Effect of Endometrial Ablation on Premenstrual Symptoms

Waddell, Guy; Pelletier, J; Desindes, Sophie; Anku-Bertholet, Catherine; Blouin, Simon; Thibodeau, Daniel T.

doi:10.1016/j.jmig.2015.01.023

Cited by 7 publications

(6 citation statements)

References 23 publications

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“…Endometrial ablation is known to improve PMS symptoms. 18 , 19 , 30 NovaSure ablation was also associated with a more pronounced reduction in PMS symptoms than Minerva treatment, with significantly more NovaSure women reporting reduced symptoms at 12 months; 85% of Nova-Sure subjects versus 67% of Minerva subjects experienced improvement. An earlier study that focused on ablation effects on PMS reported that 97% of women with PMS had symptom improvement after NovaSure ablation at a mean postoperative 5.5 months, which was a statistically similar proportion as the current value ( p =0.057).…”

Section: Discussionmentioning

confidence: 92%

Efficacy and patient satisfaction after NovaSure and Minerva endometrial ablation for treating abnormal uterine bleeding: a retrospective comparative study

Scordalakes

delRosario²,

Shimer

et al. 2018

IJWH

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ObjectiveCompare amenorrhea rate, menstrual symptoms, patient satisfaction, and adverse events in women who underwent endometrial ablation with the NovaSure versus the Minerva radiofrequency ablation systems.MethodsWe surveyed 189 premenopausal women (mean 40.8±6.2 years old) who underwent endometrial ablation for abnormal uterine bleeding using the NovaSure (n=97) or Minerva (n=92) systems, at four private US gynecology clinics, and whose procedure date was after July 2015 with follow-up ≥3 months. Women were surveyed an average of 11.3±3.9 months (range 137–532 days) after ablation.ResultsThe subject-reported amenorrhea rate was 52% higher in NovaSure subjects than Minerva subjects (64% and 42%, respectively; p=0.004). Age and bleeding cyclicity did not affect amenorrhea rate in either group. Normal-to-no bleeding was reported by >90% of subjects after either treatment. NovaSure was significantly more effective than Minerva at reducing pad/tampon use in women with any residual bleeding (2.4±5.2 items/day versus 4.7±5.5 items/day, p=0.049). NovaSure was significantly more effective than Minerva at reducing premenstrual syndrome (PMS) symptoms (p=0.019) and menstrual pain (p=0.003), and more NovaSure subjects (94%) than Minerva subjects (78%) were satisfied with clinical outcomes (p=0.003). Adverse events did not differ by treatment; three women in each group progressed to hysterectomy.ConclusionWhile overall bleeding reduction in premenopausal women with abnormal uterine bleeding was excellent with either endometrial ablation system, NovaSure treatment resulted in a higher patient-reported 1-year amenorrhea rate, and women with residual bleeding used fewer pads and tampons than Minerva-treated women. Additionally, NovaSure subjects reported better menstrual-related life quality and PMS symptom alleviation, and greater satisfaction with outcomes than Minerva-treated women.

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Section: Discussionmentioning

confidence: 92%

Efficacy and patient satisfaction after NovaSure and Minerva endometrial ablation for treating abnormal uterine bleeding: a retrospective comparative study

Scordalakes

delRosario²,

Shimer

et al. 2018

IJWH

View full text Add to dashboard Cite

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“…Endometrial ablation (EA) is one of the treatment options for this common complaint. Due to the low costs and less invasive nature of this procedure (lower intra-operative complication risks, shorter recovery time, and lower post-operative morbidity), this form of treatment seems to be a less invasive surgical treatment for menorrhagia compared to hysterectomy [2][3][4][5][6]. However, long-term follow-up shows a decrease in patient satisfaction and treatment efficacy.…”

