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PubMed1982

Prediction of remission in adult acute leukemia: development and testing of predictive models.

Logistic regression methods were applied to derive a set of models relating achievement of CR to prognostic characteristics in a group of 300 adult acute leukemia patients treated with cytosine arabinoside, vincristine, and prednisone combined with adriamycin (ADOAP) or rubidazone (ROAP). These models were tested prospectively in an independent group of 107 subsequent patients treated with ADOAP or ROAP therapy, by comparing observed outcomes to predictions of response based on the models. Several models were able to identify subgroups of patients with good, intermediate, and poor prognoses. A model regarded as clinically useful and which provided a good fit to both the population from which it was derived and the test population included the pretreatment factors age, history of an antecedent hematologic disorder, temperature, blood urea nitrogen, hemoglobin, and liver size.

Acute Disease↗
PubMed2006

Test method selection, validation against field data, and predictive modelling for impact evaluation of stabilised waste disposal.

In setting criteria for landfill classes in Annex II of the EU Landfill Directive, it proved to be impossible to derive criteria for stabilised monolithic waste due to the lack of information on release and release controlling factors in stabilised waste monofills. In this study, we present a scientific basis, which enables a realistic description of the environmental impact of stabilised waste landfills. The work in progress involves laboratory testing of different stabilisation recipes, pilot scale studies on site and evaluation of field leachate from a full-scale stabilisation landfill. We found that the pHs in run-off and in percolate water from the pilot experiment are both around neutral. The neutral pH in run-off is apparently caused by the rapid atmospheric carbonation of those alkaline constituents that are released. The soil, used as a liner protection layer, controls the release to the subsurface below the landfill. This soil layer buffers pH and binds metals. The modelling results show that the chemistry is understood rather well. Differences between predicted and actual leaching might then be attributed to discrepancies in the description of sorption processes, complexation to organic matter and/or kinetic effects in the leaching tests. We conclude that this approach resulted in a new scientific basis for environmental impact assessment of stabilised waste landfills. The integrated approach has already resulted in a number of very valuable observations, which can be used to develop a sustainable landfill for monolithic waste and to provide guidance for the management of waste to be stabilised (e.g. improved waste mix design).

Hazardous Waste↗
PubMed2003

Mathematical model predicts clinical ocular motor syndromes.

Clinical ocular motor syndromes were compared with ocular motor syndromes simulated by a mathematical model of the vestibuloocular reflex. The mathematical sensorimotor feedforward model of otolith control of three-dimensional binocular eye position is based on relevant anatomical connections of the vestibuloocular reflex from the utricles to extraocular eye muscles. This is the first attempt to simulate static ocular motor syndromes for unilateral utricular or vestibular nerve failure, lesions of the vestibular nucleus, and lesions of the ascending vestibuloocular reflex pathways. Comparison of the predicted syndromes with those found in patients with unilateral disorders of the vestibular nerve (herpes zoster neuritis), the vestibular nucleus (medullary infarction), and the medial longitudinal fasciculus (pontine infarction) showed good agreement as regards the direction of horizontal, vertical, and torsional eye deviations. The ability of the model to simulate complete or incomplete failures of single elements or entire pathways allows us to pose direct clinical questions about as yet unknown ocular motor syndromes or about the localization of the damage as well as the mechanism involved in syndromes already known.

Aged↗
PubMed1998

A constructionist model predicting the emergence, complementarity and classification of the nucleotide bases.

We are proposing an analytical matrix that models a logical process simulating the emergence of the bases of vital nucleotides. The construction and properties of the matricial model are outlined. The Graph 1 matrix specifies a unique distribution pattern of eight terms coded in binary triplet configurations and obeys specific dynamic laws. The whole set of binary triplet configurations is in dynamic equilibrium. For that reason, it is possible to carry out an analysis by entering by any one of the eight terms on the condition that the operating mode obeys all the internal laws of orientation and symmetries inherent in the matrix. The four chemical elements at the origin of life are distributed following their atomic structures in the order hydrogen (H), carbon (C), nitrogen (N) and oxygen (O) and organized according to the model. The dynamic properties of the model necessitate the running of three successive circular periodic studies per analysis in order to show the emergence of the four bases--adenine, guanine, cytosine and thymine--precisely in that order. The fifth base of the nucleotides--uracil--shows up twice but always in an intermediate position, thus in transition, as it is the case for messenger ribonucleic acid (mRNA). We show also that the model provides for a logical explanation of the law of complementarity of the bases and their chemical classification. It is proposed that subsequent developments of the dynamic laws of this matrix may lead to the study of the logical operations for the formation of protein sequences and of their analysis and to genetic bioprogramming in general. Thus, a strictly logical and dynamic approach to molecular genetics is possible.

