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Results for “Model performance”

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PubMed2002

Human haematopoiesis in steady state and following intense perturbations.

Haematopoiesis is comprised of multiple stages, originating from pluripotent stem cells through intermediate progenitors to mature differentiated cells. Consequently, during the development of blood cells numerous sites are potentially exposed to the intense perturbations induced by anticancer chemotherapy. However, little is known about human haematopoietic stem cell kinetics in health and following cytotoxic perturbations. Here we reconstruct the complex in vivo dynamics of haematopoietic populations, including the elusive pluripotent stem cells, with a detailed mathematical representation of the marrow biology. The bone marrow kinetic parameters were estimated by using white blood cell counts routinely collected in patients during high dose chemotherapy (HDCT) followed by autologous peripheral blood stem cell transplantation and granulocyte colony stimulating factor (G-CSF) injections. Studying the model performance under a wide variety of parameter values reveals that bone marrow is surprisingly robust in the physiologically feasible parameter space. We infer that the human haematopoietic pluripotent stem cell density is approximately 1 in 2 x 10(5) mononuclear cells and that most of these cells are quiescent, dividing once in 3-4 weeks. Our results suggest that the re-infused stem cell content is relatively high (10(4) kg-1 or 1/300 of CD34+ cells) which contributes to both the long-term marrow re-population as well as to short-term support. This study implies that, in most patients, the pluripotent population recovers within 4 months following HDCT. The proposed model accurately predicts the bone marrow dynamics over a wide range of perturbations caused by clinical interventions. It provides valuable insights about the haematopoietic regeneration capacity, predicts the effect of G-CSF manipulation and of ex vivo graft expansion in improving transplantation procedures, and may have implications for effective stem cell gene therapy.

Antineoplastic Combined Chemotherapy Protocols↗

PubMed2006

Relaxing the rule of ten events per variable in logistic and Cox regression.

The rule of thumb that logistic and Cox models should be used with a minimum of 10 outcome events per predictor variable (EPV), based on two simulation studies, may be too conservative. The authors conducted a large simulation study of other influences on confidence interval coverage, type I error, relative bias, and other model performance measures. They found a range of circumstances in which coverage and bias were within acceptable levels despite less than 10 EPV, as well as other factors that were as influential as or more influential than EPV. They conclude that this rule can be relaxed, in particular for sensitivity analyses undertaken to demonstrate adequate control of confounding.

Bias↗

PubMedDate not supplied

Simulating pesticide leaching and runoff in rice paddies with the RICEWQ-VADOFT model.

There is a current need to simulate leaching and runoff of pesticide from rice (Oryza sativa L.) paddies for assessing environmental impacts on a valuable agricultural system. The objective of this study was to develop a model for determining predicted environmental concentration (PEC) in soil, runoff, and ground water through the linkage of two models, rice water quality model (RICEWQ) and vadose zone transport model (VADOFT), to simulate pesticide fate and transport within a rice paddy and underlying soil profile. Model performance was evaluated with a field data set obtained from a 2-yr field experiment in 1997 and 1998 in northern Italy. The predictions of amount of pesticide running off from the paddy field and accumulating in the paddy sediment were in agreement with measured values. Leaching into the vadose zone accounted for approximately 19% of the applied dose, but only a small amount of chemical (<0.1%) was predicted to reach ground water at a 5-m depth due to sorption and transformation in the soil. The permeability of the soil and the water management practices in the paddy field were shown to have a strong influence on pesticide fate. These factors need to be well characterized in the field if model predictions are to be successful. The combined model developed in this work is an effective tool for exposure assessments for soil, surface water, and ground water, in the particular conditions of rice cultivation.

Agriculture↗

PubMed1999

Development of a new prognostic system and validation of APACHE II for surgical ICU mortality: a multicenter study in Taiwan.

