Pudendal nerve decompression in perineology : a case series

BACKGROUND: Perineodynia (vulvodynia, perineal pain, proctalgia), anal and urinary incontinence are the main symptoms of the pudendal canal syndrome (PCS) or entrapment of the pudendal nerve. The first aim of this study was to evaluate the effect of bilateral pudendal nerve decompression (PND) on the symptoms of the PCS, on three clinical signs (abnormal sensibility, painful Alcock's canal, painful "skin rolling test") and on two neurophysiological tests: electromyography (EMG) and pudendal nerve terminal motor latencies (PNTML). The second aim was to study the clinical value of the aforementioned clinical signs in the diagnosis of PCS. METHODS: In this retrospective analysis, the studied sample comprised 74 female patients who underwent a bilateral PND between 1995 and 2002. To accomplish the first aim, the patients sample was compared before and at least one year after surgery by means of descriptive statistics and hypothesis testing. The second aim was achieved by means of a statistical comparison between the patient's group before the operation and a control group of 82 women without any of the following signs: prolapse, anal incontinence, perineodynia, dyschesia and history of pelvi-perineal surgery. RESULTS: When bilateral PND was the only procedure done to treat the symptoms, the cure rates of perineodynia, anal incontinence and urinary incontinence were 8/14, 4/5 and 3/5, respectively. The frequency of the three clinical signs was significantly reduced. There was a significant reduction of anal and perineal PNTML and a significant increase of anal richness on EMG. The Odd Ratio of the three clinical signs in the diagnosis of PCS was 16,97 (95% CI = 4,68 – 61,51). CONCLUSION: This study suggests that bilateral PND can treat perineodynia, anal and urinary incontinence. The three clinical signs of PCS seem to be efficient to suspect this diagnosis. There is a need for further studies to confirm these preliminary results

Automatic smoothing and estimation in single index Poisson regression

We address the problem of smoothing parameter (h) selection when estimating the direction vector (β0) and the link function in the context of semiparametric, single index Poisson regression. The single index Poisson model (PSIM) differs from the classical nonparametric setting in two ways: first, the errors are heteroscedastic, and second, the direction parameter is unknown and has to be estimated. We propose two simple, automatic rules for simultaneously estimating β0 and h in a PSIM. The first criterion, called weighted least squares (WLS2), estimates the Kullback-Leibler risk function and has a penalty term to prevent undersmoothing in small samples. The second method, termed double smoothing (DS), is based on the estimation of an L2 approximation of the Kullback-Leibler risk and makes use of a double smoothing idea as in Wand and Gutierrez (1997). Simulations are used to investigate the behavior of various criteria in the PSIM context. Our weighted least squares and double smoothing methods out-perform both a Kullback-Leibler version of cross-validation and the weighted least squares cross-validation criterion proposed by Härdle,Hall and Ichimura (1993)

Semiparametric estimation in single index Poisson regression: a practical approach

In a single index Poisson regression model with unknown link function, the index parameter can be root-n consistently estimated by the method of pseudo maximum likelihood. In this paper, we study, by simulation arguments, the practical validity of the asymptotic behaviour of the pseudo maximum likelihood index estimator and of some associated cross-validation bandwidths. A robust practical rule for implementing the pseudo maximum likelihood estimation method is suggested, which uses the bootstrap for estimating the variance of the index estimator and a variant of bagging for numerically stabilizing its variance. Our method gives reasonable results even for moderate sized samples; thus, it can be used for doing statistical inference in practical situations. The procedure is illustrated through a real data example

Semiparametric Estimation in Single Index Poisson Regression: A Practical Approach

In a single index Poisson regression model with unknown link function, the index parameter can be root-n consistently estimated by the method of pseudo maximumum likelihood. In this paper, we study, by simulation arguments, the practical validity of the asymptotic behavior of the pseudo maximum likelihood index estimator and of some associated cross-validation bandwidths. A robust practical rule for implementing the pseudo maximum likelihood estimation method is suggested, which uses the bootstrap for estimating the variance of the index estimator and a variant of bagging for numerically stabilizing its variance. Our method gives reasonable results even for moderate sized samples thus it can be used for doing statistical inference in practical situations. The procedure is illustrated through a real data example

Semiparametric estimation in single index Poisson regression: A practical approach

In a single index Poisson regression model with unknown link function, the index parameter can be root- n consistently estimated by the method of pseudo maximum likelihood. In this paper, we study, by simulation arguments, the practical validity of the asymptotic behaviour of the pseudo maximum likelihood index estimator and of some associated cross-validation bandwidths. A robust practical rule for implementing the pseudo maximum likelihood estimation method is suggested, which uses the bootstrap for estimating the variance of the index estimator and a variant of bagging for numerically stabilizing its variance. Our method gives reasonable results even for moderate sized samples; thus, it can be used for doing statistical inference in practical situations. The procedure is illustrated through a real data example.

Biofeedback on heart rate variability in cardiac rehabilitation: Practical feasibility and psycho-physiological effects

Objective Biofeedback is a self-regulation therapy by which the patient learns how to optimize the functioning of his autonomic nervous system. It has been applied to patients with various cardiovascular disorders. The purpose of this study was to investigate the practical feasibility and the psycho-physiological effects of biofeedback applied to heart rate variability (HRV biofeedback) in order to increase cardiac coherence in coronary artery disease (CAD) patients participating in a cardiac rehabilitation programme. Methods and results In this randomised and controlled study, 31 CAD patients were randomly assigned to an experimental or to a control group. The experimental group participated in a programme of 10 sessions of cardiac coherence biofeedback training, in addition to the rehabilitation programme. The control group participated in the usual cardiac rehabilitation programme only. Physiological variables (systolic and diastolic blood pressure, SDNN) and psychosocial variables (anxiety, depression, type D personality) were measured at the start and at the end of the programme in both groups. Statistical comparisons assessed the inter and intra group differences. The small sample size precludes any firm conclusions concerning the effect of cardiac coherence biofeedback on physiological or psychological variables. However, we observed a signifi cant increase of the percentage of cardiac coherence, in relation with an increased SDNN index. Conclusions Our study demonstrated the practical feasibility of cardiac coherence biofeedback training in CAD patients. Further research is desirable to investigate the potential benefi t of cardiac coherence biofeedback as an adjunct to stress management in cardiac rehabilitation