1.Construction of a visual model for predicting the risk of recurrence of thyroid cancer after radical surgery via areola endoscopy
Qing-feng SHI ; Bu-yong ZHANG ; Xuan ZHANG ; Yang BAI ; Ling-bo XUE ; Jie LI
Chinese Journal of Current Advances in General Surgery 2025;28(10):769-775
Objective:To explore the risk factors for recurrence of thyroid cancer after radical resection via areola endoscopy,and to construct a visual risk prediction model.Methods:The clinical data of 350 thyroid cancer patients who underwent radical surgery via areola endoscopy in our hospital from January 2016 to October 2018 were retro-spectively analyzed,and they were randomly divided into the modeling group(233 cases)and the internal validation group(117 cases)in a 2:1 ratio.All patients were followed up for 3 years after surgery,and the patients of modeling group were further divided into recurrent group(51)and non recurrent group(182)according to whether they with or not recurrence.Another 163 patients with thyroid cancer who underwent laparoscopic radical mastectomy at our hos-pital from January 2019 to May 2020 were selected as the external validation group.The risk factors for recurrence of thyroid cancer after radical surgery via areola endoscopy was analyzed by using Cox regression method,and a risk prediction nomogram model was established based on this.Internal validation of the nomogram model was conducted by using the Bootstrap method,and the calibration,predictive efficacy and clinical net benefit of the nomogram model were evaluated by the calibration curve,receiver operating characteristic(ROC)curve and decision curve analysis(DCA).The external validation group data was used for external validation.Results:The recurrence rate of thyroid cancer patients after 5 years of radical surgery via areola endoscopy was 21.64%(111/513).The proportions of multiple le-sions,preoperative lymph node metastasis,TNM stages Ⅲ-Ⅳ and maximum tumor diameter,the levels of thyro-globulin(TG),triiodothyronine(T3),thyroxine(T4),free triiodothyronine(FT3),free thyroxine(FT4)and thyroid stimulating hormone(TSH)in the recurrence group were higher than those in the non recurrence group(P<0.05).The Cox regres-sion analysis results showed that the maximum tumor diameter,multiple lesions,preoperative lymph node metasta-sis,TNM stage Ⅲ-Ⅳ and TG,T3,T4,FT3,FT4 and TSH levels were all risk factors for recurrence of thyroid cancer after radical surgery via areola endoscopy(P<0.05).The risk prediction nomogram model of recurrence of thyroid cancer af-ter radical surgery under areola endoscopy was constructed based on the above influencing factors.After internal and external validation,the consistency indices of the modeling group,internal verification group and external verification group were 0.832,0.825 and 0.41 respectively,and the calibration curves of three groups were close to the standard curve.The ROC curve analysis and verification showed that the area under the curve predicted by the nomogram model of the modeling group,internal verification group and external verification group were 0.859,0.847 and 0.853 respectively.The DCA curve showed that the nomogram model had good clinical net benefits when the threshold probability of the modeling group,internal verification group and external verification group were 0.03-0.82,0.02-0.78 and 0.06-0.88 respectively.Conclusion:The maximum tumor diameter,multiple lesions,preoperative lymph node metastasis,TNM staging stage Ⅲ-Ⅳ and levels of TG,T3,T4,FT3,FT4 and TSH are all risk factors for recurrence of thy-roid cancer after radical surgery via areola endoscopy,and the risk prediction visualization nomogram model con-structed based on this is helpful for clinical screening of high-risk patients to guide early intervention and reduce the risk of recurrence.
