Background: No clear consensus yet defines the endpoints for operative learning curves in the transition to minimally invasive endoscopic techniques. This retrospective review of our first 202 patients who underwent endoscopic pituitary resection examines the statistical learning curve related to operative times-a measure of our surgical team's efficiency and complication rate, a reflection of surgical skill and maturity.
Methods: Retrospective chart review included patient demographic data, tumor type, operative time, complications, and follow-up. During the 5-year study period, surgeries were performed by an otolaryngology-neurosurgery team. Statistical analysis by Pearson's correlation delineated a learning curve for operative time and complications.
Results: Our learning curve showed comparable plateaus: 120 cases (48% males, 52% females) for operative time (mean, 134 minutes; range, 62-307 minutes) and 100 cases for incidence of cerebrospinal fluid (CSF) leak. The risk of CSF leak declined significantly with the surgeon's increasing experience. Complication rates were as follows: temporary nasal obstruction, 9.9%; CSF leak, 8.4%; postoperative epistaxis, 7%; sinusitis, 4.5%; septal osteomyelitis, 2.4%; postoperative sellar hematoma, 1.5%; anosmia, 0.5%; and septal perforation, 0.5%. The overall CSF leak rate included 5.5% intraoperative and 2.9% postoperative; most cases resolved with a lumbar drain. Four patients (2%) underwent postoperative surgical repair and lumbar drainage.
Conclusion: Our learning curve-defined endpoints for 2 measures, operative time and complication rates, support improved outcomes for reduced CSF leaks, the most common complication, with increasing operative experience. We will continue to examine the implications related to safety, efficacy, and the need for subspecialization in this minimally invasive surgery.
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http://dx.doi.org/10.1016/j.wneu.2017.03.008 | DOI Listing |
Anesth Analg
February 2025
From the Department of Surgical Specialties and Anesthesiology of São Paulo State University (UNESP), Medical School, Botucatu, Brazil.
Background: Proficiency in endotracheal intubation (ETI) is essential for medical professionals and its training should start at medical schools; however, large caseload may be required before achieving an acceptable success rate with direct laryngoscopy. Video laryngoscopy has proven to be an easier alternative for intubation with a faster learning curve, but its availability in medical training may be an issue due to its high market prices. We devised a low-cost 3-dimensionally printed video laryngoscope (3DVL) and performed a randomized trial to evaluate if the intubation success rate on the first attempt with this device is noninferior to a standard commercially available video laryngoscope (STVL).
View Article and Find Full Text PDFSleep Breath
January 2025
Department of Respiratory and Critical Care Medicine, Medical School of Nantong University, Nantong Key Laboratory of Respiratory Medicine, Affiliated Hospital of Nantong University, Nantong, 226001, China.
Background: The pathophysiology of obstructive sleep apnea (OSA) and diabetes mellitus (DM) is still unknown, despite clinical reports linking the two conditions. After investigating potential roles for DM-related genes in the pathophysiology of OSA, our goal is to investigate the molecular significance of the condition. Machine learning is a useful approach to understanding complex gene expression data to find biomarkers for the diagnosis of OSA.
View Article and Find Full Text PDFUltrasound J
January 2025
Department of Radiology, Hospital Universitari Vall d'Hebron, Passeig de la Vall d'Hebron, 119-129, 08035, Barcelona, Spain.
Background: Tele-robotic ultrasound (US) is a novel technique that might help overcome the current shortage of radiologists and poor access to radiologists and/or sonographers in remote or rural areas. Despite the promising results of this technology in the past two decades, there is still insufficient data about its advantages and limits, as well as the implementation in routine clinical practice and the learning curve for the user. The purpose of this prospective cohort-based study is to evaluate the performance of a 5G-based tele-robotic US system for abdominal and thyroid gland assessment in a cohort of healthy volunteers and outpatients, as well as assessing the learning curve and patient satisfaction.
View Article and Find Full Text PDFInt J Cardiovasc Imaging
January 2025
Artificial Intelligence Center, China Medical University Hospital, China Medical University, Taichung, Taiwan.
Coronary artery calcification (CAC) is a key marker of coronary artery disease (CAD) but is often underreported in cancer patients undergoing non-gated CT or PET/CT scans. Traditional CAC assessment requires gated CT scans, leading to increased radiation exposure and the need for specialized personnel. This study aims to develop an artificial intelligence (AI) method to automatically detect CAC from non-gated, freely-breathing, low-dose CT images obtained from positron emission tomography/computed tomography scans.
View Article and Find Full Text PDFDiscov Oncol
January 2025
Department of Medical Imaging, Shenzhen Longhua District Key Laboratory of Neuroimaging, Shenzhen Longhua District Central Hospital, Shenzhen, 518110, China.
Background: Glioblastoma multiforme (GBM) is a highly aggressive brain cancer with poor prognosis and limited treatment options. Despite advances in understanding its molecular mechanisms, effective therapeutic strategies remain elusive due to the tumor's genetic complexity and heterogeneity.
Methods: This study employed a comprehensive analysis approach integrating 113 machine learning algorithms with Mendelian Randomization (MR) analysis to investigate the molecular underpinnings of GBM.
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