ABSTRACT
BACKGROUND: To compare the efficacy of the direct anterior approach (DAA) versus the posterolateral approach (PLA) in total hip arthroplasty (THA) in terms of operation time, incision length, intraoperative blood loss, postoperative pain, and incision infection rate. METHODS: We systematically searched databases including China National Knowledge Infrastructure (CNKI), Wanfang Data, VIP Chinese sci-tech journals, Chinese Biomedical Literature Database (CBM), PubMed, and Cochrane Library up to December 2023. We included randomized controlled trials (RCTs) that compared DAA with PLA in THA, with a minimum sample size of 80 and a follow-up of at least 6 months. Studies were screened by two independent researchers, following PRISMA guidelines. Data were extracted using a pre-established feature table, capturing study design, sample size, patient demographics, and outcomes of interest. Meta-analysis was performed using RevMan 5.4.1 software. Heterogeneity was assessed using the Q-value statistical test and I² test. The fixed-effects model was used when heterogeneity was low; otherwise, the random-effects model was applied. RESULTS: A total of 19 RCTs met the inclusion criteria. The Meta-analysis revealed that DAA was associated with a longer operation time [MD = 5.89, 95%CI(2.26 to 9.51), P = 0.001] but resulted in a smaller incision length [MD = -2.99, 95%CI(-3.76 to -2.22), P < 0.00001], less intraoperative blood loss [MD=-108.36, 95%CI(-131.10 to -85.62), P < 0.00001], lower incidence of postoperative incision infection [OR = 0.39, 95%CI(0.19 to 0.83), P = 0.01], and reduced hip Visual Analog Scale (VAS) scores on the 1st and 3rd days postoperatively [MD=-0.85, 95%CI(-0.96 to -0.74), P < 0.00001; MD=-0.60, 95%CI(-1.13 to -0.07), P = 0.03]. No significant difference was observed in VAS scores on the 7th postoperative day. CONCLUSION: The DAA for THA offers advantages over PLA, including reduced incision size, blood loss, and postoperative pain, albeit with a longer operation time. These findings should guide clinical decision-making, considering the benefits and potential increased complexity of the DAA.
ABSTRACT
The emergence of face forgery has raised global concerns on social security, thereby facilitating the research on automatic forgery detection. Although current forgery detectors have demonstrated promising performance in determining authenticity, their susceptibility to adversarial perturbations remains insufficiently addressed. Given the nuanced discrepancies between real and fake instances are essential in forgery detection, previous defensive paradigms based on input processing and adversarial training tend to disrupt these discrepancies. For the detectors, the learning difficulty is thus increased, and the natural accuracy is dramatically decreased. To achieve adversarial defense without changing the instances as well as the detectors, a novel defensive paradigm called Inspector is designed specifically for face forgery detectors. Specifically, Inspector defends against adversarial attacks in a coarse-to-fine manner. In the coarse defense stage, adversarial instances with evident perturbations are directly identified and filtered out. Subsequently, in the fine defense stage, the threats from adversarial instances with imperceptible perturbations are further detected and eliminated. Experimental results across different types of face forgery datasets and detectors demonstrate that our method achieves state-of-the-art performances against various types of adversarial perturbations while better preserving natural accuracy. Code is available on https://github.com/xarryon/Inspector.