Effect Of Various Covariates Research Articles

Content adaptive JND profile by leveraging HVS inspired channel modeling and perception oriented energy allocation optimization

The existing just noticeable difference (JND) models consider the effects of various covariates, however, they rarely account for the fusion relationship between the covariates, i.e., they lack a holistic understanding of the mechanisms of visual perception and disregarding the significant impact of energy consumption on visual perception. In fact, visual perception is no exception to the rule that nerve activities and energy supply are inextricably linked. Based on this insight, this paper proposes a novel JND estimation model employing content-adaptive energy allocation. Primarily, the information theory is applied to the visual perception system by conceptualizing human visual system (HVS) as an information communication framework. Then, leveraging the relationship between energy consumption and information perception, this paper quantitatively measures the HVS energy consumption as uniform metric to describe the complicated and heterogeneous HVS perception process, and then construct JND model by fusing low-level and Semantic-level features. Numerous simulation results verify that the proposed JND model is significantly competitive with other frontier models and highly compatible with HVS.

Stocking and supplying naloxone: Findings from a representative sample of community pharmacies in Victoria, Australia.

Naloxone is an opioid receptor antagonist, which can rapidly reverse the effects of an opioid overdose. Community pharmacists may experience several barriers to stocking and supplying naloxone including a lack of confidence or knowledge and time constraints. The current study aimed to examine the extent to which Victorian community pharmacies stock and supply naloxone and determine specific characteristics associated with stocking naloxone. A representative sample of community pharmacists (n = 558) in Victoria, Australia, were contacted between October and November 2020 and invited to participate in an online survey. Data related to pharmacy- and pharmacist-related characteristics, including stocking and frequency of supplying naloxone in the past year. Multivariate logistic regression analysis was performed to examine the effect of various covariates on stocking naloxone. The sample comprised 265 pharmacists (response rate 47%). Most pharmacies were located in Melbourne (the capital city of Victoria, 59.6%) and were part of a pharmacy chain (61.5%). In total, 100 (38%) pharmacies stocked naloxone, a third of whom did not supply it in the past year. Pharmacies that provided opioid agonist treatment had 2.4 times higher odds of stocking naloxone (95% confidence interval 1.425-4.136; p = 0.001). Less than half of Victorian community pharmacies stock naloxone, with even fewer actually supplying it in the past year. Future efforts are needed to increase the number of pharmacies that stock naloxone and the frequency in which it is supplied, while also addressing possible barriers to stocking and supplying naloxone among community pharmacists.

A clinical score to predict recovery in end-stage kidney disease due to acute kidney injury.

Acute kidney injury (AKI) is a major contributor to end-stage kidney disease (ESKD). About one-third of patients with ESKD due to AKI recover kidney function. However, the inability to accurately predict recovery leads to improper triage of clinical monitoring and impacts the quality of care in ESKD. Using data from the United States Renal Data System from 2005 to 2014 (n=22922), we developed a clinical score to predict kidney recovery within 90 days and within 12 months after dialysis initiation in patients with ESKD due to AKI. Multivariable logistic regressions were used to examine the effect of various covariates on the primary outcome of kidney recovery to develop the scoring system. The resulting logistic parameter estimates were transformed into integer point totals by doubling and rounding the estimates. Internal validation was performed. Twenty-four percent and 34% of patients with ESKD due to AKI recovered kidney function within 90 days and 12 months, respectively. Factors contributing to points in the two scoring systems were similar but not identical, and included age, race/ethnicity, body mass index, congestive heart failure, cancer, amputation, functional status, hemoglobin and prior nephrology care. Three score categories of increasing recovery were formed: low score (0-6), medium score (7-9) and high score (10-12), which exhibited 90-day recovery rates of 12%, 26% and 57%. For the 12-month scores, the low, medium and high groups consisted of scores 0-5, 6-8 and 9-11, with 12-month recovery rates of 16%, 33% and 62%, respectively. The internal validation assessment showed no overfitting of the models. A clinical score derived from information available at incident dialysis predicts renal recovery at 90 days and 12 months in patients with presumed ESKD due to AKI. The score can help triage appropriate monitoring to facilitate recovery and begin planning long-term dialysis care for others.

