[Meta-analysis of clinical efficacy of ankle arthrodesis and total ankle arthroplasty in the treatment of end-stage ankle arthritis].

OBJECTIVE: To systematically review the clinical efficacy of total ankle arthroplasty (TAA) and ankle arthrodesis (AA) in the treatment of end-stage ankle arthritis. METHODS: The PubMed, EMBASE and Cochrane Library databases were searched for articles published in the treatment of end-stage ankle arthritis with AA or TAA from the establishment of the database to June 2021. Bias risk tool was used to evaluate the quality of the literature. The American Orthopaedic Foot and Ankle Society Ankle-Hindfoot Scale(AOFAS), visual analog scale (VAS), ankle osteoarthritis scale(AOS), gait analysis (pace, frequency, stride), range of motion (ROM), satisfaction, complications and reoperation rate were analyzed by meta-analysis between AA and TAA groups by RevMan 5.3 software. RESULTS: A total of 12 articles were included, including 1 050 patients in the AA group and 3 760 patients in the TAA group, totaling 4 810 patients. Meta-analysis showed that the total score of AOFAS[MD=-3.12, 95%CI(-9.02, 2.96), P=0.31], pain score [MD=1.60, 95%CI(-1.35, 4.54), P=0.29], alignmentl score[MD=-0.04, 95%CI(-0.52, 0.44), P=0.88], VAS[MD=0.10, 95%CI(-0.49, 0.68), P=0.74], and AOS total score [MD=-4.01, 95%CI(-8.28, 0.25), P=0.06], the difference was not statistically significant (P>0.05). The score of AOFAS functional in TAA group was significantly higher than that in TAA group[MD=44.22, 95%CI(-8.01, -0.43), P=0.03]. There was no significant difference in gait analysis between the two groups (P>0.05). Postoperative ROM [MD=-4.93, 95%CI(-6.35, -3.52), P<0.000 01] and change in ROM from preoperative to follow-up[MD=-5.74, 95%CI(-8.88, -2.61), P=0.0003] between two groups, the difference was statistically significant. There was no significant difference in satisfaction between the two groups [OR=1.011, 95%CI(0.46, 2.23), P=0.98]. Complications [OR=1.61, 95%CI(1.26, 2.06), P=0.0002] and non-revision reoperation [OR=1.61, 95%CI(1.17, 2.21), P=0.003] were significantly lower in the TAA group than in the AA group. There was no significant difference in the rate of revision and reoperation(P>0.05) between the two groups [OR=1.02, 95%CI(0.37, 2.78), P=0.97]. CONCLUSION: The clinical efficacy of AA is similar to that of TAA, but the non revision reoperation rate and main surgical complications of TAA are significantly reduced. Therefore, further high-quality methodological research and long-term follow-up are needed to confirm this conclusion.

Severity detection of COVID-19 infection with machine learning of clinical records and CT images.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a deadly viral infection spreading rapidly around the world since its outbreak in 2019. In the worst case a patient's organ may fail leading to death. Therefore, early diagnosis is crucial to provide patients with adequate and effective treatment. OBJECTIVE: This paper aims to build machine learning prediction models to automatically diagnose COVID-19 severity with clinical and computed tomography (CT) radiomics features. METHOD: P-V-Net was used to segment the lung parenchyma and then radiomics was used to extract CT radiomics features from the segmented lung parenchyma regions. Over-sampling, under-sampling, and a combination of over- and under-sampling methods were used to solve the data imbalance problem. RandomForest was used to screen out the optimal number of features. Eight different machine learning classification algorithms were used to analyze the data. RESULTS: The experimental results showed that the COVID-19 mild-severe prediction model trained with clinical and CT radiomics features had the best prediction results. The accuracy of the GBDT classifier was 0.931, the ROUAUC 0.942, and the AUCPRC 0.694, which indicated it was better than other classifiers. CONCLUSION: This study can help clinicians identify patients at risk of severe COVID-19 deterioration early on and provide some treatment for these patients as soon as possible. It can also assist physicians in prognostic efficacy assessment and decision making.