International journal of surgery最新文献

Background: The thyroid cartilage plane (TCP) block is a novel approach for superior laryngeal nerve (SLN) block in awake tracheal intubation (ATI). We aimed to evaluate the efficacy and safety of TCP block for ATI.

Materials and methods: Our study included a cadaver dissection and a clinical study. Detailed anatomical dissections were performed on two fresh cadavers after a bilateral TCP block with methylene blue. Sixty patients scheduled for ATI were randomized to receive either bilateral TCP block (TCP group) or fiberoptic bronchoscope-assisted topical anesthesia (FIB group) to anesthetize the vocal cords. A 22-gauge needle was advanced targeting the thyroid cartilage laminae, followed by injection of 2.5 ml lidocaine in the TCP group. Lidocaine spray was applied to anesthetize the remainder of the airway. The primary outcome was quality of airway anesthesia grade during intubation (0, excellent; 1, good; 2, fair; 3, poor; 4, very poor), with secondary outcomes including hemodynamic profile, Ramsay sedation score, and incidence of airway hemorrhage and SLN injury.

Results: The methylene blue stained all the internal branches of SLN, with one external branch not stained. In the clinical study, the quality of airway anesthesia was significantly better in the TCP group than in the FIB group (median [IQR], 0 [0-0] vs 1 [0-2], difference [95% CI]: 1 [0-1], P < 0.001). Mean arterial pressure and HR were better maintained during intubation in the TCP group (P < 0.05). Neither airway hemorrhage nor nerve injury was observed.

Conclusion: Ultrasound-guided TCP block is an effective and safe approach for the SLN blockade, providing an alternative for ATI.

Objective: This study aimed to clarify the molecular mechanisms through which nicotine (Nic) aggravates ischemic stroke (IS), with an emphasis on inflammation and pyroptosis in Microglia.

Methods: An integrative strategy was employed, combining network toxicology for molecular interaction mapping, machine learning for core gene identification, and molecular docking/dynamics for binding validation. These computational predictions were further verified by in vitro and in vivo experiments.

Results: Nic was shown to exacerbate IS injury by promoting pyroptosis through activation of the Toll-like receptor 4(TLR4)-myeloid differentiation primary response gene 88(MyD88) and NOD-like receptor family, pyrin domain containing 3(NLRP3) inflammasome pathways, thereby amplifying inflammatory responses. The convergence of computational analyses and experimental findings confirmed the synergistic effect of Nic on vascular injury and neuroinflammation, leading to worsened IS outcomes.

Conclusion: Nic accelerates IS progression by modulating pyroptosis and chronic inflammatory signaling. This combined computational-experimental approach provides novel mechanistic insights into Nic-induced stroke pathology and highlights potential molecular targets for therapeutic intervention.

Background: The optimal timing and choice of surgery for Ebstein anomaly (EA), a complex congenital heart defect, remain challenging due to the heterogeneity and lack of robust long-term data on EA. In this study, we aimed to evaluate the long-term outcomes of surgical management in patients with EA, identify the prognostic risk factors, and develop a predictive model.

Materials and methods: We conducted a retrospective analysis of data from 332 patients with EA who were treated at a tertiary center between January 2000 and December 2021. Among them, 269 underwent surgery: tricuspid valve repairs, 150; replacements, 77; and isolated bidirectional Glenn procedures, 42. Additionally, 70 patients received a concomitant Glenn shunt during valve surgery, resulting in a total of 112 Glenn procedures. The median follow-up was 10.12 years. The primary outcomes were freedom from reoperation and medical interventions. A predictive nomogram was developed using least absolute shrinkage and selection operator regression and internally validated.

Results: The early surgical mortality rate was 2.60%. Postoperative complications occurred in 15.24% of the patients, with renal failure (4.83%) and arrhythmias (2.23%) being the most common. During a median follow-up of 10.12 years, the freedom from operation rates were 97.95, 92.48, 87.04, and 83.22% at 5, 10, 15, and 20 years, respectively. However, freedom from medical intervention showed a progressive decline (94.34% at 5 years vs. 62.31% at 20). Multivariable Cox regression analysis identified preoperative hepatic congestion [hazard ratio (HR) = 3.042], Wolff-Parkinson-White (WPW) syndrome (HR = 3.463), and elevated alanine aminotransferase (ALT) level (HR = 1.023) as independent risk factors for surgery. The concomitant bidirectional Glenn procedure was associated with a significantly reduced risk of both reoperation (HR = 0.160) and medical intervention (HR = 0.259). Patients requiring interventions showed significantly worse physical and emotional quality-of-life scores than did those who were event-free (P < 0.05).

Conclusion: Timely surgical intervention guided by preoperative risk stratification optimizes the long-term outcomes of EA. The proposed nomogram was a practical tool for individualized risk assessment, supporting clinical decision making in patients with this complex condition.

