An Extended Hierarchical Task Analysis for Error Prediction in Medical Devices

This paper introduces an extended hierarchical task analysis (HTA) methodology devised to evaluate and compare user interfaces on volumetric infusion pumps. The pumps were studied along the dimensions of overall usability and propensity for generating human error. With HTA as our framework, we analyzed six pumps on a variety of common tasks using Norman’s Action theory. The introduced method of evaluation divides the problem space between the external world of the device interface and the user’s internal cognitive world, allowing for predictions of potential user errors at the human-device level. In this paper, one detailed analysis is provided as an example, comparing two different pumps on two separate tasks. The results demonstrate the inherent variation, often the cause of usage errors, found with infusion pumps being used in hospitals today. The reported methodology is a useful tool for evaluating human performance and predicting potential user errors with infusion pumps and other simple medical devices.

FoxM1B regulates NEDD4-1 expression, leading to cellular transformation and full malignant phenotype in immortalized human astrocytes.

Our recent studies have shown that the FoxM1B transcription factor is overexpressed in human glioma tissues and that the level of its expression correlates directly with glioma grade. However, whether FoxM1B plays a role in the early development of glioma (i.e., in transformation) is unknown. In this study, we found that the FoxM1B molecule causes cellular transformation and tumor formation in normal human astrocytes (NHA) immortalized by p53 and pRB inhibition. Moreover, brain tumors that arose from intracranial injection of FoxM1B-expressing immortalized NHAs displayed glioblastoma multiforme (GBM) phenotypes, suggesting that FoxM1B overexpression in immortalized NHAs not only transforms the cells but also leads to GBM formation. Mechanistically, our results showed that overexpression of FoxM1B upregulated NEDD4-1, an E3 ligase that mediates the degradation and downregulation of phosphatase and tensin homologue (PTEN) in multiple cell lines. Decreased PTEN in turn resulted in the hyperactivation of Akt, which led to phosphorylation and cytoplasmic retention of FoxO3a. Blocking Akt activation with phosphoinositide 3-kinase/Akt inhibitors inhibited the FoxM1B-induced transformation of immortalized NHAs. Furthermore, overexpression of FoxM1B in immortalized NHAs increased the expression of survivin, cyclin D1, and cyclin E, which are important molecules for tumor growth. Collectively, these results indicate that overexpression of FoxM1B, in cooperation with p53 and pRB inhibition in NHA cells, promotes astrocyte transformation and GBM formation through multiple mechanisms.

$\beta\sb2$-adrenergic receptor desensitization, internalization and phosphorylation in response to full and partial agonists

The objective of this study is to test the hypothesis that partial agonists produce less desensitization because they generate less of the active conformation of the $\beta\sb2$-adrenergic receptor ($\beta$AR) (R*) and in turn cause less $\beta$AR phosphorylation by beta adrenergic receptor kinase ($\beta$ARK) and less $\beta$AR internalization. In the present work, rates of desensitization, internalization, and phosphorylation caused by a series of $\beta$AR agonists were correlated with a quantitative measure, defined as coupling efficiency, of agonist-dependent $\beta$AR activation of adenylyl cyclase. These studies were preformed in HEK-293 cells overexpressing the $\beta$AR with hemagglutinin (HA) and 6-histidine (6HIS) epitopes introduced into the N- and C-termini respectively. Agonists chosen provided a 95-fold range of coupling efficiencies, and, relative to epinephrine, the best agonist, (100%) were fenoterol (42%), albuterol (4.9%), dobutamine (2.5%) and ephedrine (1.1%). At concentrations of these agonists yielding $>$90% receptor occupancy, the rate and extent of the rapid phase (0-30 min) of agonist induced desensitization of adenylyl cyclase followed the same order as coupling efficiency, that is, epinephrine $\ge$ fitnoterol $>$ albuterol $>$ dobutamine $>$ ephedrine. The rate of internalization, measured by a loss of surface receptors during desensitization, with respect to these agonists also followed the same order as the desensitization and exhibited a slight lag. Like desensitization and internalization, $\beta$AR phosphorylation exhibited a dependency on agonist strength. The two strongest agonists epinephrine and fenoterol provoked 11 to 13 fold increases in the level of $\beta$AR phosphorylation after just 1 min, whereas the weakest agonists dobutamine and ephedrine caused only 3 to 4 fold increases in phosphorylation. With longer treatment times, the level of $\beta$AR phosphorylation declined with the strong agonists, but progressively increased with the weaker partial agonists. The major conclusion drawn from this study is that the occupancy-dependent rate of receptor phosphorylation increases with agonist coupling efficiencies and that this is sufficient to explain the desensitization, internalization, and phosphorylation data obtained.^ The mechanism of activation and desensitization by the partial $\beta$AR agonist salmeterol was also examined in this study. This drug is extremely hydrophobic and its study presents possibly unique problems. To determine whether salmeterol induces desensitization of the $\beta$AR its action has been studied using our system. Employing the use of reversible antagonists it was found that salmeterol, which has an estimated coupling efficiency near that of albuterol caused $\beta$AR desensitization. This desensitization was much reduced relative to epinephrine. Consistent with its coupling efficiency, it was found to be similar to albuterol in its ability to induce internalization and phosphorylation of the $\beta$AR. (Abstract shortened by UMI.) ^

