Dynamic Fixation versus Static Screw Fixation for Syndesmosis Injuries in Pronation External Rotation Ankle Fractures: A Retrospective Case Control Study.

Introduction: The current standard treatment for ankle syndesmosis injury is static screw fixation. Dynamic fixation was developed to restore the dynamic function of the syndesmosis. The purpose of this study was to determine that which of static screw fixation and dynamic fixation is better for treatment of ankle syndesmosis injury in pronation-external rotation fractures. Materials and methods: Thirty patients were treated with dynamic fixation (DF group) and 28 patients with static screw fixation (SF group). The primary outcome was Olerud-Molander Ankle Outcome Score. The secondary outcome were Visual Analogue Scale score and American Orthopedic Foot and Ankle Society score, radiographic outcomes, complications and cost effectiveness. To evaluate the radiographic outcome, the tibiofibular clear space, tibiofibular overlap, and medial clear space were compared using the pre-operative and last follow-up plain radiographs. To evaluate the cost effectiveness, the total hospital cost was compared between the two groups. Results: There was no significant difference in primary outcome. Moreover, there were no significant difference in secondary outcome including Visual Analogue Scale score and American Orthopedic Foot and Ankle Society score and radiographic outcome. Two cases of reduction loss and four cases of screw breakage were observed in the SF group. No complication in the DF group was observed. Dynamic fixation was more cost effective than static screw fixation with respect to the total hospital cost. Conclusion: Although dynamic fixation provided similar clinical and radiologic outcome, dynamic fixation is more cost effective with fewer complications than static screw fixation in ankle syndesmosis injury of pronation-external rotation fractures.

Clinical significance of enzymatic lysophosphatidylcholine (LPC) assay data in patients with sepsis.

Lysophosphatidylcholine (LPC) has been suggested to serve as a useful prognostic marker for sepsis. However, existing LPC assays are complicated, time-consuming, and of limited application in real clinical situations. Thus, we investigated the serum LPC levels in sepsis patients using an enzymatic assay and analyzed the correlations between the serum LPC concentration and clinical characteristics. We prospectively collected blood samples from suspected sepsis patients, commencing on day 1 of sepsis. We analyzed all samples using an enzymatic assay. Additionally, we analyzed the serum LPC concentrations in a control group of 21 healthy blood donors. A total of 105 patients who fulfilled the sepsis criteria were included. The mean serum LPC concentration was 43.49 ± 33.09 µmol/L in sepsis patients, which was much lower than that of 21 healthy controls (234.68 ± 30.33 µmol/L, p<0.001). Bacteremic sepsis was associated with a lower serum LPC concentration than non-bacteremic sepsis (34.8 ± 26.85 vs. 49.05 ± 35.63 µmol/L, p<0.05). No difference in serum LPC concentration was evident between survivors and non-survivors. The serum LPC concentration tended to decrease with the severity of sepsis. The day 1 serum LPC concentration was decreased in patients with sepsis, especially when bacteremia was present. However, the serum LPC level did not correlate with disease severity and did not predict mortality from sepsis.

Optimal dose of vancomycin for treating methicillin-resistant Staphylococcus aureus pneumonia in critically ill patients.

A prospective cohort study was performed to determine the optimal dose of vancomycin to maintain a serum trough concentration of at least 15 to 20 mg/l and to assess the efficacy of this target vancomycin concentration in the treatment of methicillin-resistant Staphylococcus aureus pneumonia. Vancomycin pharmacokinetic parameters were estimated using a CAPSIL software program from serum concentrations of 141 patients with pneumonia treated with vancomycin, regardless of methicillin-resistant Staphylococcus aureus status, at a 28-bed medical intensive care unit. Vancomycin trough concentrations and other pharmacokinetic parameters were compared between five groups of patients differing in their renal function: (1) creatinine clearance > or =60 ml/minute, (2) creatinine clearance 30 to 60 ml/minute, (3) creatinine clearance <30 ml/minute, (4) on intermittent haemodialysis, and (5) on continuous renal replacement therapy. More than 70% of patients failed to reach the recommended therapeutic serum trough concentrations: a higher dose of vancomycin is necessary to maintain serum trough concentration at 15 to 20 mg/l, particularly in critically ill patients with creatinine clearance above 60 ml/minute and in those on intermittent haemodialysis. Among patients with methicillin-resistant Staphylococcus aureus pneumonia, no significant differences were observed in the treatment success rate, length of intensive care unit stay, and intensive care unit mortality rate between patients with vancomycin trough concentrations of >20 mg/l, 15 to 20 mg/l and <15 mg/l.

