External validation of risk prediction model M4 in an Australian population: Rationalising the management of pregnancies of unknown location.
ectopic pregnancy
miscarriage
prediction model
pregnancy of unknown location
resource allocation
ultrasonography
Journal
The Australian & New Zealand journal of obstetrics & gynaecology
ISSN: 1479-828X
Titre abrégé: Aust N Z J Obstet Gynaecol
Pays: Australia
ID NLM: 0001027
Informations de publication
Date de publication:
12 2020
12 2020
Historique:
received:
19
08
2019
accepted:
08
05
2020
pubmed:
17
6
2020
medline:
16
2
2021
entrez:
16
6
2020
Statut:
ppublish
Résumé
The prediction model M4 can successfully classify pregnancy of unknown location (PUL) into a low- or high-risk group in developing ectopic pregnancy. M4 was validated in UK centres but in very few other countries outside UK. To validate the M4 model's ability to correctly classify PULs in a cohort of Australian women. A retrospective analysis of women classified with PUL, attending a Sydney-based teaching hospital between 2006 and 2018. The reference standard was the final characterisation of PUL: failed PUL (FPUL) or intrauterine pregnancy (IUP; low risk) vs ectopic pregnancy (EP) or persistent PUL (PPUL; high risk). Each patient was entered into the M4 model calculator and an estimated risk of FPUL/IUP or EP/PPUL was recorded. Diagnostic accuracy of the M4 model was evaluated. Of 9077 consecutive women who underwent transvaginal sonography, 713 (7.9%) classified with a PUL. Six hundred and seventy-seven (95.0%) had complete study data and were included. Final outcomes were: 422 (62.3%) FPULs, 150 (22.2%) IUPs, 105 (15.5%) EPs and PPULs. The M4 model classified 455 (67.2%) as low-risk PULs of which 434 (95.4%) were FPULs/IUPs and 21 (4.6%) were EPs or PPULs. EPs/PPULs were correctly classified with sensitivity of 80.0% (95% CI 71.1-86.5%), specificity of 75.9% (95% CI 72.2-79.3%), positive predictive value of 37.8% (95% CI 33.8-42.1%) and negative predictive value of 95.3% (95% CI 93.1-96.9%). We have externally validated the prediction model M4. It classified 67.2% of PULs as low risk, of which 95.4% were later characterised as FPULs or IUPs while still classifying 80.0% of EPs as high risk.
Sections du résumé
BACKGROUND
The prediction model M4 can successfully classify pregnancy of unknown location (PUL) into a low- or high-risk group in developing ectopic pregnancy. M4 was validated in UK centres but in very few other countries outside UK.
AIM
To validate the M4 model's ability to correctly classify PULs in a cohort of Australian women.
MATERIALS AND METHODS
A retrospective analysis of women classified with PUL, attending a Sydney-based teaching hospital between 2006 and 2018. The reference standard was the final characterisation of PUL: failed PUL (FPUL) or intrauterine pregnancy (IUP; low risk) vs ectopic pregnancy (EP) or persistent PUL (PPUL; high risk). Each patient was entered into the M4 model calculator and an estimated risk of FPUL/IUP or EP/PPUL was recorded. Diagnostic accuracy of the M4 model was evaluated.
RESULTS
Of 9077 consecutive women who underwent transvaginal sonography, 713 (7.9%) classified with a PUL. Six hundred and seventy-seven (95.0%) had complete study data and were included. Final outcomes were: 422 (62.3%) FPULs, 150 (22.2%) IUPs, 105 (15.5%) EPs and PPULs. The M4 model classified 455 (67.2%) as low-risk PULs of which 434 (95.4%) were FPULs/IUPs and 21 (4.6%) were EPs or PPULs. EPs/PPULs were correctly classified with sensitivity of 80.0% (95% CI 71.1-86.5%), specificity of 75.9% (95% CI 72.2-79.3%), positive predictive value of 37.8% (95% CI 33.8-42.1%) and negative predictive value of 95.3% (95% CI 93.1-96.9%).
CONCLUSIONS
We have externally validated the prediction model M4. It classified 67.2% of PULs as low risk, of which 95.4% were later characterised as FPULs or IUPs while still classifying 80.0% of EPs as high risk.
Substances chimiques
Chorionic Gonadotropin
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
928-934Informations de copyright
© 2020 The Royal Australian and New Zealand College of Obstetricians and Gynaecologists.
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