BACKGROUND: To develop and to validate a new prognostic prediction system for patients admitted to the surgical intensive care unit (ICU), and to compare its performance with the Acute Physiology and Chronic Health Evaluation (APACHE) II system. METHODS: The database was derived from three surgical ICUs in three hospitals. For each patient, demographic data, diagnosis, APACHE II score and hospital survival data were collected. The accuracy in outcome prediction of the APACHE II was assessed by means of receiver operating characteristic (ROC) analysis. The new prognostic system was developed by using a multiple logistic regression in the developmental data set and validated with the validation data set. RESULTS: A total of 1,248 patients were included from three ICUs. The area under the ROC curve was 0.74 for the APACHE II score. The new prognostic system includes 18 variables. Goodness-of-fit tests indicated that the model performed well in the developmental and validation samples (p = 0.235 in the developmental data set and p = 0.297 in the validation set). The area under the ROC curve was 0.84 in the developmental sample and 0.77 in the validation sample for the new prognostic score. The area under the ROC curve was 0.71 in the validation sample for the APACHE II score. CONCLUSIONS: Although APACHE II correlates with mortality for surgical ICU patients in Taiwan, its accuracy is not as good as in the original study. Mortality prediction performance improved with the use of the new, local scoring system.

Adult↗

PubMed2006

Improving efficiency of uncertainty analysis in complex integrated assessment models: the case of the RAINS emission module.

Ever since the Regional Acidification Information and Simulation Model (RAINS) has been constructed, the treatment of uncertainty has remained an issue of major interest. In a recent review of the model performed for the Clean Air for Europe (CAFE) programme of the European Commission, a more systematic and structured uncertainty analysis has been recommended. This paper aims at contributing to the scientific debate how this can be achieved. Because of its complex structure on the one hand and limited research resources (time, computational capacities) on the other hand a full-blown uncertainty analysis in RAINS is hardly feasible. Therefore, all types of uncertainty require more efficient ways for uncertainty analysis. With respect to parameter uncertainty, we propose to focus research efforts for uncertainty analysis on key parameters. Among different approaches to select key parameters that have been discussed in the literature screening methods seem to be particularly appropriate for complex, deterministic Integrated Assessment models such as RAINS. Surprisingly, in Integrated Assessment modelling for air pollution problems of screening design have not been taken up so far. As a case study we consider the emission module of RAINS. We show that its structure allows for a straightforward and effective screening procedure.

Air Pollution↗

PubMed2004

Simulating urban-scale air pollutants and their predicting capabilities over the Seoul metropolitan area.

Urban-scale air pollutants for sulfur dioxide, nitrogen dioxide, particulate matter with aerodynamic diameter > or = 10 microm, and ozone (O3) were simulated over the Seoul metropolitan area, Korea, during the period of July 2-11, 2002, and their predicting capabilities were discussed. The Air Pollution Model (TAPM) and the highly disaggregated anthropogenic and the biogenic gridded emissions (1 km x 1 km) recently prepared by the Korean Ministry of Environment were applied. Wind fields with observational nudging in the prognostic meteorological model TAPM are optionally adopted to comparatively examine the meteorological impact on the prediction capabilities of urban-scale air pollutants. The result shows that the simulated concentrations of secondary air pollutant largely agree with observed levels with an index of agreement (IOA) of >0.6, whereas IOAs of approximately 0.4 are found for most primary pollutants in the major cities, reflecting the quality of emission data in the urban area. The observationally nudged wind fields with higher IOAs have little effect on the prediction for both primary and secondary air pollutants, implying that the detailed wind field does not consistently improve the urban air pollution model performance if emissions are not well specified. However, the robust highest concentrations are better described toward observations by imposing observational nudging, suggesting the importance of wind fields for the predictions of extreme concentrations such as robust highest concentrations, maximum levels, and >90th percentiles of concentrations for both primary and secondary urban-scale air pollutants.

Air↗

PubMed2003

Clinical pharmacodynamics of linezolid in seriously ill patients treated in a compassionate use programme.

