SEARCH · PubMed Health

Results for “Predictive modeling”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13Linked to original sources

PubMed1999

Multivariate predictive models for group A beta-hemolytic streptococcal pharyngitis in children.

OBJECTIVES: To create predictive models for the clinical diagnosis of group A beta-hemolytic streptococcal (GABHS) pharyngitis in children. METHODS: Patients aged 6 months to 18 years presenting to a pediatric ED with suspected GABHS pharyngitis were prospectively enrolled in the study. Clinicians recorded pertinent clinical information using a standardized form and obtained a throat swab to culture GABHS using a reference standard method. Twelve demographic and clinical features of patients with positive throat cultures were compared with the features of patients with negative throat cultures. Significantly different features were entered in a stepwise logistic regression analysis to create predictive models for the diagnosis. RESULTS: Eighty-five patients (29%) were culture-positive and 212 (71%) were culture-negative for GABHS. Respective mean ages were 6.2 years and 6.1 years in the two groups. Univariate chi-square analysis of the 12 features identified six variables that were significantly associated with GABHS. All significant features were initially included in a stepwise logistic regression analysis. In model I, four independent variables were identified: moderate to severe presentation of tonsillar swelling, moderate to severe tenderness and enlargement of cervical lymph nodes, the presence of scarlatiniform rash, and the absence of moderate to severe coryza, yielding a 95% probability for GABHS. Excluding the rare scarlatiniform rash, the remaining variables were used in the second regression analysis. In model II, three independent variables were identified: moderate to severe tonsillar swelling, moderate to severe tenderness and enlargement of cervical lymph nodes, and absence of moderate to severe coryza, yielding a probability of 65% for the diagnosis. A probability of <15% was observed in the absence of scarlatiniform rash, the absence of moderate to severe tenderness and enlargement of cervical lymph nodes, and the presence of moderate to severe coryza. CONCLUSIONS: In children with moderate to severe presentation of tonsillar swelling, tenderness and enlargement of cervical lymph nodes, and the absence of coryza, the probability of a positive throat culture is >65%. Conversely, in the absence of a moderate to severe presentation of tonsillar swelling, enlargement of cervical nodes, and the presence of coryza, the probability of a positive throat culture is <15%. If prospectively validated, these models could be integrated into a consistent treat, test, and no treatment/no testing approach to the clinical management of childhood pharyngitis.

Adolescent↗

PubMed2001

A predictive model of well-being and self-care for rural elderly women in Taiwan.

A predictive model of well-being and self-care was tested with 284 women aged 60-88 living in rural communities in Taiwan. The variables studied were age, marital status, social class, social support, perceived health, self-care agency, self-care behavior, and perceived well-being. The model was tested by path analysis. The parameters of the model were estimated with the maximum likelihood method. In the refined model, chi2 (12, N = 284) = 15.18, p =.23), 33% of the total variance in well-being was explained by self-care behavior, social support, and perceived health; 66% of the total variance in self-care behavior was explained by self-care agency and social support; 49% of the total variance in self-care agency was explained by social support, perceived health, social class, and age; 14% of the total variance in social support was explained by marital status, social class, and age; and 8% of the total variance in perceived health was explained by social support. The goodness-of-fit index was.99, indicating that the refined model fit the data well. The findings of this study contribute to a greater understanding of this predictive model for application with older women in rural Taiwan.

Adaptation, Psychological↗

PubMed1998

Derivation of a clinical prediction model for the emergency department diagnosis of ectopic pregnancy.

