Main Effect Terms Research Articles

매출변동 규모가 비대칭적 원가행태에 미치는 영향

ABJ focus on the current period sales-change direction and predicted asymmetric cost behavior. BBCM extended ABJ model by considering the prior period’s sales changes on asymmetric cost behavior. Recently, Ciftci and Zoubi(2019) investigated the impacts of current sales-change size on asymmetric cost behavior extending BBCM’s two-period model. The purpose of our study is to analyze the effects of current sales-change size on asymmetric cost behavior in Korea using Ciftci and Zoubi model. The results of the analysis are as follows. First, In the case of prior sales increase, current small(medium) sales change affects more significantly to the stickiness of cost than large current sales change. In addition, in the case of prior sales decrease, current small(medium) sales change lessens the stickiness of cost more significantly than large current sales change. These results are consistent with our hypotheses. However, medium-size sales change’ coefficient is large than that of small-size sales change, so the relationship between current sales change and cost stickiness is not monotonic, and the model including dummy variables’ main effect terms is somewhat unstable, and in the case of prior sales decrease, the model doesn’t show anti-stickiness. We need more additional research to find out these anomalies are due to difference of cost behavior between Korea and U.S. or defects of the model.

A new class of multi-stress acceleration models with interaction effects and its extension to accelerated degradation modelling

Most products operate under multiple stresses. The influences of multi-stress factors on products are commonly not independent and promote a more violent degradation through interactions, referred to as stress interaction effects. However, few studies consider such effects in multi-stress acceleration models, which may reduce the extrapolation precision and further lead to an inaccurate reliability assessment. In this paper, a new class of multi-stress acceleration models with interaction effects is designed to extrapolate more accurate reliability metrics under multi-stress operating conditions. The main stress effect terms are determined by two criteria: physical stress-based ageing law and statistical correlation. The interaction effects are interpreted as the influences of other stress variables on the main stress effects. In particular, the explicit functions of interaction effects are alternative, which can be identified by adaptive optimization using the maximum likelihood criterion. Furthermore, this multi-stress acceleration model is extended to an accelerated degradation model by integrating a generalized Wiener process with nonlinear time scale functions and random effects. The acceleration factor constant principle is utilized to identify the stress-dependent parameters, facilitating a more appropriate model development. Finally, simulation and a real-world case are performed to validate the effectiveness and practical values of the proposed model.

Variable Selection Based on Profile Forward Selection of Partial Linear Models with Interactive Terms

Due to the rapid development of information technology and data acquisition technology, the model which only considers the linear main effect can not provide accurate prediction results, and the interaction between the predictor and response variables can not be ignored, so the variable selection problem of the model with interaction terms has become an important research topic in the statistical analysis today. In this paper, we discuss the problem of variable selection for a partially linear model with interaction terms using the profile forward selection method under high dimensional data. We propose the two-stage interactive selection algorithm (iPFST) under strong genetic condition and the profile forward selection algorithm (iPFSM) under marginality principle respectively. Theoretically, we use the consistency of profile estimators to prove that profile estimators have uniform convergence rate, and use the screening consistency to prove that iPFST algorithm and iPFSM algorithm can uniformly identify all important linear main effect terms and important interaction effect terms with probability 1. Seven regularization conditions for the theorem are given. Numerical simulation shows the superiority of iPFST and iPFSM in variable selection, and the two algorithms are compared, then iPFST algorithm is better than iPFSM algorithm. Finally, we give detailed technical proof.