Design and analysis for three level hierarchical structures with count response

In numerous intervention studies and education field trials, random assignment to treatment occurs in clusters rather than at the level of observation. This departure of random assignment of units may be due to logistics, political feasibility, or ecological validity. Data within the same cluster or grouping are often correlated. Application of traditional regression techniques, which assume independence between observations, to clustered data produce consistent parameter estimates. However such estimators are often inefficient as compared to methods which incorporate the clustered nature of the data into the estimation procedure (Neuhaus 1993).1 Multilevel models, also known as random effects or random components models, can be used to account for the clustering of data by estimating higher level, or group, as well as lower level, or individual variation. Designing a study, in which the unit of observation is nested within higher level groupings, requires the determination of sample sizes at each level. This study investigates the design and analysis of various sampling strategies for a 3-level repeated measures design on the parameter estimates when the outcome variable of interest follows a Poisson distribution. ^ Results study suggest that second order PQL estimation produces the least biased estimates in the 3-level multilevel Poisson model followed by first order PQL and then second and first order MQL. The MQL estimates of both fixed and random parameters are generally satisfactory when the level 2 and level 3 variation is less than 0.10. However, as the higher level error variance increases, the MQL estimates become increasingly biased. If convergence of the estimation algorithm is not obtained by PQL procedure and higher level error variance is large, the estimates may be significantly biased. In this case bias correction techniques such as bootstrapping should be considered as an alternative procedure. For larger sample sizes, those structures with 20 or more units sampled at levels with normally distributed random errors produced more stable estimates with less sampling variance than structures with an increased number of level 1 units. For small sample sizes, sampling fewer units at the level with Poisson variation produces less sampling variation, however this criterion is no longer important when sample sizes are large. ^ 1Neuhaus J (1993). “Estimation efficiency and Tests of Covariate Effects with Clustered Binary Data”. Biometrics , 49, 989–996^

Sequential updating via dynamic hierarchical models: A Bayesian approach to longitudinal data analysis

Most statistical analysis, theory and practice, is concerned with static models; models with a proposed set of parameters whose values are fixed across observational units. Static models implicitly assume that the quantified relationships remain the same across the design space of the data. While this is reasonable under many circumstances this can be a dangerous assumption when dealing with sequentially ordered data. The mere passage of time always brings fresh considerations and the interrelationships among parameters, or subsets of parameters, may need to be continually revised. ^ When data are gathered sequentially dynamic interim monitoring may be useful as new subject-specific parameters are introduced with each new observational unit. Sequential imputation via dynamic hierarchical models is an efficient strategy for handling missing data and analyzing longitudinal studies. Dynamic conditional independence models offers a flexible framework that exploits the Bayesian updating scheme for capturing the evolution of both the population and individual effects over time. While static models often describe aggregate information well they often do not reflect conflicts in the information at the individual level. Dynamic models prove advantageous over static models in capturing both individual and aggregate trends. Computations for such models can be carried out via the Gibbs sampler. An application using a small sample repeated measures normally distributed growth curve data is presented. ^

A full pedigree based method for the statistical assessment of genetic anticipation