OBJECTIVE: To derive a clinical prediction model for estimating the pretest probability of ectopic pregnancy in ED patients with first-trimester abdominal pain or vaginal bleeding. METHODS: All hemodynamically stable first-trimester patients presenting to the ED of a tertiary care military teaching hospital over a 14-month period with a chief complaint of abdominal pain and/or vaginal bleeding had clinical data coded prior to determining outcome. They were then followed longitudinally until a criterion standard pregnancy outcome was established. RESULTS: Of the 486 patients enrolled, 280 (58%) had viable intrauterine pregnancies, 167 (34%) had nonviable intrauterine pregnancies, and 39 (8%) had ectopic pregnancies. Using a recursive partitioning model, a high-risk group was derived (that was separated from intermediate and low-risk groups), consisting of patients with abdominal peritoneal signs or definite cervical motion tenderness, with a sensitivity of 31% (95% CI: 17-48%), a specificity of 93% (95% CI: 90-95%), a positive likelihood ratio of 4.3, and a negative likelihood ratio of 0.74. A low-risk group, consisting of patients with either fetal heart tones or tissue at the cervical os, or the absence of pain other than midline menstrual-like cramping and lacking any pelvic tenderness, was differentiated from an intermediate-risk group, with a sensitivity of 96% (95% CI: 81-100%), a specificity of 22% (95% CI: 18-26%), a positive likelihood ratio of 1.2, and a negative likelihood ratio of 0.17. CONCLUSION: A clinical prediction model for estimating the probability of ectopic pregnancy in ED patients has been derived. It may prove to have practical clinical application for estimating pretest probability of ectopic pregnancy as well as assisting in medical decision making when laboratory and ultrasonographic findings are nondiagnostic. Clinical application should await prospective validation in an independent sample.

Abdominal Pain↗

PubMed2000

Accurate predictive modeling of response variables under dynamic condition without the use of past response data

One promising attribute of the dynamic predictive modeling method introduced by Rollins et al. [D.K. Rollins, J. Liang, P. Smith, Accurate simplistic predictive modeling of nonlinear dynamic processes, ISA Transactions 37(4) (1998) 193-203] is its ability to accurately predict output response without the use of online output data. The proposed method only needs online input data to accurately predict output behavior once the semi-empirical model has been identified using offline data. This ability is critical to chemical processes because many output variables (such as chemical composition) are often measured infrequently, inaccurately, or not at all. In addition, in the presence of extremely high measurement noise of the output variable, this work will demonstrate very accurate predictive performance. Finally, this article will show that the method of Rollins et al. can predict better without the use of output data than with the use of output data in the case of large measurement variance. Thus, the proposed method is being recommended for its accuracy, especially in situations where online output response data is limited or inaccurate.

Journal Article↗

PubMedDate not supplied

Optimal stopover decisions of migrating birds under variable stopover quality: model predictions and the field data.

Dataset on departure fuel loads, stopover length and fuel deposition rate of the European robins Erithacus rubecula during their migration in the Baltic area is presented. We test these empirical data against the predictions of an optimal migration model assuming that robins minimize time spent on migration, and that fuel deposition rate varies stochastically. The latter assumption sets this model apart from the alternative ones and makes it more realistic. In particular, it is applicable in frequently observed situations when fuel deposition rate is negative. Our model assumes stochastic variation of the fuel deposition rate at sites along the migratory rout and thus is applicable when negative values of fuel deposition rate are recorded. The model predicts the relationship between fuel deposition rate and departure fuel load rather well. The agreement between the observed and the predicted values of optimal stopover duration is much poorer. Predictions of optimal migration theory are known to be dependent on the form of flight equation chosen. Our model fits the data best when the costs of transport are low. This supports the idea that transport costs of fuel stores may be low, especially when fuel stores are modest.

Animal Migration↗

PubMed1999

Validating and comparing predictive models.

The bias and accuracy factors introduced by Ross [Ross, T., 1996. Indices for performance evaluation of predictive models in food microbiology. J. Appl Bacteriol. 81, 501-508] for the evaluation of the performance of models in 'predictive food microbiology' are refined by basing the calculation of those measures on the mean square differences between predictions and observations. The use of the indices is extended by presenting formulae and methods which enable evaluation of the difference between alternative models for growth of an organism of interest over a domain of environmental factors. This is done by calculating the integral mean of the square differences between the models under investigation over the domain of the environmental variables common to those models, or a sub-region of it. The use of the techniques is exemplified by evaluating the difference between four published models for the growth rate of psychrotrophic pseudomonads.

Bias↗

PubMed2002

Model-predictive control of hyperthermia treatments.

A model-predictive controller (MPC) of the thermal dose in hyperthermia cancer treatments has been developed and evaluated using simulations with one-point and one-dimensional models of a tumor. The developed controller is the first effort in: 1) the application of feedback control to pulsed, high-temperature hyperthermia treatments; 2) the direct control of the treatment thermal dose rather than the treatment temperatures; and 3) the application of MPC to hyperthermia treatments. Simulations were performed with different blood flow rates in the tumor and constraints on temperatures in normal tissues. The results demonstrate that 1) thermal dose can be controlled in the presence of plant-model mismatch and 2) constraints on the maximum allowable temperatures in normal tissue and/or the pulsed power magnitude can be directly incorporated into MPC and met while delivering the desired thermal dose to the tumor. For relatively high blood flow rates and low transducer surface intensities--factors that limit the range of temperature variations in the tumor, the linear MPC, obtained by piece-wise linearization of the dose-temperature relationship, provides an adequate performance. For large temperature variations, the development of nonlinear MPC is necessary.

