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At least 397 records · Page 22Linked to original sources

PubMed2005

Development and application of Model of Resource Utilization, Costs, and Outcomes for Stroke (MORUCOS): an Australian economic model for stroke.

OBJECTIVES: To outline the development, structure, data assumptions, and application of an Australian economic model for stroke (Model of Resource Utilization, Costs, and Outcomes for Stroke [MORUCOS]). METHODS: The model has a linked spreadsheet format with four modules to describe the disease burden and treatment pathways, estimate prevalence-based and incidence-based costs, and derive life expectancy and quality of life consequences. The model uses patient-level, community-based, stroke cohort data and macro-level simulations. An interventions module allows options for change to be consistently evaluated by modifying aspects of the other modules. To date, model validation has included sensitivity testing, face validity, and peer review. Further validation of technical and predictive accuracy is needed. The generic pathway model was assessed by comparison with a stroke subtypes (ischemic, hemorrhagic, or undetermined) approach and used to determine the relative cost-effectiveness of four interventions. RESULTS: The generic pathway model produced lower costs compared with a subtypes version (total average first-year costs/case AUD$ 15,117 versus AUD$ 17,786, respectively). Optimal evidence-based uptake of anticoagulation therapy for primary and secondary stroke prevention and intravenous thrombolytic therapy within 3 hours of stroke were more cost-effective than current practice (base year, 1997). CONCLUSIONS: MORUCOS is transparent and flexible in describing Australian stroke care and can effectively be used to systematically evaluate a range of different interventions. Adjusting results to account for stroke subtypes, as they influence cost estimates, could enhance the generic model.

Health Resources↗

PubMed2005

APP23 mice as a model of Alzheimer's disease: an example of a transgenic approach to modeling a CNS disorder.

Animal models are considered essential in research ensuing elucidation of human disease processes and subsequently, testing of potential therapeutic strategies. This is especially true for neurodegenerative disorders, in which the first steps in pathogenesis are often not accessible in human patients. Alzheimer's disease is vastly becoming a major medical and socioeconomic problem in our aging society. Valid animal models for this uniquely human condition should exhibit histopathological, biochemical, cognitive, and behavioral alterations observed in Alzheimer's disease patients. Major progress has been made since the understanding of the genetic basis of Alzheimer's disease and the development and improvement of transgenic mouse models. All present Alzheimer's disease models developed are partial but nevertheless essential in further unraveling the nature and spatial and temporal development of the complex molecular pathology underlying this condition. One of the more recent transgenic attempts to model Alzheimer's disease is the APP23 transgenic mouse. This article describes the development and assessment of this human amyloid precursor protein overexpression model. We summarize histopathological and biochemical, cognitive and behavioral observations made in heterozygous APP23 mice, thereby emphasizing the model's contribution to clarification of neurodegenerative disease mechanisms. In addition, the first therapeutic interventions in the APP23 model are included.

Alzheimer Disease↗

PubMed1996

The cluster-arranged cooperative model: a model that accounts for the kinetics of binding to A1 adenosine receptors.

To explain the equilibrium binding and binding kinetics of ligands to membrane receptors, a number of models have been proposed, none of which is able to adequately describe the experimental findings, in particular the apparent negative cooperativity of ligand binding. In this paper, a new model, the cluster-arranged cooperative model, is presented whose main characteristic is that it explains the existence of negative cooperativity in the binding of ligands to the receptor molecule. The model is based on our findings of agonist binding to A1 adenosine receptors and of ligand-induced clustering of these receptors on the cell surface. The model assumes the existence of two conformational forms of the receptor in an equilibrium which depends on the concentration of the ligand. In this way, negative cooperativity is explained by the transmission of the information between receptor molecules through the structure of the membrane. The model is able to predict the thermodynamic binding and binding kinetics of [3H]-(R)-(phenylisopropyl)adenosine to A1 adenosine receptors in the presence and absence of guanylyl imidodiphosphate. In the presence of the guanine nucleotide analogue, the linear Scatchard plots obtained for [3H]-(R)-(phenylisopropyl)adenosine binding are explained by the disappearance of cooperativity, thus suggesting that G proteins are important for the existence of negative cooperativity in ligand binding. Among other predictions, the model justifies early events in homologous desensitization since high ligand concentrations would lead to the saturation of the receptor in a low-affinity conformation that does not signal. Our model can likely explain the behavior of a number of heptaspanning and tyrosine-kinase receptors exhibiting complex binding kinetics.

