Articles: surgery.
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Moderate traumatic brain injury (TBI) is a diagnosis that describes diverse patients with heterogeneity of primary injuries. Defined by a Glasgow Coma Scale between 9 and 12, this category includes patients who may neurologically worsen and require increasing intensive care resources and/or emergency neurosurgery. Despite the unique characteristics of these patients, there have not been specific guidelines published before this effort to support decision-making in these patients. ⋯ Moderate TBI is an entity for which there is little published evidence available supporting definition, diagnosis, and management. Recommendations based on experts' opinion were informed by available evidence and aim to refine the definition and categorization of moderate TBI. Further studies evaluating the impact of these recommendations will be required.
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Anesthesia and analgesia · Sep 2024
Decision Curve Analysis of In-Hospital Mortality Prediction Models: The Relative Value of Pre- and Intraoperative Data For Decision-Making.
Clinical prediction modeling plays a pivotal part in modern clinical care, particularly in predicting the risk of in-hospital mortality. Recent modeling efforts have focused on leveraging intraoperative data sources to improve model performance. However, the individual and collective benefit of pre- and intraoperative data for clinical decision-making remains unknown. We hypothesized that pre- and intraoperative predictors contribute equally to the net benefit in a decision curve analysis (DCA) of in-hospital mortality prediction models that include pre- and intraoperative predictors. ⋯ When it comes to predicting in-hospital mortality and subsequent decision-making, preoperative demographics, comorbidities, and surgery-related data provide the largest benefit for clinicians with risk-averse preferences, whereas preoperative laboratory values provide the largest benefit for decision-makers with more moderate risk preferences. Our decision-analytic investigation of different predictor categories moves beyond the question of whether certain predictors provide a benefit in traditional performance metrics (eg, AUROC). It offers a nuanced perspective on for whom these predictors might be beneficial in clinical decision-making. Follow-up studies requiring larger datasets and dedicated deep-learning models to handle continuous intraoperative data are essential to examine the robustness of our results.
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To examine case logs reported by general surgery residents and identify potential disparities in operative experience. ⋯ Overall, URiM residents submitted fewer cases in the 5-year study period than their non-URiM peers. The gap in submitted cases between male and female residents was more pronounced, with male residents submitting significantly more cases than their female counterparts. This finding was consistent and statistically significant throughout the entire study period, in most case categories, and without narrowing of difference over time. A difference of 30 to 40 cases can amount to 1 to 3 months of surgical training and is a concerning national trend deserving the attention of every training program and our governing institutions.
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Appendicitis poses diagnostic challenges. A correct diagnosis is important during pregnancy to avoid unnecessary surgery on the one hand and delayed surgery on the other hand, as both may negatively affect pregnancy outcomes. Clinical scores for risk-stratified management of suspected appendicitis are well established in adults but have not been validated during pregnancy. This nested case-control study evaluated the diagnostic accuracy of the Appendicitis Inflammatory Response (AIR) score and imaging during pregnancy. ⋯ The results of this study suggest that the AIR score may be a suitable diagnostic tool for risk stratification of pregnant women with abdominal pain and suspected appendicitis but further validation among pregnant women is needed.