Surgical Innovation最新文献

BackgroundLaparoscopic cholecystectomy (LC) is the gold standard for gallbladder disease, yet conversion to open cholecystectomy (OC) remains necessary in 2-15% of cases. Although often life-saving, conversion increases operative time, morbidity, and hospital stay. Identifying reliable predictors is therefore crucial for surgical planning and patient counseling.MethodsA retrospective cohort study was conducted on 4535 patients who underwent LC at a tertiary center between January 2018 and May 2024. Demographic, clinical, laboratory, radiological, intraoperative, and histopathological data were extracted from medical records. Univariate and multivariate logistic regression analyses were used to identify independent predictors of conversion. A nomogram was developed to estimate individualized conversion risk.ResultsConversion to OC occurred in 304 patients (6.7%). Independent predictors included male sex (OR 1.65, 95% CI 1.09-2.50), ASA IV classification (OR 4.84, 95% CI 2.51-9.33), elevated CRP (OR 1.007 per mg/L, 95% CI 1.004-1.010), reduced lymphocyte count (OR 0.42, 95% CI 0.21-0.84), gastric or intestinal complications (OR 3.38, 95% CI 1.01-11.38), gangrenous gallbladder (OR 2.39, 95% CI 1.45-3.93), and xanthogranulomatous cholecystitis (OR 5.42, 95% CI 1.61-18.25). Gallbladder wall thickness was the strongest preoperative predictor (OR 1.20 per mm, 95% CI 1.13-1.27, P < 0.001), and existence of dense adhesions were the strongest intraoperative predictor (OR 26.77, 95% CI 16.64-43.07).ConclusionConversion to OC reflects anatomical complexity and advanced disease rather than surgical failure. Gallbladder wall thickness, inflammatory markers, adhesions, gangrene, and xanthogranulomatous cholecystitis are consistent predictors. The proposed nomogram provides individualized risk estimation to improve preoperative planning and patient counseling. Prospective multicenter validation is warranted.

PurposeThis study aimed to assess the feasibility of artificial intelligence (AI)-based models for predicting recurrence risk and supporting individualized treatment strategies in pediatric pilonidal sinus disease (PSD).MethodsClinical data from 242 pediatric PSD patients were retrospectively analyzed. Two machine learning (ML) models were developed: (1) a binary classifier for recurrence prediction and (2) a multiclass classifier for treatment modality selection. Model performance was evaluated using 5-fold cross-validation based on accuracy, area under the receiver operating characteristic curve (ROC-AUC), F1 score, and confusion matrix. Model interpretability was assessed using SHapley Additive exPlanations (SHAP) analysis to identify the most influential predictive features.ResultsAmong 242 patients, 59.1% underwent surgical excision (unroofing with secondary healing), 33.1% received crystallized phenol, and 7.8% were treated with silver nitrate. The overall recurrence rate was 5.7%, with no significant differences among treatment modalities. Longer healing duration, larger lesion size, higher body mass index (BMI), and an increased number of sinus tracts were associated with higher recurrence risk. SHAP analysis revealed that healing time, BMI, age, and the number of sinus tracts were the most influential predictors in both recurrence and treatment selection models.ConclusionAI-based predictive models can effectively estimate recurrence risk and assist in tailoring individualized management strategies for pediatric PSD. Further multicenter, prospective studies are warranted to validate these findings and support clinical integration of AI-assisted decision systems.

This was biphasic use of ICG to delineate biliary as well as vascular systems simultaneously. This is safe as well as useful for enhancing the dissection and improves patient safety.

BackgroundOur study aimed to compare the effects of repair using polypropylene suture material vs polyglycolic acid-coated (PGA) tube on the development of biliary strictures in rat common bile duct incisions.MethodsThirty female rats were randomly divided into three groups. A controlled defect was created in the common bile duct. In Group 1, the defect was repaired with 8/0 polyglycolic acid; in Group 2, with 8/0 polypropylene; and in Group 3, with 8/0 polyglycolide-co-lactide followed by wrapping with an absorbable polyglycolic acid mesh tube. In the second surgical step, at 3 months postoperatively, blood samples were again taken from all subjects, liver biopsies were obtained, and the repaired bile duct area was resected for histopathological evaluation. Liver biopsies obtained before bile duct repair and at 3 months after repair were compared among the groups. Anastomotic sites and proximal bile duct diameters were compared between groups at 3 months post-repair.ResultsPostoperative ALT and GGT levels were significantly higher in Group 1 rats, while ALP levels were statistically significantly lower in Group 2 rats. Epithelial hyperplasia was detected in 20% of rats in Group 3, with fewer proliferative fibroblasts and less collagen scar tissue compared with those in other groups. The Portal edema rate was significantly lower in Group 3 than in Groups 1 and 2.ConclusionsThe use of PGA -coated tubes after PGLA suturing suggests that these tubes may reduce strictures in biliary repair in rats by maintaining a wider anastomotic diameter.