Animals↗

PubMedDate not supplied

Evaluation of kinetic models for industrial acetic fermentation: proposal of a new model optimized by genetic algorithms.

The most important kinetic models developed for acetic fermentation were evaluated to study their ability to explain the behavior of the industrial process of acetification. Each model was introduced into a simulation environment capable of replicating the conditions of the industrial plant. In this paper, it is proven that these models are not suitable to predict the evolution of the industrial fermentation by the comparison of the simulation results with an average sequence calculated from the industrial data. Therefore, a new kinetic model for the industrial acetic fermentation was developed. The kinetic parameters of the model were optimized by a specifically designed genetic algorithm. Only the representative sequence of industrial concentrations of acetic acid was required. The main novelty of the algorithm is the four-composed desirability function that works properly as the response to maximize. The new model developed is capable of explaining the behavior of the industrial process. The predictive ability of the model has been compared with that of the other models studied.

Acetic Acid↗

PubMed2003

Three-component competitive adsorption model for flow-through PAC systems. 1. Model development and verification with a PAC/membrane system.

Natural organic matter (NOM) interferes with the adsorption of trace organic compounds on porous adsorbents such as powdered activated carbon (PAC) by pore blockage and direct competition for adsorption sites. The competitive effect of NOM in flow-through systems in which the retention time of the PAC is greater than the hydraulic retention time of the system can be magnified because NOM from the influent water can continue to adsorb on the PAC retained in the system. As a result, the adsorption capacity and the diffusion coefficient of trace compounds can decrease as NOM from the influent water accumulates. In this study, a dynamic three-component adsorption model was developed to quantitatively describe the removal of a trace compound from water in flow-through PAC processes. The system was simplified by using p-dichlorobenzene (p-DCB) to represent the NOM fraction that competes directly with the target trace organic atrazine for adsorption sites and by using poly(styrene sulfonate) (PSS-1.8k) to represent large, pore-blocking NOM. The model was based on the homogeneous surface diffusion assumption with the adsorption capacity of atrazine being gradually adjusted using a simplified version of the ideal adsorbed solution theory model developed in this study. The surface diffusion coefficients of atrazine and p-DCB were modeled as a function of the surface concentration of the pore-blocking compound, PSS-1.8k. The model was verified experimentally with a PAC/microfiltration (MF) system. The use of single-solute adsorption parameters obtained from batch isotherm and kinetic tests resulted in good model predictions for the adsorption of atrazine and the two model compounds under operating conditions typical of PAC/MF systems. The model will be applied to study various operating conditions and other system parameters of PAC/membrane systems in part 2 of this study.

Adsorption↗

PubMed2006

A molecular model for epsilon-caprolactam-based intercalated polymer clay nanocomposite: Integrating modeling and experiments.

In studying the morphology, molecular interactions, and physical properties of organically modified montmorillonite (OMMT) and polymer clay nanocomposites (PCNs) through molecular dynamics (MD), the construction of the molecular model of OMMT and PCN is important. Better understanding of interaction between various constituents of PCN will improve the design of polymer clay nanocomposite systems. MD is an excellent tool to study interactions, which require accurate modeling of PCN under consideration. Previously, the PCN models were constructed by different researchers on the basis of specific criteria such as minimum energy configuration, density of the polymer clay nanocomposite, and so forth. However, in this article we describe the development of models combining experimental and conventional molecular modeling to develop models, which are more representative of true intercalated PCN systems. The models were used for studying the morphological interactions and physical properties. These studies gave useful information regarding orientation of organic modifiers, area of coverage of organic modifiers over the interlayer clay surface, interaction of organic modifiers with clay in OMMT, interaction among different constituents of PCN, conformational and density change, and actual proportion of mixing of polymer with clay in PCN. We have X-ray diffraction and photoacoustic Fourier transform infrared spectroscopy to verify the model.

Aluminum Silicates↗

PubMed1999

Modeling of hepatic elimination and organ distribution kinetics with the extended convection-dispersion model.

