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This study intends to analyze the causes on poor clinical efficacy of kyphoplasty performed in unilateral transpedicular puncture for the treatment of senile osteoporotic vertebral compression fractures. A retrospective study was conducted on a consecutive series of 70 patients who had underwent kyphoplasty performed in unilateral transpedicular puncture for the treatment of senile osteoporotic vertebral compression fractures between March 2016 to March 2017. These patients were compared for clinical data to investigate the causes on poor clinical efficacy of kyphoplasty performed in unilateral transpedicular puncture for the treatment of senile osteoporotic vertebral compression fractures. Comparison result of the indices between these patients showed that the differences in body weight, fracture type and bone cement dispersion were statistically significant. Logistic multivariate regression analysis showed body weight (OR = 0.892, p = 0.042), fracture type 2 (OR = 0.089, p = 0.020) and bone cement dispersion (OR = 4.773, p = 0.025) are risk factors for poor clinical efficacy. The results of corresponding analysis on VAS (Visual Analogue Scale), vertebral height and Cobb angle in patients with poor clinical efficacy showed that there is a correlation between them. We believe that patients’ weight, dispersion degree of bone cement and fracture type of injured vertebra are the risk factors of kyphoplasty with poor clinical efficacy.

Abstract:In the analysis of contingency tables, often one faces two difficult criteria: sampled and target populations are not identical and prior information translates to the presence of general linear inequality restrictions. Under these situations, we present new models of estimating cell probabilities related to four well-known methods of estimation. We prove that each model yields maximum likelihood estimators under those restrictions. The performance ranking of these methods under equality restrictions is known. We compare these methods under inequality restrictions in a simulation study. It reveals that these methods may rank differently under inequality restriction than with equality. These four methods are also compared while US census data are analyzed.

In this paper, we first transform a multivariate normal random vector into a random vector with elements that are approximately independent standard normal random variables. Then we propose the multivariate version generalized from the univariate normality test based on kurtosis from the literature. Power is investigated through the Monte Carlo Simulation with different significance level, dimension, and sample size. To assess the validity and accuracy of the new tests, we carry a comparative study with several other existing tests by selecting certain types of symmetric and asymmetric alternative distributions.

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