ANALYSIS OF ANTI NUCLEAR ANTIBODY INDIRECT IMMUNOFLUORESCENCE SCREENING TEST DATA WITH THE CLINICAL ACTIVITY IN A GROUP OF SLE PATIENT IN BANDUNG

• Main Author: Satrionegoro, Trisulo
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/62178
• Institution: Institut Teknologi Bandung

Systemic Lupus Erithemathosus is an autoimmune disease that has developed in Indonesian population in recent years. This disease has many unspecific symptoms that could replicate many other disease's signs and symptoms, therefore it has created many problems in defining the presence of SLE. Specific clinical approach is the main key to unlock the morbidity and mortality of SLE, because this disease can turn from silent disease, with no symptoms to a violent burst of acute attacks to many organs, typically vital ones. Physician could approach through processes of diagnosis, question and history taking but then a laboratory result is one of the unbiased way to determine a diagnosis. The main laboratory method to evaluate SLE is ANA Screening Test, then the anti ds-DNA test and then other clinical figures unspecific to SLE. The ANA Screening Test is the gold standard to determine SLE because of its high specifity. This test will create a result of qualitative measure and a semiquantitative result, but never to determine or predict the clinical significance of the disease. This research has it goal to create a way to optimize this test so it could benefit more for the physician or the patient. Patient is elected from the status and severity of the disease where each patient's blood will be drawn and collected as Serum. This serum will be tested with the ANA indirect immunofluorescence test with the Hep-2 cell and primate liver cell as it conjugate. This fluorescence will be evaluated by pathological physician and then a qualitative data will be produced. Then this data will be analyzed with the clinical activity of each patient. The analysis using Hep-2 cell and primate liver cell gives a unique result in each patient. Patient with different clinical activity will have different result. This result, the pattern it gave, will differ among different analyst. Then this result was interpreted with the mainstream way to get a data of each pattern's auto antibody it produces. The results are that the analysis could predict 64.9% of the symptoms showed by each patient and it has a corrective value of 96.7% in a way to predict each symptom. The mean number of SLEDAI score from each patient is 6.8 and during flare the mean number increases to 17.9 thus it has a mean number of score difference 11.1. This analysis could predict 64.9% correct clinical feature that featured on patients and this analysis has an accuracy of the prediction by 96.7%. This method has the potential to be a supplementary data for the physician or the patient for the assessment and evaluation of the disease.