The conventional convection-dispersion (also called axial dispersion) model is widely used to interrelate hepatic availability (F) and clearance (Cl) with the morphology and physiology of the liver and to predict effects such as changes in liver blood flow on F and Cl. An extended form of the convection-dispersion model has been developed to adequately describe the outflow concentration-time profiles for vascular markers at both short and long times after bolus injections into perfused livers. The model, based on flux concentration and a convolution of catheters and large vessels, assumes that solute elimination in hepatocytes follows either fast distribution into or radial diffusion in hepatocytes. The model includes a secondary vascular compartment, postulated to be interconnecting sinusoids. Analysis of the mean hepatic transit time (MTT) and normalized variance (CV2) of solutes with extraction showed that the discrepancy between the predictions of MTT and CV2 for the extended and unweighted conventional convection-dispersion models decreases as hepatic extraction increases. A correspondence of more than 95% in F and Cl exists for all solute extractions. In addition, the analysis showed that the outflow concentration-time profiles for both the extended and conventional models are essentially identical irrespective of the magnitude of rate constants representing permeability, volume, and clearance parameters, providing that there is significant hepatic extraction. In conclusion, the application of a newly developed extended convection-dispersion model has shown that the unweighted conventional convection-dispersion model can be used to describe the disposition of extracted solutes and, in particular, to estimate hepatic availability and clearance in both experimental and clinical situations.

Humans↗

PubMed2003

Separating trait effects from trait-specific method effects in multitrait-multimethod models: a multiple-indicator CT-C(M-1) model.

An overview of several models of confirmatory factor analysis for analyzing multitrait-multimethod (MTMM) data and a discussion of their advantages and limitations are provided. A new class of multi-indicator MTMM models combines several strengths and avoids a number of serious shortcomings inherent in previously developed MTMM models. The new models enable researchers to specify and to test trait-specific-method effects. The trait and method concepts composing these models are explained in detail and are contrasted with those of previously developed MTMM models for multiple indicators. The definitions of the models are explained step by step, and a practical empirical application of the models to the measurement of 3 traits x 3 methods is used to demonstrate their advantages and limitations.

Affect↗

PubMed2005

Pharmacokinetic/pharmacodynamic modelling of NSAIDs in a model of reversible inflammation in the cat.

1 Data on the relationships between plasma concentration and analgesic and anti-inflammatory effects of NSAIDs are limited because most inflammation models do not permit pharmacokinetic/pharmacodynamic (PK/PD) modelling to be readily performed. 2 In this study, a kaolin-induced inflammation model in the cat was evaluated for pre-clinical characterization of the pharmacodynamic profiles of NSAIDs (determination of efficacy, potency, sensitivity (that is the slope of the concentration-effect relationship) and duration of drug response), using meloxicam as a probe article. 3 Indirect response PK/PD models described the time course and magnitude of responses produced by 0.3 mg kg(-1) meloxicam administered subcutaneously. For endpoints for which spontaneous recovery from inflammation was superimposed on drug response, a PK/PD model with a time-dependent K(in) was used to allow for the spontaneous changes of the inflammation with time. 4 The selected endpoints were suitable for studying simultaneously the analgesic, anti-inflammatory and antipyretic effects of meloxicam, allowing comparison of relative potencies for these effects. Mean+/-s.d. IC(50) or EC(50) values (ng ml(-1)) were 777+/-124 (body temperature), 841+/-187 (locomotion variable), 883+/-215 (pain score), 911+/-189 (lameness score) and 1298+/-449 (skin temperature difference). Corresponding mean times+/-s.d. of peak responses (h) were 5.6+/-1.3, 8.6+/-3.8, 5.2+/-5.0, 5.6+/-3.7 and 4.3+/-2.4, respectively. 5 As the pharmacokinetic profiles of meloxicam in cats and humans are similar, simulations of several dosage regimens in the cat provided a pre-clinical basis, illustrating the value of the cat model for predicting a clinical dose regimen for evaluation in man. The predicted loading doses (mg kg(-1)) of meloxicam in the cat producing 70% of the maximum attainable responses were 0.29 (body temperature), 0.32 (lameness score), 0.33 (overall locomotion variable), 0.36 (pain score) and 0.50 (skin temperature difference). The values are similar to or somewhat greater than the clinically recommended doses both in cats (0.3 mg kg(-1)) and humans (7.5-15 mg, that is, between 0.1 and 0.3 mg kg(-1)). 6 These findings indicate the potential value of the cat as a laboratory model, and of a PK/PD modelling approach in assisting NSAID development programs in animals and humans.

Animals↗

PubMed2002

The canine 'groove' model, compared with the ACLT model of osteoarthritis.