2.Construction of a visual model for predicting the risk of recurrence of thyroid cancer after radical surgery via areola endoscopy
Qing-feng SHI ; Bu-yong ZHANG ; Xuan ZHANG ; Yang BAI ; Ling-bo XUE ; Jie LI
Chinese Journal of Current Advances in General Surgery 2025;28(10):769-775
Objective:To explore the risk factors for recurrence of thyroid cancer after radical resection via areola endoscopy,and to construct a visual risk prediction model.Methods:The clinical data of 350 thyroid cancer patients who underwent radical surgery via areola endoscopy in our hospital from January 2016 to October 2018 were retro-spectively analyzed,and they were randomly divided into the modeling group(233 cases)and the internal validation group(117 cases)in a 2:1 ratio.All patients were followed up for 3 years after surgery,and the patients of modeling group were further divided into recurrent group(51)and non recurrent group(182)according to whether they with or not recurrence.Another 163 patients with thyroid cancer who underwent laparoscopic radical mastectomy at our hos-pital from January 2019 to May 2020 were selected as the external validation group.The risk factors for recurrence of thyroid cancer after radical surgery via areola endoscopy was analyzed by using Cox regression method,and a risk prediction nomogram model was established based on this.Internal validation of the nomogram model was conducted by using the Bootstrap method,and the calibration,predictive efficacy and clinical net benefit of the nomogram model were evaluated by the calibration curve,receiver operating characteristic(ROC)curve and decision curve analysis(DCA).The external validation group data was used for external validation.Results:The recurrence rate of thyroid cancer patients after 5 years of radical surgery via areola endoscopy was 21.64%(111/513).The proportions of multiple le-sions,preoperative lymph node metastasis,TNM stages Ⅲ-Ⅳ and maximum tumor diameter,the levels of thyro-globulin(TG),triiodothyronine(T3),thyroxine(T4),free triiodothyronine(FT3),free thyroxine(FT4)and thyroid stimulating hormone(TSH)in the recurrence group were higher than those in the non recurrence group(P<0.05).The Cox regres-sion analysis results showed that the maximum tumor diameter,multiple lesions,preoperative lymph node metasta-sis,TNM stage Ⅲ-Ⅳ and TG,T3,T4,FT3,FT4 and TSH levels were all risk factors for recurrence of thyroid cancer after radical surgery via areola endoscopy(P<0.05).The risk prediction nomogram model of recurrence of thyroid cancer af-ter radical surgery under areola endoscopy was constructed based on the above influencing factors.After internal and external validation,the consistency indices of the modeling group,internal verification group and external verification group were 0.832,0.825 and 0.41 respectively,and the calibration curves of three groups were close to the standard curve.The ROC curve analysis and verification showed that the area under the curve predicted by the nomogram model of the modeling group,internal verification group and external verification group were 0.859,0.847 and 0.853 respectively.The DCA curve showed that the nomogram model had good clinical net benefits when the threshold probability of the modeling group,internal verification group and external verification group were 0.03-0.82,0.02-0.78 and 0.06-0.88 respectively.Conclusion:The maximum tumor diameter,multiple lesions,preoperative lymph node metastasis,TNM staging stage Ⅲ-Ⅳ and levels of TG,T3,T4,FT3,FT4 and TSH are all risk factors for recurrence of thy-roid cancer after radical surgery via areola endoscopy,and the risk prediction visualization nomogram model con-structed based on this is helpful for clinical screening of high-risk patients to guide early intervention and reduce the risk of recurrence.
