Citations

Background: Understanding interactions between multiple risk factors for shoulder and elbow injuries in Major League Baseball (MLB) pitchers is important to identify potential avenues by which risk can be reduced while minimizing impact on player performance. Purpose: To apply a novel game theory–based approach to develop a machine-learning model predictive of next-season shoulder and elbow injuries in MLB pitchers and use this model to understand interdependencies and interaction effects between the most important risk factors. Study Design: Case-control study; Level of evidence, 3. Methods: Pitcher demographics, workload measures, pitch-tracking metrics, and injury data between 2017 and 2022 were used to construct a database of MLB pitcher-years, where each item in the database corresponded to a pitcher's information and metrics for that year. An extreme gradient boosting machine-learning model was trained to predict next-season shoulder and elbow injuries utilizing Shapley additive explanation values to quantify feature importance as well as interdependencies and interaction effects between predictive variables. Results: A total of 3808 pitcher-years were included in this analysis; 606 (15.9%) of these involved a shoulder or elbow injury resulting in placement on the MLB injured list. Of the >65 candidate features (including workload, demographic, and pitch-tracking metrics), the most important contributors to predicting shoulder/elbow injury were increased: pitch velocity (all pitch types), utilization of sliders (SLs), fastball (FB) spin rate, FB horizontal movement, and player age. The strongest game theory interaction effects were that higher FB velocity did not alter a younger pitcher's predicted risk of shoulder/elbow injury versus older pitchers, risk of shoulder/elbow injury increased with the number of high-velocity pitches thrown (regardless of pitch type and in an additive fashion), and FB velocity <95 mph (<152.9 kph) demonstrated strong negative interaction effects with higher SL percentage, suggesting that the overall predicted risk of injury for pitchers throwing a high number of SLs could be attenuated by lower FB velocity. Conclusion: Pitch-tracking metrics were substantially more predictive of future injury than player demographics and workload metrics. There were many significant game theory interdependencies of injury risk. Notably, the increased risk of injury that was conferred by throwing with a high velocity was even further magnified if the pitchers were also older, threw a high percentage of SLs, and/or threw a greater number of pitches.

AbstractBackgroundEvaluations of critical bleeding and massive transfusion have focused on traumatic hemorrhage. However, most critical bleeding in hospitalized patients occurs outside trauma. The purpose of this study was to provide an in‐depth description examining the critical administration threshold (CAT; ≥3 units red blood cells (RBCs) in a 1‐h period) occurrences in nontraumatic hemorrhage. This will assist in establishing the framework for future investigations in nontraumatic hemorrhage.MethodsThis is an observational cohort study of adults experiencing critical bleeding defined as being CAT+ during hospitalization from 2016 to 2021 at a single academic institution. A CAT episode started with administration of the first qualifying RBC unit and ended at the time of completion of the last allogeneic unit prior to a ≥4‐h gap without subsequent transfusion. The primary goal was to describe demographic, clinical and transfusion characteristics of participants with nontraumatic critical bleeding.Results2433 patients suffered critical bleeding, most often occurring in the operating room (71.1%) followed by the intensive care unit (20.8%). 57% occurred on the initial day of hospitalization, with a median duration of 138 (36, 303) minutes. The median number of RBCs transfused during the episode was 5 (4, 8), with median total allogeneic units of 9 (4, 9). Hospital mortality was 19.2%. The most common cause of death was multi‐organ failure (50.3%), however death within 24 h was due to exsanguination (72.7%).DiscussionThe critical administration threshold may be employed to identify critical bleeding in non‐trauma settings of life‐threatening hemorrhage, with a mortality rate of approximately 20%.