OBJECTIVE: To characterise the pharmacokinetic-pharmacodynamic relationships for linezolid efficacy. DESIGN AND STUDY POPULATION: Retrospective nonblinded analysis of severely debilitated adult patients with numerous comorbid conditions and complicated infections enrolled under the manufacturer's compassionate use programme. METHODS: Patients received intravenous or oral linezolid 600 mg every 12 hours. Plasma concentrations were obtained and a multicompartmental pharmacokinetic model was fitted. Numerical integration of the fitted functions provided the area under the concentration-time curve over 24 hours (AUC), the ratio of AUC to minimum inhibitory concentration (AUC/MIC) and the percentage of time that plasma concentrations exceeded the MIC (%T>MIC). MAIN OUTCOME MEASURES: Modelled pharmacodynamic outcomes of efficacy included probabilities of eradication and clinical cure (multifactorial logistic regression, nonparametric tree-based modelling, nonlinear regression) and time to bacterial eradication (Kaplan-Meier and Cox proportional hazards regression). Factors considered included AUC/MIC, %T>MIC, site of infection, bacterial species and MIC, and other medical conditions. RESULTS: There were 288 cases evaluable by at least one of the efficacy outcomes. Both %T>MIC and AUC/MIC were highly correlated (Spearman r2 = 0.868). In our analyses, within specific infection sites, the probability of eradication and clinical cure appeared to be related to AUC/MIC (eradication: bacteraemia, skin and skin structure infection [SSSI], lower respiratory tract infection [LRTI], bone infection; clinical cure: bacteraemia, LRTI) and %T>MIC (eradication: bacteraemia, SSSI, LRTI; clinical cure: bacteraemia, LRTI). Time to bacterial eradication for bacteraemias appeared to be related to the AUC, %T>MIC and AUC/MIC. For most sites, AUC/MIC and %T>MIC models performed similarly. CONCLUSIONS: Higher success rates for linezolid may occur at AUC/MIC values of 80-120 for bacteraemia, LRTI and SSSI. Chance of success in bacteraemia, LRTI and SSSI also appear to be higher when concentrations remain above the MIC for the entire dosing interval.

Acetamides↗

PubMed2004

The LRINEC (Laboratory Risk Indicator for Necrotizing Fasciitis) score: a tool for distinguishing necrotizing fasciitis from other soft tissue infections.

OBJECTIVE: Early operative debridement is a major determinant of outcome in necrotizing fasciitis. However, early recognition is difficult clinically. We aimed to develop a novel diagnostic scoring system for distinguishing necrotizing fasciitis from other soft tissue infections based on laboratory tests routinely performed for the evaluation of severe soft tissue infections: the Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) score. DESIGN: Retrospective observational study of patients divided into a developmental cohort (n = 314) and validation cohort (n = 140) SETTING: Two teaching tertiary care hospitals. PATIENTS: One hundred forty-five patients with necrotizing fasciitis and 309 patients with severe cellulitis or abscesses admitted to the participating hospitals. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The developmental cohort consisted of 89 consecutive patients admitted for necrotizing fasciitis. Control patients (n = 225) were randomly selected from patients admitted with severe cellulitis or abscesses during the same period. Hematologic and biochemical results done on admission were converted into categorical variables for analysis. Univariate and multivariate logistic regression was used to select significant predictors. Total white cell count, hemoglobin, sodium, glucose, serum creatinine, and C-reactive protein were selected. The LRINEC score was constructed by converting into integer the regression coefficients of independently predictive factors in the multiple logistic regression model for diagnosing necrotizing fasciitis. The cutoff value for the LRINEC score was 6 points with a positive predictive value of 92.0% and negative predictive value of 96.0%. Model performance was very good (Hosmer-Lemeshow statistic, p =.910); area under the receiver operating characteristic curve was 0.980 and 0.976 in the developmental and validation cohorts, respectively. CONCLUSIONS: The LRINEC score is a robust score capable of detecting even clinically early cases of necrotizing fasciitis. The variables used are routinely measured to assess severe soft tissue infections. Patients with a LRINEC score of > or = 6 should be carefully evaluated for the presence of necrotizing fasciitis.

Abscess↗

PubMed1993

Predicting short-term survival for patients with advanced Alzheimer's disease.

