a five-point Likert scale before and after the rotation (2 weeks long). They also rated their attitude toward the value of addiction services. Post-rotation feedback from the module and ad hoc e-mail correspondence are included. Residents 1 and 2 joined the team and engaged well in orientating with the team, eventually providing near-independent addiction medicine consultations for primary inpatient teams. Pre/post data showed large increases in confidence in learning objectives (mean scores 2.1 to 4.9 for Resident 1, and mean scores 1.5 to 4.0 for Resident 2). They both reported positive experiences, and months later reflected on both pragmatic (e.g., available resources) and attitude-related (e.g., understanding the importance of substance use context for patients) educational gains. In summary, residents from surgical specialties like podiatry may benefit from inpatient addiction medicine exposure. It is unclear whether their rotation spots could be better utilized by those in other specialties, but SUDs are prevalent in a multitude of settings, arguing for broad dissemination of SUD treatment education. Full article

Peripheral nerve injuries often lead to incomplete recovery despite surgical repair. Vitamin B12 and folic acid have been implicated in nerve regeneration, but their comparative effects have not been systematically evaluated. Twenty-four male Wistar rats underwent femoral nerve transection and were assigned to three groups: control, vitamin B12 (2500 µg/kg weekly, subcutaneous), and folic acid (40 mg/L in drinking water). Functional recovery was assessed over eight weeks using foot-base angle (FBA) during beam walking. Histological analysis evaluated axon counts and myelination (g-ratio). Both treatments accelerated early gait recovery compared to controls, with significant FBA improvement at week 4 (p < 0.05). Vitamin B12 produced sustained functional benefits through week 8 and superior myelination (lower g-ratio, p < 0.0001), whereas folic acid increased axon numbers but did not enhance myelin thickness or late-phase recovery. High-dose vitamin B12 significantly improves structural and functional outcomes after femoral nerve injury, while folic acid primarily supports early axonal regrowth. Vitamin B12 represents a promising pharmacological adjunct for peripheral nerve repair. Further research should explore optimal dosing strategies and long-term effects in clinical settings. To our knowledge, no prior study has directly compared the effects of folic acid and vitamin B12 supplementation within the rat femoral-nerve model, providing the rationale for the present head-to-head design. Full article

Disparity estimation from stereo-endoscopic images is critical for 3D reconstruction in minimally invasive surgery (MIS). However, surgical environments have inherent interference factors including soft tissue deformation, motion blur, and photometric inconsistency. Currently, self-supervised generative networks such as StyleGAN offer an alternative method, but their reliance on iterative latent optimization leads to high computational latency and limits practical deployment. In this work, we propose a temporal latent prediction method to accelerate this optimization process. Instead of designing a brand new generator, our framework learns to predict an optimized initial latent vector, thereby reducing the number of optimization steps and per-frame inference time. Crucially, this prediction-guided mechanism does not alter the architecture or inference logic of the generator, ensuring the fidelity of reconstruction is comparable to that of the original method. Experiments on Phantom and In vivo datasets demonstrate that our method reduces average optimization steps by 16–59% and cuts per-frame latency by about 2.3×, compared to baseline predictors and initialization strategies. Importantly, the final photometric loss remains nearly identical across all methods, confirming that acceleration does not compromise reconstruction quality. These results position our approach as a practical step toward efficient, self-supervised stereo-endoscopic reconstruction in clinical settings. Full article