Long-term effects of malnutrition on severity of COVID-19

The COVID-19 pandemic is a public health crisis that has the potential to exacerbate worldwide malnutrition. This study examines whether patients with a history of malnutrition are predisposed to severe COVID-19. To do so, data on 103,099 COVID-19 inpatient encounters from 56 hospitals in the United States between March 2020 and June 2020 were retrieved from the Cerner COVID-19 Dataset. Patients with a history of malnutrition between 2015 and 2019 were identified, and a random intercept logistic regression models for pediatric and adult patients were built controlling for patient demographics, socioeconomic status, admission vital signs, and related comorbidities. Statistical interactions between malnutrition and patient age were significant in both the pediatric [log-odds and 95% confidence interval: 0.094 (0.012, 0.175)] and adult [− 0.014 (− 0.021, − 0.006] models. These interactions, together with the main effect terms of malnutrition and age, imply higher odds for severe COVID-19 for children between 6 and 17 years with history of malnutrition. Even higher odds of severe COVID-19 exist for adults (with history of malnutrition) between 18 and 79 years. These results indicate that the long-term effect of malnutrition predisposes patients to severe COVID-19 in an age-dependent way.

867 Standardized order sets do not eliminate racial/ethnic inequities in postpartum pain evaluation and management

To quantify the extent to which a standardized pain management order set reduced racial/ethnic inequities in post-Cesarean pain evaluation and treatment. A follow-up retrospective cohort study comparing previously reported racial/ethnic inequities in post-Cesarean pain management (baseline period: 07/01/14–06/30/16) to data after implementation of a standardized pain management order set (03/01/17–02/28/18). Medical records were queried for number of pain assessments; pain scores> 7; scheduled non-opiate doses, and as needed opiate doses (converted to 5mg oxycodone tablet equivalents, OTE). Outcomes were grouped into 0-< 24 and 24-48 hours postpartum, and stratified by race/ethnicity (Hispanic, non-Hispanic Black (NHB), non-Hispanic White (NHW), Asian, and other). Analyses included logistic regression for the categorical outcome of pain score> 7 (severe pain), and linear regression. Main effect and interaction terms were used to calculate the difference-in-difference from baseline to follow-up. Before order set implementation (N=1701), we demonstrated NHW women had lower pain scores, more frequent pain assessments, and received more opiates than NHB women (% pain scores> 7 NHW/NHB 0-< 24h: 20%/28%; 24-48h: 25%/37%). After implementation (N=888), severe pain remained more common among NHB women (% pain scores> 7 NHW/NHB 0-< 24h: 23%/31%; 24-48h: 26%/38%). Pain management processes changed after implementation (Table), with overall fewer assessments, less opiates and more non-opiate analgesics. However, racial/ethnic inequities in number of assessments and treatment were unchanged (Table, all p for interaction > 0.05), with the exception of an increase in NSAID doses 24-48 hours postpartum for Hispanic women. A standardized pain management order set reduced overall postpartum opiate use, but did not reduce racial/ethnic inequities in pain evaluation and treatment. Future work should investigate racial equity-focused education and interventions designed to eliminate inequities in pain management.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Effects of Anticholinesterase Reversal Under General Anesthesia on Postoperative Cardiovascular Complications: A Retrospective Cohort Study.

