Intravaginal Electrical Nerve Stimulation in Women With Non-contracting Pelvic Floor

Overview

It is estimated that about 30% of women cannot voluntarily contract the pelvic floor muscles (PFM). PFM training (PFMT) represents the first therapeutic option for the treatment of female urinary incontinence (UI), however the inability to contract this muscle makes PFMT unfeasible. The primary objective of this project is to evaluate clinically the efficacy of intravaginal electrical stimulation associated with verbal instructions to provide the ability of women to contract voluntary their PFM. The secondary objective is to evaluate the UI prevalence and impact on quality of life.

This is a randomized controlled trial. A simple randomization procedure will be conducted using computer generated list. This list will be kept with a secretary not involved with the research. A concealed allocation will be performed. All participants will be recruited at Rehabilitation Center of the Clinical Hospital of Ribeirão Preto Medical School, University of São Paulo. The primary outcome of the study will be vaginal palpation, to differentiate women capable or not capable to perform a PFM contraction. The secondary outcome will be measured using the ICIQ- UI SF questionnaire. To analyze the proportions of improvement after the intervention in relation to primary outcome we will consider the proportion of women with values equal or above 2 and 3 as specified in the outcome measure section, using the modified oxford grading scale. The sample size calculation will be done based in a pilot study after the study initiate (after registration) considering we found no data from a RCT investigating exactly the same intervention. The study of Vasconcelos et al. (2017) that investigated a similar intervention in the same population performed a sample size calculation using a test of differences between proportions and Fisher's exact test based in the proportion of change in the group receiving electrical stimulation ( 0.35 point) and in the control group (CG) (0.13 point). Considering a significance level of 5% and 80% test power, in the comparison between the intervention group (IG) and control group (CG), the minimum number indicated was 61 participants per group; however as the intervention was not exactly the same and the control group received instructions to perform home training we intend to do this calculation again based in a pilot sample after the study initiate (after registration). As stated before in the initial registration, the sample size calculation was conducted based on a pilot test carried out by the researcher. The sample calculation was used for qualitative data (primary outcome measure) and non-paired sample based on the proportion of improvement after the intervention. The sample calculation compared n=14 in the control group and n= 9 in the intervention group. Considering the proportion of improvement, after intervention, in women with values equal or above 2 is suggested that a sample size of 14 participants per group would be adequate to see between group differences at power=0.90 and α=0.05. In a second situation, the proportion of improvement will be considered as a value equal or above 3, in this case a sample size of 28 participants per group would be adequate to see between group differences at power=0.80 and α=0.05, and 37 participants per group would be adequate to see between group differences at power=0.90 and α=0.05. Data analysis The data will be analyzed initially through descriptive statistics, which will enable the characterization of the sample regarding the variables collected. This methodology has as basic objective to synthesize a series of values of the same nature, allowing a global view of the variation of these values, organizing and describing the data through tables of frequencies and descriptive measures. To verify the association between the categorical variables, the data will be submitted to Fisher's exact test. The association quantification will be measured through logistic regression models, where the crude odds ratio with its respective 95% confidence intervals will be calculated. The analysis of variance (ANOVA) will be used to verify the homogeneity between the groups of quantitative variables. The Student's t-test will be used to compare two means from unpaired samples. To test whether the variances of the two groups are statistically equal, and if the data follows the normal distribution, the PROC TEST procedure of the SAS software will be used. The mixed effects linear models (random and fixed effects) will be used for the analysis of the ICIQ-S questionnaire. This method is used in the analysis of data where the responses of the same individual are grouped and the assumption of independence between observations in the same group is not adequate (Schall, 1991). In the mixed-effects model used, individuals will be considered as random effects and, as fixed effects, the groups, the times and the interaction between them. The adjustment of the model will be done through the PROC MIXED procedure of the statistical software SAS. The results will be reported as estimates of effect size. In relation to the primary outcome we will present the proportion of improvement, crude odds ratio with respective confidence intervals of 95%. For the secondary outcome measure we will present mean difference and 95% CI). Data will be analyzed Independent of compliance to intervention (intention to treat analysis). A secondary per-protocol analysis will be done to verify the effect of trial adherence on the primary outcome. This analysis will include only women who received at least 80% of the physiotherapy sessions. A sensitivity analysis will be performed if necessary to adjust for possible baseline imbalances. All statistical analyzes will be performed using the SAS® 9 statistical software. The level of significance adopted for all tests will be 5%. Quality assurance plan that addresses data validation and registry procedures, including any plans for site monitoring and auditing. Data checks to compare data entered into the registry against predefined rules for range or consistency with other data fields in the registry. Source data verification to assess the accuracy, completeness, or representativeness of registry data by comparing the data to external data sources (for example, medical records, paper or electronic case report forms, or interactive voice response systems). Data dictionary that contains detailed descriptions of each variable used by the registry, including the source of the variable, coding information if used (for example, World Health Organization Drug Dictionary, MedDRA), and normal ranges if relevant. Standard Operating Procedures to address registry operations and analysis activities, such as patient recruitment, data collection, data management, data analysis, reporting for adverse events, and change management. .