Effect of patient location on the performance of clinical models to predict pulmonary embolism

Ollenberger, Glenn P.; Worsley, Daniel F.

doi:10.1016/j.thromres.2005.11.011

Cited by 20 publications

(16 citation statements)

References 13 publications

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“…The prevalence of PE in the low probability subgroup was exceptionally high in the study from Miniati (50.0%). In the other studies, this prevalence ranged from 6.5% [1] to 18.4%[23]. The pooled prevalence of PE (including the study from Miniati) was 12.8% in the low probability group, 34.7% in the moderate and 71.1% in the high probability group.…”

Section: Resultsmentioning

confidence: 89%

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Clinical prediction rules for pulmonary embolism: a systematic review and meta-analysis

Ceriani

Combescure

Gal

et al. 2010

Journal of Thrombosis and Haemostasis

300

157

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Summary. Background: Pretest probability assessment is necessary to identify patients in whom pulmonary embolism (PE) can be safely ruled out by a negative D-dimer without further investigations. Objective: Review and compare the performance of available clinical prediction rules (CPRs) for PE probability assessment. Patients/methods: We identified studies that evaluated a CPR in patients with suspected PE from Embase, Medline and the Cochrane database. We determined the 95% confidence intervals (CIs) of prevalence of PE in the various clinical probability categories of each CPR. Statistical heterogeneity was tested. Results: We identified 9 CPR and included 29 studies representing 31215 patients. Pooled prevalence of PE for three-level scores (low, intermediate or high clinical probability) was: low, 6% (95% CI, 4-8), intermediate, 23% (95% CI, 18-28) and high, 49% (95% CI, 43-56) for the Wells score; low, 13% (95% CI, 8-19), intermediate, 35% (95% CI, 31-38) and high, 71% (95% CI, 50-89) for the Geneva score; low, 9% (95% CI, 8-11), intermediate, 26% (95% CI, 24-28) and high, 76% (95% CI, 69-82) for the revised Geneva score. Pooled prevalence for two-level scores (PE likely or PE unlikely) was 8% (95% CI,6-11) and 34% (95% CI,29-40) for the Wells score, and 6% (95% CI, 3-9) and 23% (95% CI, 11-36) for the Charlotte rule. Conclusion: Available CPR for assessing clinical probability of PE show similar accuracy. Existing scores are, however, not equivalent and the choice among various prediction rules and classification schemes (three-versus two-level) must be guided by local prevalence of PE, type of patients considered (outpatients or inpatients) and type of D-dimer assay applied.

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Section: Resultsmentioning

confidence: 89%

“…The prevalence of PE ranged from 6.5% [1] to 50.0% [16] in the low probability group, from 30.0% [21] to 41.4% [22] in the intermediate group and from 43.7% [23] to 96.3% [21] in the high probability group. The prevalence of PE in the low probability subgroup was exceptionally high in the study from Miniati (50.0%).…”

Section: Resultsmentioning

confidence: 99%

Clinical prediction rules for pulmonary embolism: a systematic review and meta-analysis

Ceriani

Combescure

Gal

et al. 2010

Journal of Thrombosis and Haemostasis

300

157

View full text Add to dashboard Cite

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“…Hospitalized patients with a low (33% of the population), intermediate (58%) or high (9%) clinical probability according to the physician showed an observed prevalence of pulmonary embolism of 13%, 44%, and 70%, respectively. Ollenberger and Worsley [21] studied the effect of patient location on the performance of two clinical models to predict pulmonary embolism. They found that the area under a fitted receiver operating characteristic curve for both models tested decreased significantly when applied to inpatients in comparison with outpatient.…”

Section: Discussionmentioning

confidence: 99%

“…Most of the previous studies have been performed in outpatients or both in-and outpatients and reported the results for the total patient group [6,[16][17][18][19][20]. Miron et al [9] performed a study in 145 consecutive hospitalized patients with clinically suspected pulmonary embolism and assessed the clinical probab- [21] studied the effect of patient location on the performance of two clinical models to predict pulmonary embolism. They found that the area under a fitted receiver operating characteristic curve for both models tested decreased significantly when applied to inpatients in comparison with outpatient.…”

Section: Discussionmentioning

confidence: 99%

A simple diagnostic strategy in hospitalized patients with clinically suspected pulmonary embolism

Kruip

Söhne

Nijkeuter³

et al. 2006

Journal of Internal Medicine

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“…Although more patients in the THREAD study required diagnostic imaging, clinical probability scoring was still helpful, as it identified the minority who were suitable for D‐dimer testing (excluding PE in 19%) and expedited diagnostic imaging for the remainder. Data from the PIOPED study has also shown that probability scores perform differently in the emergency department and hospital wards (Ollenberger & Worsley, 2006). Our calculated AUCs are comparable to prior evaluations of the Geneva and Wells’ scores (Gibson et al , 2008; Klok et al , 2008; Calisir et al , 2009).…”

Section: Discussionmentioning

confidence: 99%

Diagnosing pulmonary embolism: a comparison of clinical probability scores

et al. 2011

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Summary Pulmonary embolism (PE) is a major cause of community and in‐hospital mortality. This study aimed to compare the performance of the British Thoracic Society (BTS) score to the Wells’ score in diagnosing PE. Data from two separate prospective diagnostic PE studies were analysed. All patients underwent gold standard investigation to determine the presence or absence of PE, together with a 3‐month follow‐up. The posttest prevalence of PE was compared using both scores and the receiver operating characteristic (ROC) curves. Seven hundred and seventy‐nine patients were consented and investigated for PE. In patients with pleuritic chest pain, respiratory rate <20 breaths/min and absence of dyspnoea, 4·0% [95% confidence interval (CI) 1·9–7·9%] had PE. The BTS score allocated 463/779 patients as low probability, compared to 565/779 according to the Wells’ score. Both scores identified a low risk group in the Manchester Investigation of Pulmonary Embolism Diagnosis cohort, however the BTS low probability group in the Thromboembolism Assessment and Diagnosis study had a prevalence of 9·7% (95% CI 5·8–15·9%). For the BTS score, the areas under the ROC curves were 0·67 (95% CI 0·61–0·72) and 0·71 (95% CI 0·61–0·75). For the Wells’ score these were 0·76 (95%CI 0·71–0·81) and 0·68 (95%CI 0·64–0·73). Given the lack of BTS validation studies to date, the Wells’ score appears to be the safer assessment option.

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Effect of patient location on the performance of clinical models to predict pulmonary embolism

Cited by 20 publications

References 13 publications

Clinical prediction rules for pulmonary embolism: a systematic review and meta-analysis

Clinical prediction rules for pulmonary embolism: a systematic review and meta-analysis

A simple diagnostic strategy in hospitalized patients with clinically suspected pulmonary embolism

Diagnosing pulmonary embolism: a comparison of clinical probability scores

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