The anticholinesterase neostigmine and the muscarinic inhibitor glycopyrrolate are frequently coadministered for the reversal of neuromuscular blockade. This practice can precipitate severe bradycardia or tachycardia, but whether it affects the incidence of cardiovascular complications remains unclear. We hypothesized that anticholinesterase reversal with neostigmine and glycopyrrolate versus no anticholinesterase reversal increases the risk of postoperative cardiovascular complications among adult patients undergoing noncardiac surgery with general anesthesia. We conducted a prespecified retrospective analysis of hospital registry data from a major health care network for patients undergoing surgery with general anesthesia from January 2007 to December 2015. The primary outcome was a composite of cardiac dysrhythmia, acute heart failure, transient ischemic attack, ischemic stroke, and acute myocardial infarction within 30 days after surgery. We performed sensitivity analyses in subgroups and propensity score adjustment and explored the association between exposure and outcome in subgroups of patients with high risk of cardiovascular complications. Of the 98,147 cases receiving neuromuscular blockade, 73,181 (74.6%) received neostigmine and glycopyrrolate, while 24,966 (25.4%) did not. A total of 5612 patients (7.7%) in the anticholinesterase reversal group and 1651 (6.6%) in the control group (P < .001) experienced the primary outcome. After adjustment for clinical covariates, neostigmine and glycopyrrolate exposure was significantly associated in a dose-dependent fashion (P for trend <.001, respectively) with tachycardia (adjusted odds ratio = 2.1 [95% CI, 1.97-2.23]; P < .001) and bradycardia (adjusted odds ratio = 2.84 [95% CI, 2.49-3.24]; P < .001) but not with postoperative cardiovascular complications (adjusted odds ratio = 1.03 [95% CI, 0.97-1.1]; P = .33). We identified a significant effect modification of anticholinesterase reversal by high age, high-risk surgery, and history of atrial fibrillation (P for interaction = .002, .001, and .02, respectively). By using linear combinations of main effect and exposure-risk interaction terms, we detected significant associations between anticholinesterase reversal and cardiovascular complications toward a higher vulnerability in these patient subgroups. Neuromuscular blockade reversal with neostigmine and glycopyrrolate was associated with an increased incidence of intraoperative tachycardia and bradycardia but not with 30-day postoperative cardiovascular complications. Exploratory analyses suggest that a high postoperative cardiovascular complication risk profile may modify the effects of anticholinesterase reversal toward clinical relevance.

Increased lipogenesis and impaired β-oxidation predict type 2 diabetic kidney disease progression in American Indians.

BACKGROUNDIn this study, we identified the lipidomic predictors of early type 2 diabetic kidney disease (DKD) progression, which are currently undefined.METHODSThis longitudinal study included 92 American Indians with type 2 diabetes. Serum lipids (406 from 18 classes) were quantified using mass spectrometry from baseline samples when iothalamate-based glomerular filtration rate (GFR) was at least 90 mL/min. Affymetrix GeneChip Array was used to measure renal transcript expression. DKD progression was defined as at least 40% decline in GFR during follow-up.RESULTSParticipants had a mean age of 45 ± 9 years and median urine albumin/creatinine ratio of 43 (interquartile range 11-144). The 32 progressors had significantly higher relative abundance of polyunsaturated triacylglycerols (TAGs) and a lower abundance of C16-C20 acylcarnitines (ACs) (P < 0.001). In a Cox regression model, the main effect terms of unsaturated free fatty acids and phosphatidylethanolamines and the interaction terms of C16-C20 ACs and short-low-double-bond TAGs by categories of albuminuria independently predicted DKD progression. Renal expression of acetyl-CoA carboxylase-encoding gene (ACACA) correlated with serum diacylglycerols in the glomerular compartment (r = 0.36, and P = 0.006) and with low-double-bond TAGs in the tubulointerstitial compartment (r = 0.52, and P < 0.001).CONCLUSIONCollectively, the findings reveal a previously unrecognized link between lipid markers of impaired mitochondrial β-oxidation and enhanced lipogenesis and DKD progression in individuals with preserved GFR. Renal acetyl-CoA carboxylase activation accompanies these lipidomic changes and suggests that it may be the underlying mechanism linking lipid abnormalities to DKD progression.TRIAL REGISTRATIONClinicalTrials.gov, NCT00340678.FUNDINGNIH R24DK082841, K08DK106523, R03DK121941, P30DK089503, P30DK081943, and P30DK020572.