Section: Introductionmentioning

confidence: 99%

“…According to literature, several factors prior to endometrial ablation appear to have an influence on the success-rate of this procedure. Younger age, complaints of dysmenorrhea, multiparity, a thicker pre-procedural endometrium, a duration of menstruation above 7 days, presence of an intramural leiomyoma on transvaginal sonography, a history of sterilization or caesarean section, and a longer uterine depth are some of the possible negative influencing factors [1,2,8,9,[11][12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Prediction of unsuccessful endometrial ablation: random forest vs logistic regression

et al. 2021

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Background Five percent of pre-menopausal women experience abnormal uterine bleeding. Endometrial ablation (EA) is one of the treatment options for this common problem. However, this technique shows a decrease in patient satisfaction and treatment efficacy on the long term. Study objective To develop a prediction model to predict surgical re-intervention (for example re-ablation or hysterectomy) within 2 years after endometrial ablation (EA) by using machine learning (ML). The performance of the developed prediction model was compared with a previously published multivariate logistic regression model (LR). Design This retrospective cohort study, with a minimal follow-up time of 2 years, included 446 pre-menopausal women (18+) that underwent an EA for complaints of heavy menstrual bleeding. The performance of the ML and the LR model was compared using the area under the receiving operating characteristic (ROC) curve. Results We found out that the ML model (AUC of 0.65 (95% CI 0.56–0.74)) is not superior compared to the LR model (AUC of 0.71 (95% CI 0.64–0.78)) in predicting the outcome of surgical re-intervention within 2 years after EA. Based on the ML model, dysmenorrhea and duration of menstruation have the highest impact on the surgical re-intervention rate. Conclusion Although machine learning techniques are gaining popularity in development of clinical prediction tools, this study shows that ML is not necessarily superior to the traditional statistical LR techniques. Both techniques should be considered when developing a clinical prediction model. Both models can identify the clinical predictors to surgical re-intervention and contribute to the shared decision-making process in the clinical practice.

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“…According to literature, several factors prior to endometrial ablation appear to have an influence on the success-rate of this procedure. Younger age, complaints of dysmenorrhea, multiparity, a thicker pre-procedural endometrium, a duration of menstruation above seven days, presence of an intramural leiomyoma on transvaginal sonography, a history of sterilization or caesarean section, and a longer uterine depth are some of the possible negative influencing factors (1, 2,8,9,[11][12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Unsuccessful Endometrial Ablation: Random Forest vs Logistic Regression

Stevens

Lagaert

Bakkes

et al. 2020

Preprint

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Background: Five percent of premenopausal women experience abnormal uterine bleeding. Endometrial ablation (EA) is one of the treatment options for this common problem. However, this technique shows a decrease in patient satisfaction and treatment efficacy on the long term Study objective: To develop a prediction model to predict surgical re-intervention (for example re-ablation or hysterectomy) within two years after EA by using Machine Learning (ML). The performance of the developed prediction model was compared with a previously published multivariate logistic regression model (LR). Design: This retrospective cohort study, with a minimal follow up time of two years, included 446 pre-menopausal women (18+) that underwent an EA for complaints of heavy menstrual bleeding. The performance of the ML- and the LR model was compared using the area under the Receiving Operating Characteristic (ROC) curve. Results: We found out that the ML model (AUC of 0.65 (95% CI 0.56-0.74)) is not superior compared to the LR model (AUC of 0.71 (95% CI 0.64-0.78)) in predicting the outcome of surgical re-intervention within two years after EA. Conclusion: Although Machine Learning techniques are gaining popularity in development of clinical prediction tools, this study shows that ML is not necessarily superior to the traditional statistical LR techniques. The performance of a prediction model is influenced by the sample size, the number of features of a dataset, hyperparameter tuning and the linearity of associations. Both techniques should be considered when developing a clinical prediction model.

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Effect of Endometrial Ablation on Premenstrual Symptoms

Cited by 7 publications

References 23 publications

Efficacy and patient satisfaction after NovaSure and Minerva endometrial ablation for treating abnormal uterine bleeding: a retrospective comparative study

Efficacy and patient satisfaction after NovaSure and Minerva endometrial ablation for treating abnormal uterine bleeding: a retrospective comparative study

Prediction of unsuccessful endometrial ablation: random forest vs logistic regression

Prediction of Unsuccessful Endometrial Ablation: Random Forest vs Logistic Regression

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