Exeter Short Stems Compared With Standard Length Exeter Stems : Experience From the Australian Orthopaedic Association National Joint Replacement Registry

The standard Exeter stem has a length of 150 mm with offsets 37.5 to 56 mm. Shorter stems of lengths 95, 115 and 125 mm with offsets 35.5 mm or less are available for patients with smaller femurs. Concern has been raised regarding the behavior of the smaller implants. This paper analyzed data from the Australian Orthopaedic Association National Joint Replacement Registry comparing survivorship of stems of offset 35.5 mm or less with the standard stems of 37.5 mm offset or greater. At 7 years, there was no significant difference in the cumulative percent revision rate in the short stems (3.4%, 95% CI 2.4-4.8%) compared with the standard length stems (3.5%, 95% CI 3.3-3.8%) despite its use in a greater proportion of potentially more difficult developmental dysplasia of the hip cases.     

Predictors of a difficult intubation in the bariatric patient: does preoperative body mass index matter?

BackgroundThe incidence of difficult intubations in morbidly obese patients has been reported to be 12–20%; however, no well-established predictors of a difficult intubation exist for this patient population. Our objective was to evaluate the factors associated with a difficult intubation in morbidly obese patients undergoing laparoscopic Roux-en-Y gastric bypass at an integrated multispecialty health system with a 325-bed community teaching hospital serving 19 counties.MethodsThe anesthetic records of patients undergoing LRYGB from 2001 to 2010 were reviewed. Difficult intubations were defined as direct laryngoscopy graded ≥1 on a 0–2 difficulty scale and unplanned fiberoptic intubations. Statistical analysis included chi-square, univariate, and multivariate logistic regression.ResultsA total of 915 consecutive patients underwent LRYGB during the study period. Of these, 3 patients were excluded because of incomplete data. Of the 912 included patients, 25 (2.7%) underwent planned fiberoptic intubation, 830 (91%) had an uneventful intubation, and 57 (6.3%) had a difficult intubation. Difficult intubations were more common in men than in women (11% versus 6%, P = .027). Difficult intubations were not associated with an increasing preoperative body mass index (P = .073), the presence of obstructive sleep apnea (P = .784), or the presence of gastroesophageal reflux disease (P = .335). Multivariate predictors of a difficult intubation were Mallampati class 4 (odds ratio [OR] 2.76, P = .035), abnormal thyromental distance (OR 4.39, P = .001), restricted jaw mobility (OR 3.26, P = .018), and a history of a difficult intubation (OR 4.17, P = .002).ConclusionsAn increased Mallampati class, abnormal thyromental distance, restricted jaw mobility, and a history of difficult intubations were independent predictors of a difficult intubation. An increasing body mass index did not predict for a difficult intubation.     

The distinction between unipolar and bipolar depression: A cognitive theory perspective

Background

There is very limited data about the cognitive structure of bipolar depression when compared to unipolar depression. The aim of the study was to look into the differences between unipolar and bipolar depressed patients regarding their cognitive structure in view of Beck's cognitive theory.

Methods

In this study, 70 bipolar patients during a depressive episode, 189 unipolar depressed patients and 120 healthy subjects were recruited. The participants were interviewed by using a structured clinical diagnostic scale. To evaluate the cognitive structure differences, the Automatic Thoughts Questionnaire (ATQ) and the Dysfunctional Attitude Scale (DAS) were used.

Results

We found that on the mean ATQ total score, the unipolar depressed patients scored significantly higher (92.9 ± 22.7) than both the bipolar depressed patients (73.2 ± 24.7) and the healthy subjects (47.1 ± 19.6), even after controlling for all confounding factors, e.g. gender, marital status, depressive symptom severity (F = 157.872, p < 0.001). The bipolar depressed patients also scored significantly higher on the mean ATQ total score than the healthy controls. On the mean DAS total score, and on the mean score of its subscale of need for approval, the bipolar depressed patients scored (152.8 ± 21.2 and 48.2 ± 7.4, respectively) significantly higher than both the unipolar depressed patients (160.9 ± 29.0 and 51.9 ± 9.7, respectively) and the healthy subjects (127.9 ± 32.8 and 40.2 ± 12.2, respectively), even after controlling for any confounding factor (F = 45.803 [p < 0.001] and F = 43.206 [p < 0.001], respectively). On the mean score of the perfectionistic attitude subscale of the DAS, the depressed groups scored significantly higher than the healthy subjects, but they did not seem to separate from each other (F = 41.599, p < 0.001).

Conclusions

These results may help enhance the understanding of the potentially unique psychotherapeutic targets and the underlying cognitive theory of bipolar depression.     

Classification of carotid artery Doppler signals in the early phase of atherosclerosis using complex-valued artificial neural network

In this study, carotid arterial Doppler ultrasound signals were acquired from left carotid arteries of 38 patients and 40 healthy volunteers. The patient group had an established diagnosis of the early phase of atherosclerosis through coronary or aortofemoropopliteal angiographies. Results were classified using complex-valued artificial neural network (CVANN). Principal component analysis (PCA) and fuzzy c-means clustering (FCM) algorithm were used to make a CVANN system more effective. For this aim, before classifying with CVANN, PCA method was used for feature extraction in PCA-CVANN architecture and FCM algorithm was used for data set reduction in FCM-CVANN architecture. Training and test data were selected randomly using 10-fold cross validation. PCA-CVANN and FCM-CVANN architectures classified healthy and unhealthy subjects for training and test data with about 100% correct classification rate. These results shown that PCA-CVANN and FCM-CVANN classified Doppler signals successfully.