Background: Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are heterogeneous tumors with rising incidence, necessitating precise preoperative grading for treatment planning. Existing imaging techniques and endoscopic biopsies often fall short due to insufficient markers and tissue samples. Body composition influences tumor biology, yet traditional 2D assessments are time-consuming and lack objectivity. This study aimed to develop a rapid non-invasive predictive model by integrating automatic segmented abdominal volumetric body composition with machine learning to differentiate between low-grade and high-grade GEP-NENs.

Materials and methods: This multicenter retrospective cohort study enrolled 633 patients with GEP-NENs from three institutions. Patients were divided into: Training set (n = 403) and internal validation (n = 174) (7:3 ratio from Hospital 1); test set (n = 56 from 2 other hospitals). An nnUNetv2-based automatic segmentation algorithm for abdominal fat tissue and skeletal muscle on arterial-phase CT was applied. Visceral fat index, subcutaneous fat index, intermuscular fat index and skeletal muscle index were calculated. Features with a P-value < 0.05 were selected using univariate logistic regression and included in the prediction model built using the extreme gradient boosting algorithm. Receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were performed to evaluate the utility of the model. SHapley Additive exPlanations (SHAP) was conducted to enhance model interpretability and visualization.

Results: The automatic segmentation achieved a Dice coefficient of 0.98. For pathological grading, the model built using body composition parameters achieved an AUC of 0.863 in the training set, 0.750 in the validation set, and 0.717 in the test set. SHAP analysis revealed that the relative intermuscular adipose tissue (rIMAT) contributed the most among the body composition parameters to the model decision-making, and rIMAT levels were higher in P53-mutant and CK19-positive cases compared to negative cases.

Conclusions: Auto-segmented abdominal body composition combined with a machine learning-based model could provide an assisted, non-invasive tool for predicting pathological grade in GEP-NENs.

Background: Tris(1,3-dichloro-2-propyl) phosphate (TDCPP) is a widely used organophosphorus flame retardant that has raised growing concern because it is persistent, can bioaccumulate, and is toxic. However, its possible role in chronic kidney disease (CKD) is still not well understood.

Methods: We used network toxicology, molecular docking, transcriptomic validation, and mouse exposure experiments to uncover the mechanisms linking TDCPP exposure to kidney injury.

Results: We found 1270 overlapping targets between predicted TDCPP-binding proteins and CKD-related genes. Enrichment analyses showed strong links to inflammatory and apoptotic processes, as well as key signaling pathways including PI3K-Akt, MAPK, Ras, and cAMP. Machine learning methods (LASSO, SVM-RFE, RF) identified two hub genes, CTRB1 and HSPA1A, which were both significantly downregulated in CKD transcriptomes and showed perfect diagnostic performance (AUC = 1.0). Immune cell analysis showed that CKD tissues had increased regulatory T cells, monocytes, M2 macrophages, and neutrophils, and CTRB1/HSPA1A expression was correlated with specific immune cell subsets. Molecular docking predicted favorable binding of TDCPP to both proteins, with the strongest affinity for CTRB1 (-7.2 kcal/mol). In vivo, TDCPP exposure caused dose-dependent tubular degeneration, inflammation, and increased serum BUN and creatinine, along with marked downregulation of CTRB1 and HSPA1A.

Conclusion: Taken together, these findings suggest that TDCPP may contribute to CKD by disrupting CTRB1/HSPA1A and activating PI3K-Akt/MAPK signaling, which leads to immune dysregulation and progressive kidney injury. We propose a new adverse outcome pathway (AOP) framework linking TDCPP exposure to CKD, and highlight CTRB1 and HSPA1A as potential biomarkers and mechanistic targets for environmental nephrotoxicity.

Laparoscopic surgery offers clear benefits but remains scarce in Sudan and sub-Saharan Africa due to limited infrastructure, training, and policy support. A structured narrative approach (SANRA-guided; SWiM reporting) was used. We pre-specified eligibility criteria, searched seven databases and repositories (PubMed, Scopus, AJOL, African Index Medicus, HINARI, Google Scholar, organizational repositories) for 2018-30 June 2025, dual-screened records, and appraised included sources with JBI/AXIS/CASP/AACODS. Owing to heterogeneity, we used thematic Synthesis Without Meta-Analysis to examine the barriers, innovations, and policy pathways for expanding minimally invasive surgery (MIS) in the region. Key obstacles include equipment shortages, maintenance gaps, financing deficits, and gender inequities in training. While laparoscopy reduces relative surgical site infection (SSI) risk, absolute SSI rates remain driven by system deficits in sterility, antibiotics, and staffing. Emerging solutions - such as gasless laparoscopy, tele-mentoring, and simulation - are feasible but require financial planning and ethical safeguards for diaspora-led initiatives. Integrating MIS within National Surgical, Obstetric, and Anesthesia Plans (NSOAPs), ensuring 2%-5% annual maintenance funding, and expanding simulation-based training can enable equitable, sustainable scale-up. The review emphasizes practical implementation lessons rather than pooled statistical effects to inform regional policy and training reforms.