OBJECTIVE: The purpose of this study was to develop a statistical model for predicting short term survival in patients with dementia of the Alzheimer type (DAT). DESIGN: A prospective cohort study. SETTING: Three 25-bed intermediate medical care units using a structured approach to patient care management including palliative care options and patients from a second, traditional long-term care setting. PARTICIPANTS: Of 104 patients with advanced DAT monitored for 34 months, 68 patients (97% white male) who had at least one fever episode were included in the model development phase. Data from 71 additional DAT patients with at least one fever episode were used to test the statistical model. MAIN OUTCOME MEASURES: Six-month survival following a fever episode. RESULTS: Older age and higher severity of DAT at the time of the fever episode, palliative care, and hospital admission for long-term care within 6 months prior to the fever were found to be positively associated with likelihood of mortality within 6 months of the fever onset. Adjusted odds ratios for each of these variables were statistically significant. The model performed well in subsequent testing on an independent sample of patients. CONCLUSION: Results provide a formula which can be used to predict likelihood of dying within 6 months following onset of a fever in DAT patients. This statistical prediction is recommended for use in combination with clinical judgment to certify DAT patients for Medicare hospice coverage.

Age Factors↗

PubMed1994

Variations in maximum amplitude of facial expressions between and within normal subjects.

Definitive proof of efficacy of preventions and therapeutic interventions, and of risk factors in lower motor neuron facial paralyses continue to be confounded by the lack of repeatable quantitative measures of outcome. Clinical and research experience with human facial expression repeatedly demonstrates wide variations between subjects. To our knowledge, little information is available to isolate and describe the differences in dynamic facial expression between and within normal subjects. The purpose of this study is to use a statistical model to analyze the components of the observed variations of maximum amplitude measurement of image change during normal human subject facial expressions. Seventeen consecutive normal adult human subjects with no current or past evidence of facial nerve or ear disease were studied. Videotapes of command facial expressions were taken using specific and standardized conditions. The tapes were analyzed using a new computer-assisted image-change analysis program capable of generating dimensional data for the maximum amplitude of expression. These data were statistically analyzed using a General Linear Model with Nested variables to isolate and define component variations and errors. The General Linear Model predicted 88% of the observed total variation (p < 0.05).* A model performance this high suggests that most of the important independent variables were being studied. The major component of the variations was the difference among (between) subjects. Seventy-seven percent of the predicted variation was due to this difference (p < 0.05). Little of the variation (1%) seemed to be within-subjects. Test-retest agreement was acceptable.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗

PubMed1998

Predictors of occult pneumococcal bacteremia in young febrile children.

STUDY OBJECTIVE: Occult pneumococcal bacteremia (OPB) occurs in 2.5% to 3% of highly febrile children 3 to 36 months of age, and 10% to 25% of untreated patients with OPB experience complications, including 3% to 6% in whom meningitis develops. The purpose of this study was to identify predictors of OPB among a large cohort of young, febrile children treated as outpatients using multivariable statistical methods. METHODS: We derived and validated a logistic regression model for the prediction of OPB. We evaluated 6,579 outpatients 3 to 36 months of age with temperatures of 39 degrees C or higher who previously had been enrolled in a study of young febrile patients at risk of OPB in the emergency departments of 10 hospitals in the United States between 1987 and 1991; 164 patients (2.5%) had OPB. We randomly selected two thirds of this population for the derivation of the model and one third for validation. In the derivation set, we analyzed the univariate relationships of six variables with OPB: age, temperature, clinical score, WBC count, absolute neutrophil count (ANC), and absolute band count (ABC). All six variables were then entered into a logistic regression equation and those retaining statistical significance were considered to have an independent association with OPB. RESULTS: Patients with OPB were younger, more frequently ill-appearing, and had higher temperatures, WBC, ANC, and ABC than patients without bacteremia. Only three variables, however, retained statistically significant associations with OPB in the multivariate analysis: ANC (Adjusted odds ratio [OR] 1.15 for each 1,000 cells/mm3 increase, 95% confidence interval [CI] 1.06, 1.25), temperature (adjusted OR 1.77 for each 1 degree C increase, 95% CI 1.21, 2.58), and age younger than 2 years (adjusted OR 2.43 versus patients 2 to 3 years old, 95% CI interval 1.11, 5.34). In the derivation set, 8.1% of patients with ANCs greater than or equal to 10,000 cell/mm3 had OPB (95% CI 6.3, 10.1%) versus .8% of patients with ANCs less than 10,000 cells/mm3 (95% CI .5, 1.2%). When tested on the validation set, the model performed similarly. CONCLUSION: Independent predictors of OPB in children 3 to 36 months of age with temperatures of 39 degrees C or higher treated as outpatients include ANC, temperature, and age younger than 2 years. These predictors may be used to develop clinical strategies to limit laboratory testing and antibiotic administration to those children at greatest risk of OPB.

