Background: The goal of all surgical and orthopaedic training is to ensure necessary education and surgical skills without compromising the quality of operations or patient safety. Anterior cruciate ligament reconstruction (ACLR) is a common multi-staged orthopaedic surgical procedure with a learning curve. Previous studies focus mainly on learning or the learning curve of one surgeon and tunnel placements. The aims of this study were to define the learning curve in arthroscopic ACLRs, define the number of procedures needed before the surgical "knifetime" plateaus, examine the effect of experience on complications, and identify possible individual differences in the surgical learning curve.
Methods: The study included the first 50 consecutive ACLR operations of five orthopaedic surgeons, thus, a total of 250 patients. For comparison and statistical analysis, patients were arranged into five groups, each comprising 50 patients (=order group). Order group 1 comprised the first 10 patients operated on by each of the five surgeons, group 2 patients 11-20, group 3 patients 21-30, group 4 patients 31-40, and group 5 the last 10 patients. The learning curve was defined with a LOESS curve. Surgical time and complications, including graft failure and postoperative knee instability, were analysed between order groups and between surgeons.
Results: Median surgical time was 105 (interquartile range 82-124) min. The learning curve showed the first steep decline in surgical time and started to settle slowly after 20 reconstructions. Surgical time was significantly longer when order group 1 was compared with order group 2 (p = 0.031), and when order group 1 was compared separately with order groups 3, 4, and 5 (p < 0.001). Operation order alone explained only 17.1% of the alteration in surgical time. No significant difference emerged in graft failure rate between the order groups or the surgeons. Objective instability of the knee showed a significant difference when order group 1 was compared separately with order group 3 and with order group 4 (p = 0.004). Surgical time differed between surgeons (p < 0.001), and the shape of the learning curve showed great individual variability.
Conclusion: In the first 10 to 20 ACLR operations, the surgical time was longer and the complication rate higher, but thereafter both started to settle down. We recommend that first 10-20 ACLR operations should be supervised.
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http://dx.doi.org/10.1016/j.knee.2023.06.011 | DOI Listing |
Exp Biol Med (Maywood)
December 2024
Department of Pediatric Surgery, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial lung disease with a poor prognosis. Its non-specific clinical symptoms make accurate prediction of disease progression challenging. This study aimed to develop molecular-level prognostic models to personalize treatment strategies for IPF patients.
View Article and Find Full Text PDFJAMIA Open
February 2025
Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN 55905, United States.
Objectives: In the general hospital wards, machine learning (ML)-based early warning systems (EWSs) can identify patients at risk of deterioration to facilitate rescue interventions. We assess subpopulation performance of a ML-based EWS on medical and surgical adult patients admitted to general hospital wards.
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Front Immunol
December 2024
Department of Respiratory and Critical Care Medicine, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Background: Sepsis is an uncontrolled reaction to infection that causes severe organ dysfunction and is a primary cause of ARDS. Patients suffering both sepsis and ARDS have a poor prognosis and high mortality. However, the mechanisms behind their simultaneous occurrence are unclear.
View Article and Find Full Text PDFFront Oncol
December 2024
NeuroRadiology Unit, Ospedale del Mare, Azienda Sanitaria Locale Napoli 1 Centro (ASL NA1 Centro), Naples, Italy.
Introduction: Precision medicine refers to managing brain tumors according to each patient's unique characteristics when it was realized that patients with the same type of tumor differ greatly in terms of survival, responsiveness to treatment, and toxicity of medication. Precision diagnostics can now be advanced through the establishment of imaging biomarkers, which necessitates quantitative image acquisition and processing. The VASARI (Visually AcceSAble Rembrandt Images) manual annotation methodology is an ideal and suitable way to determine the accurate association between genotype and imaging phenotype.
View Article and Find Full Text PDFBackground: Diagnosis of cardiac amyloidosis (CA) is often missed or delayed due to confusion with other causes of increased left ventricular wall thickness. Conventional transthoracic echocardiographic measurements like global longitudinal strain (GLS) has shown promise in distinguishing CA, but with limited specificity. We conducted a study to investigate the performance of a computer vision detection algorithm in across multiple international sites.
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