3.Surgical efficacy evaluation of NF1-related dystrophic lumbosacral deformity: comparative analysis between pelvic and non-pelvic fixation
Song LI ; Zezhang ZHU ; Jie ZHOU ; Saihu MAO ; Shuqi SUN ; Zhen LIU ; Benlong SHI ; Xu SUN ; Jun QIAO ; Yong QIU
Chinese Journal of Orthopaedics 2025;45(9):604-612
Objective:To analyze the selection of internal fixation methods, surgical outcomes, and complications in patients with Neurofibromatosis Type 1 (NF1) accompanied by dystrophic lumbosacral deformities, and to evaluate the indications for pelvic fixation.Methods:A retrospective analysis was conducted on 21 patients with NF1 and associated dystrophic lumbosacral malformations (L 4 to sacrum) who underwent spinal deformity correction surgery at Nanjing Drum Tower Hospital from January 2009 to November 2022. The cohort included 11 males and 10 females, with a mean surgical age of 15.4±4.7 years (range, 7-24 years). Patients were divided into two groups based on whether pelvic fixation was performed: 10 patients in the non-pelvic fixation group (NP group) and 11 in the pelvic fixation group (P group), where fixation involved second sacral alar-iliac (S 2AI) screws or iliac screws. Radiographic parameters, including the Cobb angle of the lumbosacral fractional curve, main curve, and focal kyphosis, were compared preoperatively, postoperatively, and at the last follow-up. Results:The NP group had a significantly lower mean age (13.2±4.9 years) compared to the P group (17.5±3.5 years; t=2.287, P=0.034). Spinal instability (rotational subluxation or spondylolisthesis) due to dystrophic changes was observed in 2 patients in the NP group and 8 in the P group, a statistically significant difference (χ 2=5.838, P=0.030). In the P group, five patients underwent unilateral fixation and six underwent bilateral fixation. Implant types included 2 cases with iliac screws, 1 case with iliac screws plus S 2AI, and 8 cases with S 2AI screws alone. The utilization rate of hooks was significantly higher in the NP group (12.6%±11.5%) compared to the P group (3.5%±6.9%; t=2.230, P=0.038). The preoperative Cobb angle of the lumbosacral fractional curve was significantly smaller in the NP group (13.8°±9.0°) than in the P group (25.5°±13.9°; t=2.228, P=0.039). Postoperatively, the angles were corrected to 6.3°±6.1° and 6.4°±5.3°, respectively ( t=0.901, P=0.969), with correction rates of 57.3%±13.6% and 74.1%±17.8% ( t=2.369, P=0.029). At final follow-up, the angles remained stable (6.6°±6.6° vs. 6.3°±4.8°; t=0.116, P=0.909). For the main curve, preoperative Cobb angles were 52.5°±15.1° (NP) and 61.1°±16.9° (P; t=1.200, P=0.246), corrected to 31.3°±13.8° and 28.0°±8.4°, respectively ( t=0.646, P=0.526). Correction rates were 41.3%±13.0% in the NP group and 53.2%±11.6% in the P group ( t=2.206, P=0.037). At the final follow-up, these values were 32.4°±14.2° and 31.7°±10.3° ( t=0.133, P=0.896). Focal kyphosis, seen in 9 patients, was corrected from 19.7°±10.9° preoperatively to -13.6°±9.5° postoperatively, and remained at -14.1°±9.6° at the final follow-up ( F=33.547, P<0.001). Multi-rod systems were used in 6 cases (NP group) and 7 cases (P group), with no significant difference (χ 2=0.153, P=0.926). Two patients in the NP group developed coronal decompensation three years postoperatively, and one required revision surgery. In the P group, rod breakage occurred in 3 patients, two of whom underwent revision. Conclusions:Dystrophic rotational subluxation or spondylolisthesis of the lumbosacral spine is a primary indication for pelvic fixation in patients with NF1-associated deformities. However, complications related to internal fixation remain common. The combined use of a multi-rod screw-hook hybrid system, particularly when extending across the lumbosacral region, may reduce the risk of instrumentation failure.