Computer Simulation↗

PubMed2000

Total-body skeletal muscle mass: development and cross-validation of anthropometric prediction models.

BACKGROUND: Skeletal muscle (SM) is a large body compartment of biological importance, but it remains difficult to quantify SM with affordable and practical methods that can be applied in clinical and field settings. OBJECTIVE: The objective of this study was to develop and cross-validate anthropometric SM mass prediction models in healthy adults. DESIGN: SM mass, measured by using whole-body multislice magnetic resonance imaging, was set as the dependent variable in prediction models. Independent variables were organized into 2 separate formulas. One formula included mainly limb circumferences and skinfold thicknesses [model 1: height (in m) and skinfold-corrected upperarm, thigh, and calf girths (CAG, CTG, and CCG, respectively; in cm)]. The other formula included mainly body weight (in kg) and height (model 2). The models were developed and cross-validated in nonobese adults [body mass index (in kg/m(2)) < 30]. RESULTS: Two SM (in kg) models for nonobese subjects (n = 244) were developed as follows: SM = Ht x (0.00744 x CAG(2) + 0.00088 x CTG(2) + 0.00441 x CCG(2)) + 2.4 x sex - 0.048 x age + race + 7.8, where R:(2) = 0.91, P: < 0.0001, and SEE = 2.2 kg; sex = 0 for female and 1 for male, race = -2.0 for Asian, 1.1 for African American, and 0 for white and Hispanic, and SM = 0.244 x BW + 7.80 x Ht + 6.6 x sex - 0.098 x age + race - 3.3, where R:(2) = 0.86, P: < 0.0001, and SEE = 2.8 kg; sex = 0 for female and 1 for male, race = -1.2 for Asian, 1.4 for African American, and 0 for white and Hispanic. CONCLUSION: These 2 anthropometric prediction models, the first developed in vivo by using state-of-the-art body-composition methods, are likely to prove useful in clinical evaluations and field studies of SM mass in nonobese adults.

Adult↗

PubMed2003

A preliminary study of the application of some predictive modeling techniques to assess atmospheric mercury emissions from terrestrial surfaces.

Predictive modeling techniques are applied to investigate their potential usefulness in providing first order estimates on atmospheric emission flux of gaseous soil mercury and in identifying those parameters most critical in controlling such emissions. Predicted data by simulation and statistical techniques are compared to previously published observational data. Results showed that simulation techniques using air/soil coupling may provide a plausible description of mercury flux trends with a RMSE of 24.4ngm(-2)h(-1) and a mean absolute error of 10.2ngm(-2)h(-1) or 11.9%. From the statistical models, two linear models showed the lowest predictive abilities (R2=0.76 and 0.84, respectively) while the Generalized Additive model showed the closest agreement between estimated and observational data (R2=0.93). Predicted values from a Neural Network model and the Locally Weighted Smoother model showed also very good agreement to measured values of mercury flux (R2=0.92). A Regression Tree model demonstrated also a satisfactory predictability with a value of R2=0.90. Sensitivities and statistical analyses showed that surface soil mercury concentrations, solar radiation and, to a lesser degree, temperature are important parameters in predicting airborne Hg flux from terrestrial soils. These findings are compatible with results from recent experimental studies. Considering the uncertainties associated with mercury cycling and natural emissions, it is concluded, that predictions based on simple modeling techniques seem quite appropriate at present; they can be useful tools in evaluating the role of terrestrial emission sources as part of mercury modeling in local and regional airsheds.

Air Pollutants↗

PubMed2026

Risk Factors and Predictive Model for Postoperative High Myopia in Children Undergoing Congenital Cataract Surgery With Intraocular Lens Implantation.