Age Factors↗

PubMed2006

Rediscovering the species in community-wide predictive modeling.

Broadening the scope of conservation efforts to protect entire communities provides several advantages over the current species-specific focus, yet ecologists have been hampered by the fact that predictive modeling of multiple species is not directly amenable to traditional statistical approaches. Perhaps the greatest hurdle in community-wide modeling is that communities are composed of both co-occurring groups of species and species arranged independently along environmental gradients. Therefore, commonly used "short-cut" methods such as the modeling of so-called "assemblage types" are problematic. Our study demonstrates the utility of a multiresponse artificial neural network (MANN) to model entire community membership in an integrative yet species-specific manner. We compare MANN to two traditional approaches used to predict community composition: (1) a species-by-species approach using logistic regression analysis (LOG) and (2) a "classification-then-modeling" approach in which sites are classified into assemblage "types" (here we used two-way indicator species analysis and multiple discriminant analysis [MDA]). For freshwater fish assemblages of the North Island, New Zealand, we found that the MANN outperformed all other methods for predicting community composition based on multiscaled descriptors of the environment. The simple-matching coefficient comparing predicted and actual species composition was, on average, greatest for the MANN (91%), followed by MDA (85%), and LOG (83%). Mean Jaccard's similarity (emphasizing model performance for predicting species' presence) for the MANN (66%) exceeded both LOG (47%) and MDA (46%). The MANN also correctly predicted community composition (i.e., a significant proportion of the species membership based on a randomization procedure) for 82% of the study sites compared to 54% (MDA) and 49% (LOG), resulting in the MANN correctly predicting community composition in a total of 311 sites and an additional 117 sites (n = 379), on average, compared to LOG and MDA. The MANN also provided valuable explanatory power by simultaneously quantifying the nature of the relationships between the environment and both individual species and the entire community (composition and richness), which is not readily available from traditional approaches. We discuss how the MANN approach provides a powerful quantitative tool for conservation planning and highlight its potential for biomonitoring programs that currently depend on modeling discrete assemblage types to assess aquatic ecosystem health.

Animals↗

PubMed2005

Quantum vs. classical models of the nitro group for proton chemical shift calculations and conformational analysis.

A model based on classical concepts is derived to describe the effect of the nitro group on proton chemical shifts. The calculated chemical shifts are then compared to ab initio (GIAO) calculated chemical shifts. The accuracy of the two models is assessed using proton chemical shifts of a set of rigid organic nitro compounds that are fully assigned in CDCl3 at 700 MHz. The two methods are then used to evaluate the accuracy of different popular post-SCF methods (B3LYP and MP2) and molecular mechanics methods (MMX and MMFF94) in calculating the molecular structure of a set of sterically crowded nitro aromatic compounds. Both models perform well on the rigid molecules used as a test set, although when using the GIAO method a general overestimation of the deshielding of protons near the nitro group is observed. The analysis of the sterically crowded molecules shows that the very popular B3LYP/6-31G(d,p) method produces very poor twist angles for these, and that using a larger basis set [6-311++G(2d,p)] gives much more reasonable results. The MP2 calculations, on the other hand, overestimate the twist angles, which for these compounds compensates for the deshielding effect generally observed for protons near electronegative atoms when using the GIAO method at the B3LYP/6-311++G(2d,p) level. The most accurate results are found when the structures are calculated using B3LYP/6-311++G(2d,p) level of theory, and the chemical shifts are calculated using the CHARGE program based on classical models.

Journal Article↗

PubMed1997

[Differential characteristics and survival of women with acute myocardial infarction. Registry of Acute Myocardial Infarctions of the City of Valencia (RICVAL). Researchers of the RICVAL].

