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Pessary fitting for pelvic organ prolapse: parameters associated with specific reasons for failure

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A Commentary to this article was published on 25 February 2022

Abstract

Introduction and hypothesis

The objective was to assess if specific reasons for unsuccessful pessary fitting have different predictive parameters.

Methods

This is a prospective observational case–control study of women with symptomatic pelvic organ prolapse (POP) choosing pessary treatment. All women underwent an interview, clinical examination, and 3D/4D transperineal ultrasound (TPUS). Groups were defined based on fitting outcome: successful, pessary dislodgment, failure to relieve POP symptoms, pain/discomfort, increased/de novo urinary incontinence, or other reasons. Clinical, demographic, and TPUS parameters were assessed in the prediction of different reasons for unsuccessful fitting and receiver operating characteristic (ROC) curves were constructed.

Results

A total of 162 women were assessed and 130 were included. Levator hiatal area (HA) on maximum Valsalva divided by ring pessary size (“Valsalva HARP ratio”) was a predictor of unsuccessful fitting (OR 3.00, 95% CI 1.15–7.81, p = 0.025) with an area under the ROC curve (AUC) of 0.62 (95% CI 0.50–0.74, p = 0.04). Predictors of pessary dislodgment were: complete avulsion (OR 24.20, 95% CI 2.46–237.84, p value 0.01) and Valsalva HARP ratio (OR 2.94, 95% CI 1.32–6.55, p value 0.01) with an area under the ROC curve (AUC) of 0.92 (95% CI 0.84–0.99, p = 0.00). No significant parameter was identified in the prediction of pain/discomfort. Solitary predominant posterior compartment POP was a predictor of failure to relieve POP symptoms (OR 20.00, 95% CI 3.48–115.02, p value 0.00; AUC 0.75, 95% CI 0.53–0.98, p = 0.03).

Conclusion

Complete avulsion and a small ring pessary with respect to the levator HA in Valsalva are predictors of pessary dislodgment, whereas solitary predominant posterior compartment POP is a predictor of failure to relieve POP symptoms.

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Funding

The study was part of the GYNecological Imaging using 3D UltraSound (GYNIUS) project with number 15301, which is financed by the Dutch Research Council (NWO). Philips contributed to the project by providing the ultrasound machine and TOMTEC provided image analysis software, which was not used for the current paper. The funding sources had no involvement in the study design, analysis, interpretation of data, report writing or preparation of this publication.

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Authors and Affiliations

  1. Department of Reproductive Medicine and Gynecology, University Medical Center Utrecht, Room F 05.132, 3508, GA, Utrecht, The Netherlands

    Claudia Manzini, Carl Huub van der Vaart & Mariëlla I. J. Withagen

  2. Bergman Clinics, Women’s Health Care, Hilversum, The Netherlands

    Claudia Manzini, Carl Huub van der Vaart & Mariëlla I. J. Withagen

  3. Robotics and Mechatronics, Faculty of Electrical Engineering Mathematics and Computer Science, Technical Medical Centre, University of Twente, Enschede, The Netherlands

    Frieda van den Noort

  4. Multimodality Medical Imaging Group, Faculty of Science and Technology, Technical Medical Centre, University of Twente, Enschede, The Netherlands

    Anique T. M. Grob

Authors
  1. Claudia Manzini
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  2. Carl Huub van der Vaart
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  4. Anique T. M. Grob
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  5. Mariëlla I. J. Withagen
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Contributions

C. Manzini: project development, data collection, data analysis and interpretation, manuscript writing and editing; C.H. van der Vaart: project development, data interpretation, manuscript editing; F. van den Noort: analysis tool development, manuscript editing; A.T.M. Grob: data interpretation, manuscript editing; M.I.J. Withagen: project development, data interpretation, manuscript editing.

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Correspondence to Claudia Manzini.

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Appendix 1

Appendix 1

Tables 5, 6, 7, and 8.

Table 5 Results of univariate and multivariate binomial logistic regression in the prediction of unsuccessful (n = 50) vs successful pessary fitting (n = 80)
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Table 6 Results of univariate and multivariate binomial logistic regression in the prediction of pessary dislodgment (n = 22) vs successful pessary fitting process (n = 80)
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Table 7 Results of univariate binomial logistic regression in the prediction of pain/discomfort (n = 13) vs successful pessary fitting process (n = 80)
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Table 8 Results of univariate binomial logistic regression in the prediction of failure to relieve POP symptoms (n = 7) vs successful pessary fitting process (n = 80)
Full size table

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Manzini, C., van der Vaart, C.H., van den Noort, F. et al. Pessary fitting for pelvic organ prolapse: parameters associated with specific reasons for failure. Int Urogynecol J 33, 2037–2046 (2022). https://doi.org/10.1007/s00192-021-05053-w

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  • DOI: https://doi.org/10.1007/s00192-021-05053-w

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