T he management of patients with unruptured cerebral aneurysms (UA) remains controversial because of their uncertain natural history. Although estimates of the prevalence of intracranial aneurysms range from 0.5% to 6% on radiological and autopsy studies, the incidence of aneurismal subarachnoid hemorrhage (SAH) is 10/100.000 per year in the United States, leading to the conclusion that the majority of UAs do not rupture.1,2 The average risk of rupture of a UA is estimated to be between 1% and 2% per year. 3,4 The International Study of Unruptured Intracranial Aneurysms (ISUIA) reported on a retrospective and prospective multicenter study in 1998 and 2003. 5,6 In the latter, they observed that aneurysm location, size, and previous SAH were risk factors for rupture, with posterior circulation (PC) aneuryms collectively (including posterior communicating artery [PcoA] aneurysms) and aneurysms >7 mm located in the anterior circulation (AC) rupturing with at rates high enough to justify intervention. This observation seems to contradict the clinical perception that patients Background and Purpose-According to the International Study of Unruptured Intracranial Aneurysms (ISUIA), anterior circulation (AC) aneurysms of <7 mm in diameter have a minimal risk of rupture. It is general experience, however, that anterior communicating artery (AcoA) aneurysms are frequent and mostly rupture at <7 mm. The aim of the study was to assess whether AcoA aneurysms behave differently from other AC aneurysms. Methods-Information about 932 patients newly diagnosed with intracranial aneurysms between November 1, 2006, and March 31, 2012, including aneurysm status at diagnosis, its location, size, and risk factors, was collected during the multicenter @neurIST project. For each location or location and size subgroup, the odds ratio (OR) of aneurysms being ruptured at diagnosis was calculated. Results-The OR for aneurysms to be discovered ruptured was significantly higher for AcoA (OR, 3.5 [95% confidence interval, 2.6-4.5]) and posterior circulation (OR, 2.6 [95% confidence interval, 2.1-3.3]) than for AC excluding AcoA (OR, 0.5 [95% confidence interval, 0.4-0.6]). Although a threshold of 7 mm has been suggested by ISUIA as a threshold for aggressive treatment, AcoA aneurysms <7 mm were more frequently found ruptured (OR, 2.0 [95% confidence interval, 1.3-3.0]) than AC aneurysms of 7 to 12 mm diameter as defined in ISUIA. Conclusions-We found that AC aneurysms are not a homogenous group. Aneurysms between 4 and 7 mm located in AcoA or distal anterior cerebral artery present similar rupture odds to posterior circulation aneurysms. Bijlenga et al Risk of Aneurysm Rupture by Location and Size 3019commonly present with ruptured small aneurysms. Moreover, aneurysm locations were segregated only as being either AC or PC for risk assessment, raising concerns that the effects of pathophysiological mechanisms specific to individual arteries were combined reducing sensitivity to location as a risk factor. Work has since been published dem...
In this paper, we compare five common classifier families in their ability to categorize six lung tissue patterns in high-resolution computed tomography (HRCT) images of patients affected with interstitial lung diseases (ILD) and with healthy tissue. The evaluated classifiers are naive Bayes, k-nearest neighbor, J48 decision trees, multilayer perceptron, and support vector machines (SVM). The dataset used contains 843 regions of interest (ROI) of healthy and five pathologic lung tissue patterns identified by two radiologists at the University Hospitals of Geneva. Correlation of the feature space composed of 39 texture attributes is studied. A grid search for optimal parameters is carried out for each classifier family. Two complementary metrics are used to characterize the performances of classification. These are based on McNemar's statistical tests and global accuracy. SVM reached best values for each metric and allowed a mean correct prediction rate of 88.3% with high class-specific precision on testing sets of 423 ROIs.
BackgroundIndicators to predict healthcare-associated infections (HCAI) are scarce. Malnutrition is known to be associated with adverse outcomes in healthcare but its identification is time-consuming and rarely done in daily practice. This cross-sectional study assessed the association between dietary intake, nutritional risk, and the prevalence of HCAI, in a general hospital population.Methods and findingsDietary intake was assessed by dedicated dieticians on one day for all hospitalized patients receiving three meals per day. Nutritional risk was assessed using Nutritional Risk Screening (NRS)-2002, and defined as a NRS score ≥ 3. Energy needs were calculated using 110% of Harris-Benedict formula. HCAIs were diagnosed based on the Center for Disease Control criteria and their association with nutritional risk and measured energy intake was done using a multivariate logistic regression analysis. From 1689 hospitalised patients, 1024 and 1091 were eligible for the measurement of energy intake and nutritional risk, respectively. The prevalence of HCAI was 6.8%, and 30.1% of patients were at nutritional risk. Patients with HCAI were more likely identified with decreased energy intake (i.e. ≤ 70% of predicted energy needs) (30.3% vs. 14.5%, P = 0.002). The proportion of patients at nutritional risk was not significantly different between patients with and without HCAI (35.6% vs.29.7%, P = 0.28), respectively. Measured energy intake ≤ 70% of predicted energy needs (odds ratio: 2.26; 95% CI: 1.24 to 4.11, P = 0.008) and moderate severity of the disease (odds ratio: 3.38; 95% CI: 1.49 to 7.68, P = 0.004) were associated with HCAI in the multivariate analysis.ConclusionMeasured energy intake ≤ 70% of predicted energy needs is associated with HCAI in hospitalised patients. This suggests that insufficient dietary intake could be a risk factor of HCAI, without excluding reverse causality. Randomized trials are needed to assess whether improving energy intake in patients identified with decreased dietary intake could be a novel strategy for HCAI prevention.
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