Résumé
Abstract Introduction A new method for segmenting and quantifying the macular area based on morphological alternating sequential filtering (ASF) is proposed. Previous studies show that persons with diabetes present alterations in the foveal avascular zone (FAZ) prior to the appearance of retinopathy. Thus, a proper characterization of FAZ using a method of automatic classification and prediction is a supportive and complementary tool for medical evaluation of the macular region, and may be useful for possible early treatment of eye diseases in persons without diabetic retinopathy. Methods We obtained high-resolution retinal images using a non-invasive functional imaging system called Retinal Function Imager to generate a series of combined capillary perfusion maps. We filtered sequentially the macular images to reduce the complexity by ASF. Then we segmented the FAZ using watershed transform from an automatic selection of markers. Using Hu's moment invariants as a descriptor, we can automatically classify and categorize each FAZ. Results The FAZ differences between non-diabetic volunteers and diabetic subjects were automatically distinguished by the proposed system with an accuracy of 81%. Conclusion This is an innovative method to classify FAZ using a fully automatic algorithm for segmentation (based on morphological operators) and for the classification (based on descriptor formed by Hu's moments) despite the presence of edema or other structures. This is an alternative tool for eye exams, which may contribute to the analysis and evaluation of FAZ morphology, promoting the prevention of macular impairment in diabetics without retinopathy.
Résumé
Abstract Objective: To test the capacity of the Logistic CASUS Score on the second postoperative day, the total serum bilirubin dosage on the second postoperative day and the extracorporeal circulation time, as possible predictive factors of long-term stay in Intensive Care Unit after cardiac surgery. Methods: Eight-two patients submitted to cardiac surgery with extracorporeal circulation were selected. The Logistic CASUS Score on the second postoperative day was calculated and bilirubin dosage on the second postoperative day was measured. The extracorporeal circulation time was also registered. Patients were divided into two groups: Group A, those who were discharged up to the second day of postoperative care; Group B, those who were discharged after the second day of postoperative care. Results: In this study, 40 cases were listed in Group A and 42 cases in Group B. The mean extracorporeal circulation time was 83.9±29.4 min in Group A and 95.8±29.31 min in Group B. Extracorporeal circulation time was not significant in this study (P=0.0735). The level of P significance of bilirubin dosage on the second postoperative day was 0.0003 and an area under the ROC curve of 0.708 with a cut-off point at 0.51 mg/dl was registered. The level of P significance of Logistic CASUS Score on the second postoperative day was 0.0001 and an area under the ROC curve of 0.723 with a cut-off point at 0.40% was registered. Conclusion: The Logistic CASUS Score on the second postoperative day has shown to be better than the bilirubin dosage on the second postoperative day as a predictive tool for calculating the length of stay in intensive care unit during the postoperative care period of patients. Notwithstanding, extracorporeal circulation time has failed to prove itself as an efficient tool to predict an extended length of stay in intensive care unit.