Commentary

The presence of clinical prediction rules can serve to allow translation of a standard approach and perhaps improve the diagnostic accuracy. Even within the context of various trials for the diagnosis of pulmonary embolism, the gap between pretest likelihood is greatly variable and dependent upon the completeness of clinical information presented. Thus, a clinical characteristic alone (eg, dyspnoea following prolonged immobilisation) in the absence of such data as arterial blood gases (hypoxaemia and hypocapnoea) decreases the clinical sensitivity for the diagnosis.

How are busy clinicians to use such information in a timely, meaningful, and more standardised format? Clinical prediction rules are a step in the right direction but they must be simple in their construction and easy to apply in a busy practice setting. Furthermore, they make the interpretation of the diagnostic accuracy of various emerging confirmatory markers all the more applicable and would likely lead to less clinical bias of misinterpretation. The clinical prediction criteria proposed by Wells et al¹ meet the criteria of simplicity to derive a probability estimate for pulmonary embolism.

Although the evidence reviewed by Chunilal et al does not seem to offer a clear advantage for prediction rules over gestalt, it should be recognised that such information is gathered in controlled environments where the power of suggestion plays an integrative role in the clinician’s response. Although it is my own “gestalt” that suggests that the time may be here to embrace a clinical prediction rule to assist in the diagnosis of pulmonary embolism in the real world, more research is needed to support the use of such clinical prediction rules.