Abstract
BACKGROUND: Incorrect estimation of pretest probability and misinterpretation of test results can change post-test probability in medical decision making. The aim of this study was to evaluate how physicians assess weight of findings of congestive heart failure (CHF) and how much their estimation is correlated with findings' Diagnostic Odd Ratio (DOR). METHODS: The participants were asked to answer a questionnaire based on a scenario of a patient having dyspnea. Eighteen findings in 3 categories including: history, examination and radiographic findings were inserted along a column and a row as a matrix. The respondents had to compare each finding in the column with all other findings in the row and insert a mark in boxes below the findings of the row that had greater weight compared to the finding in the column. The weight of each finding was considered as total number of "marked boxes" in front of that finding. DOR of findings was calculated using their positive and negative likelihood ratios (LRs) based on current best evidence. Findings ranked in the order of their DOR and were compared with the ranking in the order of participants-assigned weights. We examined correlation between average weights assigned by physicians and DOR of findings. In subgroup analysis correlations between average weights assigned by physicians and DOR of history, examination and radiographic findings were examined. RESULTS: Seventy five physicians completed the questionnaire. Correlation between ranking in the order of findings' DOR and ranking in the order of clinicians-assigned weights was significant (p-value = 0.005 r = 0.64). In contrast correlations between participants-assigned weights and DOR of history, examination and radiographic findings were positive but non- significant (r = 0.181, p-value = 0.7, r = 0.343, p-value = 0.506 and r = 0.219, p-value = 0.723 respectively). CONCLUSION: Our result show that although correlation between clinicians-assigned weights and DOR of entire findings was significant, correlations between clinicians-assigned weights to the different categories of findings and their DOR were not significant. Reevaluating probabilistic reasoning by emphasis on using LRs can make pretest probability estimating and interpretation of test results more objective and would ultimate in more precise and homogenous post-test probabilities.