PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “forecasting”

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 1,099 records · Page 61Linked to original sources
PubMed1999

Positive Illusions and Forecasting Errors in Mutual Fund Investment Decisions.

This study examines the portfolio allocation decisions of 80 business students in a computer-based investing simulation. Our goal was to better understand why investors spend so much time and money on actively managed mutual funds despite the fact that the vast majority of these funds are outperformed by pas sively managed index funds. Participants' judgments and decisions provided evidence for a number of biases. First, most participants consistently overestimated both the future perfor mance and the past performance of their investments. Second, participants overestimated the intertemporal consistency of portfolio performance. Third, participants were more likely to shift their portfolio allocation following poorer performance than following better performance, and this tendency had a negative impact on portfolio returns. We speculate that these biases in investor behavior may contribute to suboptimal investment decisions in real financial markets. Copyright 1999 Academic Press.

Journal Article↗
PubMed1993

Fracture of the distal forearm as a forecaster of subsequent hip fracture: a population-based cohort study with 24 years of follow-up.

OBJECTIVE: To determine the long-term risk of hip fracture following fracture of the distal forearm. DESIGN: Registry-based cohort study comparing patients with a fracture of the distal forearm with a population-based cohort. FRACTURE COHORT: All women and men above 40 years of age with a radiologically verified fracture of the distal forearm during a 5-year period, 1968-1972, in all 1,126 women and 212 men. CONTROL COHORT: An equal number of population-based, age- and sex-matched control persons selected from a population register. MEASUREMENTS: All cohort members were followed up individually through record linkage until the first hip fracture, emigration, death, or the end of 1991. The cohort members contributed a total of 40,832 person-years of observation, and altogether 365 cases of hip fractures were observed. RESULTS: Both women and men with a fracture of the distal forearm ran an increased risk of sustaining a subsequent hip fracture. The overall relative hazard for the women was 1.54 and for men 2.27. The increased risk in the women was independent of age at inclusion, but that in the men was more pronounced in the younger age groups. CONCLUSIONS: Patients with a fracture of the distal forearm run an increased risk of sustaining a subsequent hip fracture. They therefore appear to constitute a group in which appropriate prophylactic measures against osteoporosis and fractures should be considered.

Adult↗
PubMed1991

In vitro forecasting of drugs which may interfere with the biotransformation of midazolam.

The biotransformation of midazolam is mediated by a cytochrome P-450 isozyme (P-450 IIIA) whose activity is highly variable. The kinetics of the 1'- and 4-hydroxylation of midazolam, the major routes of midazolam oxidation, by human liver microsomes have been examined to characterize further the cytochrome isozyme(s) catalysing these reactions, and to screen for drugs that might interfere with them. In hepatic microsomal preparation from two kidney donors (extensive and poor metabolisers of debrisoquine) KM values for 1'-hydroxylation were 4.2 and 6.1 microM (extensive and poor metabolisers, respectively), and for the 4-hydroxylation they were 14.7 and 18.1 microM, respectively. The corresponding Vmax values were 25.8 and 29.8 and 17.0 and 18.1 nmol.mg P-1.h-1. Both reactions appeared to be catalysed by the same or by coregulated isozymes. Midazolam hydroxylations in vitro are inhibited by many drugs, including nifedipine and other dihydropyridine-type calcium channel blockers, ergot alkaloids, cyclosporine, erythromycin and phenothiazine-type neuroleptics. A clinical case report illustrates the consequence of such a drug-drug interference with hepatic biotransformation; midazolam-induced sleep in a patient lasted for 6 days (t1/2 = 25 h).

Biotransformation↗
PubMed1985

Performance of Bayesian feedback to forecast lidocaine serum concentration: evaluation of the prediction error and the prediction interval.

The prediction performance of the Bayesian feedback method was evaluated with respect to accuracy and precision, and efficacy and safety (width of the prediction interval) on the basis of 90 predictions in 30 patients treated with lidocaine. The mean of the prediction error (PE) and the root mean squared error (RMSE) served as a measure of accuracy and precision. The variance of the standardized prediction error (SPE) was used to evaluate the estimate of the standard deviation of the prediction error. SPE was defined as PE divided by the standard deviation of the predicted concentration. The standard error of RMSE and of the variance of SPE was determined by bootstrap. The results indicate that the lidocaine serum concentration at 12 hr (C2) after starting continuous infusion can be predicted with high accuracy and precision with a single feedback measurement obtained 2-4 hr (C1) after commencement of treatment: RMSE = 20.6%. Prediction at 24 hr (C3) was less accurate: RMSE = 31.4%. Using both C1 and C2 to predict C3 improved precision (RMSE = 23.4%). The evaluation of the prediction interval revealed that the current algorithm produces an upward biased estimate, probably due to a positive bias in the estimate of the covariance matrix of the parameter estimates. It is suggested that evaluation of prediction performance should include the estimate of the prediction interval.

