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PubMed1997

Marriage: distance between birthplaces and age difference between mates.

The methodology of potential mate analysis can be used to obtain information about the determinants of marriage. This study investigates the influence of the distance between birthplaces and of age difference between mates. We use a new method of potential mate analysis that involves a sample of potential mates simulated from a sequence of actual mates. The differences between actual and potential mates are investigated using a logistic model and by direct comparison of distributions. The logistic model gives a poor fit. The comparison of distributions reveals no significant difference in distance between birthplaces for actual and potential mates or, at any rate, no difference large enough to be demonstrated by our small sample. A marked difference is observed for marriages in which the male is slightly older. The distance between birthplaces in our sample is shorter than in Great Britain.

Adult↗
PubMed1995

Factors triggering the first febrile seizure.

The symptomatology of infections as well as immunological and virological findings were analysed using a logistic model in a survey of 58 children experiencing their first febrile seizures. These were then compared with findings in 116 age- and sex-matched controls with infections but no seizures. There were no statistically significant differences in the aetiology of infections between patients and controls. High temperature was the only variable to explain the occurrence of febrile seizures in the logistic model after adjusting for duration of symptoms (partial correlation coefficient in logistic model, r = 0.31). The duration of symptoms before hospitalization was shorter in patients than in controls (mean 1.0 and 3.6 days). With a longer duration of symptoms, the likelihood of seizures diminished (r = -0.34). Patients in the seizure group had a significantly higher temperature at home than controls before hospitalization (39.4 versus 38.8 degrees C). Our findings of higher temperatures in children with febrile seizures supports its importance as the most important triggering factor in febrile convulsions.

Bacterial Infections↗
PubMed1996

[Incidence of hip fracture and prognosis in Ehime Prefecture].

Hip fracture among the elderly has increasingly attracted public health concern in Japan. For the purpose of revealing the epidemiological features of hip fracture, post-treatment prognosis, and related factors, we studied all cases of hip fracture which occurred in Ehime Prefecture during 1992 who were admitted to hospitals or clinics, and followed up the cases for a subsequent two years. The incidence rate of hip fracture was 29.2 per 100,000 for males, and 84.0 for females, which are much lower than in Europe and the Untied States. Compared with rates reported previously in Japan, the age--specific incidence rates for males in Ehime were almost identical to the respective rates estimated by a nationwide survey and the rates for Tottori. However, the rate for males 80 years old or more was found to be lower than the corresponding rate for Kagawa. In females, the age--specific incidence rates for Ehime were similar to the Japanese averages, and the rates for Tottori and Kagawa. Falling from a standing position was a leading cause of hip fracture among older patients. Osteosynthesis was the main treatment modality elected trochanteric fractures. On the other hand, prosthetic replacement was predominant in cervical fracture. Multivariate analysis using a multiple logistic model showed that medical facility category, age, type of treatment, and cause of fracture had statistically significant relations to mobility at the time of discharge. Of patients who could walk at the time of discharge, 83.7% (159/190) were alive two years after discharge. Multiple logistic model analysis identified gender as a significant contributing factor to this mortality. Among the survivors, 81.8% (130/159) retain the ability to walk. Logistic model analysis revealed that older age experience a significantly higher risk in losing mobility.

Adult↗
PubMed2004

[Growth feature of biomass of Lemna aequinoctialis and Spirodela polyrrhiza in medium with nutrient character of wastewater].

Duckweeds have an important potential in nutrient recovery from wastewater because of their rapid multiplication and high protein content in biomass. The growth rate of duckweed biomass has a direct relationship with nutrient removal and recovery. With laboratory experiments of batch culture and continuous culture, the growth curves of two duckweed species, Lemna aequinoctialis and Spirodela polyrrhiza, cultivated in different media were gotten and fitted by Logistic model. The effect of nitrogen on growth of duckweed was evaluated. Experimental results indicated that the growth curve had characteristic of sigmoidal shape and the growth rate had density-dependent characteristic. Results of statistical analysis demonstrated that Logistic model is suitable to describe the growth of single duckweed specie. The maximal growth rate from regression in medium with ammonia nitrogen was lower than those in medium with nitrate nitrogen. The maximal growth rate of Lemna aequinoctialis was higher than Spirodela polyrrhiza The paper also discussed the application of Logistic model in harvesting of duckweed biomass from wastewater.

Araceae↗
PubMed2006

Development and validation of pheochromocytoma of the adrenal gland scaled score for predicting malignant pheochromocytomas.