Work grit as a moderator of politics perceptions

PurposeThe purpose of this paper is to test the interactive effects of grit (e.g. supervisor and employee) and politics perceptions on relevant work outcomes. Specifically, the authors hypothesized that supervisor and employee grit would each demonstrate neutralizing effects when examined jointly.Design/methodology/approachThree studies (N’s=526, 229, 522) were conducted to test the moderating effect across outcomes, including job satisfaction, turnover intentions, citizenship behavior and work effort. The authors controlled for affectivity and nonlinear main effect terms in Studies 2 and 3 following prior discussion.FindingsFindings across studies demonstrated a unique pattern differentiating between grit sources (i.e. employee vs supervisor) and outcome characteristic (i.e. attitudinal vs behavioral). In sum, both employee and supervisor grit demonstrated neutralizing effects when operating in politically fraught work settings.Research limitations/implicationsDespite the single source nature of data collections, the authors took steps to minimize potential biasing factors (e.g. time separation, including affectivity). Future research will benefit from multiple sources of data as well as a more expansive view of the grit construct.Practical implicationsWork contexts have grown increasingly more political in recent years primarily as a result of social and motivational factors. Hence, the authors recommend that leaders investigate factors that minimize its potentially malignant effects. Although grit is often challenging to cultivate through interventions, selection and quality of work life programs may be useful in preparing workers to manage this pervasive source of stress.Originality/valueDespite its practical appeal, grit’s impact in work settings has been under-studied, leading to apparent gaps in science and leadership development. Creative studies, building off the research, will allow grit to maximize its contributions to both scholarship and employee well-being.

Can’t Help Myself: Self-Regulation Failure as a Moderator of the POPS–Work Outcomes Relationships

Drawing upon cognitive control theory, we examined the effects of self- regulation failure on perceptions of politics – work outcome relationships in two studies. In Study 1, we hypothesized that self-regulation failure would moderate the relationship between perceptions of politics and the workplace outcomes of job satisfaction, job effort, job tension, and emotional exhaustion. Specifically, we predicted that high levels of self-regulation failure would exacerbate the strength of the relationship between perceptions of politics and workplace outcomes. Study 1 data were gathered from 166 Chinese hotel administrators involved in development programs. After controlling for demographic factors (i.e., age, gender, organizational tenure) and main effect terms (i.e., perceptions of politics and self-regulation failure), we found support for our hypotheses that self-regulation failure moderated the relationships between perceptions of politics and job satisfaction, job effort, job tension, and emotional exhaustion. Study 2 served as a constructive replication and extension of Study 1. Using a sample of data from 390 U.S. workers, we found self-regulation failure moderated the relationships between perceptions of politics and job satisfaction, job tension, job effort, emotional exhaustion, perceived resource availability, and job performance. The form and magnitude of the interactions in both studies supported the hypotheses. Implications of these results for multiple literatures, practical implications, strengths and limitations, and directions for future research are discussed.

Properties of adaptive clinical trial signature design in the presence of gene and gene-treatment interaction

ABSTRACTTraditional phase III clinical trials are powered to detect an overall treatment effect. However, it has increasingly been shown that many treatments are effective only for a subset of a population. The adaptive signature design uses genomic/proteomic information to prospectively predict a subset of patients more sensitive to treatment. Tests for overall treatment effect and for treatment effect in the predicted subset are conducted. In this work properties of the adaptive signature design are investigated through simulation. It was found that models which excluded expression main effect terms had higher empirical power than models which included them.

Dose response severity functions for acoustic disturbance in cetaceans using recurrent event survival analysis

Behavioral response studies (BRSs) aim to enhance our understanding of the behavior changes made by animals in response to specific exposure levels of different stimuli, often presented in an increasing dosage. Here, we focus on BRSs that aim to understand behavioral responses of free‐ranging whales and dolphins to manmade acoustic signals (although the methods are applicable more generally). One desired outcome of these studies is dose‐response functions relevant to different species, signals and contexts. We adapted and applied recurrent event survival analysis (Cox proportional hazard models) to data from the 3S BRS project, where multiple behavioral responses of different severities had been observed per experimental exposure and per individual based upon expert scoring. We included species, signal type, exposure number and behavioral state prior to exposure as potential covariates. The best model included all main effect terms, with the exception of exposure number, as well as two interaction terms. The interactions between signal and behavioral state, and between species and behavioral state highlighted that the sensitivity of animals to different signal types (a 6–7 kHz upsweep sonar signal [MFAS] or a 1–2 kHz upsweep sonar signal [LFAS]) depended on their behavioral state (feeding or non‐feeding), and this differed across species. Of the three species included in this analysis (sperm whale [Physeter macrocephalus], killer whale [Orcinus orca] and long‐finned pilot whale [Globicephala melas]), killer whales were consistently the most likely to exhibit behavioral responses to naval sonar exposure. We conclude that recurrent event survival analysis provides an effective framework for fitting dose‐response severity functions to data from behavioral response studies. It can provide outputs that can help government and industry to evaluate the potential impacts of anthropogenic sound production in the ocean.