Stereotactic body radiotherapy for Ultra-Central lung Tumors: A systematic review and Meta-Analysis and International Stereotactic Radiosurgery Society practice guidelines

BackgroundStereotactic body radiotherapy (SBRT) is an effective and safe modality for early-stage lung cancer and lung metastases. However, tumors in an ultra-central location pose unique safety considerations. We performed a systematic review and meta-analysis to summarize the current safety and efficacy data and provide practice recommendations on behalf of the International Stereotactic Radiosurgery Society (ISRS). MethodsWe performed a systematic review using PubMed and EMBASE databases of patients with ultra-central lung tumors treated with SBRT. Studies reporting local control (LC) and/or toxicity were included. Studies with <5 treated lesions, non-English language, re-irradiation, nodal tumors, or mixed outcomes in which ultra-central tumors could not be discerned were excluded. Random-effects meta-analysis was performed for studies reporting relevant endpoints. Meta-regression was conducted to determine the effect of various covariates on the primary outcomes. Results602 unique studies were identified of which 27 (one prospective observational, the remainder retrospective) were included, representing 1183 treated targets. All studies defined ultra-central as the planning target volume (PTV) overlapping the proximal bronchial tree (PBT). The most common dose fractionations were 50 Gy/5, 60 Gy/8, and 60 Gy/12 fractions. The pooled 1- and 2-year LC estimates were 92 % and 89 %, respectively. Meta-regression identified biological effective dose (BED10) as a significant predictor of 1-year LC. A total of 109 grade 3–4 toxicity events, with a pooled incidence of 6 %, were reported, most commonly pneumonitis. There were 73 treatment related deaths, with a pooled incidence of 4 %, with the most common being hemoptysis. Anticoagulation, interstitial lung disease, endobronchial tumor, and concomitant targeted therapies were observed risk factors for fatal toxicity events. ConclusionSBRT for ultra-central lung tumors results in acceptable rates of local control, albeit with risks of severe toxicity. Caution should be taken for appropriate patient selection, consideration of concomitant therapies, and radiotherapy plan design.

Chronic non-communicable disease burden among reproductive-age women in India: evidence from recent demographic and health survey

BackgroundChronic disease burden among women leads to various detrimental consequences, impacting women’s health throughout their life course and off-springs. The present study explores the chronic disease profile among reproductive-aged women and analyzes the effects of various covariates on multimorbidity among reproductive-aged women in India. Here, multimorbidity is defined as an individual suffering from two or more chronic conditions.MethodsThe present study employed the most recent National Family Health Survey round, 2019–2021. The study utilized information on 695,707 non-pregnant women aged 15–49 years. The study used descriptive, bivariate, and multivariable ordered logistic regression analysis to explore the burden of chronic non-communicable diseases and multimorbidity.ResultsThe mean age of women with single chronic condition-related morbidity is 30 years, whereas it was 35 years for those with multimorbidity. Approximately 28% of urban women suffered from multimorbidity. Further, significant factors that affect multimorbidity include age, educational attainment, working status, marital status, parity, menopause, religion, region, wealth index, tobacco use, alcohol consumption, and dietary patterns.ConclusionsThe present study hints that women in the reproductive age group are at very high risk of developing multimorbidity in India. Most of the programs and policies are focused on the elderly population in terms of awareness and facilitating them with better health services. However, right now, one should also prioritize the emerging chronic condition related to chronic conditions other than hypertension, diabetes, and cancer among the study population, which is escalating as soon as women reach 30 years of age.

The relationship between brain glucose metabolism and insulin resistance in subjects with normal cognition - a study based on 18F-FDG PET.