INTRODUCTION AND OBJECTIVES: The prevalence of women who are admitted to the hospital after acute myocardial infarction is lower to that of men and their prognosis is worse. The reason for these differences is unclear. We studied the demographic and historical variables, the evolution, treatment and early survival in 269 women included in the Register of Acute Myocardial Infarctions of the City of Valencia (RICVAL) and compared them with the 855 men included in the same Register. PATIENTS AND METHODS: Register of patients admitted into a Coronary Care Unit in the City of Valencia since December, 1st, 1993 until November 30th, 1994. RESULTS: 23.9% of the patients were women with a mean age of 71.9 +/- 9 years; 46.8% of them were diabetics, 55.4% hypertensives, and 6.7% smokers. The women arrived for treatment later than men and 34.9% of them were thrombolised. The incidence in women of severe heart failure (Killip III and IV) was 40.1% and the mortality 29.7%. In women with thrombolytic treatment the mortality was 29.8%. In the logistic regression model performed, female sex predicted a higher mortality rate (odds ratio [OR] = 1.30; confidence interval [CI], 1.05-1.61). CONCLUSIONS: Early mortality in women after acute myocardial infarction is higher than in men in the RICVAL Register. The longer delay in initiating medical care and thrombolysis might be the cause for the higher proportion of heart failure among women and explain their worse prognosis after an acute myocardial infarction compared to men.

Aged↗

PubMed2003

Predicting major neurological improvement with intravenous recombinant tissue plasminogen activator treatment of stroke.

BACKGROUND AND PURPOSE: In the National Institute of Neurological Disorders and Stroke (NINDS) rt-PA Stroke Study, major neurological improvement within 24 hours (MNI) occurred significantly more frequently with recombinant tissue plasminogen activator (rtPA) treatment than with placebo. We explored the relationship between MNI and 3-month favorable outcome and sought clinical predictors of MNI. METHODS: Data from 312 rtPA-treated patients from the NINDS trial were used to assess the ability of MNI to predict favorable outcome at 3 months as defined by a modified Rankin Scale score of 0 to 1. Next, a multivariable predictive model was developed for MNI within the same data set. Clinical variables examined included age, time to treatment (TTT), diabetes, pretreatment glucose, baseline National Institutes of Health Stroke Scale score, pretreatment blood pressure, history of atrial fibrillation, weight >100 kg, and a dense artery sign. Finally, this model was used to forecast into the placebo group of the NINDS trial to assess the uniqueness of the predictors in the rtPA-treated group. RESULTS: MNI had a positive predictive value and negative predictive value of 0.70 for predicting favorable 3-month outcome. Only age [odds ratio (OR), 0.68; 95% confidence interval (CI), 0.47 to 0.99] and TTT (OR, 0.56; 95% CI, 0.34 to 0.91) appear to be independently associated with MNI. The model performed only moderately well (area under the receiver-operating characteristic curve, 0.66). Age (OR, 0.67; 95% CI, 0.45 to 0.99) but not TTT was associated with MNI in the placebo group. CONCLUSIONS: MNI may be a useful surrogate for thrombolytic activity and is predictive of favorable 3-month outcome. When rates of MNI in different populations of stroke patients treated with thrombolysis are compared, adjustments for age and TTT may be necessary.

Age Factors↗

PubMed2026

Leveraging Interradiomic Feature Relationships for Enhanced Prediction of Distant Metastasis and Characterization of Heterogeneity in Head and Neck Cancer.

