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Is it possible to predict surgical indication for pelvic organ prolapse prior to physical examination?
IUGA Academy. Soligo M. Jun 30, 2018; 213016
Topic: Pelvic Organ Prolapse
Dr. Marco Soligo
Dr. Marco Soligo

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Is it possible to predict surgical indication for pelvic organ prolapse prior to physical examination?

Soligo, M1; Turri, A1; De Ponti, E2; Nelva Stellio, L1; Messori, P3; Casati, P1; Cetin, I1

1: Buzzi Hospital - ASST-FBF-Sacco; 2: Medical physics Dep. ASST, Monza-Italy; 3: Macedonio Melloni Hospital - ASST-FBF-Sacco

Introduction: Health-related quality of life (HRQoL) questionnaires are increasingly popular for the clinical management of Pelvic Floor Disorders (PFD) and Pelvic Organ Prolapse (POP). In selecting women for POP Surgery, physical examination play a central role. However symptom severity, according to HRQoL questionnaires strongly correlates with the prolapse size[1].

A tool to select “a priori” (before physical examination) women candidate for POP surgery could be of some value (epidemiological studies, health system resource planning, patients counselling, etc…).

Objective: To investigate the potential of an electronic HRQoL questionnaire: Italian ePAQ (I.ePAQ) to predict the selection for surgery among women complaining of POP symptoms.

Methods: Consecutive women symptomatic for POP, after informed consent, underwent clinical evaluation including symptom assessment via an electronic questionnaire (I.ePAQ) and physical examination (POP-Q ICS). Then one senior urogynecologist decided on conservative vs surgical treatment. Baseline clinical records of women undergoing conservative vs surgical treatment were compared. Univariate analysis was performed and Roc curve on significantly different I.ePAQ domains were applied to establish cutoff scores associated to the clinician decision. Stata 9.0 Software (Stata Corporation, College Station, Texas, USA) was adopted (p value < 0.05 for significance).

Results: Eighty-eight women were enrolled. For 59 of them a conservative treatment was decided, while in 29 cases surgery was the option. The two groups were similar in terms of age, BMI, parity, menopausal status (table 1). I.ePAQ Prolapse and QoL domains were significantly associated with the clinical decision for surgery (table 2). The Roc curve Area for Prolapse and QoL I.ePAQ domains were respectively 0.777 (95% CI 0.680-0.875) and 0.713 (95% CI 0.598-0.829). Once merged the two I.ePAQ domains showed an Area under the Roc Curve of 0.778 (95% CI 0.681-0.875) (Figure 1). According to this a merged (Prolapse + QoL) I.ePAQ score ≥ 38.1 has a sensitivity of 93.1% and a specificity of 55.9% for identifying women that will be selected for surgery.

Conclusions: Over 88 consecutive women complaining of POP symptoms an electronic HRQoL questionnaire (I.ePAQ) can accurately predict (before physical examination) which women will be selected for surgery. This questionnaire could be easily filled in at home, prior to consultation, resulting in a valid tool for planning diagnostic and surgical needs for the health system. Though preliminary, our results highlight an area of potential interest for future research.

  1. Eur J Obstet Gynecol Reprod Biol. 2003 Feb 10;106(2):184-92.

Table 1: Comparison of Patients features between conservative vs surgical group

Conservative group

(n° = 59)

Surgical group

(n° = 29)

Rank sum test Kruskal Wallis

Age (years) median (Range)

69 (42 – 91)

70 (48 – 83)

0.455

BMI median (Range)

26.3 (18.9 – 33.5)

25.7 (20.3–32.5)

0.933

Menopause (mos) median (Range)

198 (0 – 516)

186 (0 – 384)

0.908

Parity median (Range)

2 (0 – 5)

2 (1 – 12)

0.454

Table 2: Comparison of I.ePAQ questionnaire domains between conservative vs surgical group

IePAQ domains

*

Pain mean±SD; median (Range)

25.4 ± 18.5; 25.0 (0 – 66.7)

27.6 ± 19.4; 25.0 (0 – 83.3)

0.661

Capacity mean±SD; median (Range)

5.8 ± 13.6; 0 (0 – 66.7)

4.2 ± 10.5; 0 (0 – 44.4)

0.791

Prolapse mean±SD; median (Range)

38.8 ± 29.2; 41.7 (0 – 100)

67.2 ± 20.9; 75.0 (8.3 – 100)

0.0001

QoL mean±SD; median (Range)

26.1 ± 28.0; 16.7 (0 – 100)

46.7 ± 31.2; 44.4 (0 – 100)

0.001

*Rank sum test Kruskal Wallis

Figure 1: ROC curve applied to merged (prolapse & QoL) I.ePAQ domains


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Work supported by industry: no.

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