Insulin resistance can increase the risk of cognitive dysfunction and dementia. Our purpose is to use 18F-FDG PET imaging to explore the effect of insulin resistance on brain glucose metabolism in cognitively normal subjects. A total of 189 cognitively normal subjects who underwent PET examinations were enrolled. The homeostasis model assessment of insulin resistance (HOMA-IR) was used to evaluate the presence of insulin resistance. Multivariate linear regression and generalized additive models were used to analyze the association between HOMA-IR and glucose metabolism in the whole brain and evaluate the effects of various covariates. The SPM12 software was used to evaluate the regional effect of insulin resistance on brain glucose metabolism. After being fully adjusted for confounding factors, HOMA-IR showed an approximately linear negative correlation with brain glucose metabolism (β = -0.219, T = -3.331, P = 0.021). Compared with normal subjects, insulin-resistant subjects had reduced glucose metabolism in bilateral middle temporal gyrus, bilateral middle frontal gyrus, right precentral gyrus, right inferior frontal gyrus, right cuneiform lobe and bilateral cerebellar regions. In cognitively normal subjects, systemic insulin resistance has a significant effect on brain glucose metabolism. 18F-FDG brain PET imaging could be helpful for the early diagnosis and treatment of changes in brain glucose metabolism caused by insulin resistance.

Pharmacokinetic modeling of R and S‐Methadone and their metabolites to study the effects of various covariates in post‐operative children

Methadone is a synthetic opioid used as an analgesic and for the treatment of opioid abuse disorder. The analgesic dose in the pediatric population is not well‐defined. The pharmacokinetics (PKs) of methadone is highly variable due to the variability in alpha‐1 acid glycoprotein (AAG) and genotypic differences in drug‐metabolizing enzymes. Additionally, the R and S enantiomers of methadone have unique PK and pharmacodynamic properties. This study aims to describe the PKs of R and S methadone and its metabolite 2‐ethylidene‐1,5‐dimethyl‐3,3‐diphenylpyrrolidine (EDDP) in pediatric surgical patients and to identify sources of inter‐ and intra‐individual variability. Children aged 8–17.9 years undergoing orthopedic surgeries received intravenous methadone 0.1 mg/kg intra‐operatively followed by oral methadone 0.1 mg/kg postoperatively every 12 h. Pharmacokinetics of R and S methadone and EDDP were determined using liquid chromatography tandem mass spectrometry assays and the data were modeled using nonlinear mixed‐effects modeling in NONMEM. R and S methadone PKs were well‐described by two‐compartment disposition models with first‐order absorption and elimination. EDDP metabolites were described by one compartment disposition models with first order elimination. Clearance of both R and S methadone were allometrically scaled by bodyweight. CYP2B6 phenotype was a determinant of the clearance of both the enantiomers in an additive gene model. The intronic CYP3A4 single‐nucleotide polymorphism (SNP) rs2246709 was associated with decreased clearance of R and S methadone. Concentrations of AAG and the SNP of AAG rs17650 independently increased the volume of distribution of both the enantiomers. The knowledge of these important covariates will aid in the optimal dosing of methadone in children.

Population Pharmacokinetic Analysis of Cefaclor in Healthy Korean Subjects.

The aims of this study were: (1) to perform population pharmacokinetic analysis of cefaclor in healthy Korean subjects, and (2) to investigate possible effects of various covariates on pharmacokinetic parameters of cefaclor. Although cefaclor belongs to the cephalosporin family antibiotic that has been used in various indications, there have been very few population studies on factors affecting its pharmacokinetics. Therefore, this study is very important in that effective therapy could be possible through a population pharmacokinetic study that explores effective covariates related to cefaclor pharmacokinetic diversity between individuals. Pharmacokinetic results of 48 subjects with physical and biochemical parameters were used for the population pharmacokinetic analysis of cefaclor. A one-compartment with lag-time and first-order absorption/elimination was constructed as a base model and extended to include covariates that could influence between-subject variability. Creatinine clearance and body weight significantly influenced systemic clearance and distribution volume of cefaclor. Cefaclor’s final population pharmacokinetic model was validated and some of the population’s pharmacokinetic diversity could be explained. Herein, we first describe the establishment of a population pharmacokinetic model of cefaclor for healthy Koreans that might be useful for customizing cefaclor or exploring additional covariates in patients.

Semiparametric analysis of clustered interval-censored survival data using soft Bayesian additive regression trees (SBART).

