Biomedical subjects

I L Lu

Publications and source records attributed to I L Lu.

3 recordsLinked to original sources

PubMed1998

Interactions between CO2 chemoreflexes and arterial baroreflexes.

We studied interactions between CO2 chemoreflexes and arterial baroreflexes in 10 supine healthy young men and women. We measured vagal carotid baroreceptor-cardiac reflexes and steady-state fast Fourier transform R-R interval and photoplethysmographic arterial pressure power spectra at three arterial pressure levels (nitroprusside, saline, and phenylephrine infusions) and three end-tidal CO2 levels (3, 4, and 5%, fixed-frequency, large-tidal-volume breathing, CO2 plus O2). Our study supports three principal conclusions. First, although low levels of CO2 chemoreceptor stimulation reduce R-R intervals and R-R interval variability, statistical modeling suggests that this effect is indirect rather than direct and is mediated by reductions of arterial pressure. Second, reductions of R-R intervals during hypocapnia reflect simple shifting of vagally mediated carotid baroreflex responses on the R-R interval axis rather than changes of baroreflex gain, range, or operational point. Third, the influence of CO2 chemoreceptor stimulation on arterial pressure (and, derivatively, on R-R intervals and R-R interval variability) depends critically on baseline arterial pressure levels: chemoreceptor effects are smaller when pressure is low and larger when arterial pressure is high.

Adult↗

PubMed1995

Effect of non-random missing data mechanisms in clinical trials.

A simple form of non-ignorable missing data mechanisms based on two parameters is used to characterize the amount of missing data and the severity of non-randomness in clinical trials. Based on the formulation, the effect of non-randomly missing data on simple analyses which ignore the missing data is studied for binary and normally distributed response variables. In general, the effect of the non-randomly missing data on the bias and the power increases with the severity of non-randomness. The bias can be positive or negative and the power can be less than or greater than when the data are missing at random. The results of the analysis, ignoring the missing data, can be seriously flawed if the non-randomness is severe, even when only a small proportion of the sample is missing. The problem is more pronounced in the case of normally distributed response variables with unequal variances.

Bias↗

PubMedDate not supplied

Predictors of in-treatment relapse in perinatal substance abusers and impact on treatment retention: a prospective study.

This prospective study investigated in-treatment relapse in a sample of perinatal substance abusers in intensive outpatient treatment. Sixty-four female first-time admissions to a perinatal treatment program completed comprehensive psychological and psychosocial assessment before beginning treatment. Relapse was detected by urine toxicology screening and self-report. A regression analysis resulted in variable reduction, then survival analysis identified the impact of in-treatment relapse and other predictors on treatment length. Fifty-five percent of the subjects were classified as relapsers. Two risk factors for and six protective factors from in-treatment relapse were identified. The survival curves for relapsers and nonrelapsers did not differ until covariates were considered. Subjects with more severe consequences of drug use and less social exposure to drug use during treatment tended not to relapse during treatment, perhaps in order to prevent deterioration such as loss of children or incarceration. Relapse alone did not result in fewer treatment days. Few addiction characteristics were related to either in-treatment relapse or length of treatment. Rather, personality and demographic variables were more salient in both the regression and survival models. Treatment staff may need to reconsider their views of the meaning of relapse and should develop enhanced engagement and retention strategies for women at greater risk of relapse.

Adolescent↗