Methods: From March 2020 to March 2023, 100 inpatients with DS were classified into groups A, B, C, and D based on the CARDS classification system. Preoperative radiological data were analyzed to measure the severity of central canal stenosis, facet joint arthropathy, intervertebral disc herniation, and spinal epidural lipomatosis, osteophyte formation, range of motion (ROM), and computed tomography value of the vertebral bodies. The radiological characteristics and clinical contraindications for OLIF were compared among the groups. Results: Of the 100 patients, 51% had clinical contraindications for OLIF, which included 85%, 25%, 62.5%, and 20% of patients in groups A, B, C, and D, respectively. Compared with group B, group A demonstrated greater severity of central canal stenosis, whereas group C showed a higher degree of facet joint arthropathy. More patients in groups A and C had severe central canal stenosis. Regarding the ROM results, group A had segmental stiffness, whereas group D presented relatively unstable slip segments. Conclusions Patients with different DS subtypes have varied radiological characteristics. Groups B and D are suitable candidates for OLIF. Most patients in group A are unsuitable for OLIF because of bony hyperplasia, severe spinal stenosis, and segmental stiffness.

Methods: From March 2020 to March 2023, 100 inpatients with DS were classified into groups A, B, C, and D based on the CARDS classification system. Preoperative radiological data were analyzed to measure the severity of central canal stenosis, facet joint arthropathy, intervertebral disc herniation, and spinal epidural lipomatosis, osteophyte formation, range of motion (ROM), and computed tomography value of the vertebral bodies. The radiological characteristics and clinical contraindications for OLIF were compared among the groups. Results: Of the 100 patients, 51% had clinical contraindications for OLIF, which included 85%, 25%, 62.5%, and 20% of patients in groups A, B, C, and D, respectively. Compared with group B, group A demonstrated greater severity of central canal stenosis, whereas group C showed a higher degree of facet joint arthropathy. More patients in groups A and C had severe central canal stenosis. Regarding the ROM results, group A had segmental stiffness, whereas group D presented relatively unstable slip segments. Conclusions Patients with different DS subtypes have varied radiological characteristics. Groups B and D are suitable candidates for OLIF. Most patients in group A are unsuitable for OLIF because of bony hyperplasia, severe spinal stenosis, and segmental stiffness.

Methods: From March 2020 to March 2023, 100 inpatients with DS were classified into groups A, B, C, and D based on the CARDS classification system. Preoperative radiological data were analyzed to measure the severity of central canal stenosis, facet joint arthropathy, intervertebral disc herniation, and spinal epidural lipomatosis, osteophyte formation, range of motion (ROM), and computed tomography value of the vertebral bodies. The radiological characteristics and clinical contraindications for OLIF were compared among the groups. Results: Of the 100 patients, 51% had clinical contraindications for OLIF, which included 85%, 25%, 62.5%, and 20% of patients in groups A, B, C, and D, respectively. Compared with group B, group A demonstrated greater severity of central canal stenosis, whereas group C showed a higher degree of facet joint arthropathy. More patients in groups A and C had severe central canal stenosis. Regarding the ROM results, group A had segmental stiffness, whereas group D presented relatively unstable slip segments. Conclusions Patients with different DS subtypes have varied radiological characteristics. Groups B and D are suitable candidates for OLIF. Most patients in group A are unsuitable for OLIF because of bony hyperplasia, severe spinal stenosis, and segmental stiffness.