Base Sequence↗
PubMed2004

A prediction model for community-acquired Chlamydia pneumoniae pneumonia in hospitalized patients.

BACKGROUND: The objective of the study was to identify factors that help to predict community-acquired Chlamydia pneumoniae pneumonia in hospitalized patients. PATIENTS AND METHODS: Clinical data of 83 patients with serologically confirmed C. pneumoniae pneumonia were compared with the data obtained from 72 patients with bacterial pneumonia. The criteria of bacterial pneumonia included positive blood and/or sputum cultures and negative serology for Mycoplasma pneumoniae, Chlamydia psittaci, Chlamydia pneumoniae and Coxiella burnetii. The data collected included demographics, chronic diseases, pre- and post-hospitalization course of pneumonia, clinical data on admission and laboratory findings. Descriptive statistical analysis, involving numerous variables, was followed by univariate and multivariate logistic regression analysis. RESULTS: Two different situations, one including demographic data and information on the pre-hospitalization course of pneumonia, and another based on clinical information on admission and on laboratory results, were modeled using multivariate logistic regression. Several variables selected from these two models were incorporated into the third model, and the following four variables were found to have the highest predictive value of C. pneumoniae pneumonia: nursing home residence (odds ratio [OD] 3.73, 95% confidence interval [CI] 1.39-10.06), low c-reactive protein (CRP) levels (OD 5.99, 95% CI 1.82-19.67), nonproductive cough (OD 0.32, 95% CI 0.14-0.73), and a normal urinalysis (OD 0.38, 95% CI 0.17-0.83). CONCLUSION: Our findings seem to allow for a more reliable differentiation between C. pneumoniae pneumonia and other bacterial pneumonias, but further investigations will be needed to validate the proposed model.

Adolescent↗
PubMed2003

Assessment of six mortality prediction models in patients admitted with severe sepsis and septic shock to the intensive care unit: a prospective cohort study.

INTRODUCTION: We conducted the present study to assess the validity of mortality prediction systems in patients admitted to the intensive care unit (ICU) with severe sepsis and septic shock. We included Acute Physiology and Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) II, Mortality Probability Model (MPM) II0 and MPM II24 in our evaluation. In addition, SAPS II and MPM II24 were customized for septic patients in a previous study, and the customized versions were included in this evaluation. MATERIALS AND METHOD: This cohort, prospective, observational study was conducted in a tertiary care medical/surgical ICU. Consecutive patients meeting the diagnostic criteria for severe sepsis and septic shock during the first 24 hours of ICU admission between March 1999 and August 2001 were included. The data necessary for mortality prediction were collected prospectively as part of the ongoing ICU database. Predicted and actual mortality rates, and standardized mortality ratio were calculated. Calibration was assessed using Lemeshow-Hosmer goodness of fit C-statistic. Discrimination was assessed using receiver operating characteristic curves. RESULTS: The overall mortality prediction was adequate for all six systems because none of the standardized mortality ratios differed significantly from 1. Calibration was inadequate for APACHE II, SAPS II, MPM II0 and MPM II24. However, the customized version of SAPS II exhibited significantly improved calibration (C-statistic for SAPS II 23.6 [P = 0.003] and for customized SAPS II 11.5 [P = 0.18]). Discrimination was best for customized MPM II24 (area under the receiver operating characteristic curve 0.826), followed by MPM II24 and customized SAPS II. CONCLUSION: Although general ICU mortality system models had accurate overall mortality prediction, they had poor calibration. Customization of SAPS II and, to a lesser extent, MPM II24 improved calibration. The customized model may be a useful tool when evaluating outcomes in patients with sepsis.

