Diagnostic prediction models for suspected pulmonary embolism: systematic review and independent external validation in primary care.
OBJECTIVE
To validate all diagnostic prediction models for ruling out pulmonary embolism that are easily applicable in primary care.


METHODS
Systematic review followed by independent external validation study to assess transportability of retrieved models to primary care medicine.


METHODS
300 general practices in the Netherlands.


METHODS
Individual patient dataset of 598 patients with suspected acute pulmonary embolism in primary care.


METHODS
Discriminative ability of all models retrieved by systematic literature search, assessed by calculation and comparison of C statistics. After stratification into groups with high and low probability of pulmonary embolism according to pre-specified model cut-offs combined with qualitative D-dimer test, sensitivity, specificity, efficiency (overall proportion of patients with low probability of pulmonary embolism), and failure rate (proportion of pulmonary embolism cases in group of patients with low probability) were calculated for all models.


RESULTS
Ten published prediction models for the diagnosis of pulmonary embolism were found. Five of these models could be validated in the primary care dataset: the original Wells, modified Wells, simplified Wells, revised Geneva, and simplified revised Geneva models. Discriminative ability was comparable for all models (range of C statistic 0.75-0.80). Sensitivity ranged from 88% (simplified revised Geneva) to 96% (simplified Wells) and specificity from 48% (revised Geneva) to 53% (simplified revised Geneva). Efficiency of all models was between 43% and 48%. Differences were observed between failure rates, especially between the simplified Wells and the simplified revised Geneva models (failure rates 1.2% (95% confidence interval 0.2% to 3.3%) and 3.1% (1.4% to 5.9%), respectively; absolute difference -1.98% (-3.33% to -0.74%)). Irrespective of the diagnostic prediction model used, three patients were incorrectly classified as having low probability of pulmonary embolism; pulmonary embolism was diagnosed only after referral to secondary care.


CONCLUSIONS
Five diagnostic pulmonary embolism prediction models that are easily applicable in primary care were validated in this setting. Whereas efficiency was comparable for all rules, the Wells rules gave the best performance in terms of lower failure rates.
Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3508 GA Utrecht, Netherlands j.m.t.hendriksen-9@umcutrecht.nl.
Janneke M T
JM
Hendriksen
Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3508 GA Utrecht, Netherlands.
Geert-Jan
GJ
Geersing
Department of General Practice, Academic Medical Center, Amsterdam, Netherlands.
Wim A M
WA
Lucassen
Department of Family Medicine, CAHPRI School for Public Health and Primary Care, Maastricht University, Maastricht, Netherlands.
Petra M G
PM
Erkens
Department of Family Medicine, CAHPRI School for Public Health and Primary Care, Maastricht University, Maastricht, Netherlands.
Henri E J H
HE
Stoffers
Department of General Practice, Academic Medical Center, Amsterdam, Netherlands.
Henk C P M
HC
van Weert
Department of Vascular Medicine, Academic Medical Center, Amsterdam, Netherlands.
Harry R
HR
Büller
Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3508 GA Utrecht, Netherlands.
Arno W
AW
Hoes
Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3508 GA Utrecht, Netherlands.
Karel G M
KG
Moons
D003661:Decision Support Techniques; D005260:Female; D005338:Fibrin Fibrinogen Degradation Products / Q000032:analysis; D006801:Humans; D008297:Male; D008875:Middle Aged; D011320:Primary Health Care / Q000379:methods; D011655:Pulmonary Embolism / Q000175:diagnosis*; D012307:Risk Factors; D012680:Sensitivity and Specificity
D005338:Fibrin Fibrinogen Degradation Products; C036309:fibrin fragment D