Bayes Theorem↗
PubMed1993

Meteorotropy and medical-meteorological forecasts.

The meteorotropic reaction of the human organism is a function of different factors, such as the type and intensity of the effects of the physical environment as well as individual conditions like adaptive capacity and state of health. Many medical-meteorological studies show causal correlations between conditions in the lower atmosphere and reactions of the human organism, but also combined or synergistic effects of different weather situations, which can only be proved stochastically. These effects are described and the methodology of the investigations, as well as the results, critically discussed. Furthermore, application of the results in the areas of medical-meteorological consultation, with the goal of improving living conditions, is considered.

Climate↗
PubMed1984

Analysis, forecasting, and control of three-dimensional tumor growth and treatment.

The main point of this contribution is to show how ideas of control theory, automata theory and computer science can be applied to the field of cancer research. We are stressing the modelling of three-dimensional tumor growth and the simulation of different kinds of tumor therapy (surgery, radiation therapy, chemotherapy). In the future it will be possible to schedule the optimized methods and time of tumor treatment by computer simulation prior to clinical therapy.

Cell Communication↗
PubMedDate not supplied

In vitro forecasting of drugs that may interfere with codeine bioactivation.

The O-demethylation of codeine (methylmorphine) into morphine is mediated by the polymorphic cytochrome P450 DB1 (P450 IID6). By means of in vitro screening in human liver microsomes we have studied the effect on codeine bioactivation of several drugs used as analgesics or as adjuvants for pain control. In microsomes from an extensive metabolizer subject, paracetamol (acetaminophen) and NSAIDs (acetylsalicylic acid, diclofenac, indomethacin, piroxicam, and pirprofen), benzodiazepines (chlordiazepoxide, clonazepam, diazepam, flunitrazepam, and midazolam), and anticonvulsants (carbamazepine and phenytoin) did not alter the reaction. There was marked inhibition of in vitro morphine production by neuroleptics (chlorpromazine, haloperidol, levomepromazine, and thioridazine), metoclopramide, and tricyclic antidepressants (amitriptyline, clomipramine, desipramine, imipramine, and nortriptyline). Enzyme kinetics showed competitive inhibition by neuroleptics (chlorpromazine Ki = 0.5 microM) and antidepressants (clomipramine Ki = 6.8 microM), which are substrates of the polymorphic monooxygenase. Due to the low affinity of codeine for P450 DB1 (Km = 100-200 microM), its bioactivation in extensive metabolizers, and thus its analgesic efficacy, is liable to vary greatly when it is combined with any drug that has a high affinity for the polymorphic isozyme.

Acetaminophen↗
PubMedDate not supplied

A population approach to the forecasting of amikacin plasma and urinary levels using a prescribed dosage regimen.

We retrospectively analyzed amikacin pharmacokinetics in 19 critically ill patients who received amikacin intravenously. Fourteen subjects (577 serum amikacin concentrations, 167 urine measurements) were studied to obtain data for population modeling, while 5 patients (267 serum amikacin concentrations, 68 urine measurements) were studied for the assessment of predictive performance. The population analysis was performed using serum and urine amikacin measurements; the renal clearance of amikacin was expressed as a function of creatinine clearance. A two-compartment model was fitted to the population data by using NONMEM. The population characteristics of the pharmacokinetic parameters (fixed and random effects) were estimated using the FOCE method. The population pharmacokinetic parameters with the interindividual variability (CV%) were as follows: slope (0.254, 126%) and intercept (3 l/h, 59.6%) of the linear model which relate the amikacin renal clearance to the creatinine clearance, initial volume of distribution (17.1 l, 22.2%), intercompartment clearance (5.22 l/h, 104%), steady state volume of distribution (55.2 l, 64.1%) and urinary elimination (67.5%, 36.3%). The Bayesian approach developed in this study accurately predicts amikacin concentrations in serum and urine and allows for the estimation of amikacin pharmacokinetic parameters, minimizing the risk of bias in the prediction.

Amikacin↗