Acute exacerbation of idiopathic pulmonary fibrosis: incidence, risk factors and outcome.

Although acute exacerbation of idiopathic pulmonary fibrosis (IPF) has become well recognised, the reported incidence and outcomes are highly variable, and risk factors are unknown. The aim of this study was to estimate the incidence, risk factors and impact of acute exacerbations, and other known causes of rapid deterioration. This was a retrospective review of 461 patients with IPF (269 cases were biopsy-proven). The median follow-up period was 22.9 months. Rapid deterioration requiring hospitalisation occurred in 163 (35.4%) patients, with multiple episodes in 42 patients. Acute exacerbation was the most frequent cause (55.2%), followed by infection. The 1- and 3-yr incidences of acute exacerbation were 14.2 and 20.7%, respectively. Never having smoked and low forced vital capacity (FVC) were significant risk factors. The in-hospital mortality rate was 50.0%, and the 1- and 5-yr survival rates from the initial diagnosis were 56.2 and 18.4%, respectively. Acute exacerbation was a significant predictor of poor survival after the initial diagnosis, along with increased age, low FVC and diffusing capacity of the lung for carbon monoxide, and steroid use with or without cytotoxic therapy. 1- and 3-yr incidences of acute exacerbation were 14.2 and 20.7%, respectively. Never having smoked and low FVC were risk factors. Acute exacerbation had a serious impact on the overall survival of the patients with IPF.

Human cardiovascular model and applications.

Cardiovascular diseases (CVDs) can be known as a class of diseases which affect different parts of the cardiovascular system such as the heart or blood vessels. Hemodynamic signals are an important tool used by doctors to diagnose the type of CVD occurred in a patient. Diagnosing the correct type of CVD in a patient early will allow the patient to have the suitable medical treatment. Some examples of CVDs include coronary heart disease, cerebrovascular disease and peripheral arterial disease. A human cardiovascular model is developed in order to simulate different hemodynamic signals of the cardiovascular system. The hemodynamic signals include the blood pressures, flow rates and volumes in various part of the cardiovascular system. This paper presents a model which is able to simulate hemodynamic signals and they are able to represent the human arterial blood pressure accurately. Hence this model can also be used to simulate hypertensive patients in order to design control systems for regulation of blood pressure. Signal verification has been performed and the stability of the model is being investigated. Applications of the human cardiovascular model are also presented.

Application of higher order spectra to identify epileptic EEG.

Epilepsy is characterized by the spontaneous and seemingly unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic system that detects seizure onsets would allow patients or the people near them to take appropriate precautions, and could provide more insight into this phenomenon. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, we made a comparative study of the performance of Gaussian mixture model (GMM) and Support Vector Machine (SVM) classifiers using the features derived from HOS and from the power spectrum. Results show that the selected HOS based features achieve 93.11% classification accuracy compared to 88.78% with features derived from the power spectrum for a GMM classifier. The SVM classifier achieves an improvement from 86.89% with features based on the power spectrum to 92.56% with features based on the bispectrum.

Use of complementary and alternative medicine in head and neck cancer patients.

OBJECTIVE: To determine the prevalence and profile of patients who use complementary and alternative medicine, within a cohort of head and neck cancer patients. STUDY DESIGN: Cross-sectional survey. SUBJECTS AND METHODS: Ninety-three consecutive head and neck cancer patients being followed up at the department of otolaryngology head and neck surgery were surveyed using an interviewer-administered questionnaire. RESULTS: The prevalence of complementary and alternative medicine use was 67.8 per cent. Patients who used complementary and alternative medicine were more likely to be female, better educated and younger, compared with non-users. A total of 82.5 per cent (52/63) perceived complementary and alternative medicine to be effective, even though they were aware of the lack of research and endorsement by their physician regarding such medicine. CONCLUSION: The use of complementary and alternative medicine by head and neck cancer patients is common, regardless of efficacy or cost. Clinicians should routinely ask patients about their use of complementary and alternative medicine, to facilitate communication and enable appropriate use of such medicine.