4.Development of a visualizable machine learning model for mechanical complication risk in adult spinal deformity surgery
Jie LI ; Zhen TIAN ; Zhong HE ; Xiaodong QIN ; Jun QIAO ; Saihu MAO ; Benlong SHI ; Yong QIU ; Zezhang ZHU ; Zhen LIU
Chinese Journal of Orthopaedics 2025;45(17):1137-1146
Objective:To predict mechanical complications (MC) following spinal deformity surgery for adult spine deformity (ASD) using machine learning models, identify key risk factors, and develop a visualizable tool for individualized risk assessment.Methods:Clinical and radiological data from 525 patients with ASD who underwent surgery in our hospital between January 2017 and December 2021 were collected. Patients were randomly assigned to a training set (70%) and a test set (30%) for model development. The cohort included 88 males and 437 females, with a mean age of 42.2±18.1 years. Variables included demographic data, comorbidities, local and systemic radiological parameters, paraspinal muscle fat infiltration (FI), and vertebral bone quality (VBQ) scores. Multiple machine learning algorithms: Random Forest (RF), Gaussian Naive Bayes (GNB), Light GBM, Support Vector Machine (SVM), XGBoost (XGB), and Logistic Regression (LR) were trained and evaluated. Model performance was compared using the receiver operating characteristic curve (ROC) and precision-recall curve (PRC). SHAP (Shapley Additive Explanations) was used to rank risk factors, while LIME (Local Interpretable Model-Agnostic Explanations) was applied to visualize MC risk in individual cases.Results:Of the 525 patients, 135 (25.7%) developed postoperative MC. Among these, 80 (59.3%) experienced proximal junction kyphosis or failure (PJK/PJF), 7 (5.2%) had distal junction kyphosis or failure (DJK/DJF), 28 (20.7%) sustained rod fractures, and 29 (21.5%) showed significant loss of correction. In the validation cohort, the RF model achieved the highest area under the curve (AUC=0.80), followed by GNB (0.77), XGB (0.76), LR (0.74), LightGBM (0.73), and SVM (0.66). The RF model also demonstrated the best PRC value (0.58), highest sensitivity (0.65), and lowest Brier score (0.20). GNB, Light GBM, and LR models achieved the highest accuracy (0.78 each), while LightGBM exhibited the highest specificity (0.93). SHAP analysis identified higher preoperative VBQ scores, larger T 1 pelvic angle (TPA), and higher paraspinal muscle FI as the main risk factors for MC. Based on the RF model, a LIME-based tool was successfully constructed for individualized MC risk estimation. Conclusion:The RF model demonstrated the best overall predictive performance for MC. A machine learning-based prediction model has the potential to provide valuable guidance for surgical decision-making in ASD patients.
5.A new triterpenoid from Elephantopus scaber.
Zu-Xiao DING ; Hong-Xi XIE ; Lin CHEN ; Jun-Jie HAO ; Yan-Qiu LUO ; Zhi-Yong JIANG ; Shi-Kui XU
China Journal of Chinese Materia Medica 2025;50(5):1224-1230
The chemical constituents of the petroleum ether extract derived from the 90% ethanol extract of Elephantopus scaber were investigated. By silica gel column chromatography, C_(18), MCI column chromatography and semi-preparative high performance liquid chromatography, ten compounds were isolated. Their structures were identified as 3β-hydroxy-6β,7β-epoxytaraxeran-14-ene(1), 3β-hydroxyolean-12-en-28-oic acid(2), D-friedoolean-14-ene-3β,7α-diol(3), 3β-hydroxy-11α-methoxyolean-12-ene(4), 3β-hydroxyolean-11,13(18)-diene(5), 11α-hydroxy-β-amyrin(6), betulinic acid(7), 3β-hydroxy-30-norlupan-20-one(8), 6-acetonylchelerythrine(9), and 4',5'-dehydrodiodictyonema A(10) by analysis of the 1D NMR, 2D NMR, MS, and IR spectral data. Among them, compound 1 was a new triterpene and other compounds except compounds 2 and 7 were isolated from this plant for the first time.
Triterpenes/isolation & purification*
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Drugs, Chinese Herbal/isolation & purification*
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Molecular Structure
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Asteraceae/chemistry*
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Chromatography, High Pressure Liquid
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Magnetic Resonance Spectroscopy
7.Efficacy and Safety of Systemic Thrombolysis in the Treatment of Lower Extremity Fracture Complicated With Distal Deep Vein Thrombosis.