PURPOSE: To identify risk factors associated with the development of high myopia following congenital cataract surgery and to establish a robust predictive model. DESIGN: Retrospective clinical cohort study. SUBJECTS: This retrospective study included 106 pediatric patients who underwent congenital cataract surgery with primary IOL implantation (mean follow-up 8.19 years). The model was externally validated in an independent cohort of 72 patients with a mean follow-up of 7.83 years. METHODS: Preoperative and postoperative ocular biometric parameters were collected. Risk factors for postoperative high myopia were analyzed using Cox proportional hazards regression, which served as the basis for model construction. The predictive performance of the model was rigorously evaluated for discrimination and calibration. Discriminative ability was quantified using Harrell's C-index and the area under the receiver operating characteristic curve (AUC). Model calibration was assessed via calibration plots by comparing predicted probabilities with actual observed outcomes. Internal validation was performed using a bootstrapping method (500 iterations) to ensure model stability and adjust for potential overfitting. RESULTS: An initial postoperative refraction of <+0.75D, and a higher IOL Power to Axial length Ratio (IOL/AL ratio) were identified as significant risk factors for the development of postoperative high myopia. Shorter preoperative axial length was associated with a greater magnitude of postoperative myopic shift. The predictive model demonstrated robust performance, achieving a C-index of 0.711 (internal validation C-index: 0.713). The area under the receiver operating characteristic curve (AUC) values for predicting high myopia at 5 and 10 years were 0.858 and 0.745, respectively. Furthermore, calibration curves demonstrated excellent agreement between the predicted and observed outcomes throughout the follow-up period. In external validation, the model achieved a C-index of 0.825, 5-year AUC of 0.833, and 10-year AUC of 0.713. CONCLUSIONS: Our analysis established that initial postoperative refraction <+0.75D, and an elevated IOL/AL ratio are key determinants of high myopia risk following surgery. Shorter preoperative axial length was associated with a greater magnitude of postoperative myopic shift. This predictive framework provides clinicians with a practical tool to optimize preoperative IOL selection and identify high-risk infants who require vigilant myopia prevention and balanced amblyopia management.

Humans↗

PubMed1998

Tensions of the flexor digitorum superficialis are higher than a current model predicts.

Existing isometric force models can be used to predict tension in the finger flexor tendon, however, they assume a specific distribution of forces across the tendons of the fingers. These assumptions have not been validated or explored by experimental methods. To determine if the force distributions repeatably follow one pattern the in vivo tension of the flexor digitorum superficialis (FDS) tendon of the long finger was measured in nine patients undergoing open carpal tunnel release surgery. Following the release, a tendon force transducer (Dennerlein et al. 1997 J. Biomechanics 30(4), 395-397) was mounted onto the FDS of the long finger. Tension in the tendon, contact force at the fingertip, and finger posture were recorded while the patient gradually increased the force applied by the fingertip from 0 to 10 N and then monotonically reduced it to 0 N. The average ratio of the tendon tension to the fingertip contact force ranged from 1.7 to 5.8 (mean = 3.3, s.d. = 1.4) for the nine subjects. These ratios are larger than ratios predicted by current isometric tendon force models (mean = 1.2, s. d. = 0.4). Subjects who used a pulp pinch posture (hyper-extended distal interphalangeal joint (DIP)) showed a significantly (p = 0.02) larger ratio (mean = 4.4, s.d. = 1.5) than the five subjects who flexed the DIP joint in a tip pinch posture (mean = 2.4, s.d. = 0.6). A new DIP constraint model, which selects different force distribution based on DIP joint posture, predicts force ratios that correlate well with the measured ratios (r2 = 0.85).

Adult↗

PubMed1994

Approaches to predictive modeling.

A four-component clinical model for process improvement is presented: (1) patient-related risk factors, (2) clinical processes ordered by the attending physician, (3) the hospital's execution of the physician's plan, and (4) the patient's outcome, or outcomes, resulting from the first three factors. The goal of risk adjustment in the analysis of quality of care is to account for the contribution of patient-related risk factors, so that the patient's outcome can be used as an indicator of the care ordered by the physician and executed by the hospital. Risk adjustment is usually accomplished by comparing the patient's predicted outcome, based on the patient's risk factors, to the observed outcome. Historically, three approaches to the development of prediction models have been used: (1) selection and weighting of risk factors by expert opinion, (2) univariate analyses, and (3) multivariate analyses. Future prediction models will be based on neural network techniques or cluster analysis. As these prediction models have evolved, there has been a steady increase in their predictive power.

