An Algorithm Recommendation to Detect Specific Pathology of the Lacrimal Sac.

We aimed to recommend an efficient algorithm to detect the presence of specific pathologies of the lacrimal sac (LS). The charts of 296 patients who had undergone LS biopsy were reviewed retrospectively. The age, gender, history, examination and radiological findings, sac appearance, and pathology results of the patients were recorded. The power of our data to predict the presence of potential specific pathology was identified by regression analysis. After the causality evaluation of the statistical results, an algorithm was created to differentiate specific LS pathologies from chronic dacryocystitis. Our algorithm was mainly formed by deciding on radiological examination and biopsy according to the risk scoring created by the examination findings. A specific LS pathology was observed in 11 (3.7%) patients. When we applied the recommended algorithm to cases with a suspicion of specific pathology and/or found to have a specific pathology, 36.4% of the patients would not require radiological examination and 29.6% of them would not require a biopsy. On the other hand, 80% of the frozen biopsies had been conducted on cases without a specific pathology. Managing the cases according to our algorithm would mean that frozen biopsy would be recommended in only 1 (12.5%) case without a specific pathology. Besides, the detection of cases with a specific pathology would not be prevented and the necessary diagnostic procedures would continue to be performed. Specific LS pathologies can be detected adequately, whereas decreasing unnecessary examinations and procedures in cases without a specific pathology by using our algorithm.