Popular parametric and semiparametric hazards regression models for clustered survival data are inappropriate and inadequate when the unknown effects of different covariates and clustering are complex. This calls for a flexible modeling framework to yield efficient survival prediction. Moreover, for some survival studies involving time to occurrence of some asymptomatic events, survival times are typically interval censored between consecutive clinical inspections. In this article, we propose a robust semiparametric model for clustered interval-censored survival data under a paradigm of Bayesian ensemble learning, called soft Bayesian additive regression trees or SBART (Linero and Yang, 2018), which combines multiple sparse (soft) decision trees to attain excellent predictive accuracy. We develop a novel semiparametric hazards regression model by modeling the hazard function as a product of a parametric baseline hazard function and a nonparametric component that uses SBART to incorporate clustering, unknown functional forms of the main effects, and interaction effects of various covariates. In addition to being applicable for left-censored, right-censored, and interval-censored survival data, our methodology is implemented using a data augmentation scheme which allows for existing Bayesian backfitting algorithms to be used. We illustrate the practical implementation and advantages of our method via simulation studies and an analysis of a prostate cancer surgery study where dependence on the experience and skill level of the physicians leads to clustering of survival times. We conclude by discussing our method's applicability in studies involving high-dimensional data with complex underlyingassociations.

Population Pharmacokinetics of Vixotrigine in Healthy Volunteers and Subjects with Trigeminal Neuralgia, Painful Lumbosacral Radiculopathy and Erythromelalgia.

Vixotrigine is a voltage and use dependent sodium channel blocker currently under development for treatment of various neuropathic pain indications. The objective of this work was to develop a population pharmacokinetic model and assess effects of various covariates on pharmacokinetic parameters of vixotrigine. Plasma concentration-time data from 12 Phase 1 or 2 studies were included in the analyses. The data were obtained following administration of single or multiple doses of vixotrigine in healthy volunteers and patients. One- and two-compartment pharmacokinetic models were evaluated as base structural pharmacokinetic models. The inclusion of selected covariates was assessed using a stepwise backward elimination approach (α = 0.001) once the base/full model was developed. The predictive ability of the model was evaluated using a visual predictive check (VPC). The final model was used to evaluate effect of covariates on exposure of vixotrigine. A total of 10,263 pharmacokinetic samples collected from 465 subjects were included in the analyses. The pharmacokinetics of vixotrigine was adequately described by a two-compartment model with two transit absorption compartments and first-order elimination. Predictability of the model was also established by VPC. The final model included covariates of age, weight and carbamazepine co-administration on clearance, weight on central volume of distribution, food on absorption rate constant and formulation and Japanese race on bioavailability. None of the covariates identified had a clinically relevant effect, as impact on area under the plasmaconcentration-timecurve (AUC) and maximum plasma concentration (Cmax) was within ± 25%. The model characterizes the pharmacokinetics of vixotrigine well, and the exposure of vixotrigine was comparable between healthy subjects and patients. None of the covariates evaluated have a clinically relevant impact on the pharmacokinetics of vixotrigine.

Relationship of choroidal thickness with pulsatile hemodynamics in essential hypertensive patients.

Controversy exists about the association of choroidal thickness (CTh) with blood pressure (BP) values. There is some evidence suggesting that central hemodynamics changes are associated with microvascular disease. Our study was aimed to assess the relationships between CTh and clinic and 24‐h BP and between CTh and estimated 24‐h aortic pulse pressure (aPP), 24‐h aortic systolic BP (aSBP), and 24‐h aortic augmentation index (aAIx) in a group of hypertensive patients. We enrolled 158 hypertensive subjects (mean age 48 ± 13 years) all of which underwent evaluation of the choroidal district by Swept‐Source optical coherence tomography (SS‐OCT) and 24‐h BP monitoring, in order to measure peripheral BP and to estimate central hemodynamic parameters. Inverse significant correlations of clinic PP, 24‐h aPP, 24‐h aSBP, and 24‐h aAIx with thicknesses of central ring, inner ring, and outer ring of the choroid and its overall average were found. The strongest of these correlations was that relating 24‐h aPP with overall average choroidal thickness (r = −.531; P < .001). When we divided the study population in subjects with 24‐h aPP above and below the median value (35 mm Hg), CTh were thinner in subjects with higher values of 24‐aPP as compared to those with lower ones, even after adjustment for age, and other potential confounders. The relationships of CTh with 24‐h aPP remained significant also taking into account the effects of various covariates in linear multiple regression analyses. Our findings support the concept of a cross‐talk between macro‐ and microcirculation.