PURPOSE: Distant metastasis remains a major cause of treatment failure in head and neck (HN) cancer, highlighting the need for more accurate early risk stratification. This study developed and validated a deep radiomics framework to characterize tumor heterogeneity from pretreatment computed tomography (CT) images and improve prediction of distant metastasis-free survival (DMFS). METHODS AND MATERIALS: This multicenter study included 3421 patients with HN cancer from 4 cohorts across 12 institutions. Radiomics features were extracted from primary tumors and transformed into OmicsMaps, a structured representation that spatially organizes interfeature relationships to facilitate learning of complex prognostic patterns. A convolutional neural network was trained to derive prognostic signatures, which were integrated with key clinical variables to construct an OmicsMap-clinical fusion model for patient risk stratification. Model performance was assessed using the concordance index (C-index) and time-dependent area under the receiver operating characteristic curve (AUC) in the CT Images from Large Head and Neck Cohort (RADCURE), HEAD-NECK-RADIOMICS-HN1 (HN1), and Head-Neck-Positron Emission Tomography-Computed Tomography (HN-PET-CT) cohorts. Radiogenomic analyses using RNA-seq data were conducted in the Cancer Genome Atlas Head-Neck Squamous Cell Carcinoma (TCGA-HNSC) cohort to investigate biological characteristics associated with the imaging-defined risk groups. RESULTS: The OmicsMap achieved C-index values of 0.742, 0.768, and 0.671 in the RADCURE, HN1, and HN-PET-CT cohorts, outperforming the conventional radiomics approach by 5.40%-6.37%. Incorporating clinical variables further improved generalizability, yielding a C-index of 0.864 (HN1) and 0.730 (HN-PET-CT), with time-dependent AUC of 0.727-0.895. The fusion model consistently stratified patients into distinct high- and low-risk groups for both DMFS and overall survival across cohorts (P <.01). Radiogenomic analyses revealed enrichment of immune-related pathways in the low-risk group, whereas the high-risk group exhibited a more aggressive phenotype enriched for proliferation, hypoxia, and epithelial-mesenchymal transition pathways, along with a fibrosis-prone tumor microenvironment characterized by extracellular matrix remodeling. CONCLUSIONS: Modeling interradiomic feature relationships using the OmicsMap representation substantially improves CT-based prediction of DMFS and characterization of tumor heterogeneity in HN cancer, supporting precision risk stratification in clinical oncology.

Journal Article↗

PubMed1997

Predictive accuracy of continuous propofol infusions in neurosurgical patients: comparison of pharmacokinetic models.

The performance of 10 pharmacokinetic models in predicting blood propofol concentrations was evaluated in patients during neurosurgical anesthesia. Eight patients-ASA category I or II, aged 49 +/- 18-years, weighing 71 +/- 20 kg, and scheduled for routine neurosurgery-were anesthetized with propofol and sufentanil using Ohmeda pumps controlled with a personal computer. Sufentanil was administered as a bolus of 0.3 microgram.kg-1, 5 min before induction of anesthesia, and infused at a constant rate of 0.5 microgram.kg-1.h-1 throughout the study. At induction, propofol was administered as a bolus of 1.5 mg.kg-1 followed by a continuous infusion of 6 mg.kg-1.h-1. During surgery, the propofol infusion rate was deliberately increased by 2 mg.kg-1.h-1 every 15 min up to 12 mg.kg-1.h-1. Arterial blood samples were drawn at the end of each infusion step for measurement of propofol concentrations by high-performance liquid chromatography. Measured propofol concentrations were compared with theoretical concentrations derived from 10 published pharmacokinetic models designed in different clinical settings. Each model has been assessed by calculating the median of the performance error, the median of the absolute performance error, and their 10th and 90th percentiles. Models designed for certain categories, such as children, young, or elderly patients who received propofol as a bolus injection, showed a bad predictive accuracy. The models of Gepts et al. (Anesth Analg 1987; 66:1256-1263, Anaesthesia 1988; 43(suppl):8-13), Tackley et al. (Br J Anaesth 1989;62:46-53), and Cockshott (Postgrad Med J 1985;61:55), derived from healthy patients receiving continuous propofol infusions, provided the best agreement between expected and measured propofol concentrations; they showed bias and inaccuracy lower than 17%. In conclusion, the accurate prediction of blood propofol concentrations from different continuous infusion rates in ASA I or II patients requires the selection of appropriate pharmacokinetic models derived from similar categories of patients and using a similar technique of propofol administration. However, in clinical practice, the selection of a specific set among the appropriate models is balanced by the interindividual variability in blood propofol concentrations adjusted to clinical effects.

Adult↗

PubMed2006

Relationships among team ability composition, team mental models, and team performance.

This study examined the relationship between the similarity and accuracy of team mental models and compared the extent to which each predicted team performance. The relationship between team ability composition and team mental models was also investigated. Eighty-three dyadic teams worked on a complex skill task in a 2-week training protocol. Results indicated that although similarity and accuracy of team mental models were significantly related, accuracy was a stronger predictor of team performance. In addition, team ability was more strongly related to the accuracy than to the similarity of team mental models and accuracy partially mediated the relationship between team ability and team performance, but similarity did not.

Affect↗