RESUMO
Neuropathic pain after spinal cord injury (SCI) has a significant negative impact on the patients’ quality of life. The objective of this systematic review is to examine the safety and efficacy of pregabalin (PGB) and gabapentin (GBP) in the treatment of neuropathic pain due to SCI. PubMed, the Cochrane Library, Embase, Scopus, and the Web of Science were searched up to December 2018. The reference lists of key and review studies were reviewed for additional citations. The quality of the studies was evaluated using the Cochrane Collaboration’s tools for assessing the risk of bias. A meta-analysis was performed for primary and secondary outcomes.Eight studies were eligible for inclusion. Meta-analysis of PGB vs. placebo showed that PGB was effective for neuropathic pain (standardized mean difference [SMD] = –0.40; 95% confidence interval [CI]: –0.78, –0.01), anxiety (MD = –0.68; 95% CI:–0.77, –0.59), depression (mean difference [MD] = –0.99; 95% CI: –1.08, –0.89), and sleep interference (MD = –1.08; 95% CI: –1.13, –1.02). Also, GBP was more effective than a placebo for reducing pain. No significant difference was observed between the efficacy of the two drugs (MD = –0.37; 95% CI: –1.67, 0.93). There was no significant difference between the two drugs for discontinuation due to adverse events (risk ratio = 3.00; 95% CI: 0.81, 11.15). PGB and GBP were effective vs. placebos in decreasing neuropathic pain after SCI. Also, there was no significant difference between the two drugs for decreasing pain and adverse events.
RESUMO
Night work can have a significant impact on health, well-being, performance and occupational safety of workers. Night workers often complain about the sleep disorder characterized by excessive sleepiness. The aim of the study was to determine the level of sleepiness among night workers and investigate its relationship with oral temperature in a hot industry. This cross-sectional study involved 80 night workers. Stanford Sleepiness Scale [SSS] has been used to measure the level of sleepiness. Oral temperature and SSS were recorded at different hours of night shift [23 pm to 4 am] for two consecutive nights. The analysis of results showed that there was a positive linear trend in the sleepiness scale [Pvalue<0.001] and an increasing trend in the oral temperature between 23pm and 1am. Then a decreasing trend has been observed after 1am for both of them [Pvalue <0.001]. Comparison of the results for two nights indicated that the mean sleepiness index in the second night is higher than the first [Pvalue <0.001], but the mean oral temperature in the second night was equal to that in the first night. Findings suggest a weak negative association between sleepiness and oral temperature. [r=-0.24, Pvalue =0.03]. A substantial proportion of subjects were working while sleepy, especially at late night and early morning hours. The combination of heat stress and sleepiness can lead to impaired performance. The growing amount of sleepiness index indicates the high risk of sleep disorders and the other possible problems related health among night shift workers
RESUMO
Background: Major injuries and death in accidents have roots in drowsiness. Sleepiness is a main result of insufficient sleep. It is vital to explore drowsiness and its level. There are various sorts of methods in the forms of subjective and objective approaches. The goal of this study was to detect the association of subjective and interpretive drowsiness with facial dynamic changes
Methods: This experimental study was conducted in the Virtual Reality Lab, in Khaje-Nasir Toosi University of Technology, Tehran Iran on 40 drivers in 2015. Facial Dynamic changes [eyes, mouth and eyebrows], Karolinska Sleepiness Scale [KSS] and Observer Rating of Drowsiness [ORD] were applied. The neural network and Viola-Jones were utilized for facial characteristics detection. Statistical analyses were conducted using SPSS version 21
Result: Thirty-four drivers got drowsy during the test. They were selected randomly among suburban drivers at the age in a range of 26 to 60 yr old. Descriptive statistics of the dynamic changes in eyebrows, mouth and eyes showed that these features were of meaningful changes with respect to the level of drowsiness during driving. A relationship between the dynamic changes of facial features and ORD was recognized. Moreover, there was a significant relationship between facial expression and drowsiness [P<0.05]
Conclusions: Results of KSS and ORD illustrated that there were dynamic changes in eyes and mouth and eyebrow parameters while driver felt sleepy. This research is helpful in a way that specific changes in elements of face could be effective to provide tools to predict drowsiness