APACHE↗
PubMed1995

Validation and adjustment of the mathematical prediction model for human sweat rate responses to outdoor environmental conditions.

Under outdoor conditions this model was over estimating sweat loss response in shaded (low solar radiation) environments, and underestimating the response when solar radiation was high (open field areas). The present study was conducted in order to adjust the model to be applicable under outdoor environmental conditions. Four groups of fit acclimated subjects participated in the study. They were exposed to three climatic conditions (30 degrees, 65% rh; 31 degrees C, 40% rh; and 40 degrees C, 20% rh) and three levels of metabolic rate (100, 300 and 450 W) in shaded and sunny areas while wearing shorts, cotton fatigues (BDUs) or protective garments. The original predictive equation for sweat loss was adjusted for the outdoor conditions by evaluating separately the radiative heat exchange, short-wave absorption in the body and long-wave emission from the body to the atmosphere and integrating them in the required evaporation component (Ereq) of the model, as follows: Hr = 1.5SL0.6/I(T) (watt) H1 = 0.047Me.th/I(T) (watt), where SL is solar radiation (W.m-2), Me.th is the Stephan Boltzman constant, and I(T) is the effective clothing insulation coefficient. This adjustment revealed a high correlation between the measured and expected values of sweat loss (r = 0.99, p < 0.0001).

Adolescent↗
PubMed2003

Model predictions of gas embolism growth and reabsorption during xenon anesthesia.

BACKGROUND: It is not readily obvious whether an intravascular bubble will grow or shrink in a particular tissue bed. This depends on the constituent gases initially present in the bubble, the surrounding tissue, and the delivered gas admixture. The authors used a computational model based on the physics of gas exchange to predict cerebrovascular embolism behavior during xenon anesthesia. METHODS: The authors estimated values of gas transport parameters missing from the literature. The computational model was used with those parameters to predict bubble size over time for a range of temperatures (18 degrees -39 degrees C) used during extracorporeal circulation. RESULTS: Bubble size over time is highly nonlinearly dependent on multiple factors, including diffusivity, solubility, gas partial pressures, magnitude of concentration gradients, vessel diameter, and temperature. Xenon- and oxygen-containing bubbles continue to grow during xenon delivery. Bubble volume doubles from 50 to 100 nl in approximately 3-68 min, depending on initial gas composition and bubble shape. Bubble growth and reabsorption are relatively insensitive to temperature in the physiologic and surgical range. CONCLUSIONS: Xenon anesthesia results in gas exchange conditions that favor bubble growth, which may worsen neurologic injury from gas embolism. The concentration gradients can be manipulated by discontinuation of xenon delivery to promote reabsorption of xenon-containing bubbles. Estimated growth and reabsorption rates at normothermia can be applied to temperature extremes of cardiopulmonary bypass.

Algorithms↗
PubMed2005

[Comparison of multiple prediction models for hypertension (Neural networks, logistic regression and flexible discriminant analyses)].

OBJECTIVE: In this study, we compared performances of logistic regression analysis (LR), flexible discriminant analysis (EAA) and neural networks (SA) in prediction of primary hypertension. METHODS: Predictor variables were family history, lipoprotein A, triglyceride, smoking and body mass index. The data were collected from Cardiology Clinic of Trakya University Medical Faculty in Turkey, 2001. Logistic regression analysis, flexible discriminant analysis and neural networks were used for prediction of control and hypertension groups. Comparison of the performance of all models was done using receiver operating characteristic (ROC) curve analysis. RESULTS: All models had areas under the ROC curve in the range of 0.793-0.984 and SA had sensitivity, specificity, and accuracy greater than 90% at ideal threshold. ROC curve areas of SA and LR, and SA and EAA were statistically different (p<0.001 and p<0.001 respectively), while ROC curve areas of EAA and LR did not differ (p>0.05). CONCLUSION: We concluded that family history, lipoprotein A, triglyceride, smoking and body mass index variables can be used for prediction of control and hypertension groups with statistically better performance of SA over LR and EAA.