Abstract Aims The extravascular implantable cardioverter-defibrillator (EV ICD) has been shown to be safe and effective for patients at risk of sudden cardiac death, but little is known about EV ICD lead removal in humans. This analysis aimed to characterize the EV ICD lead removal experience thus far. Methods and results This was a retrospective analysis of lead removals from the EV ICD Pilot, Pivotal, and Continued Access Studies. Patients with a successful EV ICD implant who underwent lead removal were included. The main objective was lead removal success. Ancillary objectives included characterizing technique used, procedure complications, and reimplantation status. An EV ICD system was successfully implanted in 347 patients across the 3 studies (25.9% female; 53.4 ± 13.3 years; left ventricular ejection fraction: 39.7 ± 15.9). Of these patients, 29 (8.4%) underwent lead removal with a mean lead dwell time of 12.6 ± 14.3 months (0.2–58.4). The main reason for lead removal was lead dislodgement (n = 9, 31.0%). Lead removal was successful in 27/29 (93.1%) cases [100% (19/19) success rate &lt;1 year and 80% (8/10) success rate &gt;1 year post-implant]. Simple traction was used in 22/26 (84.6%) and extraction tools in 4/26 (15.4%) successful cases where technique was known. No complications were reported for any of the removal procedures. All 11 EV ICD reimplant attempts were successful. Conclusion Complete removal of the EV ICD lead was successful in 93.1% of cases, and simple traction was sufficient in most instances. Based on these results, lead removal from the substernal space was safe and achievable up to 3 years post-implant.

Key Clinical MessageStone heart syndrome has a complex interaction with digoxin toxicity, where, theoretically, the administration of intravenous calcium can worsen a patient's condition. Research on this subject is conflicting, so it is imperative to approach it cautiously.

Abstract Objective In acupuncture therapy, the accurate location of acupoints is essential for its effectiveness. The advanced language understanding capabilities of large language models (LLMs) like Generative Pre-trained Transformers (GPTs) and Llama present a significant opportunity for extracting relations related to acupoint locations from textual knowledge sources. This study aims to explore the performance of LLMs in extracting acupoint-related location relations and assess the impact of fine-tuning on GPT’s performance. Materials and Methods We utilized the World Health Organization Standard Acupuncture Point Locations in the Western Pacific Region (WHO Standard) as our corpus, which consists of descriptions of 361 acupoints. Five types of relations (“direction_of”, “distance_of”, “part_of”, “near_acupoint”, and “located_near”) (n = 3174) between acupoints were annotated. Four models were compared: pre-trained GPT-3.5, fine-tuned GPT-3.5, pre-trained GPT-4, as well as pretrained Llama 3. Performance metrics included micro-average exact match precision, recall, and F1 scores. Results Our results demonstrate that fine-tuned GPT-3.5 consistently outperformed other models in F1 scores across all relation types. Overall, it achieved the highest micro-average F1 score of 0.92. Discussion The superior performance of the fine-tuned GPT-3.5 model, as shown by its F1 scores, underscores the importance of domain-specific fine-tuning in enhancing relation extraction capabilities for acupuncture-related tasks. In light of the findings from this study, it offers valuable insights into leveraging LLMs for developing clinical decision support and creating educational modules in acupuncture. Conclusion This study underscores the effectiveness of LLMs like GPT and Llama in extracting relations related to acupoint locations, with implications for accurately modeling acupuncture knowledge and promoting standard implementation in acupuncture training and practice. The findings also contribute to advancing informatics applications in traditional and complementary medicine, showcasing the potential of LLMs in natural language processing.

Melanoma is the deadliest form of skin cancer. The median age at diagnosis is 66. While most patients are treated with immunotherapy, the use of targeted therapy is a valid alternative for patients whose tumors harbor a BRAF or c-KIT driver mutation. These agents, while effective, come with a variety of side effects which limit their use, especially in older patients. We sought to assess the efficacy and toxicity of these agents in older melanoma patients. Melanoma patients over 65 treated with BRAF/MEK or c-KIT inhibitors were retrospectively identified, and their data were analyzed for treatment efficacy and toxicity. All data were compared using the Chi-square test for categorical comparisons and the Kruskal–Wallis method for median comparisons. One hundred and sixteen patients were identified. One hundred and six patients were treated with BRAF/MEK inhibitors. The assessed response rate (RR) was 83% and was comparable across different subgroups, including advanced line patients and those with a more aggressive disease. The median progression free survival (PFS) was 7.9 months, and the median overall survival (OS) was 15.7 months. Twenty-seven percent experienced grade 3–4 toxicity leading to a 24% treatment discontinuation rate. Another 10 patients were treated with the c-KIT inhibitor imatinib, for whom the assessed RR was 55%. The median PFS was 4.3 months, and the median OS was 22.6 months. Forty percent needed dose reductions, yet none had to stop treatment due to adverse effects. The use of targeted therapy in older patients is effective yet challenging due to toxicity. Deploying mitigation strategies can help maximizing their usefulness.