OBJECTIVES: To evaluate the diagnostic performances of the pheochromocytoma of the adrenal gland scaled score (PASS) proposed in a previous report and that of a logistic model developed in this investigation. METHODS: In all 130 patients with malignant or assumed benign pheochromocytomas, 15 predictive variables were observed. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of PASS. The logistic model was developed using the 15 predictive variables. Its performance was evaluated by calculating the area under the ROC curve and comparing it with that of the PASS. RESULTS: The PASS had the area under the ROC curve of 0.899 (95% confidence interval 0.844 to 0.954). Of the 15 variables entered in the logistic regression analysis, 9 were retained in the model. The area under the ROC curve for the logistic model was 0.983 (95% confidence interval 0.967 to 0.998). CONCLUSIONS: ROC analysis indicated that the PASS could be used for the diagnosis of malignant pheochromocytomas. The logistic model was able to improve the diagnostic performance of the PASS using a different variable weighting method. We emphasize, however, that a clinical prospective evaluation is needed to confirm their actual value.

Adrenal Gland Neoplasms↗
PubMed1995

D-dimer improves the prognostic value of combined clinical and laboratory data in equine gastrointestinal colic.

The discriminating ability of 15 parameters alone or in combinations, including results from analysis of plasma endotoxin, the Nycomed plasma D-Dimer test and phospholipase A2, were analyzed to predict morbidity and mortality in equine gastrointestinal colic. Endotoxaemia was a characteristic feature of the colic horses. The problem of adequately predicting nonsurvivors among colic horses required several parameters to be included in the logistic model: if the "classical parameters", (heart rate, respiratory rate, PCV, anion gap) were included in the model, addition of plasma D-dimer, phospholipase A2, and Cl- significantly improved the predictive value of the logistic model. Increasing heart rate and D-dimer together with decreasing chloride was a risk factor for nonsurvival. The sensitivity of this three-parameter logistic model to predict nonsurvival was 78% and specificity 77%. The Nycomed D-Dimer test is recommended as a horse-site test to predict disseminated intravascular coagulation and nonsurvival in equine colic.

Animals↗
PubMed1996

Effect of pre- and post-heat shock temperature on the persistence of thermotolerance and heat shock-induced proteins in Listeria monocytogenes.

The effect of incubation temperature, before and after a heat shock, on thermotolerance of Listeria monocytogenes at 58 degrees C was investigated. Exposing cells grown at 10 degrees C and 30 degrees C to a heat shock resulted in similar rises in thermotolerance while the increase was significantly higher when cells were grown at 4 degrees C prior to the heat shock. Cells held at 4 degrees C and 10 degrees C after heat shock maintained heat shock-induced thermotolerance for longer than cells held at 30 degrees C. The growth temperature prior to inactivation had negligible effect on the persistence of heat shock-induced thermotolerance. Concurrent with measurements of thermotolerance were measurements of the levels of heat shock-induced proteins. Major proteins showing increased synthesis upon the heat shock had approximate molecular weights of 84, 74, 63, 25 and 19 kDa. There was little correlation between the loss of thermotolerance after the heat shock and the levels of these proteins. Thermotolerance of heat shocked and non-heat shocked cells was described by traditional log-linear kinetics and a model describing a sigmoidal death curve (logistic model). Employing log-linear kinetics resulted in a poor fit to a major part of the data whereas a good fit was achieved by the use of a logistic model.

Bacterial Proteins↗
PubMed1989

The ordered logistic regression model in psychiatry: rising prevalence of dementia in old people's homes.

Ordered logistic regression is an extension of binary logistic regression, and is particularly well suited to the analysis of many psychiatric scores. Its use is demonstrated in a pair of linked cross-sectional surveys of dementia in residents of old people's homes, first to model the association of dementia with demographic characteristics, and then to explore possible reasons for a rise in the prevalence of dementia in the homes over a four-year period.

Age Factors↗
PubMed2006

Prediction of Lyme meningitis in children from a Lyme disease-endemic region: a logistic-regression model using history, physical, and laboratory findings.

