Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Hand degloving injury represents one of the most severe forms of hand trauma, characterised by challenging treatment and a complex prognostic outcome. It is crucial to effectively utilise the degloved tissues in emergency or primary repair of a hand degloving injury. This consensus provides a comprehensive review of the existing literature on definition, classification, emergency assessment, debridement, judgment of skin viability, in situ repair of the degloved skin, and adjunctive treatment for degloving injury of hand. Based on conclusion of both domestic and international experiences, this expert consensus on the classification of hand degloving injury and the emergency repair with the avulsed skin is established, aiming to provide a guidance to surgeons on standardised treatment strategy and improve the management of hand degloving injury.

Objective:To investigate the risk factors and construct a nomogram prediction model for neonatal bacterial meningitis (BM).Methods:A retrospective cohort study was conducted on 1 228 neonates who underwent lumbar puncture for cerebrospinal fluid examination in the Department of Neonatology at Gansu Provincial Women and Child Healthcare Hospital from December 2019 to February 2024. The subjects were randomly divided into a training cohort and a validation cohort at a ratio of 7∶3 using a computer program. Rank sum test or Chi-square tests were used to compare differences between the two cohorts. The subjects were divided into BM and non-BM groups based on the presence or absence of BM. Multivariate logistic regression analysis (forward stepwise regression method) was used in the training cohort to identify risk factors for BM. The area under the receiver operating characteristic curve (AUC) and the Hosmer-Lemeshow goodness-of-fit test were used to assess the discrimination and calibration of the model, respectively. Calibration curves were used to evaluate the accuracy of the model and to construct the nomogram. Internal validation was performed using the Bootstrap resampling method. Decision curve analysis was used to assess the clinical utility of the model. Results:Among the 1 228 neonates, 151 (12.3%) had BM. The training cohort included 859 neonates, of whom 106 (12.3%) had BM and 753 (87.7%) did not. The validation cohort included 369 neonates, of whom 45 (12.2%) had BM and 324 (87.8%) did not. The results of the multivariate logistic regression analysis in the training cohort showed that sepsis ( OR=4.446, 95% CI:2.583-7.653), convulsions ( OR=3.749, 95% CI:1.930-7.280), high maximum body temperature ( OR=2.027, 95% CI:1.636-2.513), and elevated C-reactive protein ( OR=1.007, 95% CI:1.003-1.012) were independent risk factors for BM, while greater gestational age at birth ( OR=0.946, 95% CI: 0.898-0.995) and higher hemoglobin levels ( OR=0.990, 95% CI:0.981-0.998) were protective factors for BM (all P<0.05). Based on these findings, a nomogram prediction model for neonatal BM was constructed and validated for accuracy. The AUC values of the nomogram model in the training and validation cohorts were 0.796 (95% CI: 0.750-0.843) and 0.781 (95% CI: 0.700-0.862), respectively. The Hosmer-Lemeshow goodness-of-fit test showed P>0.05 in both cohorts. The clinical decision curve analysis demonstrated good net benefit across most threshold ranges. Conclusions:Sepsis, convulsions, high maximum body temperature, and elevated C-reactive protein increase the risk of neonatal BM. The nomogram model constructed based on these factors, combined with gestational age and hemoglobin levels, provides a reference value for predicting the risk of neonatal BM.

Objective:To analyze the accuracy of nine estimation methods for umbilical venous catheterization (UVC) insertion depth in neonates.Methods:This prospective study enrolled neonates who underwent successful UVC placement in the Department of Neonatology at Gansu Provincial Women and Child Healthcare Hospital between September 2023 and October 2024. The standard catheter tip position was defined as the junction of the inferior vena cava and right atrium, with a deviation of ≤0.5 cm considered accurate. Patients were stratified by birth weight (BW) into three groups: <1 500 g, 1 500- 2 499 g, and ≥2 500 g. The actual UVC depth was compared with depths estimated using nine methods: Shukla formula, modified Shukla formula, JSS formula, BW formula, Tambasco formula, modified Tambasco formula, Dunn's nomogram, body surface measurement, and ultrasonographic measurement. Accuracy was evaluated using nonparametric tests and Bland-Altman agreement analysis.Results:The study included 111 neonates: 41 (36.9%) in the <1 500 g group, 55 (49.6%) in the 1 500-2 499 g group, and 15 (13.5%) in the ≥2 500 g group. In the <1 500 g group, accuracy rates ranged from 24% to 56%, with body surface measurement showing the highest accuracy (56%); the mean difference from actual depth was－0.073 cm, with 95% limits of agreement (LOA) of－1.764 to 1.618 cm. In the 1 500-2 499 g group, accuracy rate ranged from 15% to 51%, with the modified Tambasco formula being most accurate (51%); the mean difference was 0.113 cm (95%LOA:－1.558-1.783 cm). In the ≥2 500 g group, accuracy rate ranged from 0/15 to 10/15, with Dunn's nomogram being most accurate (10/15); the mean difference was－0.120 cm (95%LOA:－1.380-1.140 cm).Conclusions:The accuracy of the nine UVC depth estimation methods varied across different BW groups and among methods within the same group. Selection of an estimation method should be tailored to the neonate's birth weight.