Principal interactions analysis for repeated measures data: application to gene-gene and gene-environment interactions.

Many existing cohorts with longitudinal data on environmental exposures, occupational history, lifestyle/ behavioral characteristics, and health outcomes have collected genetic data in recent years. In this paper, we consider the problem of modeling gene-gene and gene-environment interactions with repeated measures data on a quantitative trait. We review possibilities of using classical models proposed by Tukey (1949) and Mandel (1961) using the cell means of a two-way classification array for such data. Although these models are effective for detecting interactions in the presence of main effects, they fail miserably if the interaction structure is misspecified. We explore a more robust class of interaction models that are based on a singular value decomposition of the cell-means residual matrix after fitting the additive main effect terms. This class of additive main effects and multiplicative interaction models (Gollob, 1968) provide useful summaries for subject-specific and time-varying effects as represented in terms of their contribution to the leading eigenvalues of the interaction matrix. It also makes the interaction structure more amenable to geometric representation. We call this analysis 'principal interactions analysis'. While the paper primarily focuses on a cell-mean-based analysis of repeated measures outcome, we also introduce resampling-based methods that appropriately recognize the unbalanced and longitudinal nature of the data instead of reducing the response to cell means. We illustrate the proposed methods by using data from the Normative Aging Study, a longitudinal cohort study of Boston area veterans since 1963. We carry out simulation studies under an array of classical interaction models and common epistasis models to illustrate the properties of the principal interactions analysis procedure in comparison with the classical alternatives.

Abstract P328: Genetic Variants Involved in Postprandial Triglyceride Metabolism are Modified by Fenofibrate Treatment in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) Study

Genetic variants associated with fasting plasma triglycerides (TG) have been reported in the literature. Less is known about genetic variants influencing TG response to dietary factors, specifically a fat challenge (postprandial lipemia, PPL). Additionally, little is known about genetic variants associated with response to pharmacologic agents, such as fenofibrate (FFB), which are used to reduce plasma levels of TG. Preliminary genome-wide association (GWA) analyses on three interventions: 1) FFB; 2) PPL before FFB; and 3) PPL after FFB, implicated different genetic variants associated with the TG response. Therefore, we hypothesized that FFB treatment modifies gene effects on TG response to a dietary postprandial fat challenge. We analyzed participants (N=693) from the GOLDN study who ingested a standardized high-fat meal containing 83% fat and 700 calories/m2 both before and after 3 weeks of daily FFB treatment, thereby having two postprandial plasma TG assessments. Plasma TG was measured at baseline, 3.5 hrs, and 6 hrs after each high-fat meal. The area under the curve (AUC) describing the change in plasma TG concentration over the PPL period was calculated using the trapezoid method. Standardized TG AUC residuals were obtained by using a growth curve method and a stepwise regression approach, retaining covariate terms (age, age2, age3, sex, field center, baseline TG, and principle components (EIGENSTRAT)) that were significant at 5% level. A GWA scan of ∼2.5 million typed or imputed single nucleotide polymorphisms (SNPs) was undertaken to identify gene by FFB treatment interaction effects on the TG AUC PPL response using a repeated measures mixed model with a random effect to adjust for family relatedness. The GWA model included a SNP effect, FFB effect (before or after treatment), and an interaction term (SNP*FFB). For TG AUC residuals, we found GWA significant associations with 8 variants in LDLRAD3 (11p13) for the SNP*FFB term (p&lt;5E-08), and the accompanying main effect terms had suggestive (p&lt;1E-05) associations. These 8 variants are in one linkage disequilibrium block, and indicate that FFB interacts with these variants to decrease their independent effects on TG AUC. In analyses using only the SNP, these 8 variants had p-values &lt;0.005 for TG response to PPL both before and after FFB. SNPs in this group associate with expression of CD44, a molecule which binds osteopontin which is an activator of human adipose tissue macrophages and adipocyte function. This analysis highlights a new gene implicated in TG metabolism whose effect on dietary TG responses to fat ingestion is modified by FFB, possibly by acting through CD44. Further investigation into this gene region is needed in order to enhance our understanding of the underlying mechanistic processes involved in TG metabolism during the postprandial state and the effect of FFB treatment.