Study ObjectiveThe Artisential instruments are multi-degree-of-freedom laparoscopic instruments compatible with traditional ports. Their articulation may offer advantages over conventional instruments, particularly in suturing. This study aimed to compare suturing times between conventional laparoscopic instruments and the Artisential device.DesignInternally controlled prospective cohort/case series.InterventionsA power analysis determined that 16 knots per group were needed to detect a 20s difference with 80% power and 5% alpha. Two patients undergoing laparoscopic sacrocolpopexy were enrolled. During anterior and posterior mesh fixation, half the knots were tied using two conventional laparoscopic needle drivers; the other half used an Artisential needle driver in one hand and a conventional driver in the other. All knots were tied by the same surgeon, positioned adjacently to minimize bias from laterality or pelvic depth. Each knot consisted of a surgeon's knot followed by two square knots. All cases were recorded and evaluated by 2 reviewers, using time stamps to determine knot tying duration. T-tests compared times between the groups.Measurements and Main ResultsThirty-two knots were analyzed. Mean knot time was 119 s (SD 43) with conventional instruments vs 66 s (SD 14) using the Artisential device (P < .01). All individual components-needling, surgeon's knot, and both square knots-were significantly faster with the Artisential driver (all P < .05).ConclusionThe Artisential articulating laparoscopic instrument nearly halved knot-tying time during laparoscopic sacrocolpopexy. This novel instrument may improve surgical efficiency in minimally invasive gynecologic procedures.

BackgroundRobotic surgery for rectal cancer offers enhanced visualization, instrument articulation, and ergonomic benefits in confined pelvic spaces. However, the effectiveness of robotic procedures depends heavily on trocar positioning and instrument layout. Conventional configurations often require intraoperative instrument swapping or camera repositioning, potentially disrupting workflow and increasing cognitive strain. To address these limitations, we implemented a standardized "full right" instrument configuration using the Da Vinci Xi system to improve ergonomic control and procedural stability.MethodsWe conducted a prospective analysis of 22 consecutive patients undergoing robotic rectal resection at a high-volume tertiary center using the full right configuration. All robotic arms and the assistant port were positioned along the patient's right side, with the camera fixed on Arm 2 throughout the procedure. Operative, perioperative, and pathological outcomes were evaluated.ResultsThe mean console time was 170 min, and the mean operative time was 192 min. No conversions or intraoperative complications occurred. No instrument collisions were observed. Estimated blood loss was minimal in all cases. The mean hospital stay was 5.2 days. All patients achieved complete (grade 3) mesorectal excision, with a mean lymph node yield of 16.4 and negative margins in every case. No major postoperative complications were reported.ConclusionsThe full right configuration for robotic rectal resection is associated with favorable short-term outcomes, improved ergonomic conditions, and stable instrument positioning. This layout supports consistent workflow across all operative phases and may reduce intraoperative cognitive load. Further validation through larger comparative studies is warranted.

BackgroundFlap surgery necessitates accurate identification of perforator locations for optimal outcomes. Color Doppler Sonography (CDS) has been a routine examination in preoperative planning, but its limitations in providing a comprehensive map of perforators relationships prompts exploration of alternative imaging modalities. This study introduces the application of a novel technique, three-dimensional computed tomography angiography fusion imaging (3D-CTA-FI), for precise interosseous artery perforator locating in forearm flap surgery.MethodA retrospective investigation including 23 patients receiving forearm flap surgery of posterior interosseous artery perforator was conducted, and two-phase computed tomography angiography (CTA) protocol was adopted in this study. Utilizing Mimics software, 3D models of vascular structures were meticulously reconstructed. Surgical procedures were guided by the 3D-CTA-FI, and accuracy of CDS and 3D-CTA-FI was evaluated by comparing visual and actual perforator positions.ResultsAll flaps were viable, and patients were discharged uneventfully. In our study, 3D-CTA-FI portrayed accurate depictions of vascular pedicles and perforators. The mean discrepancy between indicated and actual perforator positions was 2.9 ± 1.7 mm (Group 1) and 2.4 ± 1.7 mm (Group 2), accompanied by excellent consistency rates of 47.8% and 60.9%, respectively.ConclusionsThree-dimensional computed tomography angiography fusion imaging (3D-CTA-FI) provides detailed information of perforators in posterior interosseous artery perforator flap surgery, and its application in clinical practice is feasible and beneficial.