BACKGROUND: Differentiating Lyme meningitis (LM) from other forms of aseptic meningitis (AM) in children is a common diagnostic dilemma in Lyme disease-endemic regions. Prior studies have compared clinical characteristics of patients with LM versus patients with documented enteroviral infections. No large studies have compared patients with LM to all patients presenting with AM and attempted to define a clinical prediction model. OBJECTIVE: To create a statistical model to predict LM versus AM in children based on history, physical, and laboratory findings during the initial presentation of meningitis. METHODS: Children older than 2 years presenting to the Alfred I. duPont Hospital for Children between October 1999 and September 2004 were identified if both Lyme serology and cerebrospinal fluid (CSF) were collected during the same hospital encounter. Patients were considered to have Lyme disease only if they met Centers for Disease Control and Prevention criteria (documented erythema migrans and/or positive Lyme serology). Patients were eligible for study inclusion if they had documented meningitis (CSF white blood cell count: >8 per mm3). Retrospective chart review abstracted duration of headache and cranial neuritis (papilledema or cranial nerve palsy) on physical examination and percent CSF mononuclear cells. Using logistic-regression analysis, the type of meningitis (LM versus AM) was simultaneously regressed on these 3 variables. The Hosmer-Lemeshow test was performed and the area under the receiver operating characteristic curve was calculated. RESULTS: A total of 175 children with meningitis were included in the final statistical model. Logistic-regression analysis included 27 patients with LM and 148 patients classified as having AM. Duration of headache, cranial neuritis, and percent CSF mononuclear cells independently predicted LM. The Hosmer-Lemeshow test revealed a good fit for the model, and the Nagelkerke R2 effect size demonstrated good predictive efficacy. Odds ratios based on the logistic-regression results were calculated for these variables. The final model was transformed into a clinical prediction model that allows practitioners to calculate the probability of a child having LM. CONCLUSIONS: Longer duration of headache, presence of cranial neuritis, and predominance of CSF mononuclear cells are predictive of LM in children presenting with meningitis in a Lyme disease-endemic region. The clinical prediction model can help guide the clinician about the need for parenteral antibiotics while awaiting serology results.

Child↗
PubMed1996

A simulation study of the number of events per variable in logistic regression analysis.

We performed a Monte Carlo study to evaluate the effect of the number of events per variable (EPV) analyzed in logistic regression analysis. The simulations were based on data from a cardiac trial of 673 patients in which 252 deaths occurred and seven variables were cogent predictors of mortality; the number of events per predictive variable was (252/7 =) 36 for the full sample. For the simulations, at values of EPV = 2, 5, 10, 15, 20, and 25, we randomly generated 500 samples of the 673 patients, chosen with replacement, according to a logistic model derived from the full sample. Simulation results for the regression coefficients for each variable in each group of 500 samples were compared for bias, precision, and significance testing against the results of the model fitted to the original sample. For EPV values of 10 or greater, no major problems occurred. For EPV values less than 10, however, the regression coefficients were biased in both positive and negative directions; the large sample variance estimates from the logistic model both overestimated and underestimated the sample variance of the regression coefficients; the 90% confidence limits about the estimated values did not have proper coverage; the Wald statistic was conservative under the null hypothesis; and paradoxical associations (significance in the wrong direction) were increased. Although other factors (such as the total number of events, or sample size) may influence the validity of the logistic model, our findings indicate that low EPV can lead to major problems.

Bias↗
PubMed2006

Multinomial logistic regression approach to haplotype association analysis in population-based case-control studies.

BACKGROUND: The genetic association analysis using haplotypes as basic genetic units is anticipated to be a powerful strategy towards the discovery of genes predisposing human complex diseases. In particular, the increasing availability of high-resolution genetic markers such as the single-nucleotide polymorphisms (SNPs) has made haplotype-based association analysis an attractive alternative to single marker analysis. RESULTS: We consider haplotype association analysis under the population-based case-control study design. A multinomial logistic model is proposed for haplotype analysis with unphased genotype data, which can be decomposed into a prospective logistic model for disease risk as well as a model for the haplotype-pair distribution in the control population. Environmental factors can be readily incorporated and hence the haplotype-environment interaction can be assessed in the proposed model. The maximum likelihood estimation with unphased genotype data can be conveniently implemented in the proposed model by applying the EM algorithm to a prospective multinomial logistic regression model and ignoring the case-control design. We apply the proposed method to the hypertriglyceridemia study and identifies 3 haplotypes in the apolipoprotein A5 gene that are associated with increased risk for hypertriglyceridemia. A haplotype-age interaction effect is also identified. Simulation studies show that the proposed estimator has satisfactory finite-sample performances. CONCLUSION: Our results suggest that the proposed method can serve as a useful alternative to existing methods and a reliable tool for the case-control haplotype-based association analysis.

Algorithms↗
PubMed2006

Conventional, emerging, heredity, lifestyle, and psychosocial coronary risk factors: relationships to subclinical atherosclerosis.