Cardiac Surgical Procedures↗

PubMed2005

Experimental verification of a portal dose prediction model.

Electronic portal imaging devices (EPIDs) can be used to measure a two-dimensional (2D) dose distribution behind a patient, thus allowing dosimetric treatment verification. For this purpose we experimentally assessed the accuracy of a 2D portal dose prediction model based on pencil beam scatter kernels. A straightforward derivation of these pencil beam scatter kernels for portal dose prediction models is presented based on phantom measurements. The model is able to predict the 2D portal dose image (PDI) behind a patient, based on a PDI without the patient in the beam in combination with the radiological thickness of the patient, which requires in addition a PDI with the patient in the beam. To assess the accuracy of portal dose and radiological thickness values obtained with our model, various types of homogeneous as well as inhomogeneous phantoms were irradiated with a 6 MV photon beam. With our model we are able to predict a PDI with an accuracy better than 2% (mean difference) if the radiological thickness of the object in the beam is symmetrically situated around the isocenter. For other situations deviations up to 3% are observed for a homogeneous phantom with a radiological thickness of 17 cm and a 9 cm shift of the midplane-to-detector distance. The model can extract the radiological thickness within 7 mm (maximum difference) of the actual radiological thickness if the object is symmetrically distributed around the isocenter plane. This difference in radiological thickness is related to a primary portal dose difference of 3%. It can be concluded that our model can be used as an easy and accurate tool for the 2D verification of patient treatments by comparing predicted and measured PDIs. The model is also able to extract the primary portal dose with a high accuracy, which can be used as the input for a 3D dose reconstruction method based on back-projection.

Algorithms↗

PubMed2003

Validation of a mathematical model predicting the response to growth hormone treatment in prepubertal children with idiopathic growth hormone deficiency.

OBJECTIVE: To validate a mathematical model developed by Ranke et al. (J Clin Endocrinol Metab 1999;84:1174-7783) to predict the GH response during the first years of GH replacement therapy. PATIENTS AND METHODS: 38 children with idiopathic GH deficiency (GHD) met all inclusion criteria for the prediction model, but the group differed in some characteristics from the cohort from which the model was derived. RESULTS: Using the model for the 1st year including maximum GH after stimulation and the equation for the 6th year, the predicted value corresponded well with actual height gain. Differences were found when the growth response of the 1st year excluding maximum GH and that of the 2nd-5th year were calculated, resulting in a significant underestimation of actual height gain (-0.63 to -1.07 cm/year). CONCLUSION: The mathematical prediction model tended to underpredict the growth response to GH treatment in our patients with pronounced GHD. The severity of GHD seems to be an important parameter for the 1st year prediction.

Body Height↗

PubMed2003

Lateral facial soft-tissue prediction model: analysis using Fourier shape descriptors and traditional cephalometric methods.

This study was designed to investigate the relationship between traditional skeletal cephalometric measurement and Fourier analysis of the lateral soft-tissue profile. A random sample of 121 untreated subjects of European descent, with wide ranges of malocclusions and underlying facial patterns, was selected in the Orthodontic Unit at the University of Melbourne. Lateral cephalograms were available for all subjects. Both traditional lateral cephalometric analysis and Fourier soft-tissue profile analysis were carried out. Multivariate statistical analysis among 11 hard-tissue cephalometric measurements and the first 50 Fourier harmonics was then performed. This analysis formed the basis for a subsequently proposed soft-tissue prediction model. From this model, 50 predicted x- and y-harmonics were generated for each subject in the total sample. Calculation of Pearson's correlation coefficients between the actual and predicted harmonics revealed strong relationships for many of the lower-order harmonics. To further test the model, the prediction-coefficients derived from all 121 subjects were then used to make predictions for the first 50 x- and y-harmonics for a subgroup of 10 independent test subjects. Once again, Pearson's correlations between the actual and predicted harmonics of the test model in the lower-order harmonics revealed strong associations. Superimposition of the actual and predicted soft-tissue outlines, however, revealed that much actual detail in the region between the nose and the chin was still lost using the predicted Fourier harmonics. This suggests that soft-tissue prediction based on this Fourier test model, while already useful in Forensic facial reconstruction, may not yet be appropriate for useful diagnosis and planning in clinical disciplines.

Adolescent↗

PubMed1999

Shelf life of modified atmosphere packed cooked meat products: a predictive model.