Body Mass Index↗
PubMed1999

A mathematical model predicting the frequency of aberrant rearrangements in the T-cell receptor gene.

The T-cell receptor (TCR) genetic loci undergo an orderly process of recombination in ontogeny in order to generate a diverse array of antigen receptors. Normally occurring, out-of-frame and incomplete rearrangements produce non-productive TCR transcripts. Abnormalities in the rearrangement process occur at very low frequencies but may predominate in inborn errors of recombination. Detecting these abnormalities in surviving pools of lymphocytes is difficult and typically focuses on identification of abnormally rearranged alleles or on detecting abnormalities in recombinase proteins. Thus, there currently exists no rapid screening method to identify aberrant V(D)J recombination. To address this issue, a mathematical model was developed to predict the error rate from the measured proportions of different non-productive TCR alleles. Since the proportions of different non-productive rearrangements vary in a characteristic fashion in response to abnormalities in the recombination process, the mathematical model presented here provides a tool to indirectly assess the error rate of TCR recombination. The model was applied to a group of patients with Omenn's syndrome, most of whom had an unknown primary defect. The results indicate that these patients had a > 90% rate of aberrant TCR recombination.

Alleles↗
PubMed2005

Accuracy of a predictive model for severe hepatic fibrosis or cirrhosis in chronic hepatitis C.

AIM: To assess the accuracy of a model in diagnosing severe fibrosis/cirrhosis in chronic hepatitis C virus (HCV) infection. METHODS: The model, based on the sequential combination of the Bonacini score (BS: ALT/AST ratio, platelet count and INR) and ultrasonography liver surface characteristics, was applied to 176 patients with chronic HCV infection. Assuming a pre-test probability of 35%, the model defined four levels of post-test probability of severe fibrosis/cirrhosis: <10% (low), 10-74% (not diagnostic), 75-90% (high) and >90% (almost absolute). The predicted probabilities were compared with the observed patientso distribution according to the histology (METAVIR). RESULTS: Severe fibrosis/cirrhosis was found in 67 patients (38%). The model discriminated patients in three comparable groups: 34% with a very high (>90%) or low (<10%) probability of severe fibrosis, 33% with a probability ranging from 75% to 90%, and 33% with an uncertain diagnosis (i.e., a probability ranging from 10% to 74%). The observed frequency of severe fibrosis/cirrhosis was within the predefined ranges. CONCLUSION: The model can correctly identify 67% of patients with a high (>75%) or low (<10%) probability of cirrhosis, leaving only 33% of the patients still requiring liver biopsy.

Alanine Transaminase↗
PubMed2002

Development and validation of models predicting the toxicity of major seawater ions to the mysid shrimp, Americamysis bahia.

The concentration and balance of major ions that comprise total dissolved solids (TDS) can influence the toxicity of effluents discharged to freshwater and marine environments. An additional complicating factor in waters released to saltwater systems is the effluent salinity since the toxicity of major ions changes with the salinity of the test solution. A study was conducted to evaluate the toxicity of six major seawater ions (bicarbonate, borate, calcium, magnesium, potassium, and sulfate) to the mysid shrimp, Americamysis bahia, at salinities of 10 and 20/1000. Logistic regression models were developed to predict organism survival at deficient and excess concentrations of the ions. Calcium and potassium caused significant mortality to mysid shrimp in both excess and deficient (relative to artificial seawater) solutions. Bicarbonate, borate, and magnesium displayed significant toxicity only in excess concentrations, while sulfate had no adverse impacts at any of the concentrations tested. As the salinity of the test solutions decreased, mysid shrimp tolerated increasingly lower calcium and potassium concentrations. Similarly, as salinity increased, the upper tolerance levels of calcium, potassium, and magnesium also increased. The models developed during these studies, and similar models developed by other researchers, were used to evaluate 11 actual effluents with unexplained toxicity that might be associated with TDS ions. The models correctly identified calcium as the primary toxicant in 9 of the 11 effluents. These results indicate the models can be used as an important tool to identify toxicity associated with major seawater ions.

Animals↗