Background: Previous meta-analyses examined only the short-term differences between
lidocaine and steroids vs lidocaine alone in treating lumbar degenerative diseases. Long-term
outcomes (1-2 years) in patients with lumbar disc herniation (LDH) and lumbar central spinal
stenosis (LCSS) have not yet been systematically evaluated.
Objective: The objective of our study was to assess quantitatively the difference in efficacy
at 1 to 2 years between lidocaine alone vs lidocaine and steroids for the management of LDH
or LCSS.
Study Design: We conducted a meta-analysis.
Methods: PubMed, EMBASE, and the Cochrane library were electronically searched up to July
22, 2016, for randomized controlled trials comparing lidocaine alone vs in combination with
steroids for the treatment of LDH and LCSS. Effective pain relief (EPR), Numeric Rating Scale
(NRS-11), Oswestry Disability Index (ODI), opioid intake (OI), and total employed increased
rate (TEIR) were the endpoints. Risk ratios (RRs) or weighted mean difference (WMD) with
95% confidence intervals (CIs) were calculated, and the pooled analysis was conducted using
RevMan 5.2.
Results: Seven trials were included. EPR was not significantly different at 1 and 2 years,
with RR = 1.08 (95% CI, 0.90-1.30; P = .39) and RR = 1.04 (95% CI, 0.92-1.18; P = .51),
respectively, in patients treated with lidocaine alone vs in combination with steroids. The NRS11 was also similar at 1 and 2 years. ODI and OI were not significantly different at 1 and 2
years. A similar TEIR effect was also observed for the 2 treatments.
Limitations: This meta-analysis relied on a small sample size of trials. Significant
heterogeneity among studies was observed. Several significant differences in terms of age of
the patients were reported in one included trial.
Conclusion: This meta-analysis confirmed the similar effects associated with lidocaine alone
vs in combination with steroids for the management of LDH and LCSS. Studies with longer
follow-up periods are still recommended.
Key words: Effective pain relief, lidocaine, long-term, lumbar central spinal stenosis, lumbar
disc herniation, Numeric Rating Scale, opioid intake, Oswestry Disability Index, steroids, total
employed increased rate
We introduce the propagation of Pearcey Gaussian (PG) beams in a strongly nonlocal nonlinear medium (SNNM) analytically. Our results show that PG beams propagating in the SNNM have two different focusing positions. The intensity peak appears at different focusing positions depending on the selection of the nonlinear parameters. In addition, the effects of the nonlinear parameters and the scaling factor on the trajectory, the position of the intensity focusing, the intensity evolution between focus locations, and the radiation force are studied.
The task of identifying urban architectural styles occupies a very necessary position in the fields of construction of smart cities, sustainable urban development and community regeneration. The research method proposed in this paper can improve on the inconveniences of traditional methods of identifying urban architectural styles, such as: the community building is relatively old, and the integration of more periods of architectural style can significantly affect the test results. It is an established fact that data cannot be collected and processed efficiently by humans alone, and can not enter such qualitative and descriptive research methods into the computer for auxiliary research. This paper is based on the explosion of information data use in the 21st century, and use deep learning technology to process unstructured data with convolutional neural networks as the core to assist in the identification of urban architectural styles. With the rapid development of deep learning technology in recent years, its classification techniques for identification of street images of urban buildings can be used for urban management, and a new strong underpinning for the allocation of urban resources, urban diversification management, and the transformation of old communities in the later period has been provided by the proper classification of urban architectural styles. Notwithstanding its restrictions, the approach presented in this research has shown promise and the valuable value of deep learning-based techniques for the study of architectural styles, and this approach has universal significance.
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