ABSTRACT
Objective:To evaluate the effectiveness of inspiratory muscle training in middle-aged and elderly patients with obstructive sleep apnea(OSA).Methods:The randomized controlled trials (RCT) on the effect of inspiratory muscle training in middle-aged and elderly patients with OSA were collected using the databases of PubMed, Embase, Cochrane Library, Web of Science, Chinese National Knowledge Infrastructure, Chinese Biomedical Literature Database and Wanfang database, the time was from the construction of the database to December 2020. The literature quality was evaluated and data were extracted from the included literature. RevMan5.3 software was used to analyze the collected data.Results:A total of 8 RCTs were included. Meta-analysis showed that inspiratory muscle training could reduce apnea hypopnea index(AHI)( P<0.05), Epworth Sleepiness Scale(ESS)( P<0.01) and Pittsburgh Sleep Quality Index(PQSI)( P<0.01), but had no effect on lowest oxygen saturation ( P>0.05). Conclusions:Inspiratory muscle training is a safe and feasible training method that can decrease AHI, ESS and PSQI in middle-aged and elderly patients with OSA.
ABSTRACT
Objective:To evaluate the effectiveness of expiratory muscle training in patients with chronic obstructive pulmonary disease.Methods:The randomized controlled trials (RCT) and controlled clinical trials (CCT) on the effect of expiratory muscle training in patients with chronic obstructive pulmonary disease were collected using the databases of PubMed, Embase, Cochrane Library, CNKI, CBM and Wanfang, time is from the construction of the database to November 2019. The literature quality was evaluated and data were extracted from the included literature. Data were analyzed with Revman5.3 software.Results:A total of 8 RCTs and 1 CCT were included. The Meta-analysis showed that Mean difference and its 95% confidence interval of P Imax, P Emax, FEV1, 6MWD and SGRQ score were 0.58 (-1.34, 2.51), 8.11 (-2.64, 18.86), -0.12 (-0.22, -0.01), -16.47(-40.76, 7.82), -1.52 (-3.75, 0.70) (all P>0.05, except for FEV1, P=0.03). Conclusions:In the pulmonary rehabilitation program of COPD patients, EMT combined with IMT does not achieve better results than IMT alone, it is recommended that we can only use IMT instead of EMT combined with IMT, and the same training effect will be achieved with less time and cost.
ABSTRACT
Numerous studies addressing different methods of head injury prognostication have been published. Unfortunately, these studies often incorporate different head injury prognostication models and study populations, thus making direct comparison difficult, if not impossible. Furthermore, newer artificial intelligence tools such as machine learning methods have evolved in the field of data analysis, alongside more traditional methods of analysis. This study targets the development of a set of integrated prognostication model combining different classes of outcome and prognostic factors. Methodologies such as discriminant analysis, logistic regression, decision tree, Bayesian network, and neural network were employed in the study. Several prognostication models were developed using prospectively collected data from 513 severe closed head-injured patients admitted to the Neurocritical Unit at National Neuroscience Institute of Singapore, from April 1999 to February 2003. The correlation between prognostic factors at admission and outcome at 6 months following injury was studied. Overfitting error, which may falsely distinguish different outcomes, was compared graphically. Tenfold cross-validation technique, which reduces overfitting error, was used to validate outcome prediction accuracy. The overall prediction accuracy achieved ranged from 49.79% to 81.49%. Consistently high outcome prediction accuracy was seen with logistic regression and decision tree. Combining both logistic regression and decision tree models, a hybrid prediction model was then developed. This hybrid model would more accurately predict the 6-month post-severe head injury outcome using baseline admission parameters.
