External validation of models to predict the outcome of pregnancies of unknown location: a multicentre cohort study

التفاصيل البيبلوغرافية
العنوان: External validation of models to predict the outcome of pregnancies of unknown location: a multicentre cohort study
المؤلفون: N. Mitchell-Jones, Shabnam Bobdiwala, B. Guruwadahyarhalli, Evangelia Christodoulou, Tom Bourne, F. Ayim, D. Gould, Dirk Timmerman, S. Guha, V. Vathanan, Laure Wynants, B. Van Calster, C. Kyriacou, Catriona Stalder, B. Chohan, O. Abughazza, Maya Al-Memar, J. Farren
المساهمون: Epidemiologie, RS: CAPHRI - R5 - Optimising Patient Care, Imperial Health Charity, Genesis Research Trust
المصدر: Bjog
Bjog-an International Journal of Obstetrics and Gynaecology, 128(3), 552-562. Wiley
بيانات النشر: John Wiley and Sons Inc., 2020.
سنة النشر: 2020
مصطلحات موضوعية: Pregnancy Tests, General Gynaecology, beta human chorionic gonadotrophin (BhCG) ratio, 0302 clinical medicine, Pregnancy, Medicine, Chorionic Gonadotropin, beta Subunit, Human, Prospective Studies, Prospective cohort study, 11 Medical and Health Sciences, education.field_of_study, 030219 obstetrics & reproductive medicine, Ectopic pregnancy, Obstetrics, HCG, Beta human chorionic gonadotrophin ratio, Obstetrics and Gynecology, Obstetrics & Gynecology, WOMEN, ECTOPIC PREGNANCY, Pregnancy, Ectopic, prediction model, Calibration, pregnancy of unknown location, ectopic pregnancy, Original Article, Female, Life Sciences & Biomedicine, SERUM PROGESTERONE, Cohort study, Adult, medicine.medical_specialty, Population, progesterone, prediction model validation, Sensitivity and Specificity, 03 medical and health sciences, Predictive Value of Tests, MANAGEMENT, Humans, False Positive Reactions, Lost to follow-up, Obstetrics & Reproductive Medicine, education, Science & Technology, business.industry, External validation, Reproducibility of Results, Original Articles, Missing data, medicine.disease, Triage, ROC Curve, business
الوصف: Objective To validate externally five approaches to predict ectopic pregnancy (EP) in pregnancies of unknown location (PUL): the M6P and M6NP risk models, the two‐step triage strategy (2ST, which incorporates M6P), the M4 risk model, and beta human chorionic gonadotropin ratio cut‐offs (BhCG‐RC). Design Secondary analysis of a prospective cohort study. Setting Eight UK early pregnancy assessment units. Population Women presenting with a PUL and BhCG >25 IU/l. Methods Women were managed using the 2ST protocol: PUL were classified as low risk of EP if presenting progesterone ≤2 nmol/l; the remaining cases returned 2 days later for triage based on M6P. EP risk ≥5% was used to classify PUL as high risk. Missing values were imputed, and predictions for the five approaches were calculated post hoc. We meta‐analysed centre‐specific results. Main outcome measures Discrimination, calibration and clinical utility (decision curve analysis) for predicting EP. Results Of 2899 eligible women, the primary analysis excluded 297 (10%) women who were lost to follow up. The area under the ROC curve for EP was 0.89 (95% CI 0.86–0.91) for M6P, 0.88 (0.86–0.90) for 2ST, 0.86 (0.83–0.88) for M6NP and 0.82 (0.78–0.85) for M4. Sensitivities for EP were 96% (M6P), 94% (2ST), 92% (N6NP), 80% (M4) and 58% (BhCG‐RC); false‐positive rates were 35%, 33%, 39%, 24% and 13%. M6P and 2ST had the best clinical utility and good overall calibration, with modest variability between centres. Conclusions 2ST and M6P performed best for prediction and triage in PUL. Tweetable abstract The M6 model, as part of a two‐step triage strategy, is the best approach to characterise and triage PULs.
Tweetable abstract The M6 model, as part of a two‐step triage strategy, is the best approach to characterise and triage PULs.
وصف الملف: Print-Electronic
اللغة: English
تدمد: 1471-0528
1470-0328
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b53df30cc0a7bb227a267869b6ada1b6Test
http://europepmc.org/articles/PMC7821217Test
حقوق: OPEN
رقم الانضمام: edsair.doi.dedup.....b53df30cc0a7bb227a267869b6ada1b6
قاعدة البيانات: OpenAIRE