Shi-Qiang LIAO ; Shu-Ming SHI ; Qiang ZHANG ; Chuan-Yong LI ; Guang-Feng ZHENG ; Zhi-Chang PAN ; Jian-Jie RONG
Acta Academiae Medicinae Sinicae 2025;47(2):237-243
Objective To evaluate the efficacy and safety of systemic thrombolysis(ST)and standard anticoagulation(SA)in the treatment of lower extremity fracture complicated with distal deep vein thrombosis(DDVT).Methods We retrospectively analyzed the clinical data of 60 patients with lower extremity fracture complicated with DDVT treated from January 2021 to December 2023.When the lower limb venography indicated a calf thrombus burden score ≥3 points,a retrievable inferior vena cava filter(IVCF)was successfully placed in the healthy femoral vein before orthopedic surgery.The patients who received further anticoagulant or thrombolytic therapy after surgery were allocated into a ST group(n=30,urokinase ST and SA)and a SA group(n=30,only SA).The two groups were compared in terms of calf thrombus burden score,thrombus dissolution rate,IVCF placement time,IVCF retrieval rate,intercepted thrombi,hemoglobin level,platelet count,D-dimer level,and complications.Results There was no statistically significant difference in the calf thrombus burden score between the two groups before treatment(P=0.431).However,after treatment,the scores in both groups decreased(both P<0.001),with the ST group showing lower score than the SA group(P=0.002).The thrombus dissolution rate in the ST group was higher than that in the SA group(P<0.001).There was no statistically significant difference in the IVCF placement time between the two groups(P=0.359),and the IVCF retrieval rate was 100% in both groups.The ST group had fewer intercepted thrombi than the SA group(P=0.002).There was no statistically significant difference in hemoglobin level(P=0.238),platelet count(P=0.914),or D-dimer level(P=0.756)between the two groups before treatment.However,after treatment,both groups showed an increase in platelet count(both P<0.001)and a decrease in D-dimer level(both P<0.001).There was no statistically significant difference in the occurrence of complications between the two groups(P=0.704).Conclusions Both SA and ST demonstrate safety and efficacy in the treatment of lower extremity fractures complicated with DDVT,serving as valuable options for clinical application.Compared with SA,ST not only enhances the thrombus dissolution in the calf but also mitigates the risk of thrombosis associated with IVCF.
Humans
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Venous Thrombosis/therapy*
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Retrospective Studies
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Thrombolytic Therapy/methods*
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Male
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Female
;
Middle Aged
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Fractures, Bone/complications*
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Lower Extremity/injuries*
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Anticoagulants/therapeutic use*
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Aged
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Treatment Outcome
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Adult
8.Reassessment of non-acute occlusion in intracranial flow diverter implantation: an animal experimental study based on optical coherence tomography, intravascular ultrasound, and pathological correlation
Zhuangzhuang WEI ; Qi TIAN ; Shuailong SHI ; Jie YANG ; Ji MA ; Zhen LI ; Haiqiang SANG ; Yi TANG ; Yuncai RAN ; Yong ZHANG ; Baohong WEN ; Shanshan XIE ; Jinjuan CHEN ; Enjie LIU ; Xinwei HAN ; Tengfei LI
Chinese Journal of Neurology 2025;58(6):607-614
Objective:To investigate and summarize the imaging and pathological features of non-acute occlusion following flow diverter (FD) implantation in animal models.Methods:Four experimental pigs (experimental group) that experienced non-acute occlusion (occlusion time exceeding 24 hours) within the FD stent implanted in the common carotid artery, and 19 pigs (control group) that did not experience stent occlusion during the same period were involved. Using an interventional approach under digital subtraction angiography (DSA), the 4 occluded FD lumens were mechanically opened. Optical coherence tomography (OCT), intravascular ultrasound (IVUS) and histopathological examinations were performed to evaluate the intraluminal composition and characteristics of the occlusive tissues. These findings were compared with non-occluded FD stents to summarize the imaging and pathological changes within the occluded FD lumen.Results:The occlusion times of the FD stents in the 4 experimental pigs were 16 weeks, 20 weeks, 20 weeks, and 24 weeks postoperatively. All occluded stents were successfully recanalized under DSA, with a technical success rate of 4/4. Among the 19 non-occluded FD stents, OCT and IVUS revealed uniform (16 stents) or non-uniform (3 stents) neointimal coverage