Mapping the Functional Assessment of Cancer Therapy-General or -Colorectal to SF-6D in Chinese Patients with Colorectal Neoplasm

ObjectivesTo map Functional Assessment of Cancer Therapy-General (FACT-G) and Functional Assessment of Cancer Therapy-Colorectal (FACT-C) subscale scores onto six-dimensional health state short form (derived from short form 36 health survey) (SF-6D) preference-based values in patients with colorectal neoplasm, with and without adjustment for clinical and demographic characteristics. These results can then be applied to studies that have used FACT-G or FACT-C to predict SF-6D utility values to inform economic evaluation. MethodsOrdinary least square regressions were estimated mapping FACT-G and FACT-C onto SF-6D by using cross-sectional data of 537 Chinese subjects with different stages of colorectal neoplasm. Mapping functions for SF-6D preference-based values were developed separately for FACT-G and FACT-C in four sequential models for addition of variables: 1) main-effect terms, 2) squared terms, 3) interaction terms, and 4) clinical and demographic variables. Predictive performance in each model was assessed by the R2, adjusted R2, predicted R2, information criteria (Akaike information criteria and Bayesian information criteria), the root mean square error, the mean absolute error, and the proportions of absolute error within the threshold of 0.05 and 0.10. ResultsModels including FACT variables and clinical and demographic variables had the best predictive performance measured by using R2 (FACT-G: 59.98%; FACT-C: 60.43%), root mean square error (FACT-G: 0.086; FACT-C: 0.084), and mean absolute error (FACT-G: 0.065; FACT-C: 0.065). The FACT-C–based mapping function had better predictive ability than did the FACT-G–based mapping function. ConclusionsModels mapping FACT-G and FACT-C onto SF-6D reached an acceptable degree of precision. Mapping from the condition-specific measure (FACT-C) had better performance than did mapping from the general cancer measure (FACT-G). These mapping functions can be applied to FACT-G or FACT-C data sets to estimate SF-6D utility values for economic evaluation of medical interventions for patients with colorectal neoplasm. Further research assessing model performance in independent data sets and non-Chinese populations are encouraged.

Statistical Modeling and Evaluation of Parallel Spacesharing Job Scheduling Algorithms for PCcluster using Design of Experiments 'DOE'

