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Predictive approach in managing voiding dysfunction after surgery for deep endometriosis: a personalized nomogram

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Abstract

Introduction and hypothesis

The aim was to develop a nomogram based on clinical and surgical factors to predict the likelihood of voiding dysfunction after surgery for deep endometriosis.

Methods

This was a retrospective study of 789 patients (training set) who underwent surgery for deep endometriosis with colorectal involvement from January 2005 through December 2017 at Tenon University Hospital. A multivariate logistic regression analysis of selected risk factors was performed to construct a nomogram to predict postoperative voiding dysfunction. The nomogram was externally validated in 333 patients (validation set) from Rouen University Hospital.

Results

Postoperative voiding dysfunction occurred in 23% of the patients (180/789) in the training set. Age, colorectal involvement/management, colpectomy and parametrectomy were the main factors associated with an increased risk of voiding dysfunction and were included in the nomogram. The predictive model had an internal concordance index of 0.79 (95% CI: 0.77–0.81) after the 200 repetitions of bootstrap sample corrections and showed good calibration. The ROC area related to the nomogram for external validation was 0.74 (95% CI: 0.72–0.76).

Conclusions

The nomogram we present here, based on four clinical and imaging characteristics, could be useful in predicting postoperative voiding dysfunction for women undergoing surgery for deep endometriosis. Patients could thus be better informed about this postoperative risk and the surgical strategy adapted according to individual risk. The accuracy of the tool was validated externally but additional validation is required.

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Authors and Affiliations

  1. Department of Gynecology and Obstetrics, Tenon University Hospital, Assistance Publique des Hôpitaux de Paris (AP-HP), Sorbonne University, 4 rue de la Chine, 75020, Paris, France

    Elie Vesale, Louise Benoit, Emile Darai & Sofiane Bendifallah

  2. Clinique Tivoli-Ducos, Bordeaux, France

    Horace Roman

  3. Expert Center in the Diagnosis and Multidisciplinary Management of Endometriosis, Rouen University Hospital, Rouen, France

    Carole Abo

  4. Department of Surgery, Rouen University Hospital, Rouen, France

    Jean-Jacques Tuech

  5. Groupe de Recherche Clinique 6 (GRC6-UPMC): Centre Expert En Endométriose (C3E), UMR_S938 Sorbonne University, Paris, France

    Emile Darai & Sofiane Bendifallah

Authors
  1. Elie Vesale
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  2. Horace Roman
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  3. Carole Abo
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  4. Louise Benoit
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  5. Jean-Jacques Tuech
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  6. Emile Darai
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  7. Sofiane Bendifallah
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Contributions

Dr. Vesale: Protocol/project development, data collection or management, data analysis, manuscript writing/editing.

Pr. Roman: Data collection or management, manuscript writing/editing.

Dr. Abo: Data collection or management, manuscript writing/editing.

Dr. Benoit: Data analysis, manuscript writing/editing.

Dr. Tuech: Data analysis, manuscript writing/editing.

Pr. Darai: Protocol/project development, manuscript writing/editing.

Dr. Bendifallah: Protocol/project development, data collection or management, manuscript writing/editing.

Corresponding author

Correspondence to Louise Benoit.

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Vesale, E., Roman, H., Abo, C. et al. Predictive approach in managing voiding dysfunction after surgery for deep endometriosis: a personalized nomogram. Int Urogynecol J 32, 1205–1212 (2021). https://doi.org/10.1007/s00192-020-04428-9

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  • DOI: https://doi.org/10.1007/s00192-020-04428-9

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