Meral Çetin

A Comparison of the Benefits of Sonography and Electrophysiologic Measurements as Predictors of Symptom Severity and Functional Status in Patients With Carpal Tunnel Syndrome

OBJECTIVES To clarify whether sonography or electrophysiologic testing is a better predictor of symptom severity and functional status in carpal tunnel syndrome (CTS) and to assess the diagnostic value of sonography in patients with idiopathic CTS. DESIGN Cross-sectional. SETTING University hospital physical medicine and rehabilitation clinic. PARTICIPANTS Thirty-four hands with CTS and 38 normative hands were evaluated. INTERVENTIONS Not applicable. MAIN OUTCOME MEASURES The Boston Carpal Tunnel Questionnaire, which comprised symptom severity and functional status scale, was applied to CTS patients. Bilateral upper-extremity nerve conduction studies of median and ulnar nerves and sonographic imaging of the median nerve were performed in all participants. Sonographic evaluation was performed by a physician blinded to the physical and electrophysiologic findings of the subjects. RESULTS Cross-sectional areas (CSAs) of the median nerve at the carpal tunnel entrance and proximal carpal tunnel were 12.5+/-2.6 and 10.6+/-2.6 versus 15.6+/-4.2 and 11.5+/-3.2 in CTS patients versus controls, respectively. Increased CSA of the median nerve at the carpal tunnel entrance (P<.002) and at the proximal carpal tunnel (P<.000) were detected in the hands with CTS. Flattening ratios did not differ in a statistically significant manner between the groups (P>.05). The best predictor of symptom severity was median nerve sensory distal latency and that of functional status was median nerve motor distal latency. The optimum cutoff value for median nerve CSA was 11.2mm(2) at the carpal tunnel entrance and 11.9mm(2) at the proximal carpal tunnel. Sensitivity, specificity, and positive and negative predictive values at the proximal carpal tunnel (88%, 66%, 71%, 80%, respectively) were higher than those at the carpal tunnel entrance (68%, 62%, 65%, 66%, respectively). CONCLUSIONS The best predictors of symptom severity and functional status in idiopathic CTS seem to be the electrophysiologic assessments rather than sonographic measurements. On the other hand, sonography may be helpful in the diagnosis of idiopathic CTS.

Rehabiliation of flexor tendon injuries by use of a combined regimen of modified Kleinert and modified Duran techniques

Çetin A, Dinçer F, Keçik A, Çetin M: Rehabilitation of flexor tendon injuries by use of a combined regimen of modified Kleinert and modified Duran techniques. Am J Phys Med Rehabil 2001;80:721–728. Objective: Kleinert (active extension, rubber-band passive flexion) and Duran (passive extension, passive flexion) protocols are two basic types of early motion programs for rehabilitation of flexor tendon injuries. Researchers have been working on various modifications or combinations of these two protocols to improve rehabilitation results. The purpose of this study was to analyze the quality of the functional results of flexor tendon repair after a postoperative regimen of early mobilization by use of a combined regimen of modified Kleinert and modified Duran techniques. Design: Thirty-seven patients (74 digits) with repaired flexor tendon injuries were treated. Functional results of the fingers were evaluated by the Buck-Gramcko system and total active motion measurements. Results: The results were excellent in 73% of the fingers, good in 24%, fair in 1.5%, and none was rated poor. Conclusion: Our results are comparable with the previous studies that used various postoperative rehabilitation techniques. This postoperative management provides an effective way of achieving satisfactory results. Patient-assisted passive exercises are very safe and more cost effective than therapist-assisted passive exercises.

Outlier detection in a preliminary test estimator of the mean

Abstract Pre-test estimator has earlier been introduced to estimate the mean of a normal distribution when non-sample prior information is available. In this paper, our aim is to consider the pre-test estimator for the mean in the presence of outliers. A well known procedure to define the pre-test estimator of the mean is based on the sample mean. However, the sample mean is not a robust location estimator. In order to overcome this problem, we replace it by M-location estimators. In particular, we use the M-location estimators obtained from Huber [6] , Hampel[3] and Tukey [12] . Also, we use the median as an alternative location estimator. Cook’s squared distance (Cook [2]) is used to study the influential observations in a Monte Carlo study. We conduct a simulation study to illustrate the performance of the pre-test estimator of the mean in the presence of outliers in the data.

Robust model selection criteria for robust Liu estimator

In linear regression analysis, outliers often have large influence in the model/variable selection process. The aim of this study is to select the subsets of independent variables which explain dependent variables in the presence of multicollinearity, outliers and possible departures from the normality assumption of the error distribution in robust regression analysis. In this study to overcome this combined problem of multicollinearity and outliers, we suggest to use robust selection criterion with Liu and Liu-type M(LM) estimators.

A simulation study on classic and robust variable selection in linear regression

In linear regression analysis, outliers often have large influence in the variable selection process. The aim of this study is to select the subsets of independent variables, which explain dependent variables in the presence of outliers and possible departures from the normality assumption of the error distribution in robust regression analysis. We compared robust and classical variable selection. Here, as a classics selection criteria we used Cp, AICC and AICF which we proposed. Besides we used Andrews, Huber and Hampel M-estimators in computing of the robust variable selection criteria.

A simulation study on the influence of ties on uniform scores test for circular data

Uniform scores test is a rank-based method that tests the homogeneity of k-populations in circular data problems. The influence of ties on the uniform scores test has been emphasized by several authors in several articles and books. Moreover, it is suggested that the uniform scores test should be used with caution if ties are present in the data. This paper investigates the influence of ties on the uniform scores test by computing the power of the test using average, randomization, permutation, minimum, and maximum methods to break ties. Monte Carlo simulation is performed to compute the power of the test under several scenarios such as having 5% or 10% of ties and tie group structures in the data. The simulation study shows no significant difference among the methods under the existence of ties but the test loses its power when there are many ties or complicated group structures. Thus, randomization or average methods are equally powerful to break ties when applying uniform scores test. Also, it can be concluded that k-sample uniform scores test can be used safely without sacrificing the power if there are only less than 5% of ties or at most two groups of a few ties.

Robust model selection criteria for robust S and LTS estimators

Outliers and multi-collinearity often have large influence in the model/variable selection process in linear regression analysis. To investigate this combined problem of multi-collinearity and outliers, we studied and compared Liu-type S (liuS-estimators) and Liu-type Least Trimmed Squares (liuLTS) estimators as robust model selection criteria. Therefore, the main goal of this study is to select subsets of independent variables which explain dependent variables in the presence of multi-collinearity, outliers and possible departures from the normality assumption of the error distribution in regression analysis using these models.