Karl-Ernst Biebler

Effects of Topically Applied Dexamethasone on Mucosal Wound Healing Using a Drug-Releasing Stent

Objective/Hypothesis: Evaluation of the impact of continuously topically released dexamethasone using a drug‐releasing stent on quality of regenerated mucosa after full thickness injury in the paranasal sinuses.

Effects of a dexamethasone-releasing stent on osteoneogenesis in a rabbit model.

Background This study is an evaluation of wound healing in an animal model for surgery of frontal sinusitis and treatment effect of topically released dexamethasone using a drug-releasing stent with special emphasis of osteoneogenesis. Methods A prospective, controlled, randomized, double-blinded animal study was performed. Nineteen New Zealand white rabbits were subjected to surgery via an external approach, a 4-mm circular wound was created on the medial side of the maxillary sinus and the underlying bone was denuded of periosteum. The wound was covered in a randomized fashion with either a silicone foil or a new dexamethasone-releasing stent system. Twelve to 30 days later, the animals were killed and a histological examination was performed. Results In comparison with the baseline bony thickness (40 micrometer) obtained in one animal, osteoneogenesis occurred on both paranasal sides but was significantly less if a dexamethasone-releasing stent was applied (117 [95% CI, 116–128]; 52 [95% CI, 43–64]; p < 0.001). Maximal bony thickness was observed in both treatment groups between days 20 and 25 with a tendency toward a higher percentage decrease in the dexamethasone-treated sides (p < 0.08). Using a visual analog scale (0–5) a significantly smoother bony surface was observed for dexamethasone (2 [95% CI, 1.1–1.9]; 2 [95% CI, 1.8–2.2]; p < 0.01). Conclusion Using a new drug-releasing stent system, dexamethasone efficiently decreases postoperative osteoneogenesis in a standardized animal wound model for endoscopic sinus surgery. Therefore, the use of this system may be of value to decrease restenosis rates using corticosteroids in selected patients after frontal sinus surgery, especially the endoscopic modified Lothrop procedure.

Data Mining and Metrics on Data Sets

One needs suitable metrics for topologically based methods of the data analysis. Examples of distances and metrics are given. A general method for the generation of metrics is developed. Its usefulness is demonstrated in support of classification methods for mixed type data

Cluster- and Discriminant Analysis With Both Metric and Categorial Data

Questions in medicine and biological sciences which require a cluster or discriminant analysis frequently appear. If there isn’t clarity concerning a probability theoretical data model, topologically based methods should be preferred. In this paper, a topological data model is defined for both metric and categorial variables. Every categorial character can be transformed into dichotomous characters. Therefore, we restrict the description to continuous and binary variables. A cluster analysis regarding this data space topology is illustrated on hand of a data set from forensic medicine.

Transformations of Confidence Intervals for Risk Measures

The relative risk and the odds ratio are discussed briefly in connection with their point estimations and confidence estimations. At an example is proved that the numeric conversion of the confidence limits of the odds ratio does not yield a confidence interval for the relative risk necessarily.

Splines and compartment models : an introduction

Interpolating Splines of Degree n Interpolating Cubic Splines Interpolating Cubic Splines with Several Extreme Characteristics Smoothing Cubic Splines Estimation of Smoothing Parameters Interpolating Quadratic Splines Smoothing Quadratic Splines Splines and Average Functions Compartment Models Calculability and Identifiability Compartment Models and Associated Residence Time Distributions Calculation Methods Related to Compartment Models Varied Minimum Chi-square Parameter Estimation Pharmacokinetics for Multiple Applications Mathematica(R) Programs for Selected Problems.

How Exactly Do We Know Inheritance Parameters

There are different concepts to quantify the information contained in a data set. The classic result is from R.A.Fisher: Regarding a sample over a random variable. The Fisher-Information is defined under certain assumptions as the inverse of the Rao-Cramer barrier in the well known inequality of the same name. The Fisher-Informations are considered for the simplest genetic models of intheritance. This applies to medically relevant ranges of the inheritance model parameter and large data sets. The results are compared with exact calculations.