Aim: This study aimed to compare the efficacy and safety of ultrasound-guided percutaneous balloon dilatational tracheotomy (US-PDT) versus surgical tracheotomy (ST) in patients with acute respiratory failure (ARF).
Methods: In this retrospective cohort study, 278 patients with ARF were enrolled from January 2022 to January 2025. These patients were divided into the US-PDT group (n = 135) and the ST group (n = 143) based on the surgical method used. Perioperative indicators, procedural success rates, inflammatory markers, hospitalization outcomes, and complications were systematically compared between the two groups.
Results: The US-PDT group demonstrated superior outcomes across all measures. It was associated with a significantly shorter procedure time, smaller incision length, reduced intraoperative blood loss, and shorter duration of mechanical ventilation (all p < 0.001). The US-PDT group also showed a higher single-attempt procedural success rate, alongside a lower accidental extubation rate (all p < 0.001). Postoperative inflammatory markers (erythrocyte sedimentation rate [ESR], C-reactive protein [CRP], and procalcitonin [PCT]) were significantly lower in the US-PDT group (p < 0.001). Furthermore, the US-PDT group experienced reduced ventilator-associated pneumonia (VAP) incidence, higher weaning success, shorter intensive care unit (ICU) and hospital stays, and lower ICU and overall mortality (all p < 0.05). Complication rates were also significantly lower in the US-PDT group (p < 0.05).
Conclusions: US-PDT is a more efficient, safer, and less invasive alternative to ST for ARF patients, resulting in better clinical outcomes, reduced inflammation, fewer complications, and improved survival rates.
Aim: Fingertip defects are common injuries in hand surgery, and their functional reconstruction remains a clinical challenge. This study aims to compare the clinical efficacy of the modified antegrade digital artery-nerve V-Y island flap with that of the bilateral neurovascular bundle-bearing V-Y island flap in repairing distal fingertip defects.
Methods: This single-center retrospective study included 120 patients with distal fingertip defects treated between October 2021 and October 2024. Among them, 50 underwent repair using the modified antegrade digital artery-nerve V-Y island flap (group A), while 70 received the bilateral neurovascular bundle-bearing V-Y island flap (group B). Perioperative metrics (operative time, intraoperative blood loss, hospital stay duration), sensory function (static two-point discrimination [s2-PD], excellent/good rate based on S3+ grading), joint mobility (metacarpophalangeal, proximal interphalangeal, and distal interphalangeal joints), Michigan Hand Outcomes Questionnaire (MHQ) scores, peripheral circulation parameters (transcutaneous partial pressure of oxygen [TcPO2], blood perfusion units [BPU]), and complication rates at 6 months postoperatively were compared between the two groups.
Results: Baseline characteristics showed no statistically significant differences between the two groups (p > 0.05). Group A had longer operative times than group B but demonstrated significantly lower intraoperative blood loss and shorter hospital stay (p < 0.05). At 6 months postoperatively, group A demonstrated superior s2-PD and a higher excellent/good rate based on S3+ grading (p < 0.05); however, there was no significant difference in joint mobility between groups (p > 0.05). Compared to group B, group A achieved significantly higher total MHQ scores and subscale scores for hand function, daily activities, work performance, aesthetic appearance, and patient satisfaction, as well as lower pain scores, at 6 months postoperatively (p < 0.001). Additionally, TcPO2 and BPU values were higher in group A (p < 0.001). No significant between-group difference in overall complication rates was observed (p > 0.05).
Conclusions: Compared to the bilateral neurovascular bundle-bearing V-Y island flap repair surgery, the modified antegrade digital artery-nerve V-Y island flap repair surgery reduces intraoperative blood loss and shortens hospitalization time. This technique offers advantages in sensory recovery, overall hand function, patient satisfaction, and restoration of peripheral circulation without increasing the risk of complications. These results suggest its potential as a more effective reconstructive option for fingertip defects.
Aim: This study aimed to identify key ultrasound (US) characteristics that differentiate complicated acute appendicitis (CAA) from non-complicated acute appendicitis (NCAA) and to develop and validate a US-based predictive model for preoperative diagnosis.
Methods: A retrospective analysis was conducted on 178 patients with surgically confirmed acute appendicitis between June 2022 and May 2025. All patients underwent a standardized preoperative US examination. Clinical and sonographic variables were compared between the CAA (n = 63) and NCAA (n = 115) groups. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for variable selection, followed by multivariable logistic regression to construct a predictive model. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA).
