Objective: The aim of this study is to determine if the cumulative summation test for the learning curve (LC-CUSUM) and the cumulative summation graph (CUSUM) can be used to demonstrate landmark points of competence and maintenance of proficiency in stapes surgery over a continuous time period.
Study Design: Retrospective review from January 1999 until August 2014.
Setting: Tertiary referral hospital.
Patients: All adult patients with confirmed otosclerosis.
Intervention(s): Two-hundred and four primary and revision stapedotomy.
Main Outcome Measure(s): Learning curves were constructed using the CUSUM and LC-CUSUM. Failure was defined as closure of the ABG >10 dB in less than 10% of patients to demonstrate the landmark point of competency and to highlight any fluctuations over a prolonged period.
Results: When the failure rate was defined as closure of the ABG >10 dB, it was not possible to create useful LC-CUSUM and CUSUM graphs, but by redefining the failure rate as > 15 dB, competency was reached at case 43 and maintained with natural fluctuations occurring between cases 137 and 149 and again at case 196.
Conclusions: LC-CUSUM and CUSUM are a more robust analytical method of illustrating the learning curve and suggest that the traditional benchmark of closure of the ABG ≤10 dB in more than 90% of patients may need reconsideration. It can also be used as standardized audit tools when monitoring results and used to plan future training programs as they clearly define a point when novice trainees become competent.
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http://dx.doi.org/10.1097/MAO.0000000000000887 | DOI Listing |
Int J Surg
January 2025
Department of Cardiovascular Surgery, Xijing Hospital, Xi'an, Shaanxi, China.
Background: The impact of aortic arch (AA) morphology on the management of the procedural details and the clinical outcomes of the transfemoral artery (TF)-transcatheter aortic valve replacement (TAVR) has not been evaluated. The goal of this study was to evaluate the AA morphology of patients who had TF-TAVR using an artificial intelligence algorithm and then to evaluate its predictive value for clinical outcomes.
Materials And Methods: A total of 1480 consecutive patients undergoing TF-TAVR using a new-generation transcatheter heart valve at 12 institutes were included in this retrospective study.
JAMA Neurol
January 2025
Department of Neural and Pain Sciences, University of Maryland School of Dentistry, Baltimore.
Importance: Biomarkers would greatly assist decision-making in the diagnosis, prevention, and treatment of chronic pain.
Objective: To undertake analytical validation of a sensorimotor cortical biomarker signature for pain consisting of 2 measures: sensorimotor peak alpha frequency (PAF) and corticomotor excitability (CME).
Design, Setting, And Participants: This cohort study at a single center (Neuroscience Research Australia) recruited participants from November 2020 to October 2022 through notices placed online and at universities across Australia.
Curr Pain Headache Rep
January 2025
Department of Pain Medicine, Division of Anesthesiology, Critical Care & Pain Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
Purpose Of Review: Quickly referenceable, streamlined, algorithmic approaches for advanced pain management are lacking for patients, trainees, non-pain specialists, and interventional specialists. This manuscript aims to address this gap by proposing a comprehensive, evidence-based algorithm for managing neuropathic, nociceptive, and cancer-associated pain. Such an algorithm is crucial for pain medicine education, offering a structured approach for patient care refractory to conservative management.
View Article and Find Full Text PDFHum Genet
January 2025
TCS Research, Tata Consultancy Services, Hyderabad, India.
Variants of uncertain significance (VUS) represent variants that lack sufficient evidence to be confidently associated with a disease, thus posing a challenge in the interpretation of genetic testing results. Here we report an improved method for predicting the VUS of Arylsulfatase A (ARSA) gene as part of the Critical Assessment of Genome Interpretation challenge (CAGI6). Our method uses a transfer learning approach that leverages a pre-trained protein language model to predict the impact of mutations on the activity of the ARSA enzyme, whose deficiency is known to cause a rare genetic disorder, metachromatic leukodystrophy.
View Article and Find Full Text PDFInvest Ophthalmol Vis Sci
January 2025
Institute of Vision Research, Department of Ophthalmology, Yonsei University College of Medicine, Seoul, Korea.
Purpose: Descemet membrane endothelial keratoplasty (DMEK) has emerged as a novel approach in corneal transplantation over the past two decades. This study aims to identify predisposing risk factors for post-DMEK ocular hypertension (OHT) and develop a preoperative predictive model for post-DMEK OHT.
Methods: Patients who underwent DMEK at Gangnam Severance Hospital between 2017 and 2024 were included in the study.
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