Population Pharmacokinetic Analysis of Tiropramide in Healthy Korean Subjects.

The purpose of this study was to perform population pharmacokinetic (PPK) analysis of tiropramide in healthy Korean subjects, as well as to investigate the possible effects of various covariates on pharmacokinetic (PK) parameters of tiropramide. Although tiropramide is commonly used in digestive system-related diseases as an antispasmodic, PPK reporting and factors affecting PKs are not clearly reported. Thus, this study for healthy subjects is very significant because it could find new covariates in patients that had not been reported before or predict PPK for patients in the clinic by establishing PPK in healthy adults. By using Phoenix NLME, PK, demographic, and genetic data (collected to explain PK diversity of tiropramide in population) analyses were performed. As a basic model, a one-compartment with first-order absorption and lag-time was established and extended to include covariates that influenced the inter-subject variability. The total protein significantly influenced the distribution volume and systemic clearance of tiropramide, but genetic factors such as ABCB1 (1236C>T, 2677G>T/A, and 3435C>T), CYP2D6 (*1 and *10), OCT2 (808G>T), and PEPT1 (1287G>C) genes did not show any significant association with PK parameters of tiropramide. The final PPK model of tiropramide was validated, and suggested that some of the PK diversity in the population could be explained. Herein, we first describe the establishment of the PPK model of tiropramide for healthy Korean subjects, which may be useful as a dosing algorithm for the diseased population.

Screening and Treatment for Osteoporosis After Stroke

Background and Purpose- Stroke is a risk factor for subsequent osteoporosis and fractures. We sought to understand current rates and predictors of screening and treatment for bone loss after stroke. Methods- Using the Ontario Stroke Registry from July 1, 2003 to March 31, 2013, we identified patients ≥65 years who were seen in the emergency department or hospitalized with stroke at 11 regional stroke centers in Ontario, Canada and discharged alive. We calculated the cumulative incidence of (1) screening with bone mineral density testing and (2) treatment with medications for fracture prevention, within 1 year after the index stroke, accounting for the competing risk of death. We then used cause-specific hazard models to estimate the effect of various covariates on the cause-specific hazard of bone mineral density testing and osteoporosis pharmacotherapy. Results- In the sample of 16 581 patients, 5.1% overall and 2.9% of those without prior testing underwent screening bone mineral density testing, and 15.5% overall and 3.2% of those not previously on treatment were prescribed medications for fracture prevention within 1 year after stroke. Results were similar in all subgroups of patients. Female sex, prestroke osteoporosis, and poststroke falls and fractures were associated with increased rates of osteoporosis pharmacotherapy. Conclusions- Patients with recent stroke are infrequently screened and treated for osteoporosis, which may increase the risk of fractures. Future work should focus on identifying and treating patients who are at increased risk of fractures after stroke.

Estimating snow leopard density using fecal DNA in a large landscape in north-central Nepal

Although abundance estimates have a strong bearing on the conservation status of a species, less than 2% of the global snow leopard distribution range has been sampled systematically, mostly in small survey areas. In order to estimate snow leopard density across a large landscape, we collected 347 putative snow leopard scats from 246 transects (490 km) in twenty-six 5 × 5km sized sampling grid cells within 4393 km2 in Annapurna-Manaslu, Nepal. From 182 confirmed snow leopard scats, 81 were identified as belonging to 34 individuals; the remaining were discarded for their low (<0.625) quality index. Using maximum likelihood based spatial capture recapture analysis, we developed candidate model sets to test effects of various covariates on density and detection of scats on transects. The best models described the variation in density as a quadratic function of elevation and detection as a linear function of topography. The average density estimate of snow leopards for the area of interest within Nepal was 0.95 (SE 0.19) animals per 100 km2 (0.66–1.41 95% CL) with predicted densities varying between 0.1 and 1.9 in different parts, thus highlighting the heterogeneity in densities as a function of habitat types. Our density estimate was low compared to previous estimates from smaller study areas. Probably, estimates from some of these areas were inflated due to locally high abundances in overlap zones (hotspots) of neighboring individuals, whose territories probably range far beyond study area borders. Our results highlight the need for a large-scale approach in snow leopard monitoring, and we recommend that methodological problems related to spatial scale are taken into account in future snow leopard research.