Hand degloving injury represents one of the most severe forms of hand trauma, characterised by challenging treatment and a complex prognostic outcome. It is crucial to effectively utilise the degloved tissues in emergency or primary repair of a hand degloving injury. This consensus provides a comprehensive review of the existing literature on definition, classification, emergency assessment, debridement, judgment of skin viability, in situ repair of the degloved skin, and adjunctive treatment for degloving injury of hand. Based on conclusion of both domestic and international experiences, this expert consensus on the classification of hand degloving injury and the emergency repair with the avulsed skin is established, aiming to provide a guidance to surgeons on standardised treatment strategy and improve the management of hand degloving injury.

Objective:To investigate the risk factors and construct a nomogram prediction model for neonatal bacterial meningitis (BM).Methods:A retrospective cohort study was conducted on 1 228 neonates who underwent lumbar puncture for cerebrospinal fluid examination in the Department of Neonatology at Gansu Provincial Women and Child Healthcare Hospital from December 2019 to February 2024. The subjects were randomly divided into a training cohort and a validation cohort at a ratio of 7∶3 using a computer program. Rank sum test or Chi-square tests were used to compare differences between the two cohorts. The subjects were divided into BM and non-BM groups based on the presence or absence of BM. Multivariate logistic regression analysis (forward stepwise regression method) was used in the training cohort to identify risk factors for BM. The area under the receiver operating characteristic curve (AUC) and the Hosmer-Lemeshow goodness-of-fit test were used to assess the discrimination and calibration of the model, respectively. Calibration curves were used to evaluate the accuracy of the model and to construct the nomogram. Internal validation was performed using the Bootstrap resampling method. Decision curve analysis was used to assess the clinical utility of the model. Results:Among the 1 228 neonates, 151 (12.3%) had BM. The training cohort included 859 neonates, of whom 106 (12.3%) had BM and 753 (87.7%) did not. The validation cohort included 369 neonates, of whom 45 (12.2%) had BM and 324 (87.8%) did not. The results of the multivariate logistic regression analysis in the training cohort showed that sepsis ( OR=4.446, 95% CI:2.583-7.653), convulsions ( OR=3.749, 95% CI:1.930-7.280), high maximum body temperature ( OR=2.027, 95% CI:1.636-2.513), and elevated C-reactive protein ( OR=1.007, 95% CI:1.003-1.012) were independent risk factors for BM, while greater gestational age at birth ( OR=0.946, 95% CI: 0.898-0.995) and higher hemoglobin levels ( OR=0.990, 95% CI:0.981-0.998) were protective factors for BM (all P<0.05). Based on these findings, a nomogram prediction model for neonatal BM was constructed and validated for accuracy. The AUC values of the nomogram model in the training and validation cohorts were 0.796 (95% CI: 0.750-0.843) and 0.781 (95% CI: 0.700-0.862), respectively. The Hosmer-Lemeshow goodness-of-fit test showed P>0.05 in both cohorts. The clinical decision curve analysis demonstrated good net benefit across most threshold ranges. Conclusions:Sepsis, convulsions, high maximum body temperature, and elevated C-reactive protein increase the risk of neonatal BM. The nomogram model constructed based on these factors, combined with gestational age and hemoglobin levels, provides a reference value for predicting the risk of neonatal BM.

