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    The Pakistan Palatal Fistula Difficulty Index (PPFDI): Development and Initial Validation of a Novel Scoring Index for Surgical Complexity and Referral Guidance.

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    Palatal fistulae remain the most common complication following cleft palate repair, with recent studies reporting incidence rates ranging from 2% to 35%. Existing classification systems offer limited guidance on surgical complexity or referral pathways. This study developed and validated the Pakistan Palatal Fistula Difficulty Index (PPFDI), a novel scoring system designed to quantify fistula complexity based on 6 domains: location, size, configuration, number of fistulae, recurrence history, and velopharyngeal function. A 3-tiered framework was proposed to guide referral based on complexity level and surgeon experience. Each domain was scored on a 3-point ordinal scale, yielding a total score range of 6 to 18. Content and face validity were established through a modified Delphi process involving 30 expert cleft surgeons, with all 6 domains achieving ≥70% agreement. Inter-rater reliability was assessed using standardized, anonymized clinical case files (n=30) independently scored by 4 senior cleft surgeons. The PPFDI demonstrated strong inter-rater reliability (ICC=0.87, 95% CI: 0.87-0.95), with domain-specific ICCs ranging from 0.78 to 0.92. The mean PPFDI score was 11.1 (SD=2.9), with 43.3% of cases classified as high complexity (score ≥12). Agreement between PPFDI-informed referral tier and clinician-determined referral need was 91.7% (Cohen kappa=0.81), indicating excellent alignment. The PPFDI offers a reliable and clinically meaningful method to stratify palatal fistula complexity and may support more structured decision-making in both low-resource and high-resource settings. Further validation through multicenter studies and correlation with surgical outcomes is warranted to confirm its broader clinical applicability

    Does the volume of Onyx injected influence outcomes after middle meningeal artery embolization for subdural hematoma?

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    BACKGROUND AND OBJECTIVES: Recent literature has highlighted the efficacy of liquid embolic agents like Onyx for middle meningeal artery (MMA) embolization of subdural hematoma (SDH). Our study aims to assess whether the volume of Onyx injected affects outcomes in patients undergoing MMA embolization for SDH. METHODS: This was a retrospective study of patients who underwent MMA embolization using Onyx for SDH at a single institution between March 2019- December 2024. Patients who underwent embolization using particles were excluded. Patients were dichotomized into two groups (≥0.7 ml or \u3c 0.7 ml) based on the 75th percentile of median volume of Onyx injected. The primary outcome of interest was embolization failure, defined as increase in hematoma thickness or need for surgical evacuation. The secondary outcome of interest was extended length of stay (eLOS), defined as LOS above the 75th percentile of the median. RESULTS: A total of 123 MMA embolization procedures were included. The mean age of the cohort was 71.7 ± 13.5 years, and 26 % (n = 32) were female. 70.7 % of patients (n = 87) received a lower volume (\u3c 0.7 ml) of Onyx. Volume of Onyx was not associated with embolization failure or eLOS. Female gender (OR: 0.24, 95 % CI: 0.06-0.89, P = 0.034) was associated with lower odds of eLOS, while baseline functional dependence was associated with higher odds of eLOS (OR: 6.34, 95 % CI: 2.24-17.97, P \u3c 0.001). CONCLUSION: The volume of Onyx injected does not predict embolization failure or eLOS after MMA embolization for SDH. Future research could help validate our preliminary findings through prospective multicenter studies

    Targeting Mitochondrial Reactive Oxygen Species: JP4-039\u27s Potential as a Cardiovascular Therapeutic.

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    JP4-039, a mitochondrial-targeted nitroxide, has emerged as a promising candidate in addressing the intricate interplay of reactive oxygen species (ROS) in cardiovascular disease (CVD). Given the substantial mortality and economic burden associated with CVD globally, novel therapeutic strategies targeting oxidative stress hold significant promise. The pathophysiology of CVD encompasses multifaceted mechanisms, including endothelial dysfunction, inflammation, and oxidative stress, where dysregulated ROS levels play a pivotal role. JP4-039, by selectively targeting mitochondrial ROS, offers a targeted approach to mitigate oxidative stress-induced damage in cardiovascular tissue. Current research elucidates the molecular mechanisms underlying JP4-039\u27s antioxidant properties, including its ability to scavenge superoxide radical anions and mitigate oxidative chain reactions within mitochondria. Moreover, preclinical studies highlight JP4-039\u27s efficacy in ameliorating CVD-related pathologies, including atherosclerosis and cardiac hypertrophy, through its antioxidative and anti-inflammatory effects. Future milestones in JP4-039 research involve optimizing its pharmacokinetic (PK) properties and exploring potential synergistic effects with existing cardiovascular therapies, followed by advancing into clinical trials

    A supervised machine learning approach for predicting the need for postsurgical intervention in acromegaly.

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    OBJECTIVE: Patients with growth hormone (GH)-secreting pituitary adenomas (PAs) experience various symptoms and comorbidities, which can ultimately lead to increased mortality. This study aimed to develop and validate a machine learning (ML) model for predicting long-term outcomes in patients with GH-secreting PAs following endonasal transsphenoidal surgery (ETS). METHODS: The authors conducted a retrospective three-institution cohort study that included patients with GH-secreting PAs treated with ETS between 2013 and 2023. Clinical, radiological, and biochemical data were collected. The main outcome of interest was the intervention-free rate (IFR) after primary ETS. Supervised ML algorithms, including decision trees and random forests, were developed to predict the IFR. Model performance was evaluated using area under the receiver operating characteristic curve (AUROC) and Shapley Additive Explanations (SHAP) values. RESULTS: The median follow-up for 100 patients with GH-secreting PAs (53% female) was 64 months (range 1-130 months). Additional intervention for persistent or recurrent acromegaly was required in 32% of patients. Following primary ETS alone, the 3-year IFR was 70% and the 5-year IFR was 67%. Multiple ML models were developed and evaluated using AUROCs. The decision tree analysis achieved an accuracy of 81% and emphasized the importance of both gross-total resection (GTR) and patient age in determining the long-term IFR. To better understand the factors that contributed to model performance, SHAP analysis was applied to the best-performing model. The SHAP dependence plots showed that key factors associated with a longer IFR included tumor size \u3c 9 mm, GTR, patient age \u3e 65 years, and Knosp grade 0. CONCLUSIONS: This ML model offers a more nuanced and potentially more accurate approach to identify patients more likely to develop recurrent or persistent acromegaly following primary ETS and require additional treatment. Following external validation, this ML model could improve personalized treatment planning and follow-up strategies and enhance patient care and resource allocation in clinical practice

    Young Professionals

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