Innovative Surgical Sciences最新文献

Objectives: Recent studies show that osteoarthritis and metabolic syndrome (MetS) represent significant global health concerns, sharing common pathological processes involving inflammation and oxidative stress. The study aimed to compare the radiological and histological severity of osteoarthritis in patients with and without MetS and further correlates them with oxidative stress and inflammatory markers in serum and synovial fluid (SF). Hypothesis: The study hypothesized that IL-17 and advanced oxidation protein products (AOPPs) are correlated with OA severity and progression in MetS patients.

Methods: This cross-sectional study included 78 patients of advanced knee osteoarthritis, 40 with MetS and 38 without, matched for age. Clinical history and anthropometric measurements were recorded, and presurgical knee X-rays were evaluated using the Kellgren-Lawrence system. Histological grading of hematoxylin & eosin stained infrapatellar fat pad (IFP) and cartilage sections was performed. AOPPs and Interleukin-17 levels were measured in serum and SF, employing sandwich enzyme-linked immunosorbent assay.

Results: In the MetS group, the severity of osteoarthritis was higher compared to non-MetS group, as evidenced by histological evaluation of the articular cartilage and IFP (p<0.05). The histological grading of IFP demonstrated positive correlation (p<0.05) with histological cartilage grade. Additionally, it exhibited a positive correlation with interleukin-17 and AOPPs in both SF and serum (p<0.05). While histological cartilage grade showed a positive correlation with AOPPs concentration in the serum and SF (p<0.05).

Conclusions: MetS accelerates osteoarthritis progression, and positive correlation between molecular markers and histological severity suggests the contribution of inflammation and oxidative stress in the disease's pathogenesis.

Objectives: The integration of advanced technologies is transforming surgical practice, particularly through robotic systems. This study presents the early clinical implementation of the Dexter^® surgical robot for cholecystectomy and evaluates clinical outcomes using the IDEAL framework.

Methods: Twenty patients underwent elective robotic-assisted cholecystectomy using the Dexter^® robot. A thorough implementation process, including rigorous surgeon and nurse training and standardized care protocols, was established. Data on operative metrics, complications, and patient outcomes were analyzed, and patient well-being was assessed via a postoperative phone survey.

Results: Six surgeons and thirty nurses were trained, with surgeons completing a minimum of 20 h of simulation. Preoperative and operative times were significantly reduced through this process. Comparing the first 10 operations to the second, docking time decreased from 11.4 ± 4.1 min to 7.1 ± 2.1 min (p=0.0144) and operative time improved from 130.5 ± 25.7 min to 99.7 ± 21.8 min (p=0.0134). Mean intraoperative blood loss was minimal, averaging 19.5 ± 31.4 mL, and the average length of hospital stay was 3.1 ± 1.4 days. Postoperative pain levels were low, and patient satisfaction was high, as assessed by telephone survey.

Conclusions: Our findings highlight the value of the IDEAL framework in guiding the systematic evaluation and implementation of new surgical technologies such as the Dexter^® robot. A structured approach is essential to improve patient outcomes and safety in the coming digital transformation of surgery.