EVALUATION OF THE RELEASE RATE OF A CHEMOTHERAPEUTIC AGENT INCORPORATED AS A COATING ON A BIODEGRADABLE URETERAL STENT. IN VITRO STUDY

INTRODUCTION

To assess the release rate of Mitomycin C (MMC) after its adherence to a biodegradable ureteral stent (BraidStent™-MMC) by dip coating in order to evaluate its potential application as an adjuvant treatment for upper tract urothelial carcinoma.

MATERIAL AND METHODS

The dip coating technique is applied to a total of 10 fragments of the BraidStent™ catheter which has a polymeric matrix as a coating. Each 3 cm fragment is immersed 10 times in pure MMC crystallising in methanol and finally obtaining the formation of microlayers on its surface. After drying, each fraction of the stent is immersed in 5 ml of artificial urine to study its interaction with this medium. The samples remain in an orbital shaker at 36ºC and the medium is exchanged under sterile conditions after 12, 24, 48, 48, 72, 96 and 120h. At each replacement, the remaining urine is analysed by HPLC-DAD to quantify the presence of the cytotoxic agent.   

RESULTS

During the first 12h, MMC is completely released reaching a mean concentration of 52.22 mg/L. Comparing this result with those previously obtained with the first BraidStent ™ -MMC formulation (10.82mg/L), it is determined that this technique allows to increase the release rate up to 5 times.

CONCLUSIONS

The release rate of Mitomycin C from a biodegradable ureteral stent is increased by integrating a polymeric matrix with microlayers in its coating. Further trials are needed to achieve the therapeutic dose for clinical application in oncology patients.

A predictive model for the treatment approach to community-acquired pneumonia in patients needing ICU admission

OBJECTIVE

To create a predictive model for the treatment approach to community-acquired pneumonia (CAP) in patients needing Intensive Care Unit (ICU) admission.

DESIGN

Multicenter prospective study.

SETTING

Twenty-six Spanish ICUs.

PATIENTS

One hundred seven patients with CAP, all of them with accurate etiological diagnosis, divided in three groups according to their etiology in typical (bacterial pneumonia), Legionella and other atypical (Mycoplasma, Chlamydia spp. and virus). For the multivariate analysis we grouped Legionella and other atypical etiologies in the same category.

METHODS

We recorded 34 variables including clinical characteristics, risk factors and radiographic pattern. We used a multivariate logistic regression analysis to find out a predictive model.

RESULTS

We have the complete data in 70 patients. Four variables: APACHE II, (categorized as a dummy variable) serum sodium and phosphorus and "length of symptoms" gave an accurate predictive model (c = 0.856). From the model we created a score that predicts typical pneumonia with a sensitivity of 90.2% and specificity 72.4%.

CONCLUSION

Our model is an attempt to help in the treatment approach to CAP in ICU patients based on a predictive model of basic clinical and laboratory information. Further studies, including larger numbers of patients, should validate and investigate the utility of this model in different clinical settings.