Substitution Urethroplasty with Closure Versus Nonclosure of the Buccal Mucosa Graft Harvest Site: A Randomized Controlled Trial with a Detailed Analysis of Oral Pain and Morbidity

BackgroundOptimal surgical management of the buccal mucosa harvest site in patients with urethral stricture disease during buccal mucosa graft urethroplasty (BMGU) remains controversial. ObjectiveTo analyze in detail intensity and quality of pain as well as oral morbidity following closure (C) versus nonclosure (NC) of the donor site. Design, setting, and participantsRandomized controlled trial on 135 patients treated with BMGU between October 15, 2014 and December 18, 2015. InterventionFollowing computer-based randomization, 63 and 72 patients, respectively, received C and NC of the donor site at the inner cheek. Preoperatively, on days 1, 5, and 21 as well as at 3 and 6 mo postoperatively, patients completed standardized questionnaires, including validated questions on intensity and quality of pain as well as oral morbidity. Outcome measurements and statistical analysisThe coprimary end points were intensity and quality of oral pain. Secondary end points included oral morbidity and intensity of pain of the perineogenital region. Generalized linear mixed models evaluated the effect of various covariates on intensity and quality of oral pain, oral morbidity, as well as intensity of pain of the perineogenital region. Results and limitationsThere was noninferiority for NC versus C in intensity and affective quality of oral pain at every time point following BMGU. Oral morbidity and complications included pain, bleeding, swelling, numbness, alteration of salivation and taste, as well as impairment of mouth opening, smiling, whistling, diet, and speech. Time from BMGU had significant effects on intensity (p<0.001) and quality of oral pain (sensory pain: p<0.001, affective pain: p<0.001, total pain: p<0.001). Length of buccal mucosa graft had significant effects on intensity (p=0.001) and quality of oral pain (sensory pain: p=0.020, total pain: p=0.042). ConclusionsNC is noninferior to C of the donor site in intensity and quality of oral pain, and offers a treatment alternative. Time from BMGU and length of the buccal mucosa graft have effects on oral morbidity and complications. Patient summaryWe investigated pain, morbidity, and complications following closure (C) versus nonclosure (NC) of the buccal mucosa harvest site in patients undergoing buccal mucosa graft urethroplasty (BMGU). We found that NC is not worse than C regarding oral pain. In addition, time from BMGU and length of the buccal mucosa graft have effects on oral morbidity and complications.

Do we provide affordable, accessible and administrable health care? An assessment of SES differential in out of pocket expenditure on delivery care in India

BackgroundReproductive and Child Health (RCH) financing is a key area of focus which can lead towards an overall empowerment of women through financial inclusion. The major objectives of this paper are: first; to examine the socio-economic differentials in Out of Pocket Expenditure (OOPE) on delivery care, second; to look into the role of insurance coverage, third; to analyse various sources of financing, and fourth; to measure the adjusted effect of various covariates on the level of OOPE. MethodsData were extracted from the National Sample Survey Organisations (NSSO), 71st round “Key indicators of social consumption in India, Health” conducted by the GoI during January to June 2014. Multivariate Generalised Linear Regression Model (GLRM) has been used to analyse the various covariates of OOPE on maternity care. FindingsMultivariate analysis has demonstrated a significant association between socioeconomic status of women and the level of OOPE on delivery care. Level of education, urban residence, higher caste and social group affiliation, strong economic conditions, and use of private facilities for the child birth among the mothers were a significant predictor of the expenditure on maternity care. ConclusionDespite various efforts by the central and state governments to reduce financial burden, still a large number of households are paying a significant amount from their own pockets. There is an immediate need to re-look in the aspects of insurance coverage and high level of OOPE in delivery care.

