Predicting major complications in patients undergoing laparoscopic and open hysterectomy for benign indications
Metadata
Show full item recordEditorial
Canadian Medical Association
Date
2022-10-03Referencia bibliográfica
CMAJ 2022 October 3;194:E1306-17. doi: [10.1503/cmaj.220914]
Sponsorship
British Society for Gynaecological EndoscopyAbstract
Background: Hysterectomy, the most
common gynecological operation,
requires surgeons to counsel women
about their operative risks. We aimed to
develop and validate multivariable logistic
regression models to predict major
complications of laparoscopic or abdominal
hysterectomy for benign conditions.
Methods: We obtained routinely collected
health administrative data from
the English National Health Service (NHS)
from 2011 to 2018. We defined major
complications based on core outcomes
for postoperative complications including
ureteric, gastrointestinal and vascular
injury, and wound complications. We
specified 11 predictors a priori. We used
internal–external cross-validation to
evaluate discrimination and calibration
across 7 NHS regions in the development
cohort. We validated the final
models using data from an additional
NHS region.
Results: We found that major complications
occurred in 4.4% (3037/68 599) of
laparoscopic and 4.9% (6201/125 971) of
abdominal hysterectomies. Our models
showed consistent discrimination in the
development cohort (laparoscopic,
C-statistic 0.61, 95% confidence interval
[CI] 0.60 to 0.62; abdominal, C-statistic
0.67, 95% CI 0.64 to 0.70) and similar or
better discrimination in the validation
cohort (laparoscopic, C-statistic 0.67, 95%
CI 0.65 to 0.69; abdominal, C-statistic
0.67, 95% CI 0.65 to 0.69). Adhesions
were most predictive of complications in
both models (laparoscopic, odds ratio
[OR] 1.92, 95% CI 1.73 to 2.13; abdominal,
OR 2.46, 95% CI 2.27 to 2.66). Other
factors predictive of complications
included adenomyosis in the laparoscopic
model, and Asian ethnicity and
diabetes in the abdominal model. Protective
factors included age and diagnoses
of menstrual disorders or benign
adnexal mass in both models and diagnosis
of fibroids in the abdominal model.
Interpretation: Personalized risk estimates
from these models, which
showed moderate discrimination, can
inform clinical decision-making for
people
with benign conditions who may
require hysterectomy.