Background: Compared to open esophagectomy (OE), minimally invasive esophagectomy (MIE) is associated with lower morbidity and mortality. However, lymph node (LN) dissection around the recurrent laryngeal nerve (RLN) is still an important factor that affects the length of the learning curve of MIE. This study aims to evaluate the surgical outcomes of the first nearly 5-year period and explore the learning curve for LN dissection around the RLN in McKeown MIE by a new single surgical team.
Methods: A total of 285 consecutive patients who underwent McKeown MIE between March 2016 and September 2020 were included at our institution. According to the cumulative sum (CUSUM) analysis of LN dissection around the RLN, the patients were divided into three groups: exploration period, adjustment period, and stable period. We assessed the impact of surgical proficiency on postoperative outcomes and explored the learning curve for LN dissection around the RLN in McKeown MIE.
Results: The CUSUM graph showed that a point of upward inflection for LN dissection around the RLN was observed in 151 cases. After 151 cases, LNs around the right and left RLNs were dissected thoroughly compared to the exploration and adjustment period (P = 0.010 and P = 0.012, respectively), and the postoperative incidence of hoarseness significantly decreased from 11.1 to 1.5% (P<0.001).
Conclusions: Our study results revealed that not only are the LN, around the RLN, sufficiently dissected but also the incidence of hoarseness significantly decreased in the stable phase. Consequently, the learning curve length was approximately 151 cases for LN dissection around the RLN in McKeown MIE.
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http://dx.doi.org/10.3389/fonc.2021.654674 | DOI Listing |
JMIR Form Res
January 2025
Department of Psychology, The University of Texas at San Antonio, San Antonio, TX, United States.
Background: Perception-related errors comprise most diagnostic mistakes in radiology. To mitigate this problem, radiologists use personalized and high-dimensional visual search strategies, otherwise known as search patterns. Qualitative descriptions of these search patterns, which involve the physician verbalizing or annotating the order he or she analyzes the image, can be unreliable due to discrepancies in what is reported versus the actual visual patterns.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Univ Rennes, CHU Rennes, INSERM, LTSI - UMR 1099, F-35000 Rennes, France.
Background: To reduce the mortality related to bladder cancer, efforts need to be concentrated on early detection of the disease for more effective therapeutic intervention. Strong risk factors (eg, smoking status, age, professional exposure) have been identified, and some diagnostic tools (eg, by way of cystoscopy) have been proposed. However, to date, no fully satisfactory (noninvasive, inexpensive, high-performance) solution for widespread deployment has been proposed.
View Article and Find Full Text PDFJ Laparoendosc Adv Surg Tech A
January 2025
Department of Surgical Disciplines, All India Institute of Medical Sciences, New Delhi, India.
Laparo-endoscopic hernia surgery is recommended by various international bodies. However, its uptake by general surgeon is low. We aim to assess the impact of Three Dimensional (3D) endovision system in learning laparoscopic transabdominal preperitoneal (TAPP) repair of groin hernia and transferability of skills acquired from 3D to the Two Dimensional (2D) environment.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Anesthesiology, Daping Hospital, Army Medical University, Chongqing, China.
Background: Recent research has revealed the potential value of machine learning (ML) models in improving prognostic prediction for patients with trauma. ML can enhance predictions and identify which factors contribute the most to posttraumatic mortality. However, no studies have explored the risk factors, complications, and risk prediction of preoperative and postoperative traumatic coagulopathy (PPTIC) in patients with trauma.
View Article and Find Full Text PDFAnn Surg Oncol
January 2025
Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Background: Hematologic changes after splenectomy and hyperthermic intraperitoneal chemotherapy (HIPEC) can complicate postoperative assessment of infection. This study aimed to develop a machine-learning model to predict postoperative infection after cytoreductive surgery (CRS) and HIPEC with splenectomy.
Methods: The study enrolled patients in the national TriNetX database and at the Johns Hopkins Hospital (JHH) who underwent splenectomy during CRS/HIPEC from 2010 to 2024.
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