Modeling the effectiveness of nebulized terbutaline for decompensated chronic obstructive pulmonary disease patients in the emergency department.

Short-acting β2-agonists (SABA) are widely used in the emergency department (ED) to treat patients with decompensated chronic obstructive pulmonary disease (COPD). We sought to model the effectiveness of nebulized SABA (terbutaline) on clinically relevant parameters associated with a reduction in work of breathing or respiratory muscle fatigue in decompensated COPD patients admitted to the ED.Forty consecutive decompensated COPD patients (having received at least one dose of nebulized terbutaline during their stay in the ED) were included in an observational cohort study. The terbutaline dose received at time t was expressed as cumulative dose and as a rate (mg/day). The associations between the terbutaline dose and time-dependent outcome parameters (respiratory rate, heart rate, arterial blood gases, and, as a marker of terbutaline's systemic effect, serum potassium) were analyzed using a nonlinear, mixed-effects model. The effect of various covariates influencing terbutaline's effectiveness (baseline characteristics and concomitant treatments) was assessed on the model.Among the investigated patients, a total of 377 time-dependent observations were available for analysis. Neither the cumulative dose nor the dose rate at time t significantly influenced the arterial blood gas parameters or heart rate. The cumulative dose of terbutaline was associated with a lower serum potassium level (P < 0.001) and, less significantly, a lower respiratory frequency (P = 0.036). In a tertile analysis, the need for post-ED hospitalization was not associated with the cumulative dose or dose rate of terbutaline.Overall, the results of our modeling study strongly suggest that terbutaline dose did not influence time-dependent outcomes other than serum potassium, and thus call into question the systematic administration of inhaled SABA to patients admitted to the ED for decompensated COPD.

An accelerated failure time model for investigating pedestrian crossing behavior and waiting times at signalized intersections

The waiting process is crucial to pedestrians in the street-crossing behavior. Once pedestrians terminate their waiting behavior during the red light period, they would cross against the red light and put themselves in danger. A joint hazard-based duration model is developed to investigate the effect of various covariates on pedestrian crossing behavior and to estimate pedestrian waiting times at signalized intersections. A total of 1181 pedestrians approaching the intersections during red light periods were observed in Beijing, China. Pedestrian crossing behaviors are classified into immediate crossing behavior and waiting behavior. The probability and effect of various covariates for pedestrians’ immediate crossing behavior are identified by a logit model. Four accelerated failure time duration models based on the exponential, Weibull, lognormal and log-logistic distributions are proposed to examine the significant risk factors affecting duration times for pedestrians’ waiting behavior. A joint duration model is developed to estimate pedestrian waiting times. Moreover, unobserved heterogeneity is considered in the proposed model. The results indicate that the Weibull AFT model with shared frailty is appropriate for modelling pedestrian waiting durations. Failure to account for heterogeneity would significantly underestimate the effects of covariates on waiting duration times. The proposed model provides a better understanding of pedestrian crossing behavior and more accurate estimation of pedestrian waiting times. It may be applicable in traffic system analysis in developing countries with high flow of mixed traffic.

Application of the varying coefficient model to the behaviour risk factor surveillance data in Italy: a study of changing smoking prevalence among sub-populations.

