Prognostic tools for hypertrophic scar formation based on fundamental differences in systemic immunity

Unpredictable hypertrophic scarring (HS) occurs after approximately 35% of all surgical procedures and causes significant physical and psychological complaints. Parallel to the need to understanding the mechanisms underlying HS formation, a prognostic tool is needed. The objective was to determine whether (systemic) immunological differences exist between patients who develop HS and those who develop normotrophic scars (NS) and to assess whether those differences can be used to identify patients prone to developing HS. A prospective cohort study with NS and HS groups in which (a) cytokine release by peripheral blood mononuclear cells (PBMC) and (b) the irritation threshold (IT) after an irritant (sodium lauryl sulphate) patch test was evaluated. Univariate regression analysis of PBMC cytokine secretion showed that low MCP‐1, IL‐8, IL‐18 and IL‐23 levels have a strong correlation with HS (P < .010‐0.004; AUC = 0.790‐0.883). Notably, combinations of two or three cytokines (TNF‐a, MCP‐1 and IL‐23; AUC: 0.942, Nagelkerke R²: 0.727) showed an improved AUC indicating a better correlation with HS than single cytokine analysis. These combination models produce good prognostic results over a broad probability range (sensitivity: 93.8%, specificity 86.7%, accuracy 90,25% between probability 0.3 and 0.7). Furthermore, the HS group had a lower IT than the NS group and an accuracy of 68%. In conclusion, very fundamental immunological differences exist between individuals who develop HS and those who do not, whereas the cytokine assay forms the basis of a predictive prognostic test for HS formation, the less invasive, easily performed irritant skin patch test is more accessible for daily practice.     

Zwei Fälie von Delirium potatorum

Ohne Zusammenfassung     

The influence of the spring activator on the mobility of the lower jaw in traumatically injured patients

For functional rehabilitation and improvement of mandibular mobility, 14 patients with dislocated collum or collum fracture dislocations were treated with a spring activator after surgical-conservative treatment. With an interincisal distance of<12 mm, therapy was started with a loop spring. The average age of the patients was 26.6 years. Eight patients showed additional traumatic injuries, 2 patients were seriously polytraumatically injured. The clinical investigations referring to the maximum mouth opening and maximal interincisal distance resulted in a good to very good functional rehabilitation in all cases. The average maximal interincisal distance of 31.7 mm at the beginning of the spring activator therapy could be increased to 47.3 mm. The largest increase of the maximal interincisal distance was observed after 4 weeks of therapy. The type of reaction, however, differed interindividually. Three patients showed a spontaneous improvement of the interincisal distance within the first 2 to 3 weeks of removal of intermaxillary fixation, whereas 7 patients whowed no improvement or only slightly improved values until insertion of the spring activator. An enlargement of the interincisal distance could be achieved in almost every patient within a relatively short period of time despite a drastically reduced mouth opening. Consequently, because of its mode of action in the form of a neuromuscular influence, the spring activator is especially suitable for the functional rehabilitation of patients with fractures of the condylar process.     

Methods for epidemiologic analyses of multiple exposures: A review and comparative study of maximum-likelihood,preliminary-testing,and empirical-bayes regression

Many epidemiologic investigations are designed to study the effects of multiple exposures. Most of these studies are analysed either by fitting a risk-regression model with all exposures forced in the model, or by using a preliminary-testing algorithm, such as stepwise regression, to produce a smaller model. Research indicates that hierarchical modelling methods can outperform these conventional approaches. I here review these methods and compare two hierarchical methods, empirical-Bayes regression and a variant I call ‘semi-Bayes’ regression, to full-model maximum likelihood and to model reduction by preliminary testing. I then present a simulation study of logistic-regression analysis of weak exposure effects to illustrate the type of accuracy gains one may expect from hierarchical methods. Finally, I compare the performance of the methods in a problem of predicting neonatal mortality rates. Based on the literature to date, I suggest that hierarchical methods should become part of the standard approaches to multiple-exposure studies.