AbstractPurposeA dual‐source CT system can be operated in a high‐pitch helical mode to provide a temporal resolution of 66 ms, which reduces motion artifacts in CT pulmonary angiography (CTPA). It can also be operated in a multi‐energy (ME) mode to provide iodine maps, beneficial in the evaluation of pulmonary embolism (PE). No energy‐integrating detector (EID) CT can perform simultaneous ME and high‐pitch acquisition. This phantom study aimed to evaluate the ability of a photon‐counting‐detector (PCD) CT to perform simultaneous high‐pitch and ME imaging for CTPA.MethodsA motion phantom was used to mimic the respiratory motion. Two tubes filled with iodine with intravascular thrombus mimicked by injecting glue within the tubes were placed along with 5, 10, and 15 mg/mL iodine samples, on a motion phantom at 20 and 30 revolutions per minute. Separate high‐pitch and ME EID‐CT scans and a single high‐pitch ME PCD scan were acquired and virtual monoenergetic images and iodine maps reconstructed. Percent thrombus occlusion was measured and compared between static and moving images.ResultsWhen there was motion, EID‐CT ME suffered from significant motion artifacts. The measured iodine concentrations with PCD‐CT in high‐pitch ME were more stable when there was a motion, with a lower standard deviation than EID‐CT in ME mode. The estimated percent thrombus occlusion dropped significantly with applied motion on EID‐CT, while PCD‐CT high‐pitch ME mode showed good agreement between measurements on static or moving images.ConclusionPCD‐CT with combined ME and high‐pitch mode facilitates simultaneous accurate iodine quantification and assessment of intravascular occlusion.

Abstract Aims The Shock Academic Research Consortium (SHARC) recently proposed pragmatic consensus definitions to standardize classification of cardiogenic shock (CS) in registries and clinical trials. We aimed to describe contemporary CS epidemiology using the SHARC definitions in a cardiac intensive care unit (CICU) population. Methods and results The Critical Care Cardiology Trials Network (CCCTN) is a multinational research network of advanced CICUs coordinated by the TIMI Study Group (Boston, MA). Cardiogenic shock was defined as a cardiac disorder resulting in SBP &lt; 90 mmHg for ≥30 min [or the need for vasopressors, inotropes, or mechanical circulatory support (MCS) to maintain SBP ≥ 90 mmHg] with evidence of hypoperfusion. Primary aetiologic categories included acute myocardial infarction-related CS (AMI-CS), heart failure-related CS (HF-CS), and non-myocardial (secondary) CS. Post-cardiotomy CS was not included. Heart failure-related CS was further subcategorized as de novo vs. acute-on-chronic HF-CS. Patients with both cardiogenic and non-cardiogenic components of shock were classified separately as mixed CS. Of 8974 patients meeting shock criteria (2017–23), 65% had isolated CS and 17% had mixed shock. Among patients with CS (n = 5869), 27% had AMI-CS (65% STEMI), 59% HF-CS (72% acute-on-chronic, 28% de novo), and 14% secondary CS. Patients with AMI-CS and de novo HF-CS were most likely to have had concomitant cardiac arrest (P &lt; 0.001). Patients with AMI-CS and mixed CS were most likely to present in more severe shock stages (SCAI D or E; P &lt; 0.001). Temporary MCS use was highest in AMI-CS (59%). In-hospital mortality was highest in mixed CS (48%), followed by AMI-CS (41%), similar in de novo HF-CS (31%) and secondary CS (31%), and lowest in acute-on-chronic HF-CS (25%; P &lt; 0.001). Conclusion SHARC consensus definitions for CS classification can be pragmatically applied in contemporary registries and reveal discrete subpopulations of CS with distinct phenotypes and outcomes that may be relevant to clinical practice and future research.