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Background: Since the release of ChatGPT, numerous positive applications for this artificial intelligence (AI) tool in higher education have emerged. Faculty can reduce workload by implementing the use of AI. While course evaluations are a common tool used across higher education, the process of identifying useful information from multiple open-ended comments is often time consuming. The purpose of this study was to explore the use of ChatGPT in analyzing course evaluation comments, including the time required to generate themes and the level of agreement between instructor-identified and AI-identified themes., Methods: Course instructors independently analyzed open-ended student course evaluation comments. Five prompts were provided to guide the coding process. Instructors were asked to note the time required to complete the analysis, the general process they used, and how they felt during their analysis. Student comments were also analyzed through two independent Open-AI ChatGPT user accounts. Thematic analysis was used to analyze the themes generated by instructors and ChatGPT. Percent agreement between the instructor and ChatGPT themes were calculated for each prompt, along with an overall agreement statistic between the instructor and two ChatGPT themes., Results: There was high agreement between the instructor and ChatGPT results. The highest agreement was for course-related topics (range 0.71-0.82) and lowest agreement was for weaknesses of the course (range 0.53-0.81). For all prompts except themes related to student experience, the two ChatGPT accounts demonstrated higher agreement with one another than with the instructors. On average, instructors took 27.50 ± 15.00 min to analyze their data (range 20-50). The ChatGPT users took 10.50 ± 1.00 min (range 10-12) and 12.50 ± 2.89 min (range 10-15) to analyze the data. In relation to reviewing and analyzing their own open-ended course evaluations, instructors reported feeling anxiety prior to the process, satisfaction during the process, and frustration related to findings., Conclusions: This study offers valuable insights into the potential of ChatGPT as a tool for analyzing open-ended student course evaluation comments in health professions education. However, it is crucial to ensure ChatGPT is used as a tool to assist with the analysis and to avoid relying solely on its outputs for conclusions., (© 2024. The Author(s).)

Background: The purpose of this study was to examine the impact of ARC on levetiracetam concentrations during the first week following acute TBI. The hypothesis was levetiracetam concentrations are significantly lower in TBI patients with augmented renal clearance (ARC) compared to those with normal renal clearance., Methods: This is a prospective cohort pharmacokinetic study of adults with moderate to severe TBI treated with levetiracetam during the first week after injury. Serial blood collections were performed daily for analysis of levetiracetam, cystatin C, and 12-hr creatinine clearance (CrCl) determinations. Patients were divided into two cohorts: with (CrCl ≥130 ml/min/1.73 m 2 ) and without ARC., Results: Twenty-two patients with moderate to severe TBI were included. The population consisted primarily of young male patients with severe TBI (mean age 40 years old, 68% male, median admission GCS 4). Each received levetiracetam 1000 mg IV every 12 h for the study period. ARC was present in 77.3% of patients, with significantly lower levetiracetam concentrations in ARC patients and below the conservative therapeutic range (< 6mcg/mL) for all study days. In patients without ARC, the serum concentrations were also below the expected range on all but two study days (Days 4 and 5). Four of the 22 (18.2%) patients exhibited seizure activity during the study period (two of these patients exhibited ARC). Cystatin C concentrations were significantly lower in patients with ARC, though the mean for all patients was within the typical normal range., Conclusions: ARC has a high prevalence in patients with moderate to severe TBI. Levetiracetam concentrations after standard dosing were low in all TBI patients, but significantly lower in patients with ARC. This study highlights the need to consider personalized drug dosing in TBI patients irrespective of the presence of ARC., Clinical Trial Registration: This study was registered at cliicaltrials.gov (NCT02437838) Registered on 08/05/2015, https://clinicaltrials.gov/ct2/show/NCT02437838 ., (© 2023. The Author(s).)

Background: A growing body of literature describes teaching practices that are positively associated with student achievement. Observing, characterizing, and providing feedback on these teaching practices is a necessary, yet significant challenge to improving teaching quality. This study describes the design, implementation, and evaluation of an instructional coaching program created to provide formative feedback to instructors based on their use of evidence-based teaching practices., Methods: The program was designed for formative purposes utilizing an instrument adapted from the Teaching Practices Inventory. All faculty were invited to participate in the program on a voluntary basis when the program launched in Fall 2019. Program coaches included any School personnel who completed required training. Two rounds of instrument development were conducted with multiple observers and assessed using Krippendorff's Alpha. The program was evaluated using an anonymous post-session survey., Results: Interrater reliability of the form improved over two rounds of piloting and no differences were found in scoring between trainees and education professionals. Seventeen observations were completed by nine coaches. Instructors indicated that feedback was practical, timely, specific, and collegial, suggesting that including student perspectives (e.g., focus groups, student course evaluations) in the coaching program might be helpful., Conclusions: Creating programs that emphasize and foster the use of evidence-based teaching are critical for health professions education. Additional research is needed to further develop coaching programs that ensure teaching practices in the health professions are optimizing student learning., (© 2022. The Author(s).)

Background: The majority of patients with hemorrhagic stroke experience enhanced renal clearance or augmented renal clearance (ARC). The purpose of this study was to determine the impact of enhanced renal clearance or ARC on vancomycin pharmacokinetic (PK) parameters., Methods: This was a post hoc analysis of a prospective study of adult patients with aneurysmal subarachnoid hemorrhage (aSAH) or intracerebral hemorrhage (ICH) admitted to the neurosciences intensive care unit who received vancomycin. Creatinine clearance (CrCl) was measured and also estimated using the Cockcroft-Gault equation. Predicted PK parameters were compared with calculated PK parameters using serum peak and trough concentrations., Results: Seventeen hemorrhagic stroke patients met inclusion criteria. All patients experienced enhanced renal clearance on the day that the vancomycin concentrations were obtained, and 12 patients (71%) experienced ARC. The mean calculated elimination rate constant was significantly higher than the predicted value (0.141 ± 0.02 vs. 0.087 ± 0.01 h -1 ; p = 0.004) and the mean calculated half-life was significantly lower than the predicted half-life (6.5 ± 0.9 vs. 8.7 ± 0.6 h; p = 0.03)., Conclusions: Patients with hemorrhagic stroke and enhanced renal clearance displayed PK alterations favoring an increased elimination of vancomycin than expected. This may result in underexposure to vancomycin, leading to treatment failure., Competing Interests: Competing interestsThe authors declare that they have no competing interests., (© The Author(s). 2019.)