Distinguishing Low-Risk from No-Risk PE Patients in EM
Search Strategy: You vaguely remember an SAEM abstract presented by a guy named Kline who has done a lot of PE research. You go to PUBMED, type in clinical decision rules, pulmonary embolism, and you get a lot of stuff including some from Kline, but none of them seem to be what you were thinking about, and you wonder if abstracts don’t come up. Luckily, Dr. Carpenter happens to be working in EM 1, so you ask for some help. He tells you to look up the journal, which you do, and find the supplemental annual meeting issue (May each year), which contains the abstract you were looking for (and 6 other abstracts with this guy’s name on it!). The abstract references a previously published article about the “PERC” score, which you also pull. Finally, you conduct a PUBMED Clinical Queries search for Pulmonary Embolism Clinical Prediction Guide using narrow/specific settings.
While working an evening shift in the deuce with 44 waiting room patients staring you in the face, your next patient is a young woman with pleuritic chest pain and dyspnea. Otherwise healthy with normal vital signs, she has clear lungs, no chest wall tenderness, and an unremarkable physical exam. She smokes 5 cigarettes/day and uses depoprovera, but has no other risk factors. She looks absolutely fine, but you are working with Aubin, and you know how she is. You have 5 minutes, so decide to do a quick PUBMED search to see if you can find any evidence to convince your attending that this patient is soooo low risk that you don’t even need to send a D-Dimer, so you can get this patient out of here and see someone sick. As Jerry Hoffman says, there are low risk and then there are no risk patients.
Population: ED patients presenting with reason to suspect PE
Intervention: Application of PE Clinical Decision Rule and/or D-dimer testing
Comparison: Clinical Gestalt without CDR or D-dimer testing
Outcome: PE-related morbidity and mortality, Over-test complications and cost-effectiveness
Search Strategy: While attending the January 2007 Best Evidence in Emergency Medicine course at the Silver Star Mountain Resort in British Columbia, you’d heard about one or two meta-analyses addressing this specific question. Digging out your BEEM manual, you quickly locate both articles and find two randomized controlled trials by quickly scanning the references of the two meta-analyses.
First years: Does This Patient Have Pulmonary Embolism? JAMA 2003; 290: 2849-2858.
Second years: Comparison of the Unstructured Clinician Estimate of Pretest Probability for Pulmonary Embolism to the Canadian Score and the Charlotte Rule: A Prospective Observational Study. Acad EM 2005; 12: 1155-1163.
Third years: Bayes Pulmonary Embolism Assisted Diagnosis: A New Expert System for Clinical Use. Emerg Med J 2007; 24: 157-164.
Fourth years: Clinical Criteria to Prevent Unnecessary Diagnostic Testing in Emergency Department Patients with Suspected Pulmonary Embolism. J Thromb Haemost 2004; 2: 1247-1255.
Article 1: Does This Patient Have Pulmonary Embolism? JAMA 2003; 290:21; 2849-2858
Article 2: Comparison of the Unstructured Clinician Estimate of Pretest Probability for Pulmonary Embolism to the Canadian Score and the Charlotte Rule: A Prospective Observational Study Acad EM 2005; 12: 587-593
Article 3: Bayes Pulmonary Embolism Assisted Diagnosis: A New Expert System for Clinical Use, Emerg Med J 2007; 24: 157-164
Article 4: Clinical Criteria to prevent unnecessary diagnostic testing in emergency department patients with suspected pulmonary embolism Journal of Thrombosis & Haemostasis, 2004; 2: 1247-1255
When clinically suspected, a reasonable pre-test probability for PE in the ED is 25-30%. Experienced clinicians’ clinical gestalt estimate of PE pre-test probability correlates well with increasing PE prevalence and compares favorably to validated Clinical Decision Rules. However, none of these methods (gestalt, Charlotte, Well’s) is sufficient to bring the post-test probability below 1% by themselves. Clinical gestalt (LR- = 0.45) displays similar ability to identify low-risk PE patients as the Charlotte Rule (LR- = 0.72), and the Canadian Well’s PE CDR < 2 (LR- = 0.48). More experienced clinicians tend to have more low risk patients diagnosed with PE. The PERC score applied to ED patients with dyspnea and/or pleuritic chest pain with PE felt so unlikely by the treated board-certified EM physician that further testing is unnecessary, can detect the rare (~2%) PE hiding in this group. Computerized Bayesian decision models offer a future promising, if somewhat intellectually challenging, diagnostic assistance device for complicated diagnoses like PE when electronic medical record technology catches up with these clinical prediction program software. When clinically suspected, a reasonable pre-test probability for PE in the ED is 25-30%.