Journal of Clinical Medicine, Journal Year: 2024, Volume and Issue: 13(17), P. 5028 - 5028
Published: Aug. 25, 2024
: Spinal tuberculosis (STB) is frequently misdiagnosed due to the multitude of symptoms it presents with. This review aimed investigate biomarkers that have potential accurately diagnose spinal TB in its early stages.
Language: Английский
Infection and Drug Resistance, Journal Year: 2025, Volume and Issue: Volume 18, P. 31 - 42
Published: Jan. 1, 2025
Background: Early differentiation between spinal tuberculosis (STB) and acute osteoporotic vertebral compression fracture (OVCF) is crucial for determining the appropriate clinical management treatment pathway, thereby significantly impacting patient outcomes. Objective: To evaluate efficacy of deep learning (DL) models using reconstructed sagittal CT images in early STB from OVCF, with aim enhancing diagnostic precision, reducing reliance on MRI biopsies, minimizing risks misdiagnosis. Methods: Data were collected 373 patients, 302 patients recruited a university-affiliated hospital serving as training internal validation sets, an additional 71 another external set. MVITV2, Efficient-Net-B5, ResNet101, ResNet50 used backbone networks DL model development, training, validation. Model evaluation was based accuracy, sensitivity, F1 score, area under curve (AUC). The performance compared accuracy two spine surgeons who performed blinded review. Results: MVITV2 outperformed other architectures set, achieving 98.98%, precision 100%, sensitivity 97.97%, score AUC 0.997. notably exceeded that surgeons, achieved rates 77.38% 93.56%. confirmed models' robustness generalizability. Conclusion: improved surpassing experienced accuracy. These offer promising alternative to traditional imaging invasive procedures, potentially promoting accurate diagnosis, healthcare costs, improving findings underscore potential artificial intelligence revolutionizing disease diagnostics, have substantial implications. Keywords: learning, tuberculosis, fractures, imaging,
Language: Английский
Citations
0
Journal of Critical Care, Journal Year: 2025, Volume and Issue: 87, P. 155027 - 155027
Published: Jan. 22, 2025
Radiomics involves the integration of computer technology, big data analysis, and clinical medicine. Currently, there have been initial advancements in fields acute cerebrovascular disease cardiovascular disease. The objective radiomics is to extract quantitative features from medical images for analysis predict risk or treatment outcome, help differential diagnosis, guide decisions management. applied research has reached a more advanced stage yet encounters several obstacles, including need standardization alignment with requirements severe illnesses. Future should aim seamlessly incorporate various disciplines, leverage artificial intelligence advancements, cater critical medicine, enhance effectiveness technological innovation application diagnosing treating
Language: Английский
Citations
0
Surgical Infections, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 20, 2025
Background: The risk of poor surgical site healing in patients with spinal tuberculosis due to M. infection is known be higher than other patients. Early identification and diagnosis are critical if we reduce the disability mortality associated tuberculosis. We aimed develop validate a novel predictive score for predicting following procedure Patients Methods: retrospectively analyzed clinical data who were hospitalized orthopedic ward four regional medical centers Guizhou Province between January 2015 October 2022. Univariate LASSO analysis was used identify factors, construct evaluate models procedure. Subsequently, 110 patients, admitted 2023 February 2024, as an external prospective validation cohort test efficacy prediction model. Results: Seven predictors identified factors undergoing areas under receiver operating characteristic curve model constructed based on significant 0.753 (95% CI: 0.693-0.813) 0.779 0.696-0.863) training sets, respectively. Decision demonstrated that yielded good benefit. Finally, applied newly developed assessment set; area 0.846 0.769-0.923) better effectiveness. Conclusion: exhibits discriminatory power represents beneficial tool facilitating suitable postoperative management.
Language: Английский
Citations
0
European Spine Journal, Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 7, 2025
Language: Английский
Citations
0
Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 109 - 121
Published: Jan. 1, 2025
Language: Английский
Citations
0
BMC Infectious Diseases, Journal Year: 2024, Volume and Issue: 24(1)
Published: June 22, 2024
Abstract Background Spinal tuberculosis (STB) is a local manifestation of systemic infection caused by Mycobacterium tuberculosis, accounting for significant proportion joint cases. This study aimed to explore the diagnostic value MRI combined with mannose-binding lectin (MBL) STB. Methods 124 patients suspected having STB were collected and divided into non-STB groups according their pathological diagnosis. Serum MBL levels measured using ELISA Pearson analysis was constructed determine correlation between ROC plotted analyze All subjects included in underwent an MRI. Results The sensitivity diagnosis 84.38% specificity 86.67%. serum group significantly lower than group. results indicated that MBL’s area under curve (AUC) 0.836, 82.3% 77.4%. 96.61%, 92.31%, indicating combining two methods more effective either one alone. Conclusions Both had certain values STB, but use resulted accuracy
Language: Английский
Citations
1
Journal of Clinical Medicine, Journal Year: 2024, Volume and Issue: 13(17), P. 5028 - 5028
Published: Aug. 25, 2024
: Spinal tuberculosis (STB) is frequently misdiagnosed due to the multitude of symptoms it presents with. This review aimed investigate biomarkers that have potential accurately diagnose spinal TB in its early stages.
Language: Английский
Citations
0