暂无摘要。

BACKGROUND: Pre-anesthetic evaluation is an important aspect of perioperative patient management. However, anesthesiologists often encounter challenges during anesthesia due toconditions that are not detected during pre-anesthetic evaluations.
METHODS: Case 1 involved a 74-year-old female patient scheduled for cranioplasty and meningioma excision. Severe pancytopenia was detected during anesthesia. Cranioplasty was onlyperformed, the surgery was terminated, and drug-induced pancytopenia was diagnosed andtreated. The pre-anesthetic test results were normal, except for anemia. Case 2 involved a71-year-old male patient who discovered large ecchymosis during general anesthesia preparation in the operating room for choledochal cyst surgery. Surgery was canceled to evaluatethe bleeding tendency, and acquired coagulation factor VIII deficiency was diagnosed andtreated. The pre-anesthetic tests were normal, except for prolongation of the activated partial thromboplastin time.
CONCLUSIONS: Abrupt hematologic and hemostatic changes may occur during anesthesiaeven though pre-anesthetic evaluation findings are normal.

OBJECTIVE: Pre-operative risk classification of patients undergoing anesthesia is an essential interest and has been the focus of many research and categorizations. On the other hand, the ideal categorization system, based on medical doctors\' clinical experience and cooperation with other disciplines, has not been developed yet.
METHODS: In this study, 218 consecutive patient undergoing laparoscopic cholecystectomy operations were included. A novel fuzzy logic evaluation model consisting of 270 rules was constructed. Five major (pulmonary, cardiac, diabetes mellitus and renal or liver disease) and three minor criteria (patients\' age, cigarette smoking and body mass index) were chosen to be used during high-risk groups determination.
RESULTS: The verification of the success of risk value decision with the proposed novel fuzzy logic algorithm is the main goal of this study. On the other hand, though not essential aim, a statistical consistency check was also included to have a deeper understanding and evaluation of the graphical results. During the statistical analysis the 0-30%, 30-60% and 60-90% risk ranges were found to be in a very strong positive relationship with complication occurrence. In this study, 172, 31, 15 patients were in 0-30, 30-60 and 60-90% risk ranges, respectively. Complication rates were 7/172 (4.07%) in 0-30% range, 3/31 (9.68%) in 30-60% range; and 2/15 (13.33%) in 60-90% range.
CONCLUSIONS: Fuzzy based risk classification model was successfully used to predict medical results for patients undergoing laparoscopic cholecystectomy operations and reliable deductions were reached.

暂无摘要。