Biomedical subjects

T G Tape

Publications and source records attributed to T G Tape.

25 records · Page 2Linked to original sources

PubMedDate not supplied

Echocardiography, endocarditis, and clinical information bias.

Although clinical information provided to the interpreter of imaging tests may improve disease detection, it may also bias the interpreter towards certain diagnoses, increasing the chance of false positives. To determine the possibility of this bias, the authors studied patients who were referred for echocardiography with a clinical suspicion of endocarditis. Hospital charts from a two-year period were reviewed to determine clinical data available to the echocardiographer, echocardiogram results, and the final diagnosis. Four clinical features, when present at the time of echocardiography, were associated with increased numbers of false-positive results. Test specificity was 97% (34/35) for patients without any of these features, but dropped to 80% (16/20) when two or more features were present. The authors conclude that clinical information may bias echocardiogram interpretations such that both test specificity and the posttest probability of disease may be overestimated when tests are used in clinical practice.

Echocardiography↗

PubMedDate not supplied

Medical students' and residents' estimates of cardiac risk.

Resident physicians' and medical students' perceptions of atherosclerotic heart disease (ASHD) risks and their understanding of risk appraisal concepts were studied. Subjects estimated the average risks of death from ASHD, from motor vehicle accidents, and from all causes for men in three age groups. Given a patient with severe hypertension, they then estimated relative risk and used their estimates to calculate individual patient risks. Risk estimates varied widely. Only 36% of the subjects were consistently accurate estimators of ASHD and all-causes risks. Subjects who had family histories of heart disease performed significantly better than others. Only about half the subjects were able to compute the hypertensive patient's risk correctly. Thus, residents and students were not adept at estimating the average risks of death from various causes or using the estimates to assess a patient's risk. Better physician understanding of these concepts might lead to improved patient counseling in risk factor reduction.

Accidents, Traffic↗

PubMedDate not supplied

Use of clinical judgment analysis to explain regional variations in physicians' accuracies in diagnosing pneumonia.

The authors sought to explain regional differences in physicians' accuracies in diagnosing pneumonia by prospectively studying emergency department patients at three sites and analyzing differences in physicians' diagnostic strategies and patient characteristics. They enrolled 1,119 Illinois patients, 150 Nebraska patients, and 142 Virginia patients presenting with fever or respiratory symptoms for whom physicians ordered a chest radiograph because of suspicion of pneumonia. Emergency department physicians recorded patients' clinical findings and estimated the probability that a chest radiograph would show pneumonia. A measure of accuracy, the correlation between physicians' probability estimates and actual outcomes, was 0.41 (95% CI 0.36-0.46) at Illinois, 0.66 (95% CI 0.54-0.75) at Nebraska, and 0.55 (95% CI 0.42-0.65) at Virginia. Physicians' strategies at the three sites differed markedly in their weightings of asthma, signs of consolidation, cough, tachypnea, age, and gender. These differences in weighting paralleled differences in the optimal clinical strategies derived from patient data at the three sites. Differences in diagnostic accuracy were best explained by differences in the difficulties of diagnosing pneumonia in the populations. Physicians at each site used clinical findings in a way that was close to optimal for their location. This type of analysis provides a new tool for understanding the sources of regional variations in clinical practice.

Adult↗

PubMedDate not supplied

Relation of physicians' predicted probabilities of pneumonia to their utilities for ordering chest x-rays to detect pneumonia.

To investigate the relation between physicians' predicted probabilities of pneumonia and their utilities for ordering chest x-rays to detect pneumonia, the authors studied 52 physicians who ordered chest x-rays of 886 patients presenting to an emergency department with fever or respiratory complaints. Physicians estimated the probability of pneumonia prior to obtaining the results of the chest x-ray. Utilities were assessed by asking physicians to consider a hypothetical patient presenting with acute respiratory symptoms, with unknown chest x-ray status, and to rank on a scale from +50 ("best thing I could do") to -50 ("worst thing I could do") their rating scale utilities for not diagnosing pneumonia and not ordering a chest x-ray when the patient had pneumonia (i.e., missing a pneumonia), and for diagnosing pneumonia and ordering a chest x-ray when the patient did not have pneumonia (i.e., ordering an unnecessary x-ray). The utility for ordering an unnecessary x-ray was negatively correlated with average predicted probability (r = -0.1495, p = 0.29), whereas the utility for missing a pneumonia was positively correlated with average predicted probability (r = 0.2254, p = 0.11), although the correlations were not statistically significant. Relative chagrin, defined as the difference in these utilities, was significantly inversely correlated with average predicted probability (r = -0.2992, p less than 0.035), even after adjusting for the prevalence of pneumonia seen by each physician (partial r = -0.42, p less than 0.0027). It is concluded that physicians who experienced greater regret over missing a pneumonia than over ordering an unnecessary x-ray estimated lower probabilities of pneumonia for patients for whom they ordered x-rays.(ABSTRACT TRUNCATED AT 250 WORDS)

