James L. Rosenberger

Transmucosal administration of midazolam for premedication of pediatric patients. Comparison of the nasal and sublingual routes.

Background:Nasal transmucosal midazolam is effective for premedication of pediatric patients; however, 61-74% of these patients cry at nasal drug administration. Sublingual benzodiazepines, including midazolam, are effective in adults. The current blinded randomized study compared acceptance of and behavioral responses to transmucosal midazolam administered via the intranasal and sublingual routes. Methods:Ninety-three patients aged 0.5-10 yr were stratified by age: 30 infants and toddlers, 0.5-2 yr; 39 preschoolers, 2.1- 5 yr; and 24 school age, 5.1-10 yr. They were randomized to receive 0.2 mg/kg of midazolam in the nose or under the tongue without or with additional flavoring. For the group receiving sublingual flavored midazolam, the syringe tip was dipped in candy flavor and sugar. Duration of crying and compliance with instructions for sublingual drug administration were recorded. Hemoglobin oxygen saturation by pulse oximetry and sedation score were recorded by three observers before drug administration, at 2.5-min intervals for 10 min, at separation from parents, and during induction with halothane in O2. Results:Children accepted midazolam administered via the sublingual route better than that given intranasally. In children not crying before drug administration, the frequency and duration of crying was greater following intranasal compared with sublingual administration (71% vs. 18% (P<0.0001) and 48 ± 56 vs. 25 ± 49 s (P = 0.004), respectively). Lack of total compliance with instructions for sublingual administration did not alter drug effect, and there were no differences between the three study groups in maximum sedation, response to separation from parents, and behavior at induction of anesthesia; 80% displayed adequate or excellent behavior. Finally, the addition of candy flavor did not improve acceptance of or compliance with sublingual midazolam administration. Conclusions:Sublingual administration of midazolam is as effective as, and better accepted than, intranasal midazolam as a preanesthetic sedative in children.

Comparison of the safety and efficacy of intranasal midazolam or sufentanil for preinduction of anesthesia in pediatric patients.

Nasal administration of sufentanil or midazolam is effective for preinduction of pediatric patients, but there are no data on which to base a choice between them. This blinded randomized study compares behavioral and physiologic responses to sedation with one of these medications followed by inhalation or intravenous induction. Ninety-five patients aged 0.5-10 yr scheduled for elective surgery were stratified by age: 30 infants 0.5-2 yr, 38 preschoolers 2.1-5 yr, and 27 school-age children 5.1-10 yr. They were randomized to receive 0.04 ml/kg of midazolam (0.2 mg/kg) or sufentanil (2 micrograms/kg). Hemoglobin oxygen saturation by pulse oximetry (SpO2) and sedation score were recorded prior to drug administration, at 2.5-min intervals for 10 min, at separation, and during induction with graded halothane in oxygen. Intubation was performed under deep halothane or 3 mg/kg of thiopental and 0.1 mg/kg of pancuronium. Chest wall compliance was assessed qualitatively in all patients prior to intubation. To assess the effects of a mild standardized stress on unpremedicated patients, 75 of the children with parents present were scored before and after oximeter probe placement: of these, in 63% the sedation score did not change; 33% appeared more anxious; and only 4% seemed reassured. Children of all ages reacted negatively to physicians, and 23% were crying prior to administration of drugs. Sufentanil appeared less unpleasant to receive than midazolam: children cried 46 +/- 100 versus 76 +/- 73 s (P less than 0.05), respectively, but by 7.5 min, no child was crying. Median behavior scores at maximum anxiolysis were not different, but response to sufentanil was more variable.(ABSTRACT TRUNCATED AT 250 WORDS)

Experimental Designs for Model Discrimination

Abstract We present designs that perform well for several objectives simultaneously. Three different approaches are discussed: to augment a given design in an optimal way, to evaluate a mixture of the various criteria, and to optimize one objective subject to achieving a prescribed efficiency level for the others. Our sample designs are for the situation of discriminating between a second- and third-degree polynomial fit, under the D-criterion and geometric mixtures of D-criteria.

Exchange Algorithms for Constructing Model-Robust Experimental Designs

Optimal experimental design procedures, utilizing criteria such as D-optimality, are useful for producing designs for quantitative responses, often under nonstandard conditions such as constrained design spaces. However, these methods require a priori knowledge of the exact form of the response function, an often unrealistic assumption. Model-robust designs are those that, from our perspective, are efficient with respect to a set of possible models. In this paper, we develop a model-robust technique motivated by a connection to multiresponse D-optimal design. This link spawns a generalization of the modified Fedorov exchange algorithm, which is then used to construct exact model-robust designs. We also study the effectiveness of designs robust for a small set of models compared with designs that account for much larger sets. We give several examples and compare our designs with two model-robust procedures in the literature.

Model-Robust Two-Level Designs Using Coordinate Exchange Algorithms and a Maximin Criterion

We propose a candidate-list-free exchange algorithm that facilitates construction of exact, model-robust, two-level experiment designs. In particular, we investigate two model spaces previously considered in the literature. The first assumes that all main effects and an unknown subset of two-factor interactions are active, but that the experimenter knows the number of active interactions. The second assumes that an unknown subset of the main effects, and all associated two-factor interactions, are active. Previous literature uses two criteria for design construction: first, maximize the number of estimable models; then, differentiate between designs equivalent in estimability by choosing the design with the highest average -efficiency. We adopt a similar strategy, but (1) do not impose orthogonality or factor level balance constraints, resulting in generally equal or larger numbers of estimable models, and (2) use a flexible secondary criterion that maximizes the minimum -efficiency. We provide results for many situations of interest. We also provide online supplementary material that includes algorithmic details, designs, and MATLAB code.

