Objective To determine the effect of closed tracheal suction system versus open tracheal suction system on the rate of ventilator-associated pneumonia in adults. Methods We searched The Cochrane Library (Issue 1, 2007), PubMed (1966 to 2006) and CBM (1980 to 2007), and also hand searched relevant journals. Randomized controlled trials involving closed tracheal suction system versus open tracheal suction system for ventilator-associated pneumonia in adults were included. Data were extracted and the quality of trials was critical assessed by two reviewers independently. The Cochrane Collaboration’s RevMan 4.2.8 software was used for data analyses. Result Five randomized controlled trials involving 739 patients were included. Results of meta-analyses showed that compared to open tracheal suction system, closed tracheal suction system did not increase the rate of ventilator-associated pneumonia (RR 0.83, 95%CI 0.50 to 1.37) or case fatality (RR 1.05, 95%CI 0.85 to 1.31). No significant differences were observed between open tracheal suction system and closed tracheal suction system in the total number of bacteria (RR 0.83, 95%CI 0.50 to 1.37), the number of SPP colony (RR 2.87, 95%CI 0.94 to 8.74) and the number of PSE colony (RR 1.46, 95%CI 0.76 to 2.77). There was no significant difference between the two groups in the duration of ventilation and length of hospital stay. Conclusion Open or closed tracheal suction systems have similar effects on the rate of ventilator-associated pneumonia, case fatality, the number of SPP and PSE colonies, duration of ventilation and length of hospital stay. However, due to the differences in interventions and statistical power among studies included in this systematic review, further studies are needed to determine the effect of closed or open tracheal suction systems on these outcomes.
Objective To systematically review the research progress of artificial intelligence (AI) combined with multimodal data in the field of malignant risk assessment for thyroid nodules (TN), analyze current technological application bottlenecks and future development directions. MethodsRelevant literatures on the application of AI combined with multimodal data in TN risk assessment in recent years were retrieved and reviewed. ResultsAI, by integrating multimodal data such as ultrasound, cytopathology, and molecular markers, can effectively address the limitations of subjectivity in traditional ultrasound evaluation, uncertainty results of fine needle aspiration biopsy and diagnostic blind spots associated with single molecular markers. However, current research still faces challenges including insufficient generalization ability of small sample, lack of clinical interpretability in black-box algorithms, and insufficient standardization of multimodal data. To tackle these challenges, strategies such as promoting federated learning for multi-center data sharing, establishing interpretable AI integrated with clinical diagnostic pathways, and optimizing deep integration of liquid biopsy with AI provide new directions for overcoming existing obstacles. ConclusionAI combined with multimodal data offers an innovative technical pathway for TN malignancy risk assessment, which is expected to address inherent limitations of traditional diagnostic models and facilitate comprehensive precision management from risk stratification to prognostic monitoring.
Non-invasive biomarkers, due to their non-invasive and safe characteristics, hold significant potential for the diagnosis and prognosis of epilepsy. This review summarizes the research progress and future directions of non-invasive biomarkers for epilepsy, encompassing electrophysiological, imaging, biochemical, and genetic markers, and discusses biomarkers for specific types of epilepsy, such as structural lesion-related epilepsy, infection and inflammation-related epilepsy, autoimmune epilepsy, endocrine hormone-related epilepsy, and metabolic epilepsy, to facilitate their clinical application.