The effect of temperature, concentration of dissolved CO2 and water activity on the growth of Lactobacillus sake was investigated by developing predictive models for the lag phase and the maximum specific growth rate of this specific spoilage organism for gas-packed cooked meat products. Two types of predictive model were compared: an extended Ratkowsky model and a response surface model. In general, response surface models showed a slightly better correlation, but the response surface model for the maximum specific growth rate showed illogical predictions at low water activities. The concentration of dissolved CO2 proved to be a significant independent variable for the maximum specific growth rate as well as for the lag phase of L. sake. Synergistic actions on the shelf life-extending effect were noticed between temperature and dissolved CO2, as well as between water activity and dissolved CO2. The developed models were validated by comparison with the existing model of Kant-Muermans et al. (1997) and by means of experiments in gas-packed cooked meat products. Both developed models proved to be useful in the prediction of the microbial shelf life of gas-packed cooked meat products.

Animals↗

PubMed2005

Clinical prediction model to characterize pulmonary nodules: validation and added value of 18F-fluorodeoxyglucose positron emission tomography.

BACKGROUND: The added value of 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) scanning as a function of pretest risk assessment in indeterminate pulmonary nodules is still unclear. OBJECTIVE: To obtain an external validation of the prediction model according to Swensen and colleagues, and to quantify the potential added value of FDG-PET scanning as a function of its operating characteristics in relation to this prediction model, in a population of patients with radiologically indeterminate pulmonary nodules. DESIGN, SETTING, AND PATIENTS: Between August 1997 and March 2001, all patients with an indeterminate solitary pulmonary nodule who had been referred for FDG-PET scanning were retrospectively identified from the database of the PET center at the VU University Medical Center. RESULTS: One hundred six patients were eligible for the study, and 61 patients (57%) proved to have malignant nodules. The goodness-of-fit statistic for the model (according to Swensen) indicated that the observed proportion of malignancies did not differ from the predicted proportion (p = 0.46). PET scan results, which were classified using the 4-point intensity scale reading, yielded an area under the evaluated receiver operating characteristic curve of 0.88 (95% confidence interval [CI], 0.77 to 0.91). The estimated difference of 0.095 (95% CI, -0.003 to 0.193) between the PET scan results classified using the 4-point intensity scale reading and the area under the curve (AUC) from the Swensen prediction was not significant (p = 0.058). The PET scan results, when added to the predicted probability calculated by the Swensen model, improves the AUC by 13.6% (95% CI, 6 to 21; p = 0.0003). CONCLUSION: The clinical prediction model of Swensen et al was proven to have external validity. However, especially in the lower range of its estimates, the model may underestimate the actual probability of malignancy. The combination of visually read FDG-PET scans and pretest factors appears to yield the best accuracy.

Aged↗

PubMed2004

Universal predictive models on octanol-air partition coefficients at different temperatures for persistent organic pollutants.

Owing to the importance of octanol-air partition coefficients (KOA) in describing the partition of organic pollutants from air to environmental organic phases, the paucity of KOA data at different environmental temperatures, and the difficulty or high expenditures involved in experimental determination, the development of predictive models for KOA is necessary. Approaches such as this are greatly needed to evaluate the environmental fate of the ever-increasing list of production chemicals. Partial least squares (PLS) regression with 18 molecular structural descriptors was used to develop predictive models based on directly measured KOA values of selected chlorobenzenes, polychlorinated biphenyls (PCBs), polychlorinated naphthalenes, polychlorinated dibenzo-p-dioxins/dibenzofurans, polybrominated diphenyl ethers, polycyclic aromatic hydrocarbons, and organochlorine pesticides (OPs). An optimization procedure resulted in two temperature-dependent universal predictive models that explained at least 91 % of the variance of log KOA. Model 1 was the more general of the two models that could be used for all the persistent organic pollutant (POP) classes investigated. Although model 1 performed poorly for select OPs, this was attributed to wide variability in structural types within this subset of POPs and their diversity compared to the other POP classes that were investigated. The exclusion of the structurally complex OP subset resulted in a more precise model, model 5. Intermolecular dispersive interactions (induced dipole-induced dipole forces) between octanol and solute molecules play a decisive role in governing KOA and its temperature dependence. Further investigations are needed to better characterize the steric structures of the POPs under study, especially of OPs.

Air↗