BackgroundThe rapid advancement of artificial intelligence (AI) has led to its increasing application in the medical field, particularly in providing accurate and reliable information for complex medical queries. PurposeThis study evaluates the performance of four AI engines-Perplexity, Chat GPT, DeepSeek, and Gemini in answering 100 multiple-choice questions derived from the American Board of Surgery In-Training Examination (ABSITE). A set of questions focused on five surgical subspecialties including colorectal surgery, acute care and trauma surgery (ACS), upper GI Surgery, breast and endocrine surgery, and hepatopancreatobiliary surgery (HPB).Data collectionWe evaluated these AI engines' ability to provide accurate and focused medical knowledge as the main objective. The research study consisting of a two-month duration was conducted from January 1, 2025, to March 28, 2025. All AI engines received identical questions through then a comparison between correct and wrong responses was performed relative to the ABSITE key answers. Each question was entered manually into the chatbots, ensuring no memory retention bias.Statistical analysisThe researchers conducted their statistical analysis with JASP software for performance evaluation between different subspecialties and AI engines through univariate and multivariate investigations.ResultsAmong the available AI tools, DeepSeek produced the most accurate responses at 74% while Chat GPT delivered 70% accuracy Gemini achieved 69% and Perplexity attained 65%. Results showed that Chat GPT achieved 83.3% accuracy in colorectal surgery yet DeepSeek scored the best at 84.6% and 67.6% for HPB Surgery and ACS respectively. Perplexity achieved a 100% accuracy rate in breast and endocrine surgery which proved to be the highest score recorded throughout the study. The analysis showed that Chat GPT exhibited performance variability between different Surgical subspecialties since it registered significant variations (P < .05), especially in acute care and trauma Surgery. The results of logistic regression indicated that Gemini along with Perplexity scored the most consistent answers among AI systems with a significant odds ratio of 2.5 (P < .01). AI engines show different combinations of precision and reliability when solving medical questions about surgery yet DeepSeek stands out by remaining the most reliable overall.ConclusionsMedical application AI models need additional development because performance results show major differences between medical specialties.

AimThis study aims to systematically analyze the global research landscape of polymeric materials in surgical applications, identifying core themes, technological trends, and clinical translation potential over the past decade.MethodsA bibliometric analysis was conducted using the Web of Science Core Collection (2016-2025). A targeted search strategy combining polymer-related, surgery-related, and functional biomedical keywords was applied. Data were analyzed using the Bibliometrix R package and VOSviewer to explore publication trends, international collaborations, keyword co-occurrence, and citation networks. Key studies were manually reviewed to interpret their technological contributions.ResultsA total of 4668 original articles were retrieved, showing a 15.8% annual growth. China led global output (49.9%), followed by the USA. Keyword clustering revealed four major themes: nanoparticle-based drug delivery, biological responses and angiogenesis, clinical surgical applications (eg, hemostasis, adhesion), and multifunctional hydrogels. Research hotspots included antibacterial, adhesive, and hemostatic materials. Highly cited studies focused on injectable, self-healing, and bioactive hydrogels for complex wound repair and organ-specific applications.ConclusionThe field of surgical polymeric materials is rapidly advancing toward multifunctional, minimally invasive, and responsive systems. This bibliometric study provides a data-driven knowledge map to guide future research and promote clinical translation, helping bridge the gap between material innovation and surgical application. Future research should also focus on optimizing the scalability and cost-effectiveness of these technologies while addressing regulatory and safety challenges. Large-scale clinical trials and interdisciplinary education help bridge the gap between materials science and clinical implementation.