Genetic anticipation is defined as a decrease in age of onset or increase in severity as the disorder is transmitted through subsequent generations. Anticipation has been noted in the literature for over a century. Recently, anticipation in several diseases including Huntington's Disease, Myotonic Dystrophy and Fragile X Syndrome were shown to be caused by expansion of triplet repeats. Anticipation effects have also been observed in numerous mental disorders (e.g. Schizophrenia, Bipolar Disorder), cancers (Li-Fraumeni Syndrome, Leukemia) and other complex diseases. ^ Several statistical methods have been applied to determine whether anticipation is a true phenomenon in a particular disorder, including standard statistical tests and newly developed affected parent/affected child pair methods. These methods have been shown to be inappropriate for assessing anticipation for a variety of reasons, including familial correlation and low power. Therefore, we have developed family-based likelihood modeling approaches to model the underlying transmission of the disease gene and penetrance function and hence detect anticipation. These methods can be applied in extended families, thus improving the power to detect anticipation compared with existing methods based only upon parents and children. The first method we have proposed is based on the regressive logistic hazard model. This approach models anticipation by a generational covariate. The second method allows alleles to mutate as they are transmitted from parents to offspring and is appropriate for modeling the known triplet repeat diseases in which the disease alleles can become more deleterious as they are transmitted across generations. ^ To evaluate the new methods, we performed extensive simulation studies for data simulated under different conditions to evaluate the effectiveness of the algorithms to detect genetic anticipation. Results from analysis by the first method yielded empirical power greater than 87% based on the 5% type I error critical value identified in each simulation depending on the method of data generation and current age criteria. Analysis by the second method was not possible due to the current formulation of the software. The application of this method to Huntington's Disease and Li-Fraumeni Syndrome data sets revealed evidence for a generation effect in both cases. ^

Clinical decisions related to CBC screening of asymptomatic full-term infants at risk for group B streptococcus disease

Objective. Although complete blood count (CBC) changes occur with the development of clinical sepsis in newborns, the CBC has not been reported to be a sensitive predictor of sepsis in asymptomatic full-term newborn infants, nor has it been reported to be related to risk factors for sepsis or clinical decisions. The objective of this study was to evaluate the relationship between the WBC/I:T (immature:total neutrophil) ratio and maternal group B streptococcal (GBS) risk factors (rupture of membranes ≥18 hours, maternal temperature ≥100.4°F, maternal age ≤20 years, previous infant with invasive GBS disease, maternal GBS bacteriuria, and black ethnicity); and to evaluate the relationship between the WBC/I:T ratios and providers' clinical decisions (observe versus repeat the CBC or complete sepsis evaluation) in the asymptomatic full-term newborn at risk for early-onset GBS sepsis. ^ Methods. Medical records of infants admitted to the well baby nursery at a tertiary care teaching hospital in Houston, TX between 1/1/99 and 12/31/00 whose gestational ages were ≥35 weeks; who had mothers with GBS positive or unknown culture status and inadequate intrapartum antibiotic prophylaxis; and who had screening CBCs performed in the first 30 hours of life because of GBS risk were reviewed (n = 412). Demographic information, maternal GBS risk factors, CBC results, clinical decisions, and rationales for clinical decisions were collected. ^ Results. With the exception of black ethnicity (p = .0000, odds ratio = 0.213), no statistically significant differences in risk factors between infants with normal and abnormal WBC counts or normal and abnormal I:T ratios were found. Infants with abnormal WBCs had a significantly higher likelihood of having a CBC repeated (p = 0.002 for WBC). Providers documented the CBC result in the rationale for clinical decisions in 62% of the cases. ^ Conclusion. The CBC results were not related to maternal risk factors for GBS except for ethnicity. Black infants had significantly lower WBC levels than infants of other ethnicities, although this difference was clinically insignificant. Infants with abnormal WBCs had a significantly higher likelihood of undergoing repeat CBCs but not sepsis evaluations. Provider rationale was difficult to evaluate due to insufficient documentation. The screening CBC result did not impact the clinicians' decisions to initiate sepsis evaluations in this population. ^

Robust effect sizes and their confidence intervals for group difference between trajectories in hierarchical linear growth model

