Risk factors for deep vein thrombosis after traumatic lower extremity fracture: A systematic review and meta-analysis.

BACKGROUND: The study aimed to predict the risk factors of deep vein thrombosis of lower extremity after traumatic fracture of lower extremity, so as to apply effective strategies to prevent deep vein thrombosis of lower extremity, improve survival rate, and reduce medical cost. METHODS: The English and Chinese literatures published from January 2005 to November 2023 were extracted from PubMed, Embase, Willey Library, Scopus, CNKI, Wanfang, and VIP databases. Statistical analysis was performed using Stata/SE 16.0 software. RESULTS: A total of 13 articles were included in this paper, including 2699 venous thromboembolism (VTE) patients and 130,507 normal controls. According to the meta-results, 5 independent risk factors can be identified: history of VTE was the most significant risk factor for deep vein thrombosis after traumatic lower extremity fracture (risk ratio [RR] = 6.45, 95% confidence interval [CI]: 1.64-11.26); age (≥60) was the risk factor for deep vein thrombosis after traumatic lower extremity fracture (RR = 1.60, 95% CI: 1.02-2.18); long-term braking was a risk factor for deep vein thrombosis after traumatic lower extremity fracture (RR = 1.52, 95% CI: 1.11-1.93); heart failure was a risk factor for deep vein thrombosis after traumatic lower extremity fracture (RR = 1.92, 95% CI: 1.51-2.33); obesity was a risk factor for deep vein thrombosis after traumatic lower extremity fracture (RR = 1.59, 95% CI: 1.35-1.83). CONCLUSION: The study confirmed that the history of deep vein thrombosis, age (60 + years), previous history of VTE, obesity, prolonged bed rest, and heart failure are all associated with an increased risk of VTE. By identifying these significant risk factors, we can more intensively treat patients at relatively high risk of VTE, thereby reducing the incidence of VTE. However, the limitation of the study is that the sample may not be diversified enough, and it fails to cover all potential risk factors, which may affect the universal applicability of the results. Future research should include a wider population and consider more variables in order to obtain a more comprehensive risk assessment.

Prognostic models for immunotherapy in non-small cell lung cancer: A comprehensive review.

The introduction of immune checkpoint inhibitors (ICIs) has revolutionized the treatment of lung cancer. Given the limited clinical benefits of immunotherapy in patients with non-small cell lung cancer (NSCLC), various predictors have been shown to significantly influence prognosis. However, no single predictor is adequate to forecast patients' survival benefit. Therefore, it's imperative to develop a prognostic model that integrates multiple predictors. This model would be instrumental in identifying patients who might benefit from ICIs. Retrospective analysis and small case series have demonstrated the potential role of these models in prognostic prediction, though further prospective investigation is required to evaluate more rigorously their application in these contexts. This article presents and summarizes the latest research advancements on immunotherapy prognostic models for NSCLC from multiple omics perspectives and discuss emerging strategies being developed to enhance the domain.