of the stent struts, presenting as homogeneous high/slightly high signal intensity or medium echogenicity. Histopathological examination indicated that the neointima was primarily composed of smooth muscle cells and a small amount of fibrous connective tissues. In contrast, the 4 occluded FD stents demonstrated excessive neointimal proliferation and plaque formation, leading to luminal loss, as shown by OCT and IVUS. The occlusion tissues predominantly presented as homogeneous high signal intensity with weak attenuation (fibrous plaques) on OCT, with some regions showing blurred low signal intensity and strong attenuation (lipid plaques). IVUS presented homogeneous echogenicity (fibrous plaques) and hypoechogenic zones (lipid plaques). Histopathological examination showed that the occlusion tissues mainly consisted of smooth muscle cells, fibrous connective tissues, and lipids, accompanied by numerous foam cells and a minor presence of inflammatory cells.Conclusions:Histopathological examinations confirm that non-acute occlusion of FD is mainly caused by excessive hyperplasia of intima along with the formation of fibrous plaques and lipid plaques. OCT and IVUS have typical finding in imaging that can assist in determining the cause of stent occlusion as well as the lesion's nature, thereby providing crucial guidance for subsequent clinical treatment and drug selection.
9.Development and validation of a recognition and classification system for portal hypertensive gastropathy based on deep learning
Haowen GU ; Jie YANG ; Yong XIAO ; Xinyue WAN ; Wei HU ; Xianmu XIE ; Dingpeng HUANG ; Chengming YAO ; Xinliang SHI ; Shiqian LIU ; Li HUANG ; Chi ZHANG ; Biqing ZHENG ; Mingkai CHEN
Chinese Journal of Digestive Endoscopy 2025;42(10):789-795
Objective:To develop a deep learning-based system for real-time recognition and classification of portal hypertensive gastropathy (PHG) and evaluate its ability to assist junior endoscopists.Methods:A total of 2 848 gastroscopy images from 832 patients with liver cirrhosis were selected from Digestive Endoscopy Center databases of Renmin Hospital of Wuhan University, Wuhan Hospital of Traditional Chinese and Western Medicine, and the Second Hospital of Jingzhou from January 2015 to October 2023. This system referred to 3 endoscopic features of Baveno Ⅱ scoring system. Three models were developed respectively for gastric antral vascular ectasia (GAVE), mosaic-like pattern (MLP), and red marks (RM). The specific classification references were as follows: (1) GAVE model: 0 no, 1 yes; (2) MLP model: 0 no, 1 mild, 2 severe; (3) RM model: 0 no, 1 isolated, 2 fused. The classification results for endoscopic characteristics of PHG of 3 endoscopy experts were taken as the gold standard. The yolov8-m model was used for training. The training dataset, validation dataset, and test dataset were allocated at a ratio of 8∶1∶1. The test dataset was used to evaluate the performance of models and their auxiliary effects on endoscopists. The accuracy, recall, precision, specificity and Kappa coefficient were calculated. Results:The accuracy, recall, specificity of GAVE model were 96.0% (48/50), 87.5% (7/8) and 97.6% (41/42). There was no significant difference between its accuracy and the gold standard ( χ2=316.226, P=1.000). The precision of GAVE1 and GAVE0 were 87.5% (7/8) and 97.6% (41/42) respectively. The accuracy of MLP model was 84.1% (132/157), and there was no significant difference compared with the gold standard ( χ2=3.286, P=0.193). The precision and recall of MLP2 were 88.2% (15/17) and 75.0% (15/20). The precision and recall of MLP1 were 77.9% (60/77) and 88.2% (60/68). The precision and recall of MLP0 were 90.5% (57/63) and 82.6% (57/69). The accuracy of RM model was 87.9% (123/140), and there was no significant difference compared with the gold standard ( χ2=2.891, P=0.409). The precision and recall of RM2 were 94.7% (18/19) and 78.3% (18/23). The precision and recall of RM1 were 72.2% (26/36) and 81.3% (26/32). The precision and recall of RM0 were 92.9% (79/85) and 92.9% (79/85). The mean accuracy of the three junior endoscopists, with and without the assistance of the GAVE model, MLP model, and RM model, respectively increased from 95.3% to 99.3%, from 83.9% to 91.9%, and from 81.9% to 83.1%. The overall consistency analysis of the 3 junior endoscopists with the gold standard indicated that the consistency of the GAVE model before and after assistance was extremely strong (both an overall Kappa of 1.000); the consistency before assistance of the MLP model was moderate (with an overall Kappa of 0.601), which increased to extremely strong after assistance (with an overall Kappa of 0.964); and the consistency of the RM model before and after assistance was also relatively strong (with an overall Kappa of 0.792 before and 0.798 after). Conclusion:The deep learning system accurately identifies and classifies PHG features and significantly enhances diagnostic performance of junior endoscopists.
