Dataset Information

Estimating postvoid residual volume without measuring residual bladder volume during serial cystometrograms.

ABSTRACT: The postvoid residual volume (PVR) is a common urodynamic parameter used to quantify the severity of lower urinary tract dysfunction. However, the serial cystometrograms that are typically used to assess bladder function in animal models make measuring PVR very difficult. Current approaches are to either remove PVR after each void to measure it, which is disruptive to the bladder, or to neglect the unknown contribution to PVR from ureter flow, which results in inaccurate estimates. We propose a procedure to estimate PVR during a serial cystometrogram that requires only a single measurement, rather than measuring after each void. Moreover, this measurement can occur at the end of the experiment such that it does not affect the bladder during data collection. We mathematically express PVR for all voids during a serial cystometrogram using a linear recurrence equation and use this equation to build an estimation procedure for PVR. Using in vivo measurements in urethane anesthetized rats and computer simulations we show that the estimation procedure is at least as accurate in determining PVR as the traditional method of measuring PVR after each void. Furthermore, we demonstrate the adverse effects of repeated PVR measurements in a common animal model of cystitis. Using the proposed procedure can increase the efficiency and accuracy of determining PVR for a serial cystometrogram and is less disruptive to the system under study. This, in turn, allows the calculation of other urodynamic parameters that are critical for research studies, including voiding efficiency and bladder capacity.

SUBMITTER: Danziger ZC

PROVIDER: S-EPMC5008678 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Estimating postvoid residual volume without measuring residual bladder volume during serial cystometrograms.

Danziger Zachary C ZC Grill Warren M WM

American journal of physiology. Renal physiology 20160420 2

The postvoid residual volume (PVR) is a common urodynamic parameter used to quantify the severity of lower urinary tract dysfunction. However, the serial cystometrograms that are typically used to assess bladder function in animal models make measuring PVR very difficult. Current approaches are to either remove PVR after each void to measure it, which is disruptive to the bladder, or to neglect the unknown contribution to PVR from ureter flow, which results in inaccurate estimates. We propose a ...[more]

PMID: 27097895

Similar Datasets

Project description:Personalized medicine has received increasing attention among statisticians, computer scientists, and clinical practitioners. A major component of personalized medicine is the estimation of individualized treatment rules (ITRs). Recently, Zhao et al. (2012) proposed outcome weighted learning (OWL) to construct ITRs that directly optimize the clinical outcome. Although OWL opens the door to introducing machine learning techniques to optimal treatment regimes, it still has some problems in performance. (1) The estimated ITR of OWL is affected by a simple shift of the outcome. (2) The rule from OWL tries to keep treatment assignments that subjects actually received. (3) There is no variable selection mechanism with OWL. All of them weaken the finite sample performance of OWL. In this article, we propose a general framework, called Residual Weighted Learning (RWL), to alleviate these problems, and hence to improve finite sample performance. Unlike OWL which weights misclassification errors by clinical outcomes, RWL weights these errors by residuals of the outcome from a regression fit on clinical covariates excluding treatment assignment. We utilize the smoothed ramp loss function in RWL, and provide a difference of convex (d.c.) algorithm to solve the corresponding non-convex optimization problem. By estimating residuals with linear models or generalized linear models, RWL can effectively deal with different types of outcomes, such as continuous, binary and count outcomes. We also propose variable selection methods for linear and nonlinear rules, respectively, to further improve the performance. We show that the resulting estimator of the treatment rule is consistent. We further obtain a rate of convergence for the difference between the expected outcome using the estimated ITR and that of the optimal treatment rule. The performance of the proposed RWL methods is illustrated in simulation studies and in an analysis of cystic fibrosis clinical trial data.

Dataset Information

Estimating postvoid residual volume without measuring residual bladder volume during serial cystometrograms.

Publications

Estimating postvoid residual volume without measuring residual bladder volume during serial cystometrograms.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets