Diagnostic reasoning in cardiovascular medicine

ABSTRACT Research in cognitive psychology shows that expert clinicians make a medical diagnosis through a two step process of hypothesis generation and hypothesis testing. Experts generate a list of possible diagnoses quickly and intuitively, drawing on previous experience. Experts remember specific examples of various disease categories as exemplars, which enables rapid access to diagnostic possibilities and gives them an intuitive sense of the base rates of various diagnoses. After generating diagnostic hypotheses, clinicians then test the hypotheses and subjectively estimate the probability of each diagnostic possibility by using a heuristic called anchoring and adjusting. Although both novices and experts use this two step diagnostic process, experts distinguish themselves as better diagnosticians through their ability to mobilize experiential knowledge in a manner that is content specific. Experience is clearly the best teacher, but some educational strategies have been shown to modestly improve diagnostic accuracy. Increased knowledge about the cognitive psychology of the diagnostic process and the pitfalls inherent in the process may inform clinical teachers and help learners and clinicians to improve the accuracy of diagnostic reasoning. This article reviews the literature on the cognitive psychology of diagnostic reasoning in the context of cardiovascular disease.

Univariate and Multivariate Base Rates of Score Elevations, Reliable Change, and Inter-Rater Discrepancies in the BRIEF-A Standardization Samples

The Behavior Rating Inventory of Executive Function–Adult Version (BRIEF-A) is a standardized rating scale of subjective executive functioning. We provide univariate and multivariate base rates (BRs) for scale/index scores in the clinical range ( T scores ≥65), reliable change, and inter-rater information not included in the Professional Manual. Participants were adults (ages = 18–90 years) from the BRIEF-A self-report ( N = 1,050) and informant report ( N = 1,200) standardization samples, as well as test–retest ( n = 50 for self, n = 44 for informant) and inter-rater ( n = 180) samples. Univariate BRs of elevated T scores were low (self-report = 3.3%–15.4%, informant report = 4.5%–16.3%). Multivariate BRs revealed the common occurrence of obtaining at least one elevated T-score across scales (self-report = 26.5%–37.3%, informant report = 22.7%–30.3%), whereas virtually none had elevated scores on all scales. Test–retest scores were highly correlated (self = .82–.94; informant = .91–.96). Inter-rater correlations ranged from .44 to .68. Significant ( p < .05) test–retest T-score differences ranged from 7 to 12 for self-report, from 6 to 8 for informant report, and from 16 to 21 points for inter-rater T-score differences. Applications of these findings are discussed.

Experts use base rates in real-world sequential decisions

Human behavior is often assumed to be irrational, full of errors, and affected by cognitive biases. One of these biases is base-rate neglect, which happens when the base rates of a specific category are not considered when making decisions. We argue here that while naïve subjects demonstrate base-rate neglect in laboratory conditions, experts tested in the real world do use base rates. Our explanation is that lab studies use single questions, whereas, in the real world, most decisions are sequential in nature, leading to a more realistic test of base-rate use. One decision that lends itself to testing base-rate use in real life occurs in beach volleyball—specifically, deciding to whom to serve to win the game. Analyzing the sequential choices in expert athletes in more than 1,300 games revealed that they were sensitive to base rates and adapted their decision strategies to the performance of the opponent. Our data describes a threshold at which players change their strategy and use base rates. We conclude that the debate over whether decision makers use base rates should be shifted to real-world tests, and the focus should be on when and how base rates are used.

Clinical Assessment of Visual Motion Perception in Children With Brain Damage: A Comparison With Base Rates and Control Sample

Aim: In this study, we examined (1) the presence of abnormally low scores (below 10th percentile) in various visual motion perception aspects in children with brain damage, while controlling for their cognitive developmental delay; (2) whether the risk is increased in comparison with the observation and expectation in a healthy control group and healthy population.Methods: Performance levels of 46 children with indications of brain damage (Mage = 7y4m, SD = 2y4m) on three visual motion perception aspects (global motion, motion speed, motion-defined form) were evaluated. We used developmental age as entry of a preliminary reference table to classify the patient’s performance levels. Then we compared the percentages of abnormally low scores with percentages expected in the healthy population using estimated base rates and the observed percentages in the control sample (n = 119).Results: When using developmental age as reference level, the percentage of low scores on at least one of the three tasks was significantly higher than expected in the healthy population [19/46, 41% (95%CI: 28–56%), p = 0.03]. In 15/19 (79% [95%CI: 61–97%] patients only one aspect of motion perception was affected. Four patients performed abnormally low on two out of three tasks, which is also higher than expected (4/46, 8.7%, 95%CI: 2.4–20.8% vs. 2.1%; z = 2.61, p &lt; 0.01). The observed percentages in the patient group were also higher than found in the control group.Interpretation: There is some evidence that children with early brain damage have an increased risk of isolated and combined motion perception problems, independent of their performance IQ.

Cognitive Impairment in Late-Life Depression: A Comparative Study of Healthy Older People, Late-Life Depression, and Mild Alzheimer's Disease Using Multivariate Base Rates of Low Scores

Late-Life Depression (LLD) is often associated with cognitive impairment. However, distinction between cognitive impairment due to LLD and those due to normal aging or mild Alzheimer's Disease (AD) remain difficult. The aim of this study was to present and compare the multivariate base rates of low scores in LLD, mild AD, and healthy control groups on a battery of neuropsychological tests. Participants (ages 60–89) were 352 older healthy adults, 390 patients with LLD, and 234 patients with mild AD (i.e., MMSE ≥ 20). Multivariate base rates of low scores (i.e., ≤ 5th percentile) were calculated for each participant group within different cognitive domains (verbal episodic memory, executive skills, mental processing speed, constructional praxis, and language/semantic memory). Obtaining at least one low score was relatively common in healthy older people controls (from 9.4 to 17.6%), and may thus result in a large number of false positives. By contrast, having at least two low scores was unusual (from 0.3 to 4.6%) and seems to be a more reliable criterion for identifying cognitive impairment in LLD. Having at least three low memory scores was poorly associated with LLD (5.9%) compared to mild AD (76.1%) and may provide a useful way to differentiate between these two conditions [χ(1)2 = 329.8, p &lt; 0.001; Odds Ratio = 50.7, 95% CI = 38.2–77.5]. The multivariate base rate information about low scores in healthy older people and mild AD may help clinicians to identify cognitive impairments in LLD patients, improve the clinical decision-making, and target those who require regular cognitive and clinical follow-up.