Correcting Bias Introduced by Aerial Counts in Angler Effort Estimation

Abstract A critical part of most any roving angler survey is angler effort estimation. Various methods have been proposed and implemented to calculate this important parameter, and one of the most effective methods for estimation over large areas utilizes aerial counts of anglers. In this paper, we describe effort estimation methodology used for a creel survey conducted by the Pennsylvania Fish and Boat Commission in the lower Juniata River and lower and middle Susquehanna River during 2007. Daytime angler effort estimates were calculated using an augmented aerial survey, which includes both aerial counts and data collected by creel agents on the ground. Interview angler effort data obtained via a modified roving ground survey were used to produce estimates of daily effort distributions, which were then used to expand instantaneous aerial counts to daily effort estimates. We present two ratios that ameliorate biases introduced by the aerial survey. An angler-to-people ratio calculated from the ground data...

Model-robust designs for split-plot experiments

Split-plot experiments are appropriate when some factors are more difficult and/or expensive to change than others. They require two levels of randomization resulting in a non-independent error structure. The design of such experiments has garnered much recent attention, including work on exact D-optimal split-plot designs. However, many of these procedures rely on the a priori assumption that the form of the regression function is known. We relax this assumption by allowing a set of model forms to be specified, and use a scaled product criterion along with an exchange algorithm to produce designs that account for all models in the set. We include also a generalization which allows weights to be assigned to each model, though they appear to have only a slight effect. We present two examples from the literature, and compare the scaled product designs with designs optimal for a single model. We also discuss a maximin alternative.

The Discovery and Ecology of a Member of the Cambarus acuminatus Complex (Decapoda: Cambaridae) in Valley Creek, Southeastern Pennsylvania

Abstract The Cambarus acuminatus complex is a poorly known group of crayfish species whose range has traditionally been assumed to extend from the Patapsco River drainage in Maryland southward to the Saluda River basin in South Carolina. During a recent crayfish survey of southeastern Pennsylvania, we collected a member of the C. acuminatus complex [Cambarus (Puncticambarus) sp.] from Valley Creek. Collections were made from several habitats [pools, riffles, shallow lateral areas (SL), main-channel areas (MC)], and dominant substrate classes, current velocity, and depth were recorded in each sampling area. These collections represent a new crayfish record for Pennsylvania and the first documented occurrence of the C. acuminatus complex north of the Patapsco drainage. Life history characteristics of the population of C. (P.) sp. inhabiting Valley Creek are provided and their variation among habitats and seasons is discussed. In pools, C. (P.) sp. density was negatively related to current velocity, depth, and % sand, and positively related to % silt. In riffles, C. (P.) sp. density was negatively related to current velocity. Comparisons among habitats indicated that C. (P.) sp. was abundant in SL but was scarce in MC. Although MC tended to have faster current, greater depth, more sand, and less silt than SL, other factors could have been responsible for the relative scarcity of C. (P.) sp. in MC. More conclusively, there was a positive relationship between C. (P.) sp. density and % cobble in MC of pools, suggesting that activities such as urbanization that result in sediment deposition and burial of rocky substrates may have a negative effect on density in MC. Since MC are important for large, reproductive individuals, reduced density in these areas may affect the reproductive potential of the population. These findings indicate that Valley Creek supports an unusual and potentially threatened crayfish population that requires further study and highlight the need for additional fieldwork in the region.

A Bayesian Approach to Sequential Optimization based on Computer Experiments

Computer experiments are used frequently for the study and improvement of a process under study. Optimizing such process based on a computer model is costly, so an approximation of the computer model, or metamodel, is used. Efficient global optimization (EGO) is a sequential optimization method for computer experiments based on a Gaussian process model approximation to the computer model response. A long-standing problem in EGO is that it does not consider the uncertainty in the parameter estimates of the Gaussian process. Treating these estimates as if they are the true parameters leads to an improper assessment of the precision of the approximation, a precision that is crucial to assess not only in optimization but in metamodeling in general. One way to account for these uncertainties is to use bootstrapping, studied by previous authors. Alternatively, some other authors have mentioned how a Bayesian approach may be the best way to incorporate the parameter uncertainty in the optimization, but no fully Bayesian approach for EGO has been implemented in practice. In this paper, we present a fully Bayesian implementation of the EGO method. The proposed Bayesian EGO algorithm is validated through simulation of noisy nonlinear functions and compared with the standard EGO method and the bootstrapped EGO. We also apply the Bayesian EGO algorithm to the optimization of a stochastic computer model. It is shown how a Bayesian approach to EGO allows one to optimize any function of the posterior predictive density. Copyright

Effect of pituitary hollow fiber units and thyroid supplementation on growth in the little mouse.

Abstract Hollow fiber units containing allogeneic pituitary cells were implanted intracranially into heterozygous (lit/+) and homozygous, mutant (lit/lit) C57BL/6J “little” weanling mice. Over the 48 days of the experiment, heterozygous mice with pituitary cell implants had a lower percentage weight gain than control mice. Homozygous, mutant mice with cell implants, however, made significant weight gains over mutant controls. Long bone lengths were lower, and organ and carcass weights were higher, in heterozygous mice receiving pituitary cell implants than in control mice, but corresponding measurements in mutant mice with and without implants were not significantly different. Supplementation of the diet with thyroid powder increased the percentage weight gain during the latter half of the 48-day period in both genotypes with and without implanted cells. Thyroid-supplemented mutant mice with pituitary cell implants had significantly higher organ and carcass weights than other mutant groups. The little mouse may serve as a model for pituitary studies and for the treatment of isolated growth hormone deficiency type 1 in man.