Tehran University Medical Journal

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Airway management is one of the most important subjects in medicine. This article reviews the history, assessment of airway prior to anesthesia, techniques and equip-ment of airway management and management of patients with anticipated and unan-ticipated difficult airways. This article covers recent literature on airway appliances and devices and their use in different circumstances. Airway assessment methods especially the recent Iranian method have been reviewed and discussed briefly in this article. On the whole the article covers the etiology of difficult airway and offers guidelines for safe practice of anesthesia in patients in whom airway is anticipated to be difficult.

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Background: Failed endotracheal intubation is one of the principal causes of morbidity and mortality in anesthetized patients. If the anesthetist can anticipate which patients may be more difficult to intubate, can reduce the risks of anesthesia greatly and be more prepared for any difficulties that may occur. The aim of this study was to investigate the inability of patients to protrude the lower jaw in predicting difficult intubation.
Methods: In this prospective study, we enrolled 300 patients, above 16 years of age or older, who were scheduled for elective surgery. For all of the patients, before each operation, a single anesthesiologist measured the temporomandibular mobility, which was defined as the difference between the distances, from the lower incisors to the upper incisors in a neutral position and at maximum mandibular protrusion. At the time of intubation, another anesthesiologist, blinded to the preoperative airway assessment test, performed a laryngoscopy in which the laryngoscopic view of the larynx was determined according to the Cormack and Lehane scoring system. Difficult intubation was defined as laryngoscopic views of grade III and IV.
Results: Twenty-one patients were identified as having difficult intubation. Only one patient could not be intubated. The forward movement of the mandible was significantly greater in patients with easy intubation compared to those with difficult intubation (6.42±1.95 mm vs. 3.58±1.26 mm respectively, P<0.001). The use of a cut-off point of less than 5 mm for prediction of difficult intubation showed a sensitivity of 92.86% and a specificity of 70.43%.
Conclusion: The forward movement of the mandible is significantly greater in patients with easy intubation compared those with difficult intubation Although infrequent difficulties may arise, most patients that do not have indicators of difficult intubation will be easy to intubate under anesthesia.

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Background: Whatever its etiology, the inflammatory reactions of preeclampsia lead to the activation of endothelium and result in vascular damage. CRP is considered a sensitive index of systemic inflammation, so it is used as predictive factor for disease. This study was carried out to test the screening and predictive abilities of the CRP test in order to detect and diagnose pregnant women prone to preeclampsia prior to the onset of symptoms.

Methods: In this prospective cohort study, conducted in Arash Hospital between 2005 and 2006, we determined the CRP levels of 201 pregnant women at 10-16 weeks of pregnancy. Based on exclusion criteria and illness, 31 patients were excluded and 170 patients were followed until the end of their pregnancies.

Results: In this study, the mean serum CRP values of those who had preeclamptic and those who had normal pregnancies were compared and the statistical differences were significant: 6.18 mg/L for preeclamptic patients compared with 4.12 mg/L for normal patients (p=0.003). Using a chi-square test, we found that patients whose CRP level was ≥4 were six times more likely to have preeclampsia than those with CRP levels <4 (k=9.4 p=0.002 OR=6.15 95% CI=0.69-22.28).

Conclusion: This study confirms the results of previous reports indicating a significant relationship between rising serum CRP in the first trimester of pregnancy and preeclampsia at third trimester. More studies consisting of other inflammation factors are necessary to find an acceptable and reasonable screening test to diagnose pregnant women who are prone to preeclampsia.

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Background: Millions of deaths occur around the world each year due to lack of access to appropriate treatment for chronic kidney disease patients. Given the importance and mortality rate of this disease, early and low-cost prediction is very important. The researchers intend to identify chronic kidney disease through the optimal combination of techniques used in different stages of data mining.
Methods: This cross-sectional research was conducted from February 1999 to May 2014. The used data set included 4145 samples and 32 attributes, where Each sample corresponded to a patient and each attribute corresponded to the demographic and clinical traits. There were several eligibility criteria for the patients for clinical testing. These criteria for the clinical testing included having 18 years of age and older, living in Isfahan city, willing to participate in the study, lack of fever and cold during laboratory tests, no strenuous exercise 48 hours before laboratory tests, and fasting. Individuals who had an incomplete questionnaire or were unwilling to perform accurate tests were excluded from the study. The target variable is kidney disease, the values of which include sick and healthy. Four data mining techniques have been used in the dataset. These techniques are support vector machine (SVM), random forest (RF), artificial neural network (ANN) and Chi-square automatic interaction detection (CHAID).
Results: Accuracy is the evaluation criteria for comparing available data mining methods. Based on the accuracy criterion, the support vector machine performed better than other techniques (random forest, neural network and CHAID). The best rule is that if the patients consume salt in their diet, their age is between 50 and 69, and they have diabetes. they are 82% more likely to develop chronic kidney disease.

Conclusion: The derived rules also showed that if we use salt and we have diabetes, we are at the risk of developing chronic kidney disease. Moreover, having diabetes can increase the risk of mortality in chronic kidney patients. Aged people should also be more careful about getting chronic kidney disease. Because, they are more prone to develop chronic kidney disease.

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Conclusion: The study indicated that in the KNN model, the rules derived from it can be effective in mortality prediction in patients admitted to ICUs.