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve

Post-stroke spasticity, a common sequelae of upper motor neuron lesions, results in motor control deficits and pathological hypertonia that not only reduce patients' activities of daily living but may also cause impairment of adaptive neuroplasticity. Repetitive peripheral magnetic stimulation (rPMS), as a novel non-invasive neuromodulation technique, demonstrates unique clinical potential through targeted modulation of electromagnetic coupling effects in the peripheral neuromuscular system. Although current international studies have validated the therapeutic potential of rPMS for spasticity, significant heterogeneity persists in elucidating its mechanisms of action, optimizing parameter protocols, and standardizing outcome assessment systems. This review innovatively synthesized recent randomized controlled trials (RCTs) and mechanistic evidence, systematically summarizing rPMS-mediated multidimensional intervention paradigms for upper- and lower-limb spasticity. It rigorously examined the correlations between stimulation frequency parameters (low-frequency vs. high-frequency), anatomical targeting (nerve trunk vs. motor point), and clinical outcomes including spasticity severity, motor function, and quality of life. Crucially, the analysis reveals that rPMS may ameliorate spasticity after stroke through dual mechanisms involving local neuroelectrophysiological modulation and central sensorimotor network reorganization, thereby providing a theoretical foundation for developing individualized rPMS clinical protocols and establishing precision treatment strategies.
Humans ; Lower Extremity/physiopathology* ; Upper Extremity/physiopathology* ; Muscle Spasticity/physiopathology* ; Stroke/physiopathology* ; Magnetic Field Therapy/methods* ; Spasm/etiology* ; Stroke Rehabilitation ; Randomized Controlled Trials as Topic

Objective:To summarized the clinical characteristics and surgical management of anterior cervical enterogenic in pediatric patients. Methods:Clinical data were retrospectively analyzed for 9 children with pathologically confirmed anterior cervical enterogenic cysts（including bronchogenic and esophagogenic subtypes） treated at the Children's Hospital of Shandong University（Jinan Children's Hospital） between January 1, 2020, and November 30, 2023. Results:Nine patients（6 males and 3 females） were involved in this study, aged 14 days to 10 years old. There were 4 cases on the left side, 4 on the right side, and 1 in the middle of the neck. All patients presented with neck masses. The patients were followed up from 3 months to 35 months after surgery and recovered well, with no recurrence or complications observed. Conclusion:①Anterior intestinal cysts in children are rare and easy to be misdiagnosed. ②Concurrent branchial cleft fistulas or associated anomalies may coexist, necessitating comprehensive evaluation. ③Preoperative diagnosis is not easy and mainly depends on pathological diagnosis. ④The treatment of anterior cervical enterogenic cysts in children is surgical resection of the lesion.
Humans ; Male ; Female ; Child ; Retrospective Studies ; Child, Preschool ; Infant ; Neck ; Cysts/surgery*

As the brain's resident immune cells, microglia perform crucial functions such as phagocytosis, neuronal network maintenance, and injury restoration by adopting various phenotypes. Dynamic imaging of these phenotypes is essential for accessing brain diseases and therapeutic responses. Although numerous probes are available for imaging pro-inflammatory microglia, no PET tracers have been developed specifically to visualize anti-inflammatory microglia. In this study, we present an ¹⁸F-labeled PET tracer (QTFT) that targets the P2Y₁₂, a receptor highly expressed on anti-inflammatory microglia. [¹⁸F]QTFT exhibited high binding affinity to the P2Y₁₂ (14.43 nmol/L) and superior blood-brain barrier permeability compared to other candidates. Micro-PET imaging in IL-4-induced neuroinflammation models showed higher [¹⁸F]QTFT uptake in lesions compared to the contralateral normal brain tissues. Importantly, this specific uptake could be blocked by QTFT or a P2Y₁₂ antagonist. Furthermore, [¹⁸F]QTFT visualized brain lesions in mouse models of epilepsy, glioma, and aging by targeting the aberrantly expressed P2Y₁₂ in anti-inflammatory microglia. In a pilot clinical study, [¹⁸F]QTFT successfully located epileptic foci, showing enhanced radioactive signals in a patient with epilepsy. Collectively, these studies suggest that [¹⁸F]QTFT could serve as a valuable diagnostic tool for imaging various brain disorders by targeting P2Y₁₂ overexpressed in anti-inflammatory microglia.