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.
Design Systematic review followed by independent external validation study to assess
transportability of retrieved models to primary care medicine.
Setting 300 general practices in the Netherlands.
Participants Individual patient dataset of 598 patients with suspected acute pulmonary
embolism in primary care.
Main outcome measures 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.

Diagnostic prediction models for suspected pulmonary embolism: systematic review and independent external validation in primary care by Janneke M T Hendriksen, et al. BMJ2015; 351 (Published 08 September 2015)

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