Cost-Benefit Analysis↗

PubMedDate not supplied

Comparing methods of learning clinical prediction from case simulations.

Feedback to physicians about how they use information in making judgments can improve the quality of their judgments, but questions remain about which types of feedback are most effective. The authors conducted a controlled study of feedback in 60 medical students learning to predict the risk of cardiovascular death based on the presence or absence of five risk factors. After a pretest of 40 cases abstracted from patient records, the students worked through 173 computer-simulated cases and a posttest of 40 patient cases. The students received no feedback, probability feedback (correct probability of cardiac death for each case), cognitive feedback (the correct cue weights compared with their own weights derived from the previous set of cases), or both types of feedback. Students who received probability feedback markedly improved both base rate calibration and discrimination. Those who received only cognitive feedback showed no improvement over control on any of the measures of learning. All subjects were highly consistent in their weightings. The superiority of probability feedback differed from previous findings that cognitive feedback was essential for mastery of multiple-cue-probability learning tasks. The information on cue-outcome relationships given by cognitive feedback may be more useful when these relationships are complex and the combining rule is not known, while the precise outcome information provided by probabilistic feedback is more useful when the combining rule is known and the cue-outcome relationships are straightforward. Thus, the optimal method of learning depends on the nature of the task.

Adult↗

PubMedDate not supplied

Reproducibility of predictor variables from a validated clinical rule.

It has been suggested that clinical prediction rules are not reproducible, and that the most important variables frequently do not appear in replicate models. The authors studied the reproducibility of a validated rule for predicting radiographic evidence of pneumonia (ROC areas for the training and validation cohorts, 0.816 and 0.821, respectively). Two hundred replicate samples of size 250 and size 500 were generated by sampling without replacement from the original training cohort of 905 patients with a 14.6% prevalence of pneumonia. Forward selection was performed among 31 candidate variables by stepwise logistic regression. Using as reproducibility criteria: 1) inclusion of all five variables from the original model in the original order; 2) inclusion of all five variables in any order; 3) inclusion of the first three variables; 4) inclusion of the first two variables; 5) inclusion of the first variable; and 6) inclusion of any of the five variables: 2.5%, 13.5%, 48.5%, 85.5%, 98.0%, and 100% of replicate models of sample size 500, respectively, met the criteria, whereas 0%, 0%, 16.5%, 49.0%, 71.5%, and 97.5% of models of sample size 250 met the criteria (all comparisons by sample size p < .0001 except for criteria 1 and 6, p = 0.07). Mean ROC areas in the training and validation samples were 0.829 and 0.791 for replicate models of sample size 500, and 0.831 and 0.779 for models of sample size 250. There was no significant difference in ROC areas between training and validation cohorts for 80.5% of models of sample size 500, and for 75.3% of models of sample size 250.(ABSTRACT TRUNCATED AT 250 WORDS)

Ambulatory Care↗

PubMedDate not supplied

Advance directives: a policy-capturing approach.

Policy capturing was used to provide insight into those factors that people consider important in the decision of whether to accept life-sustaining medical treatment. First, open-ended interviews with community-dwelling elderly persons (n = 30) were conducted to determine the factors they would consider when drafting an advance directive. College students (n = 53) then made judgments as to whether they would accept life-sustaining treatment for each of 100 hypothetical vignettes comprising a similar set of factors. Results revealed that 1) students made consistent judgments, 2) there was considerable variability in their mean judgments, 3) the most influential factors were mental and physical functioning, 4) mental and physical functioning had an interactive effect on judgments, and 5) subjective estimates of importance were significantly related to policy-capturing weights. This approach for studying the relationship of individuals' values to their acceptance of life-sustaining therapy may be useful in future studies of patient and surrogate decision making.

Advance Directives↗