Randomized controlled trials (RCTs) are often limited because of ethical or operational reasons. Quasi-experimental studies could be an alternative to RCTs to make causal inferences without randomization by controlling the confounding effects of the study. This paper introduced the general statistical analysis methods of quasi-experimental design through basic ideas, characteristics, limitations and applications in medicine, including difference-in-difference models, instrumental variables, regression discontinuity design, interrupted time series, and so on, and to provide references for future research.
This study introduced the inverse probability weight and overlap weight by propensity score and how to test the balance and estimate the effect after weighting. Four R packages that can be used for propensity score weight analysis were introduced and compared.
ObjectiveTo investigate the effectiveness of arthroscopic GraftLink technique reconstruction combined with suture anchor fixation in treatment of anterior cruciate ligament (ACL) rupture and medial collateral ligament (MCL) grade Ⅲ injury.MethodsBetween June 2015 and February 2018, 28 patients with ACL rupture and MCL grade Ⅲ injury were treated. Arthroscopic GraftLink technique was used to reconstruct ACL with autologous peroneus longus tendon (PLT), and suture anchor fixation was used to repair MCL. There were 22 males and 6 females, aged 21-47 years, with an average age of 30.4 years. The cause of injury included traffic accident in 18 cases, falling from height in 7 cases, and sports injury in 3 cases. The time from injury to admission was 1-2 weeks, with an average of 1.3 weeks. The preoperative Lysholm score of knee joint was 46.8±3.0 and the International Knee Documentation Commission (IKDC) score was 49.2±2.7. The American Orthopaedic Foot and Ankle Society (AOFAS) score of ankle joint was 98.29±0.72. Both Lachman test and valgus stress test were positive. There were 8 cases of meniscus injury and 2 cases of cartilage injury.ResultsThe operation time ranged from 55 to 90 minutes, with an average of 72.5 minutes. All incisions healed by first intention after operation, and no complications related to operation occurred. All patients were followed up 6-38 months, with an average of 20.7 months. At 3 months after operation, the range of motion of the knee joint was 116- 132°, with an average of 122°. Lachman test showed that the anterior translation more than 5 mm in 2 cases, and the others were negative; while the valgus stress test showed that all patients were positive. At 6 months after operation, the Lysholm score and IKDC score of knee joint were 90.2±1.8 and 93.5±2.3, respectively, which were significantly higher than preoperative scores (t=31.60, P=0.00; t=29.91, P=0.01); AOFAS score of ankle joint was 97.86±0.68, with no significant difference compared with preoperative score (t=2.89, P=0.08). KT-1000 test showed that the difference of anterior relaxation between bilateral knee joints was less than 2 mm in 25 cases and 3 to 5 mm in 3 cases.ConclusionThe method of ACL reconstruction via arthroscopic GraftLink technique with PLT and MCL repair via suture anchor fixation has the advantages of less knee injury and faster recovery, and there is no significant impact on ankle function after tendon removal.
With the continuous improvement of the accuracy of predictive models, the problems of algorithmic bias and the lack of fairness have become increasingly prominent. This not only may lead to significant differences in the accessibility of medical services and the effectiveness of diagnosis and treatment among different groups, but also may trigger medical risks such as misdiagnosis and missed diagnosis, treatment delays, as well as ethical disputes and legal issues under algorithmic discrimination, becoming the key reasons restricting the implementation of technology. At present, research on fairness has shifted from ethical and conceptual discussions to quantitative calculations, exploration of bias layer mechanisms, and exploration of technical mitigation strategies. This article, through a comprehensive analysis and discussion of the fairness issue of clinical prediction models, systematically sorts out the sources of model unfairness, fairness assessment and mitigation methods, as well as commonly used toolkits, and at the same time explores the future development trends. This study aims to sort out the current status of fairness studies on predictive models and promote the responsible application of artificial intelligence in the medical field.
ObjectiveTo introduce and validate the censoring unbiased deep learning (CUDL) algorithm suitable for survival data and to explore its utility in survival analysis. MethodsThe principles of the CUDL algorithm were detailed, followed by an introduction to its software implementation steps and parameter settings. Using the construction of a long-term survival prognosis model for patients with myocardial infarction (MI) as a case study, the algorithms were compared with the conventional Cox proportional hazards model and random survival forest model. ResultsIn the task of predicting the 5-year survival probability of patients, the mean Brier score (BS) of both the Buckley-James censoring unbiased deep learning (BJDL) model and the regularized BJDL were superior to that of the Cox proportional hazards model (mean BS: 0.1722 and 0.1715 vs. 0.1765, P<0.001). The regularized BJDL also outperformed the random survival forest model (RSF500) (mean BS: 0.1715 vs. 0.1750, P<0.001). ConclusionThe BJDL can effectively leverage censored information within survival data to achieve accurate predictions without the need to satisfy the proportional hazards assumption. It provides a novel methodological alternative for the analysis of medical survival data.