OBJECTIVE: The frequently used anterior cruciate ligament transection (ACLT) model of osteoarthritis (OA) in the dog, makes use of a permanent trigger (joint instability) for inducing degenerative changes. The present study evaluates a canine model of degenerative cartilage damage, mimicking OA, which is induced without making use of permanent joint instability. METHODS: The articular cartilage of the weight-bearing areas of the femoral condyles in one knee of ten beagle dogs was damaged by making grooves, without damaging the subchondral bone. Surgery was followed by 10 weeks intensified loading of the affected joint. Subsequently, joint damage and inflammation were evaluated. The effects were compared with those of the ACLT model. RESULTS: Histological analysis showed chondrocyte clusters around cartilage lesions and moderate loss of proteoglycans in the 'groove' model. Synovial inflammation was mild. Biochemical analysis of cartilage showed changes in matrix proteoglycan turnover, proteoglycan content, and collagen damage, all characteristics of OA. Synovial fluid MMP-1, -3 and -13 activity was enhanced. Changes were found in condyles and plateau, were similar for all animals tested, and were similar to the changes observed in the ACLT model. CONCLUSION: The presently described canine 'groove' model shows characteristics identical to those seen in the ACLT model but differs in a way that the changes are induced without joint instability. The latter is expected to make the 'groove' model more sensitive to treatment.

Animals↗

PubMed2001

Evaluation of a model for total body protein mass based on dual-energy X-ray absorptiometry: comparison with a reference four-component model.

The aim of the present study was to evaluate a model of body composition for assessing total body protein (TBP) mass using dual-energy X-ray absorptiometry (DXA), with either measured or assumed total body water (TBW); it was intended to provide a less complex or demanding alternative technique to, for example, the four-component model (4-CM). The following measurements were obtained in healthy adults (n 46) aged 18--62 years, and children (n 30) aged 8--12 years: body weight (BWt), body volume (BV; under-water weighing), TBW ((2)H-dilution space or predicted using an assumed hydration fraction of fat-free mass (HF(ffm))), bone mineral content (BMC; DXA) and fat-free soft tissue (FFST; DXA). TBP was calculated using the 4-CM (TBP = 3.05BWt -- 0.290TBW -- 2.734BMC -- 2.74BV) and the DXA model (TBP = FFST -- 0.2302BMC -- TBW). DXA measurements were obtained using the Lunar DPX (Lunar Radiation Corporation, Madison, WI, USA) or Hologic QDR 1000/W (Hologic, Waltham, MA, USA). Precision of the DXA model for TBP with measured TBW (4.6--6.8 % mean TBP) was slightly worse than the 4-CM (4.0--5.4 %), whereas that modelled with assumed HF(ffm) was more precise (2.4--5.2 %) because it obviated imprecision associated with measuring TBW. Agreement between the 4-CM and DXA model with measured TBW was also worse (e.g. bias, 15 % of the mean; 95 % limits of agreement up to +/-39 % for adults measured on the Lunar DPX) than when a constant for HF(ffm) was assumed (3.7 % and +/-21 % respectively). Most of the variability in agreement between these various models was due to interpretation of biological factors, rather than to measurement imprecision. Therefore, the DXA model, which is less complex and demanding than the 4-CM, is of value for assessing TBP in groups of healthy subjects, but is of less value for individuals in whom there may be substantial differences from reference 4-CM estimates.

Absorptiometry, Photon↗

PubMed2004

Modelling of nutrient partitioning in growing pigs to predict their anatomical body composition. 1. Model description.

A dynamic mechanistic model was developed for growing and fattening pigs. The aim of the model was to predict growth rate and the chemical and anatomical body compositions from the digestible nutrient intake of gilts (20-105 kg live weight). The model represents the partitioning of digestible nutrients from intake through intermediary metabolism to body protein and body fat. State variables of the model were lysine, acetyl-CoA equivalents, glucose, volatile fatty acids and fatty acids as metabolite pools, and protein in muscle, hide-backfat, bone and viscera and body fat as body constituent pools. It was assumed that fluxes of metabolites follow saturation kinetics depending on metabolite concentrations. In the model, protein deposition rate depended on the availability of lysine and of acetyl-CoA. The anatomical body composition in terms of muscle, organs, hide-backfat and bone was predicted from the chemical body composition and accretion using allometric relationships. Partitioning of protein, fat, water and ash in muscle, organs, hide-backfat and bone fractions were driven by the rates of muscle protein and body fat deposition. Model parameters were adjusted to obtain a good fit of the experimental data from literature. Differential equations were solved numerically for a given set of initial conditions and parameter values. In the present paper, the model is presented, including its parameterisation. The evaluation of the model is described in a companion paper.