Objective:To analyze the accuracy of nine estimation methods for umbilical venous catheterization (UVC) insertion depth in neonates.Methods:This prospective study enrolled neonates who underwent successful UVC placement in the Department of Neonatology at Gansu Provincial Women and Child Healthcare Hospital between September 2023 and October 2024. The standard catheter tip position was defined as the junction of the inferior vena cava and right atrium, with a deviation of ≤0.5 cm considered accurate. Patients were stratified by birth weight (BW) into three groups: <1 500 g, 1 500- 2 499 g, and ≥2 500 g. The actual UVC depth was compared with depths estimated using nine methods: Shukla formula, modified Shukla formula, JSS formula, BW formula, Tambasco formula, modified Tambasco formula, Dunn's nomogram, body surface measurement, and ultrasonographic measurement. Accuracy was evaluated using nonparametric tests and Bland-Altman agreement analysis.Results:The study included 111 neonates: 41 (36.9%) in the <1 500 g group, 55 (49.6%) in the 1 500-2 499 g group, and 15 (13.5%) in the ≥2 500 g group. In the <1 500 g group, accuracy rates ranged from 24% to 56%, with body surface measurement showing the highest accuracy (56%); the mean difference from actual depth was－0.073 cm, with 95% limits of agreement (LOA) of－1.764 to 1.618 cm. In the 1 500-2 499 g group, accuracy rate ranged from 15% to 51%, with the modified Tambasco formula being most accurate (51%); the mean difference was 0.113 cm (95%LOA:－1.558-1.783 cm). In the ≥2 500 g group, accuracy rate ranged from 0/15 to 10/15, with Dunn's nomogram being most accurate (10/15); the mean difference was－0.120 cm (95%LOA:－1.380-1.140 cm).Conclusions:The accuracy of the nine UVC depth estimation methods varied across different BW groups and among methods within the same group. Selection of an estimation method should be tailored to the neonate's birth weight.

Objective:To explore the effect of accurately localized mini anterolateral thigh perforator flap in repairing medium-sized skin and soft tissue defects in fingers.Methods:The study was a retrospective observational study. From December 2019 to September 2022, 15 patients with medium-sized skin and soft tissue defects who met the inclusion criteria in fingers were admitted to the Second Affiliated Hospital of Wenzhou Medical University, including 12 males and 3 females, aged 23 to 62 years. After debridement, the wounds were all accompanied by exposed tendons, bones, vessels and nerves, with an area from 4.0 cm×3.0 cm to 8.0 cm×3.5 cm. Computed tomography angiography and color Doppler ultrasonography examinations were performed on both lower limbs of the patient before surgery to accurately locate the anterolateral thigh perforators. When the flap with area from 6.0 cm×3.0 cm to 11.0 cm×4.0 cm was harvested, the flap was thinned. The artery and vein perforators of the flap were anastomosed respectively with the digital artery and dorsal metacarpal vein. If there was avulsion injury, infection, or burn in the recipient area, the main arterial and veinous vessels carried by the skin flap was anastomosed with the radial artery and accompanying vein. The lateral thigh cutaneous nerve carried by the flap was anastomosed with the stump of the digital nerve. The types of perforators of the lateral thigh artery were observed during operation and compared with the location of the vessels before operation. After operation, the survival and adverse complication of the flap were closely observed. During follow-up, the skin flap color, texture, and shape were observed; the wound healing in donor area was observed. At the last follow-up, the two-point discriminative distance of the affected finger pulp was measured, and the function of the affected finger was evaluated using the trial standard for the evaluation of functions of upper limbs of Hand Surgery Society of Chinese Medical Association, and the interphalangeal joint movement of the affected finger was observed; the patients' complaints about the adverse effects of flap resection on lower limbs were recorded.Results:During the operation, it was observed that the perforators of the flaps in 11 patients were the descending branch of the lateral circumflex thigh artery, in two patients, the perforators of skin flaps were the oblique branch of the lateral thigh artery, and the perforators in another two patients were the transverse branch of the lateral circumflex thigh artery, which were consistent with the preoperative vascular localization. After operation, all flaps survived without vascular crisis and infection. The patients were followed up for 6-12 months, the flaps had excellent color, texture, and appearance; only linear scars remained on the donor wound. At the last follow-up, the two-point discrimination distance in the finger pulp was 7-11 mm; the affected finger function was rated as excellent in 6 cases, good in 6 cases, and fair in 3 cases; the flexion and extension function of the finger was not affected; two patients complained of numbness in the lateral thigh after excision of the skin flap, and the other 13 patients had no complain of adverse complaints.Conclusions:The perforating branch in lateral thigh region can be accurately located by computed tomography angiography and color Doppler ultrasonography, accurate positioning of perforators before operation can reduce the damage to the donor area during the incision of the flap, the appearance and function of the affected finger can be restored to the maximum extent by thinning the transplanted flap and rebuilding the finger sensation. Therefore, it is an effective and reliable way to repair the medium-sized skin and soft tissue defects of fingers with the mini thigh anterolateral perforator flap.

