Evaluation of a new prediction model for the estimation of risk of obstetrical anal sphincter injuries
André, Kristin LU
; Stuart, Andrea
LU
and Källén, Karin
LU
(2025)
In American Journal of Obstetrics and Gynecology
- Abstract
Background: Obstetrical anal sphincter injuries are complications of vaginal birth that have the potential to cause substantial maternal morbidity. Predicting these injuries might help to improve maternal care as well as antenatal counseling and patient education. Previous attempts to create prediction models have in many cases involved variables only known postpartum, which limits their use in an antenatal setting. Other models include parameters that are not applicable to a Northern European population. Objective: This study aimed to develop and validate a clinically useful model for the prediction of risk of obstetrical anal sphincter injuries. Study Design: The model was developed using a retrospective nationwide cohort from the... (More)
Background: Obstetrical anal sphincter injuries are complications of vaginal birth that have the potential to cause substantial maternal morbidity. Predicting these injuries might help to improve maternal care as well as antenatal counseling and patient education. Previous attempts to create prediction models have in many cases involved variables only known postpartum, which limits their use in an antenatal setting. Other models include parameters that are not applicable to a Northern European population. Objective: This study aimed to develop and validate a clinically useful model for the prediction of risk of obstetrical anal sphincter injuries. Study Design: The model was developed using a retrospective nationwide cohort from the Swedish Medical Birth Register consisting of 1,209,421 deliveries between 2005 and 2016. After exclusion criteria (cesarean delivery, forceps delivery, missing data) were applied, the data set was randomly divided into a development data set (n=422,011) and a validation data set (n=422,010). In the development data set, all variables were assessed using univariable analysis with modified Poisson regression. A prediction model was then built using multivariate analysis with modified Poisson regression, wherein variables with P≤.2 were included. Both forward and backward selection were used, and variables with P≥.05 were excluded. Validation was performed by evaluating the agreement between the predicted and observed rate of obstetrical anal sphincter injuries after the prediction model was applied to the validation data set. Results: Antenatal variables associated with increased risk of obstetrical anal sphincter injury included primiparity, previous cesarean delivery, previous sphincter injury, increasing age, increasing birthweight, and maternal origin from sub-Saharan Africa or South/Southeast Asia. Smoking, increasing maternal height, and body mass index appeared to lower the risk. Vacuum extraction also increased the risk of sphincter injury. We developed 1 model including the previously mentioned antenatal parameters and 1 model also including vacuum extraction. The final prediction model including instrumental delivery can be used for predicting the risk of sphincter injury for delivery with or without vacuum extraction with higher accuracy. This model demonstrated strong discrimination with an AUC of 0.79 (95% confidence interval, 0.78–0.79), and was able to predict risks up to 24% with moderate to high accuracy. Conclusion: Using antenatally available data, obstetrical anal sphincter injuries can be predicted with moderate certainty. This prediction model has been externally validated and can be used for individualized antenatal counseling and identification of persons at high risk for whom preventative strategies might improve outcomes. Further validation in other populations outside of Scandinavia is recommended before clinical implementation.
(Less)
- author
- André, Kristin
LU
; Stuart, Andrea
LU
and Källén, Karin
LU
- organization
- publishing date
- 2025
- type
- Contribution to journal
- publication status
- epub
- subject
- keywords
- birth injury, high risk, obstetrical anal sphincter injury, perineal tear, prediction model, risk factor
- in
- American Journal of Obstetrics and Gynecology
- publisher
- Elsevier
- external identifiers
-
- pmid:40639778
- scopus:105012584734
- ISSN
- 0002-9378
- DOI
- 10.1016/j.ajog.2025.07.005
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2025 The Author(s)
- id
- 194ad885-ab47-4d87-801b-db97e7b0be14
- date added to LUP
- 2025-12-22 10:48:33
- date last changed
- 2025-12-22 10:49:45
@article{194ad885-ab47-4d87-801b-db97e7b0be14,
abstract = {{<p>Background: Obstetrical anal sphincter injuries are complications of vaginal birth that have the potential to cause substantial maternal morbidity. Predicting these injuries might help to improve maternal care as well as antenatal counseling and patient education. Previous attempts to create prediction models have in many cases involved variables only known postpartum, which limits their use in an antenatal setting. Other models include parameters that are not applicable to a Northern European population. Objective: This study aimed to develop and validate a clinically useful model for the prediction of risk of obstetrical anal sphincter injuries. Study Design: The model was developed using a retrospective nationwide cohort from the Swedish Medical Birth Register consisting of 1,209,421 deliveries between 2005 and 2016. After exclusion criteria (cesarean delivery, forceps delivery, missing data) were applied, the data set was randomly divided into a development data set (n=422,011) and a validation data set (n=422,010). In the development data set, all variables were assessed using univariable analysis with modified Poisson regression. A prediction model was then built using multivariate analysis with modified Poisson regression, wherein variables with P≤.2 were included. Both forward and backward selection were used, and variables with P≥.05 were excluded. Validation was performed by evaluating the agreement between the predicted and observed rate of obstetrical anal sphincter injuries after the prediction model was applied to the validation data set. Results: Antenatal variables associated with increased risk of obstetrical anal sphincter injury included primiparity, previous cesarean delivery, previous sphincter injury, increasing age, increasing birthweight, and maternal origin from sub-Saharan Africa or South/Southeast Asia. Smoking, increasing maternal height, and body mass index appeared to lower the risk. Vacuum extraction also increased the risk of sphincter injury. We developed 1 model including the previously mentioned antenatal parameters and 1 model also including vacuum extraction. The final prediction model including instrumental delivery can be used for predicting the risk of sphincter injury for delivery with or without vacuum extraction with higher accuracy. This model demonstrated strong discrimination with an AUC of 0.79 (95% confidence interval, 0.78–0.79), and was able to predict risks up to 24% with moderate to high accuracy. Conclusion: Using antenatally available data, obstetrical anal sphincter injuries can be predicted with moderate certainty. This prediction model has been externally validated and can be used for individualized antenatal counseling and identification of persons at high risk for whom preventative strategies might improve outcomes. Further validation in other populations outside of Scandinavia is recommended before clinical implementation.</p>}},
author = {{André, Kristin and Stuart, Andrea and Källén, Karin}},
issn = {{0002-9378}},
keywords = {{birth injury; high risk; obstetrical anal sphincter injury; perineal tear; prediction model; risk factor}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{American Journal of Obstetrics and Gynecology}},
title = {{Evaluation of a new prediction model for the estimation of risk of obstetrical anal sphincter injuries}},
url = {{http://dx.doi.org/10.1016/j.ajog.2025.07.005}},
doi = {{10.1016/j.ajog.2025.07.005}},
year = {{2025}},
}