Hierarchical linear growth model (HLGM), as a flexible and powerful analytic method, has played an increased important role in psychology, public health and medical sciences in recent decades. Mostly, researchers who conduct HLGM are interested in the treatment effect on individual trajectories, which can be indicated by the cross-level interaction effects. However, the statistical hypothesis test for the effect of cross-level interaction in HLGM only show us whether there is a significant group difference in the average rate of change, rate of acceleration or higher polynomial effect; it fails to convey information about the magnitude of the difference between the group trajectories at specific time point. Thus, reporting and interpreting effect sizes have been increased emphases in HLGM in recent years, due to the limitations and increased criticisms for statistical hypothesis testing. However, most researchers fail to report these model-implied effect sizes for group trajectories comparison and their corresponding confidence intervals in HLGM analysis, since lack of appropriate and standard functions to estimate effect sizes associated with the model-implied difference between grouping trajectories in HLGM, and also lack of computing packages in the popular statistical software to automatically calculate them. ^ The present project is the first to establish the appropriate computing functions to assess the standard difference between grouping trajectories in HLGM. We proposed the two functions to estimate effect sizes on model-based grouping trajectories difference at specific time, we also suggested the robust effect sizes to reduce the bias of estimated effect sizes. Then, we applied the proposed functions to estimate the population effect sizes (d ) and robust effect sizes (du) on the cross-level interaction in HLGM by using the three simulated datasets, and also we compared the three methods of constructing confidence intervals around d and du recommended the best one for application. At the end, we constructed 95% confidence intervals with the suitable method for the effect sizes what we obtained with the three simulated datasets. ^ The effect sizes between grouping trajectories for the three simulated longitudinal datasets indicated that even though the statistical hypothesis test shows no significant difference between grouping trajectories, effect sizes between these grouping trajectories can still be large at some time points. Therefore, effect sizes between grouping trajectories in HLGM analysis provide us additional and meaningful information to assess group effect on individual trajectories. In addition, we also compared the three methods to construct 95% confident intervals around corresponding effect sizes in this project, which handled with the uncertainty of effect sizes to population parameter. We suggested the noncentral t-distribution based method when the assumptions held, and the bootstrap bias-corrected and accelerated method when the assumptions are not met.^

Cloning and characterization of the full length cDNA and promoter of mouse tissue transglutaminase

Transglutaminases are a family of enzymes that catalyze the covalent cross-linking of proteins through the formation of $\varepsilon$-($\gamma$-glutaminyl)-lysyl isopeptide bonds. Tissue transglutaminase (Tgase) is an intracellular enzyme which is expressed in terminally differentiated and senescent cells and also in cells undergoing apoptotic cell death. To characterize this enzyme and examine its relationship with other members of the transglutaminase family, cDNAs, the first two exons of the gene and 2 kb of the 5$\sp\prime$ flanking region, including the promoter, were isolated. The full length Tgase transcript consists of 66 bp of 5$\sp\prime$-UTR (untranslated) sequence, an open reading frame which encodes 686 amino acids and 1400 bp of 3$\sp\prime$-UTR sequence. Alignment of the deduced Tgase protein sequence with that of other transglutaminases revealed regions of strong homology, particularly in the active site region.^ The Tgase cDNA was used to isolate and characterize a genomic clone encompassing the 5$\sp\prime$ end of the mouse Tgase gene. The transcription start site was defined using genomic and cDNA clones coupled with S1 protection analysis and anchored PCR. This clone includes 2.3 kb upstream of the transcription start site and two exons that contain the first 256 nucleotides of the mouse Tgase cDNA sequence. The exon intron boundaries have been mapped and compared with the exon intron boundaries of three members of the transglutaminase family: human factor XIIIa, the human keratinocyte transglutaminase and human erythrocyte band 4.1. Tissue Tgase exon II is similar to comparable exons of these genes. However, exon I bears no resemblance with any of the other transglutaminase amino terminus exons.^ Previous work in our laboratory has shown that the transcription of the Tgase gene is directly controlled by retinoic acid and retinoic acid receptors. To identify the region of the Tgase gene responsible for regulating its expression, fragments of the Tgase promoter and 5$\sp\prime$-flanking region were cloned into the chloramphenicol actetyl transferase (CAT) reporter constructs. Transient transfection experiments with these constructs demonstrated that the upstream region of Tgase is a functional promoter which contains a retinoid response element within a 1573 nucleotide region spanning nucleotides $-$252 to $-$1825. ^