Results: Compared to the NCAA group, the CAA group had significantly older age, longer symptom duration, higher white blood cell (WBC), and higher neutrophil percentage (NE%) (p < 0.05). Significant US-based predictors included greater appendiceal outer diameter (AOD), increased periappendiceal inflammatory fat thickness (PIFT), and higher incidences of periappendiceal fluid collection (PAFC), marginal indistinctness (MI), and altered bowel peristalsis (ABP). The final model identified eight independent predictors: age, symptom duration, WBC, NE%, PIFT, PAFC, MI, and ABP. The nomogram showed excellent discrimination (AUC = 0.890), good calibration (Hosmer-Lemeshow test, p = 0.108), and sustained performance during internal validation (AUC = 0.902). DCA confirmed high clinical utility.
Conclusions: The proposed US-based nomogram provides an accurate, non-invasive tool for preoperative differentiation of CAA from NCAA, potentially aiding in risk stratification and treatment decision-making.
Aim: This study aimed to construct a risk stratification model for prostate cancer (PCa) ultrasound imaging data and machine learning algorithms, with the goal of providing an effective tool for early diagnosis, personalized treatment, and clinical decision-making.
Methods: A total of 211 histopathologically confirmed PCa patients were retrospectively enrolled and categorized into low-risk (n = 65), intermediate-risk (n = 55), and high-risk (n = 91) groups based on prostate-specific antigen levels, Gleason scores, and clinical T stage. From ultrasound images, 135 quantitative radiomic features-including morphological, texture, and edge descriptors-were extracted using the PyRadiomics toolkit. Feature dimensionality was reduced using the Pearson correlation coefficient (PCC), followed by recursive feature elimination (RFE) with 10-fold nested cross-validation to select the most informative features. Three machine learning algorithms-support vector machine (SVM), random forest (RF), and logistic regression (LR)-were trained and evaluated. Model performance was assessed using accuracy, sensitivity, specificity, and area under the curve (AUC).
Results: The RF model achieved the best performance in both training and test cohorts, with AUCs of 0.87 and 0.86, and accuracies of 90% and 88%, respectively. DeLong's test confirmed that RF significantly outperformed SVM (p = 0.016) and LR (p = 0.004) in AUC comparison. The RF model also demonstrated robust predictive ability across risk subgroups: in the high-risk group, it achieved an AUC of 0.89, accuracy of 89%, sensitivity of 88%, and specificity of 90%; in the intermediate- and low-risk groups, AUCs were 0.86 and 0.81, respectively. Feature importance analysis revealed that wavelet-transformed Gray Level Dependence Matrix (GLDM) texture features, particularly DependenceEntropy and DependenceVariance, were the most predictive, highlighting the value of intratumoral textural heterogeneity in risk classification.
Conclusions: The RF-based ultrasound radiomics model enables accurate stratification of PCa risk, with remarkable performance in identifying high-risk patients.
Aim: This study aims to construct an intensive care unit (ICU) pre-experience pattern for patients undergoing lung cancer surgery and their family members, to provide a novel mechanism of communication between healthcare professionals and patients that may improve treatment adherence and satisfaction with hospitalisation.
Methods: Initially, an item pool was created for pre-experienced ICUs through a comprehensive literature review, prior qualitative research, and expert panel discussions, resulting in 146 items. Inputs from experts were sought through Delphi surveys to construct an ICU pre-experience pattern for patients undergoing lung cancer surgery and their family members. The Delphi study included 22 multidisciplinary experts from intensive care, nursing management, clinical medicine, and social psychology. Subsequent rounds of consultation were guided by consistency in the findings of the consultation. Two rounds of consultations were performed using 5-point Likert scales to assess importance and feasibility. Consensus criteria included a mean score of ≥3.5 and a coefficient of variation (CV) of ≤0.25.
Results: A total of 146 items, including 5 primary, 29 secondary, and 112 tertiary items, were incorporated in the final pattern. These included items structured around 5 critical time phases: '24 hours preceding ICU admission', 'Postoperative ICU admission before anaesthesia emergence', 'Postoperative ICU admission after anaesthesia emergence', 'First postoperative day/transfer day', and 'Following ICU discharge'. Key dimensions include the objectives of ICU admission, description of ICU personnel and environment, psychological preparation, clinical procedures, and post-ICU care. Two rounds of expert consultations yielded a 100% recovery rate (RR). An acceptable level of consensus was achieved, with mean importance and feasibility scores ranging from 4.41 to 5.00 in Round 2, and a CV below 0.25 for all items. The high authority coefficients (Cr) (0.84 and 0.83) confirm a trend toward higher expert consensus on the clinical relevance and practical applicability of the developed pattern.