Adipose Tissue↗

PubMed2004

Modelling of nutrient partitioning in growing pigs to predict their anatomical body composition. 2. Model evaluation.

The objective of the present paper was to evaluate a dynamic mechanistic model for growing and fattening pigs presented in a companion paper. The model predicted the rate of protein and fat deposition (chemical composition), rate of tissue deposition (anatomical composition) and performance of pigs depending on nutrient intake. In the model evaluation, the predicted response of the pig to changes in model parameters and to changes in nutrient intakes is presented. As a result of the sensitivity analysis, changes in the maintenance energy requirements and the fractional degradation rate of muscle protein had the greatest impact on tissue deposition rates. The model was also highly sensitive to changes in the maximum velocity and steepness parameter of the lysine utilisation for muscle protein synthesis. The model was further tested by independent published results. The model successfully predicted the response of pigs to a wide range of variation in nutrient composition. Consequently, the model can be applied to develop feeding strategies to optimise pig production. It also enables prediction of the slaughter performance and the meat quality.

Adipose Tissue↗

PubMed2006

Role of conceptual models in a physical therapy curriculum: application of an integrated model of theory, research, and clinical practice.

The Department of Physical Therapy, University of Alberta, Edmonton, Alberta, Canada, recently implemented a Master of Physical Therapy (MPT) entry-level degree program. As part of the curriculum design, two models were developed, a Model of Best Practice and the Clinical Decision-Making Model. Both models incorporate four key concepts of the new curriculum: 1) the concept that theory, research, and clinical practice are interdependent and inform each other; 2) the importance of client-centered practice; 3) the terminology and philosophical framework of the World Health Organization's International Classification of Functioning, Disability, and Health; and 4) the importance of evidence-based practice. In this article the general purposes of models for learning are described; the two models developed for the MPT program are described; and examples of their use with curriculum design and teaching are provided. Our experiences with both the development and use of models of practice have been positive. The models have provided both faculty and students with a simple, systematic structured framework to organize teaching and learning in the MPT program.

Biomedical Research↗

PubMed2004

The bystander effect model of Brenner and Sachs fitted to lung cancer data in 11 cohorts of underground miners, and equivalence of fit of a linear relative risk model with adjustment for attained age and age at exposure.

Bystander effects following exposure to alpha-particles have been observed in many experimental systems, and imply that linearly extrapolating low dose risks from high dose data might materially underestimate risk. Brenner and Sachs (2002 Int. J. Radiat. Biol. 78 593-604; 2003 Health Phys. 85 103-8) have recently proposed a model of the bystander effect which they use to explain the inverse dose rate effect observed for lung cancer in underground miners exposed to radon daughters. In this paper we fit the model of the bystander effect proposed by Brenner and Sachs to 11 cohorts of underground miners, taking account of the covariance structure of the data and the period of latency between the development of the first pre-malignant cell and clinically overt cancer. We also fitted a simple linear relative risk model, with adjustment for age at exposure and attained age. The methods that we use for fitting both models are different from those used by Brenner and Sachs, in particular taking account of the covariance structure, which they did not, and omitting certain unjustifiable adjustments to the miner data. The fit of the original model of Brenner and Sachs (with 0 y period of latency) is generally poor, although it is much improved by assuming a 5 or 6 y period of latency from the first appearance of a pre-malignant cell to cancer. The fit of this latter model is equivalent to that of a linear relative risk model with adjustment for age at exposure and attained age. In particular, both models are capable of describing the observed inverse dose rate effect in this data set.

Air Pollutants, Radioactive↗

PubMed1993

Dynamic life table model for Aedes aegypti (Diptera: Culicidae): analysis of the literature and model development.

