Correlation between cognitive impairment and serum markers in patients with obstructive sleep apnea-hypopnea syndrome.

Background: Previous studies have revealed that sleep structure and hypoxemia are two important environmental factors for cognitive impairment in patients with obstructive sleep apnea-hypopnea syndrome (OSAHS). We hypothesized that the pathophysiological mechanisms between these two factors may also be involved in cognitive impairment in patients with OSAHS. Previous studies have suggested that alterations in serum glucose and lipid metabolism, inflammatory responses, and astrocyte markers not only contribute to sleep structural disorders in OSAHS but also affect the occurrence and development of this disease.

Relationship between slow-wave sleep and serum γ-glutamine transaminase in non-obese men with obstructive sleep apnea-hypopnea syndrome.

Background: Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a disease characterized with intermittent hypoxia and sleep fragmentation. Obesity and gender are major risk factors for the onset of OSAHS. Previous studies on obese men with OSAHS have been performed, while few studies on non-obese men with OSAHS have been carried out.

Improved methods for estimating fraction of missing information in multiple imputation.

Multiple imputation (MI) has become the most popular approach in handling missing data. Closely associated with MI, the fraction of missing information (FMI) is an important parameter for diagnosing the impact of missing data. Currently γ , the sample value of FMI estimated from MI of a limited , is used as the estimate of γ, the population value of FMI, where is the number of imputations of the MI.

Fraction of Missing Information () at Different Missing Data Fractions in the 2012 NAMCS Physician Workflow Mail Survey.

In his 1987 classic book on multiple imputation (MI), Rubin used the fraction of missing information, , to define the relative efficiency (RE) of MI as RE = (1 + /), where is the number of imputations, leading to the conclusion that a small (≤5) would be sufficient for MI. However, evidence has been accumulating that many more imputations are needed. Why would the apparently sufficient deduced from the RE be actually too small? The answer may lie with .

Determining Sufficient Number of Imputations Using Variance of Imputation Variances: Data from 2012 NAMCS Physician Workflow Mail Survey.

How many imputations are sufficient in multiple imputations? The answer given by different researchers varies from as few as 2 - 3 to as many as hundreds. Perhaps no single number of imputations would fit all situations. In this study, , the minimally sufficient number of imputations, was determined based on the relationship between , the number of imputations, and , the standard error of imputation variances using the 2012 National Ambulatory Medical Care Survey (NAMCS) Physician Workflow mail survey.

Consent for genetic research in a general population: an update on the National Health and Nutrition Examination Survey experience.

Purpose: The study determines the consent rates for storage of biologic samples for future research with and without genetic studies and describes trends in sociodemographic factors associated with consent.

Methods: We performed an analysis of the characteristics of consenting individuals participating in three data cycles of the National Health and Nutrition Examination Survey, a nationally representative survey of the U.S.