10.Bone loss in patients with spinal cord injury: Incidence and influencing factors.
Min JIANG ; Jun-Wei ZHANG ; He-Hu TANG ; Yu-Fei MENG ; Zhen-Rong ZHANG ; Fang-Yong WANG ; Jin-Zhu BAI ; Shu-Jia LIU ; Zhen LYU ; Shi-Zheng CHEN ; Jie-Sheng LIU ; Jia-Xin FU
Chinese Journal of Traumatology 2025;28(6):477-484
PURPOSE:
To investigate the incidence and influencing factors of bone loss in patients with spinal cord injury (SCI).
METHODS:
A retrospective case-control study was conducted. Patients with SCI in our hospital from January 2019 to March 2023 were collected. According to the correlation between bone mineral density (BMD) at different sites, the patients were divided into the lumbar spine group and the hip joint group. According to the BMD value, the patients were divided into the normal bone mass group (t > -1.0 standard deviation) and the osteopenia group (t ≤ -1.0 standard deviation). The influencing factors accumulated as follows: gender, age, height, weight, cause of injury, injury segment, injury degree, time after injury, start time of rehabilitation, motor score, sensory score, spasticity, serum value of alkaline phosphatase, calcium, and phosphorus. The trend chart was drawn and the influencing factors were analyzed. SPSS 26.0 was used for statistical analysis. Correlation analysis was used to test the correlation between the BMD values of the lumbar spine and bilateral hips. Binary logistic regression analysis was used to explore the influencing factors of osteoporosis after SCI. p < 0.05 was considered statistically significant.
RESULTS:
The incidence of bone loss in patients with SCI was 66.3%. There was a low concordance between bone loss in the lumbar spine and the hip, and the hip was particularly susceptible to bone loss after SCI, with an upward trend in incidence (36% - 82%). In this study, patients with SCI were divided into the lumbar spine group (n = 100) and the hip group (n = 185) according to the BMD values of different sites. Then, the lumbar spine group was divided into the normal bone mass group (n = 53) and the osteopenia group (n = 47); the hip joint group was divided into the normal bone mass group (n = 83) and the osteopenia group (n = 102). Of these, lumbar bone loss after SCI is correlated with gender and weight (p = 0.032 and < 0.001, respectively), and hip bone loss is correlated with gender, height, weight, and time since injury (p < 0.001, p = 0.015, 0.009, and 0.012, respectively).
CONCLUSIONS
The incidence of bone loss after SCI was high, especially in the hip. The incidence and influencing factors of bone loss in the lumbar spine and hip were different. Patients with SCI who are male, low height, lightweight, and long time after injury were more likely to have bone loss.
Humans
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Spinal Cord Injuries/complications*
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Male
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Female
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Retrospective Studies
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Incidence
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Adult
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Bone Density
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Middle Aged
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Case-Control Studies
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Osteoporosis/etiology*
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Lumbar Vertebrae
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Bone Diseases, Metabolic/etiology*
;
Aged
;
Risk Factors

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