The container-inhabiting mosquito simulation model (CIMSiM) is a weather-driven, dynamic life table simulation model of Aedes aegypti (L.). It is designed to provide a framework for related models of similar mosquitoes which inhibit artificial and natural containers. CIMSiM is an attempt to provide a mechanistic, comprehensive, and dynamic accounting of the multitude of relationships known to play a role in the life history of these mosquitoes. Development rates of eggs, larvae, pupae, and the gonotrophic cycle are based on temperature using an enzyme kinetics approach. Larval weight gain and food depletion are based on the differential equations of Gilpin & McClelland compensated for temperature. Survivals are a function of weather, habitat, and other factors. The heterogeneity of the larval habitat is depicted by modeling the immature cohorts within up to nine different containers, each of which represents an important type of mosquito-producing container in the field. The model provides estimates of the age-specific density of each life stage within a representative 1-ha area. CIMSiM is interactive and runs on IBM-compatible personal computers. The user specifies a region of the world of interest; the model responds with lists of countries and associated cities where historical data on weather, larval habitat, and human densities are available. Each location is tied to an environmental file containing a description of the significant mosquito-producing containers in the area and their characteristics. In addition to weather and environmental information, CIMSiM uses biological files that include species-specific values for each of the parameters used in the model. Within CIMSiM, it is possible to create new environmental and biological files or modify existing ones to allow simulations to be tailored to particular locations or to parameter sensitivity studies. The model also may be used to evaluate any number and combination of standard and novel control methods.

Aedes↗

PubMed1997

Evaluation of logistic versus linear regression models for predicting pulmonary hypertension syndrome (ascites) using cold exposure or pulmonary artery clamp models in broilers.

Syndromes such as ascites (pulmonary hypertension syndrome) present difficulties both in the interpretation of associated physiological observations and in their analyses. The ability to predict which physiological variables have the greatest influence on survival or, more importantly, which individuals are most susceptible or resistant to ascites would be very useful selection tools. When addressed in this manner, ascites data become binary data sets (healthy or affected). Binary data can be problematic in that they do not meet all of the assumptions necessary for more traditional analyses such as ANOVA and linear regression. Binary data are discrete and do not have normally distributed errors, which violates a fundamental assumption of linear models. The predictive abilities of linear and logistic regression were evaluated in two replicated experiments using two methods to induce ascites, cold exposure (COLD) and surgical clamping of one pulmonary artery (PAC). The logistic and linear predictive models were derived using the same data and variables. The first data set from PAC and COLD were used to develop the predictive models and the replicate data sets of PAC and COLD were used as "test data sets" for the prediction of ascites. The linear models developed were complex, using four or five variables and requiring up to seven different measurements. On average, the linear models predicted ascites correctly 87.6% of the time. The logistic models were simple (single variable) models that predicted ascites correctly 92.0% of the time. The variables used in the logistic models were derivations of the ratio of right ventricular weight to total ventricular weight, either corrected for age or the body weight of the bird. Although linear regression predicted the incidence of ascites almost as well as logistic regression did, logistic regression is the more appropriate test statistic to use.

Analysis of Variance↗

PubMed2000

Modeling the uncertainty of surgical procedure times: comparison of log-normal and normal models.

BACKGROUND: Medical institutions are under increased economic pressure to schedule elective surgeries efficiently to contain the costs of surgical services. Surgical scheduling is complicated by variability inherent in the duration of surgical procedures. Modeling that variability, in turn, provides a mechanism to generate accurate time estimates. Accurate time estimates are important operationally to improve operating room utilization and strategically to identify surgeons, procedures, or patients whose duration of surgeries differ from what might be expected. METHODS: The authors retrospectively studied 40,076 surgical cases (1,580 Current Procedural Terminology-anesthesia combinations, each with a case frequency of five or more) from a large teaching hospital, and attempted to determine whether the distribution of surgical procedure times more closely fit a normal or a log-normal distribution. The authors tested goodness-of-fit to these data for both models using the Shapiro-Wilk test. Reasons, in practice, the Shapiro-Wilk test may reject the fit of a log-normal model when in fact it should be retained were also evaluated. RESULTS: The Shapiro-Wilk test indicates that the log-normal model is superior to the normal model for a large and diverse set of surgeries. Goodness-of-fit tests may falsely reject the log-normal model during certain conditions that include rounding errors in procedure times, large sample sizes, untrimmed outliers, and heterogeneous mixed populations of surgical procedure times. CONCLUSIONS: The authors recommend use of the log-normal model for predicting surgical procedure times for Current Procedural Terminology-anesthesia combinations. The results help to legitimize the use of log transforms to normalize surgical procedure times before hypothesis testing using linear statistical models or other parametric statistical tests to investigate factors affecting the duration of surgeries.

Databases, Factual↗