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Models Stratify Hysterectomy Risk With Benign Conditions

New models are meant to assist clinicians in counseling patients before a hysterectomy surgery. ....

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Online Tool Predicts Complications From Hysterectomy

Researchers have developed multivariable logistic regression models to provide personalized risk estimates that aid in shared decision-making for patients undergoing hysterectomy for benign disease. ....

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Easy-to-use tool predicts complications in patients undergoing hysterectomy for benign disease

Easy-to-use tool predicts complications in patients undergoing hysterectomy for benign disease
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United Kingdom , Krupa Madhvani , English National Health Service , Queen Mary University Of London , Canadian Medical Association Journal , Queen Mary University ,

Predicting major complications in patients undergoing laparoscopic and open hysterectomy for benign indications

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 hysterecto ....

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Simple prediction tools provide personalized risk estimates for patients undergoing hysterectomy for benign disease

Researchers have developed easy-to-use online prediction tools that provide personalized risk estimates for patients undergoing hysterectomy for benign disease. ....

United Kingdom , Krupa Madhvani , Emily Henderson , English National Health Service , Queen Mary University Of London , Canadian Medical Association Journal , Queen Mary University ,