Conclusions: This study developed an ICU pre-experience pattern for patients undergoing lung cancer surgery and their family members. This pattern provides a theoretical framework and a potential approach that may help alleviate anxiety and enhance treatment adherence.
Aim: This study aims to evaluate the predictive performance of preoperative blood lipid profiles combined with thyroid ultrasound features for postoperative nausea and vomiting (PONV) after thyroid lobectomy, and to develop a nomogram for individualized risk assessment.
Methods: This retrospective study included 269 patients who underwent thyroid lobectomy for nodular thyroid disease at the People's Hospital of Pingyang between January 2022 and December 2024. Study participants were divided into non-PONV (n = 102) and PONV (n = 167) groups. Preoperative clinical details, thyroid ultrasound parameters, and lipid profiles were compared between the two groups. Statistically significant variables (p < 0.05) from the univariate analysis were included in the multivariate logistic regression to identify independent risk predictors. A nomogram was constructed and internally validated using bootstrap resamples (1000 iterations).
Results: Multivariate analysis identified Apfel score, thyroid volume, maximum nodule diameter, presence of diffuse changes, total cholesterol (TC), high-density lipoprotein cholesterol (HDL), and low-density lipoprotein cholesterol (LDL) as independent risk predictors of PONV. The nomogram showed favorable discriminative performance with an area under the receiver operating characteristic curve of 0.804 (95% CI: 0.749-0.859) and a bias-corrected area under the curve (AUC) of 0.794 (95% CI: 0.737-0.850) after bootstrap validation. Additionally, the model demonstrated favorable calibration and superior clinical utility, as assessed using the decision curve analysis.
Conclusions: Multivariate analysis identified that preoperative blood lipid profiles and thyroid ultrasound features are independently associated with PONV. Incorporating these indicators along with established clinical risk factors into a nomogram enables accurate individualized prediction and may support targeted prophylactic interventions.
Aim: Surgical smoke generated during electrosurgery contains various toxic substances, including carbon monoxide (CO), hydrogen sulfide (H2S), formaldehyde (HCHO), total volatile organic compounds (TVOC), and particulate matter 2.5 (PM2.5), which pose a significant health threat to both surgical staff and patients. This study investigates the effectiveness of a novel gas-liquid drainage tube in removing surgical smoke and improving the safety of the surgical environment.
Methods: A gas detector and an air quality monitor were used to measure the concentrations of CO, carbon dioxide (CO2), PM2.5, HCHO, TVOC, and H2S in the rat model during electrosurgery. Animals were divided into two groups (n = 3 each): an experimental group employing a novel gas-liquid drainage tube and a control group using a traditional drainage tube. Measurements were taken at various time points (1, 5, 10, 15, 30, 60, and 120 min) and fixed distances from the surgical site (0, 10, 30, 50, 100, and 150 cm). Additionally, the effectiveness of the drainage tube in maintaining surgical field clarity during the procedure was evaluated using an image subtraction algorithm.
Results: Compared to the control group, the novel gas-liquid drainage tube significantly reduced the concentrations of CO, CO2, PM2.5, HCHO, TVOC, and H2S in the experimental group (p < 0.05). Furthermore, the drainage tube effectively reduced hazards and cleared smoke, thus improving the clarity of the surgical field.
Conclusions: This device effectively reduces the concentration of harmful gases and particulate matter generated during electrosurgical procedures. These findings suggest that it may contribute to creating a cleaner, safer surgical environment.
Colorectal cancer, currently the third most common malignancy worldwide, can be significantly reduced through early detection and endoscopic resection of polyps. This review discusses the main classifications of colonic lesions and the most effective evidence-based technologies for their detection, characterization, and management. A practical roadmap for risk stratification and a management algorithm are proposed, based on the latest recommendations from the European and American Societies of Gastrointestinal Endoscopy. By combining clinical experience with a critical analysis of key studies from the past decade, this article provides practical tools to enhance optical diagnosis and guide therapeutic decisions, minimizing the need for surgical interventions. This review serves as an essential resource for clinicians, offering practical guidance for effective and individualized management of colorectal lesions, thereby enhancing cancer prevention and optimizing healthcare resource utilization.
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