Using the Peanut Exercise Ball to Reduce Cesarean Section Rates: A Randomized Controlled Trial

Overview

This study is designed as a prospective, randomized controlled trial that will compare the use of the peanut exercise ball in laboring patients compared with no use of the exercise ball. We hypothesize that use of the peanut ball decreases the incidence of cesarean section.

This study is designed as a prospective, randomized controlled trial that will compare the use of the peanut exercise ball in laboring patients compared with no use of the exercise ball. The investigators plan to include all pregnant women over the age of 18 who present to VCU Labor and Delivery in labor or for induction of labor with a fetus in cephalic presentation. They will have the peanut shaped exercise ball placed between the maternal legs in either the supine or upright position during labor. The peanut ball can be seen at this link, which is similar to the ball the investigators use on Labor and Delivery (http://www.amazon.com/Isokinetics-Inc-Brand-Peanut-Ball/dp/B0026N2JWG). We use various sizes of this durable, non-latex exercise ball. There is a small size (for women ,5'3" that is 40inches), medium size for women 5'3" to 5'"7 (50inches) and a large for women \>5'7" (60inches). The length of time using the peanut ball will be quantified by charting in OB TraceVue software (which is currently standard practice with peanut ball use). Each patient will be assigned a number in order starting at 1. Each patient will then be randomized using a block randomization scheme with pre-assigned envelopes in the labor and delivery team room starting at number 1. Each participant will have an envelope pulled in order of their number assignment when admitted to labor and delivery and consent obtained. Exclusion criteria for this study include women with multifetal gestations, fetus in breech or transverse position, musculoskeletal abnormalities in the mother which might preclude them from proper positioning on the peanut ball. This study is a prospective, two-armed randomized controlled trial (RCT) with interim analyses planned after 50% and 75% of the patients have completed the study. Using nTerim 2.0, 2000 total subjects (1000 per group) will be needed to have a study powered at 80% to detect a difference in the C-section rate if the treatment and control groups have C-section rates of 11.25% and 15%, respectively, using a one-sided test at the 0.05 level. The primary outcome will be the observed incidence of cesarean section delivery in the two populations of randomized, laboring women. Bayesian stopping rules, for expected success and futility, are to be added to this study. Bayesian stopping rules have advantages over other traditional types of interim analyses. Specifically, they can be used for Bayesian or frequentist (e.g. traditional) trial designs without requiring the statistical analysis or study design to be altered. Additionally, the study is not penalized for additional 'looks' at the data, as is the case in traditional interim analyses. A drawback of this strategy is that the methods used to analyze the data (e.g. frequentist and Bayesian) have different interpretations and may not come to the same conclusion. The investigators plan on conducting three interim analyses, after sample sizes of 500, 1000, and 1500 have been achieved. At each look, the predicted probability of trial success, assuming the full 2004 subjects are accrued, will be calculated. The predictive probability is defined as the probability that the unanticipated C-section rate for the Peanut Ball (PB) group is lower than that of the control (C), as measured assuming the full 2004 subjects are accrued and conditional on the data obtained from the subjects that the study has already accrued. If this probability is small (e.g. \< 0.10), then the study will stop for futility. If the predicted probability with the current sample size is large, meaning it is likely that the Peanut ball group has a lower unanticipated C-section rate, then the study will be stopped for expected success. Predicted probabilities of 0.95, 0.90, and 0.90 for the interim analyses at 500, 1000, and 1500 subjects will be used to determine expected success, respectively. If neither of these conditions are met, the study will continue to accrue subjects until a maximum of 2004 subjects. The calculation of the predictive probabilities are slightly different for futility and trial success. For the futility analysis, the posterior distribution of an unanticipated C-section will be will be specified as a beta distribution with Xig +1 and Nig - Xig +1 degrees of freedom (Beta(Xig +1, Nig - Xig +1)), where Xig denotes the total number of unanticipated C-sections for the group g (PB, C) for assessment i (1,2,3) from the total sample size in each group (Nig). This distribution comes from the commonly used beta-binomial posterior distribution using and uninformative (uniform) prior. For each treatment group and interim analysis, an unanticipated C-section rate will be simulated from the respective posterior distribution (pigj) and, based on this simulated value, a simulated number of additional unanticipated C-sections will be calculated. This process will repeat itself 10,000 times, and for each iteration, the total estimated rate of unanticipated C-sections will be calculated. The posterior probability for futility, P(pi,PB+0.0375\<pi,C) after accruing the total 2004 subjects will be calculated by summing up the instances where pi,PBj+0.0375\<pi,Cj, where pi,gj is the predictive probability of an unanticipated C-section after full enrollment for simulation j. The offset, 0.0375, is calculated from the hypothesized difference from the original power analysis (0.15-0.1125=0.0375) A similar process will be used for efficacy, however, the predictive probability will be calculated from the inequality P(pi,PB\<pi,C). The investigators will collect the data, perform data entry and review charts to ensure accuracy of information. Medical Record Numbers will be collected with data collection to ensure that we can adequately review the chart of the patient for data collection.The investigators will also collect information on mode of delivery (vaginal, operative vaginal, csection), gravidity, parity, age, bmi, epidural anesthesia (yes/no), induction vs spontaneous labor, gestational age at delivery, dilation at admission, fetal position at delivery, birth weight, cord ph, Apgars, dystocia, length of active phase of labor and second stage of labor.

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Eligibility

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Outcomes