BackgroundBehaviour risk factor surveillance (BRFS) data can be an important source of information for studying changes in various health outcomes and risk factors. Results obtained from surveillance data analysis are vital for informing health policy interventions, particularly with regards to evolutionary aspects. The objective of this analysis was to recommend a method that can be used for analysing trends in the association among variables from large public health data sets. This was demonstrated by examining the changing effects of various covariates, representing different sub-populations, on smoking status over time.MethodsIn our work, we propose the use of varying coefficient models (VCM) with non-parametric techniques to catch the dynamics of the evolutionary processes under study. This is a useful method, which allows coefficients to vary with time using smooth functions. Italian BRFS data from 2008-2012 was used with a sample size of 185,619 observations. In the application, a time VCM is fit for a smoking status binary outcome variable using the P-spline estimation method. The model includes ten independent variables comprising socio-demographic, health risk and behaviour variables.ResultsThe VCM fit for the data indicates that the coefficients for some of the categories for the age and the alcohol consumption variables varied with time. The main results show that Italians aged 18-29 and 40-49 had higher odds of being smokers compared to those aged 60-69; however, these odds significantly decreased in the period 2008-2012. In addition, those who do not drink had lower odds for being a smoker compared to high risk drinkers and these odds decreased further during the observation period.ConclusionThe application of the VCM to the BRFS data in Italy has shown that this method can be useful in detecting which sub-populations require interventions. Although the results have shown a decrease in the odds of being a smoker for certain age groups and non-drinkers, other sub-populations have not decreased their odds and health inequalities remain. This observation indicates that efforts and interventions are still required to target these non-changing sub-populations in order to modify their smoking behaviour.

Abstract P5-18-24: Population pharmacokinetics of trastuzumab emtansine, a HER2-targeted antibody-drug conjugate, in patients with HER2-positive metastatic breast cancer: clinical implications of the effect of various covariates

Abstract Background: Trastuzumab emtansine (T-DM1) is a HER2-targeted antibody-drug conjugate composed of the humanized monoclonal antibody trastuzumab, the potent cytotoxic agent DM1 (a microtubule inhibitor), and a stable thioether linker. To estimate typical pharmacokinetic (PK) parameter values and interpatient variability, a population PK model for T-DM1 was previously developed from 1 phase 1 (0.3 to 4.8 mg/kg in qw or q3w regimens) and 2 phase 2 (3.6 mg/kg q3w) trials (Gupta, J Clin Pharmacol 2012). The model reported here has been updated with additional data from 2 randomized trials (phase 2 TDM4450g and phase 3 EMILIA, 3.6 mg/kg q3w). Another phase 2 trial (TDM4688g) was used for external validation of the model. The effect of demographic and pathophysiological covariates on the PK of T-DM1 was explored to better understand the clinical factors that might affect exposure and clinical outcome for individual patients. Methods: For the current analysis, 9934 T-DM1 serum concentration-time data points from 671 patients were simultaneously fitted using NONMEM® software. T-DM1 concentration-time data to date are best described using a 2-compartment linear model. All relevant and plausible covariates likely to have an effect on T-DM1 systemic exposure, or likely to have clinical relevance, were explored for possible correlation with the key T-DM1 PK parameters of clearance (CL) and central volume of distribution (Vc). These covariates include those related to demographics, renal and hepatic function, disease status, and treatment history. Results: The estimated CL for T-DM1 is 0.68 L/day, Vc is 3.13 L, and the terminal half-life is 3.94 days. Interindividual variability (IIV) of the base model is 25.6% and 17.5% for CL and Vc, respectively. Patients with greater body weight, sum of longest dimension of target lesions, serum concentration of shed HER2 extracellular domain, and aspartate aminotransferase concentrations, as well as patients with lower serum albumin and baseline trastuzumab concentrations, have statistically faster CL. Patients with greater body weight also have statistically larger Vc. Incorporation of these covariates (P&amp;lt;0.001 by likelihood ratio test) decreased IIV of CL and Vc to 19.1% and 11.7%, respectively. All covariates together explain 44.4% and 55.8% of IIV in CL and Vc, respectively. The model sensitivity analysis suggests that a patient with a statistically significant PK covariate value at the 5th or 95th percentile of the population will have a &amp;lt;20% difference in cumulative exposure (as represented by area under the T-DM1 concentration-time curve) compared with a typical patient with a median covariate value. Conclusions: A relatively small IIV for the estimated T-DM1 PK parameters of CL and Vc was observed. None of the evaluated covariates had a clinically meaningful magnitude of effect on T-DM1 exposure (&amp;lt;20% difference for patients with 5th and 95th percentiles vs patients with median value of covariates) that would justify a further dose adjustment. The body weight–based dose of 3.6 mg/kg q3w without further correction for other factors is considered appropriate in ongoing clinical trials. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P5-18-24.