space-sharing job scheduling algorithms play an indispensible role in efficient allocation of processors of PC-cluster to the competing jobs to achieve one of the performance objective(s) viz. minimized mean response time (MRT), minimized average bounded slowdown or maximized throughput. Traditional performance modeling and evaluation studies of parallel space- sharing job scheduling algorithms are incompetent of predicting the combined or interaction effect on the response resulting due to simultaneous variation of two process variables. Present work is undertaken to predict and quantize the influence of main and interaction effects of the input scheduling process variables on the output MRT values using statistical approach of design of experiments (DOE). DOE based Response surface methodology (RSM) oriented experimental design is chosen to evaluate MRT values for two scheduling algorithms namely First Come First Serve (FCFS) and Fit Processors First Served (FPFS). Two empirical interaction models are suggested for both scheduling algorithms that predict MRT on the basis of multiple regression equations involving main and interaction effect terms of scheduling process variables. High value of adjusted coefficient of determination R 2 and insignificant lack of fit represent the goodness of fit of both the models to accurately predict the MRT values. Both the empirical interaction models are validated against additional experimental results. The comparative performance evaluation study on the basis of MRT reveals that the FPFS algorithm tends to outweigh the traditional FCFS policy.

Pharmacodynamic (PD) assessment of blood pressure (BP) in a randomized dose-ranging trial of sorafenib (S).

3016 Background: Hypertension may be a PD marker for efficacy of VEGF signaling pathway (VSP) inhibitors. The effects of S doses >800 mg/d on BP are not well characterized. To determine precisely the BP response to escalated doses of S, advanced solid tumor patients (pts; ECOG PS < 2 and screening BP < 140/90 mmHg on no antihypertensives) underwent serial 12-hour ambulatory BP measurement sessions (ABP) on different doses of S. Methods: The primary objective was to detect an increase in diastolic BP (DBP) proportional to the increased dose (based on prior data, assumed mean DBP increase for 400 mg BID = 6.0; on increased dose = 9.0 mmHg). ABP were conducted pre/post 7 d of S 400 mg BID. All pts then received no drug for 7 d, followed by another ABP. Pts with no > grade 2 toxicities during the first 2 wks were then randomized to receive escalated dose S at 400mg TID or 600mg BID. All pts repeated ABP after 7 d of additional S. Readings were collected every 10 min during daytime hrs (minimum # readings for evaluable session = 50). Results: 54 of a planned 58 pts were evaluable for data analysis by January 2011. Mean DBP elevation from baseline to Day 7 was 8.0 (SD= 6.5; 95% CI 6.3-9.8) mmHg. The variance in the change in DBP during the washout phase was unexpected, with 32/54 pts having DBP return to baseline (BL); 15/54 had DBP remain elevated and 7/54 had DBP decline below BL. After the 7 d washout, 18 were randomized to 400 mg TID, 19 to 600 mg BID, and 17 received 400 mg BID again. To detect the dose escalation effects on ABP, Day 22 DBP was fit to a regression model with main effect terms for Day 7 DBP and Day 14 DBP and interaction terms for BL DBP, age, sex, race (AA vs. other), and BSA. The final model (R2= 0.73; p < 0.00001) included terms for BL, Day 7, and Day 14 DBP. Compared to 400 mg BID, mean DBP with 400 mg TID was 4.7 mmHg greater (p=0.15, 95% CI -1.7, 11). Mean DBP for the 600 mg BID arm was 2.6 mmHg greater (p=0.41, 95% CI -3.7, 8.8). The difference between the 2 dose escalation arms was not significant (p=0.25). Conclusions: Escalating S dose in a pt population did not uniformly lead to further DBP elevations. To enhance efficacy of S, and perhaps other VSP inhibitors, will likely require a more complex PD-based scheme than dose-to-hypertension.

Specification Issues in Assessing the Moderating Role of Issue Importance: A Comment on Grynaviski and Corrigan (2006)

The empirical study of spatial issue voting has experienced a resurgence in recent years due to advances in data collection and research design. Grynaviski and Corrigan make several important contributions to this literature. In this note, we comment on one of Grynaviski and Corrigan's recommendations—to not include a main effect for issue importance when estimating models assessing the interactive relationship between importance and policy proximity. According to the authors, including the main importance term is incorrect because it is not necessary in representing a scale-invariant functional form under some assumptions and is insufficient under others. In deriving their reduced-form expression, the authors produce a model that is unintuitive and inappropriate for most data. Moreover, the restrictions Grynaviski and Corrigan impose on their model can produce perverse empirical predictions. We show that a model including main effect terms for importance is indeed scale invariant and that inclusion of the main importance term is necessary for scale invariance with respect to partial utility functions.