The authors examined the relationship between calcified coronary atherosclerosis and an array of cardiovascular risk factors in sequential logistic models to determine the extent to which these markers overlap in their identification of patients at risk for developing coronary heart disease. The prevalence of coronary artery calcium using electron beam computed tomography was 19.4% in this cross-sectional study of a prospective, consecutive, screening cohort of 1999 healthy United States Army personnel (aged 39-50 years). The proportion of the total variance of coronary artery calcium explained by sequential logistic models incorporating conventional, emerging, hereditary, lifestyle, and psychosocial cardiovascular risk variables increased progressively from 9.7% to 14.5%. The best-fit logistic model for the prediction of coronary artery calcium identified age, male gender, Framingham risk score, total cholesterol, high-density lipoprotein cholesterol, triglycerides, smoking, a family history of coronary heart disease, white race, physical inactivity, and lower depression scores as significant independent correlates of coronary artery calcium. These data indicate that the explanatory power of models for atherosclerosis can be significantly improved with the use of emerging, heredity, lifestyle, and psychosocial factors. The large residual variance, however, supports the potential of atherosclerosis imaging to incrementally and independently identify coronary heart disease risk.

Adult↗
PubMed2000

Discrimination between neoplastic and nonneoplastic brain lesions by use of proton MR spectroscopy: the limits of accuracy with a logistic regression model.

BACKGROUND AND PURPOSE: The most accurate method of clinical MR spectroscopy (MRS) interpretation remains an open question. We sought to construct a logistic regression (LR) pattern recognition model for the discrimination of neoplastic from nonneoplastic brain lesions with MR imaging-guided single-voxel proton MRS data. We compared the LR sensitivity, specificity, and receiver operator characteristic (ROC) curve area (Az) with the sensitivity and specificity of blinded and unblinded qualitative MRS interpretations and a choline (Cho)/N-acetylaspartate (NAA) amplitude ratio criterion. METHODS: Consecutive patients with suspected brain neoplasms or recurrent neoplasia referred for MRS were enrolled once final diagnoses were established by histopathologic examination or serial neurologic examinations, laboratory data, and imaging studies. Control spectra from healthy adult volunteers were included. An LR model was constructed with 10 input variables, including seven metabolite resonance amplitudes, unsuppressed brain water content, water line width, and the final diagnosis (neoplasm versus nonneoplasm). The LR model output was the probability of tumor, for which a cutoff value was chosen to obtain comparable sensitivity and specificity. The LR sensitivity and specificity were compared with those of qualitative blinded interpretations from two readers (designated A and B), qualitative unblinded interpretations (in aggregate) from a group of five staff neuroradiologists and a spectroscopist, and a quantitative Cho/NAA amplitude ratio > 1 threshold for tumor. Sensitivities and specificities for each method were compared with McNemar's chi square analysis for binary tests and matched data with a significance level of 5%. ROC analyses were performed where possible, and Az values were compared with Metz's method (CORROC2) with a 5% significance level. RESULTS: Of the 99 cases enrolled, 86 had neoplasms and 13 had nonneoplastic diagnoses. The discrimination of neoplastic from control spectra was trivial with the LR, reflecting high homogeneity among the control spectra. An LR cutoff probability for tumor of 0.8 yielded a specificity of 87%, a comparable sensitivity of 85%, and an area under the ROC curve of 0.96. Sensitivities, specificities, and ROC areas (where available) for the other methods were, on average, 82%, 74%, and 0.82, respectively, for readers A and B, 89% (sensitivity) and 92% (specificity) for the group of unblinded readers, and 79% (sensitivity), 77% (specificity), and 0.84 (Az) for the Cho/NAA > 1 criterion. McNemar's analysis yielded significant differences in sensitivity (n approximately 86 neoplasms) between the LR and reader A, and between the LR and the Cho/NAA > 1 criterion. The differences in specificity between the LR and all other methods were not significant (n approximately 13 nonneoplasms). Metz's analysis revealed a significant difference in Az between the LR and the Cho/NAA ratio criterion.

Adolescent↗
PubMed1986

Frequency-dependent selection in logistic growth models.

This paper describes the dynamics of a continuously reproducing diploid population with two alleles at one locus. The dependent variables are allele frequency and population density. We modify the basic density-dependent logistic growth model by inserting three possible types of frequency dependence in the fitness functions. These models are analyzed and contrasted with the purely density-dependent situation. Examples are given of periodic fluctuations in allele frequency and population density, which would be impossible for purely density-dependent fitness functions.

Animals↗