Objective:Verstaile free superficial circumflex iliac artery perforator flap(SCIAPF) were adopted for various reconstructive scenarios, and its clinical effect and value was evaluated.Methods:Retrospective analysis was performed on 42 patients with tissue defects admitted in the Department of Orthopeadic of the Second Affiliated Hospital of Wenzhou Medical University from January 2015 to May 2019. Nine patients had injury in the foot, 8 in ankle, 8 in calf, 7 in forearm, 9 in hand, and 1 in the mouth. All of the defects were repaired by SCIAPF, including 28 single soft tissue defect wounds, 8 multiple soft tissue defect, and 6 composite defects. The size of soft tissue defect were 1.2 cm×1.8 cm-14.0 cm×20.8 cm. The size of flaps were 1.5 cm×2.0 cm-15.3 cm×22.3 cm. The patients entered follow up by outpatient clinic visit and telephone reviews to observe the survival of the flaps, functional recovery and complications.Results:In this series, there were 28 flaps, including 18 pedicled with superficia branch of superficial circumflex iliac artery, 2 pedicled with deep branch of superficial circumflex iliac artery, and 8 pedicled with 2 branches. Six were chimeric flaps. Among them, 4 flaps were iliac bone flaps with superficial branch of superficial circumflex iliac artery flaps, and 2 were superficial iliac circumflex artery flap with sartorius muscle flap. Eight cases were resurfaced with lobulated SCIAPF. Arterial anastomoses: end-to-side in 35 arteries and end-to-end in 7 arteries. Venous anastomosis: end-to-end in 27 veins and end-to-side in 15 veins. Venous return through superficial iliac circumflex vein in 25 flaps, through venae comitantes in 12 flaps and through both in 5 flaps. All flap donor sites were sutured directly. All flaps survived uneventfully except for one that compromised with end-to-side anastomotic dehiscence and bleeding, and survived after re-anastomosis. All flaps and donor sites healed primarily. During the follow-up of 6-24(mean, 11.5) months, the pliable flaps were ruddy in colour and soft in texture, without obvious bloatness and pigmentation. The donor site healed well with linear scars in 35 cases and mild scar hyperplasia in 7 cases. The donor hip function were normal. Three patients suffered a numbness of the thigh caused by intraoperative injury lateral femoral cutaneous nerve and it disappeared completely after 3 months.Conclusion:New applications of lobulated or chimeric SCIAPF, based on the SCIA vasculature or its branches, can meet most of the clinical repair requirement.

OBJECTIVE: To investigate the consistency and diagnostic performance of magnetic resonance imaging (MRI) for detecting microvascular invasion (MVI) of hepatocellular carcinoma (HCC) and the validity of deep learning attention mechanisms and clinical features for MVI grade prediction. METHODS: This retrospective study was conducted among 158 patients with HCC treated in Shunde Hospital Affiliated to Southern Medical University between January, 2017 and February, 2020. The imaging data and clinical data of the patients were collected to establish single sequence deep learning models and fusion models based on the EfficientNetB0 and attention modules. The imaging data included conventional MRI sequences (T₁WI, T₂WI, and DWI), enhanced MRI sequences (AP, PP, EP, and HBP) and synthesized MRI sequences (T1mapping-pre and T1mapping-20 min), and the high-risk areas of MVI were visualized using deep learning visualization techniques. RESULTS: The fusion model based on T1mapping-20min sequence and clinical features outperformed other fusion models with an accuracy of 0.8376, a sensitivity of 0.8378, a specificity of 0.8702, and an AUC of 0.8501 for detecting MVI. The deep fusion models were also capable of displaying the high-risk areas of MVI. CONCLUSION The fusion models based on multiple MRI sequences can effectively detect MVI in patients with HCC, demonstrating the validity of deep learning algorithm that combines attention mechanism and clinical features for MVI grade prediction.
Humans ; Carcinoma, Hepatocellular ; Retrospective Studies ; Liver Neoplasms ; Magnetic Resonance Imaging ; Algorithms