Identification of Patients at Risk for Postoperative Respiratory Complications Using a Preoperative Obstructive Sleep Apnea Screening Tool and Postanesthesia Care Assessment

Patients with obstructive sleep apnea are at risk for perioperative morbidity. The authors used a screening prediction model for obstructive sleep apnea to generate a sleep apnea clinical score (SACS) that identified patients at high or low risk for obstructive sleep apnea. This was combined with postanesthesia care unit (PACU) monitoring with the aim of identifying patients at high risk of postoperative oxygen desaturation and respiratory complications. In this prospective cohort study, surgical patients with a hospital stay longer than 48 h who consented were enrolled. The SACS (high or low risk) was calculated; all patients were monitored in the PACU for recurrent episodes of bradypnea, apnea, desaturations, and pain-sedation mismatch. All patients underwent pulse oximetry postoperatively; complications were documented. Chi-square, two-sample t test, and logistic regression were used for analysis. The oxygen desaturation index (number of desaturations per hour) was calculated. Oxygen desaturation index and incidence of postoperative cardiorespiratory complications were primary endpoints. Six hundred ninety-three patients were enrolled. From multivariable logistic regression analysis, the likelihood of a postoperative oxygen desaturation index greater than 10 was increased with a high SACS (odds ratio = 1.9, P < 0.001) and recurrent PACU events (odds ratio = 1.5, P = 0.036). Postoperative respiratory events were also associated with a high SACS (odds ratio = 3.5, P < 0.001) and recurrent PACU events (odds ratio = 21.0, P < 0.001). Combination of an obstructive sleep apnea screening tool preoperatively (SACS) and recurrent PACU respiratory events was associated with a higher oxygen desaturation index and postoperative respiratory complications. A two-phase process to identify patients at higher risk for perioperative respiratory desaturations and complications may be useful to stratify and manage surgical patients postoperatively.

Formulation and in vitro Evaluation of Alfuzosin Extended Release Tablets Using Directly Compressible Eudragit.

The aim of the present study was the determination of formulation factors and the in vitro evaluation of an extended release dosage form of a freely soluble weakly basic drug (alfuzosin hydrochloride). Binary mixer of one hydrophilic polymer (hydroxypropylmethylcellulose) and one directly compressible Eudragit (RS PO) was used in tablets prepared by direct compression. The amounts of both polymers were taken as independent variables for the 32 Factorial design. The percent drug releases at 1, 6, 12 and 20 h were selected as responses. The main effect and interaction terms were quantitatively evaluated using mathematical model. Dissolution data were fitted to zero order, first order, and Higuchi's release kinetics to evaluate kinetic data. Both the diffusion and erosion mechanisms were responsible for drug release as shown by the power law. The release of Alfuzosin was prolonged for 20 h by binary mixer indicating the usefulness of the formulations for once daily dosage forms.

Politics as a Moderator of the Accountability—Job Satisfaction Relationship: Evidence Across Three Studies

The current study examined the interactive relationship between felt accountability and organizational politics perceptions on job satisfaction in three samples, which included employees in a wide array of work settings. We hypothesized that job satisfaction would decline (increase) as felt accountability became more intense for those perceiving heightened (limited) levels of politics. After controlling for demographic factors (e.g., age, gender, and organizational tenure), affectivity (e.g., negative and positive), and nonlinear main effect terms (e.g., felt accountability2 and politics perceptions2), results supported the study's hypothesized relationship. Namely, findings indicated that accountability predicted unfavorable levels of job satisfaction when coupled with heightened politics perceptions. Implications of results for theory and practice, strengths and limitations, and directions for future research are provided.