D R Holleman1, D L Simel. 1. Medical Service, Lexington Veterans Affairs Medical Center, KY 40511, USA.
Abstract
OBJECTIVE: To describe strategies for using multiple clinical examination items to estimate disease probabilities; and to evaluate the diagnostic accuracy of each strategy. DESIGN: Prospective observational study. SETTING: Medical preoperative evaluation clinic at a university-affiliated Veterans Affairs Medical Center. PATIENTS: Previously reported consecutive series of patients referred for outpatient medical preoperative risk assessment. MEASUREMENTS AND MAIN RESULTS: Pulmonary clinical examination and spirometry were the measurements. A strategy of using likelihood ratios (LRs) from seven clinical examination items was least accurate (p < .0001). Three alternative strategies were equivalent in diagnostic accuracy (p > or = .2): (1) using the single best clinical examination item and its LR, (2) using the LRs from three clinical examination items chosen by logistic regression, and (3) using the adjusted LRs chosen in strategy 2. When compared with using LRs from all seven items, the strategies of using three LRs chosen by logistic regression or using adjusted likelihood ratios better discriminated patients with airflow limitation from those without (receiver operating characteristic [ROC] areas 0.79 vs 0.69; p = .02). Using the single best clinical finding did not statistically degrade the clinical examination's discriminating ability (ROC areas 0.79 vs 0.75; p = .20). CONCLUSIONS: Describing the rational clinical examination requires evaluating conditional independence of examination components. Conditional independence assumptions were violated when seven clinical examination items were used to estimate posterior probability of airflow limitation. Focusing on clinical examination items identified through logistic models overcame violations of independence; further statistical adjustment did not improve diagnostic accuracy. Clinicians can use the single most predictive clinical examination finding to avoid inaccuracy from violating the independence assumption.
OBJECTIVE: To describe strategies for using multiple clinical examination items to estimate disease probabilities; and to evaluate the diagnostic accuracy of each strategy. DESIGN: Prospective observational study. SETTING: Medical preoperative evaluation clinic at a university-affiliated Veterans Affairs Medical Center. PATIENTS: Previously reported consecutive series of patients referred for outpatient medical preoperative risk assessment. MEASUREMENTS AND MAIN RESULTS: Pulmonary clinical examination and spirometry were the measurements. A strategy of using likelihood ratios (LRs) from seven clinical examination items was least accurate (p < .0001). Three alternative strategies were equivalent in diagnostic accuracy (p > or = .2): (1) using the single best clinical examination item and its LR, (2) using the LRs from three clinical examination items chosen by logistic regression, and (3) using the adjusted LRs chosen in strategy 2. When compared with using LRs from all seven items, the strategies of using three LRs chosen by logistic regression or using adjusted likelihood ratios better discriminated patients with airflow limitation from those without (receiver operating characteristic [ROC] areas 0.79 vs 0.69; p = .02). Using the single best clinical finding did not statistically degrade the clinical examination's discriminating ability (ROC areas 0.79 vs 0.75; p = .20). CONCLUSIONS: Describing the rational clinical examination requires evaluating conditional independence of examination components. Conditional independence assumptions were violated when seven clinical examination items were used to estimate posterior probability of airflow limitation. Focusing on clinical examination items identified through logistic models overcame violations of independence; further statistical adjustment did not improve diagnostic accuracy. Clinicians can use the single most predictive clinical examination finding to avoid inaccuracy from violating the independence assumption.