Sphenoid sinus mucocele: 10 cases and literature review.

INTRODUCTION: Sphenoid sinus mucoceles represent only 1-2 per cent of all paranasal sinus mucoceles. Patients may present with a myriad of symptoms. Pre-operative investigations include nasoendoscopy, computed tomography and/or magnetic resonance imaging. Treatment is by endoscopic sinus surgery. METHODOLOGY: A retrospective review of the archives of the Singapore General Hospital otolaryngology department (1999-2006) identified 10 cases of sphenoid sinus mucocele. Patient demographics, presenting symptoms, investigations and treatment were evaluated. RESULTS: The 10 patients identified (three women and seven men) had a mean age of 54.5 years (range 24-70 years). Thirty per cent of patients had a history of nasopharyngeal carcinoma treated with radiotherapy. Presenting symptoms, in order of decreasing frequency, were: ocular symptoms (50 per cent), headaches (30 per cent), nasal discharge (30 per cent) and facial pain (10 per cent). All patients underwent pre-operative computed tomography or magnetic resonance imaging. Twenty per cent of patients had evidence of intracranial involvement on imaging. All patients underwent uncomplicated transnasal sphenoidotomy and drainage of the mucocele. There was no clinical or radiological evidence of recurrence at a mean follow up of 29 months (range 4-90 months). CONCLUSION: Sphenoid sinus mucocele is a rare condition. In this study, radiation to the head and neck appeared to be a predisposing factor, and eye symptoms were the commonest presentation. Endoscopic sinus surgery is a safe and effective treatment modality.

Alkaloids from Piper sarmentosum and Piper nigrum.

Detailed chemical studies on the roots of Piper sarmentosum and Piper nigrum have resulted in several alkaloids. The roots of P. sarmentosum gave a new aromatic compound, 1-nitrosoimino-2,4,5-trimethoxybenzene (1). Piper nigrum roots gave pellitorine (2), (E)-1-[3',4'-(methylenedioxy)cinnamoyl]piperidine (3), 2,4-tetradecadienoic acid isobutyl amide (4), piperine (5), sylvamide (6), cepharadione A (7), piperolactam D (8) and paprazine (9). Structural elucidation of these compounds was achieved through NMR and MS techniques. Cytotoxic activity screening of the plant extracts indicated some activity.

Computer-based detection of diabetes retinopathy stages using digital fundus images.

Diabetes mellitus is a heterogeneous clinical syndrome characterized by hyperglycaemia and the long-term complications are retinopathy, neuropathy, nephropathy, and cardiomyopathy. It is a leading cause of blindness. Diabetic retinopathy is the progressive pathological alterations in the retinal microvasculature, leading to areas of retinal nonperfusion, increased vascular permeability, and the pathological proliferation of retinal vessels. Hence, it is beneficial to have regular cost-effective eye screening for diabetes subjects. Nowadays, different stages of diabetes retinopathy are detected by retinal examination using indirect biomicroscopy by senior ophthalmologists. In this work, morphological image processing and support vector machine (SVM) techniques were used for the automatic diagnosis of eye health. In this study, 331 fundus images were analysed. Five groups were identified: normal retina, mild non-proliferative diabetic retinopathy, moderate non-proliferative diabetic retinopathy, severe non-proliferative diabetic retinopathy, and proliferative diabetic retinopathy. Four salient features blood vessels, microaneurysms, exudates, and haemorrhages were extracted from the raw images using image-processing techniques and fed to the SVM for classification. A sensitivity of more than 82 per cent and specificity of 86 per cent was demonstrated for the system developed.

Automatic identification of epileptic electroencephalography signals using higher-order spectra.

Epilepsy is a pathological condition characterized by the spontaneous and unforeseeable occurrence of seizures, during which the perception or behaviour of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on electroencephalography (EEG) recordings. The use of non-linear features motivated by the higher-order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal), and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model classifier and a support vector machine classifier. Results show that the classifiers were able to achieve 93.11 per cent and 92.67 per cent classification accuracy respectively, with selected HOS-based features. About 2 h of EEG recordings from ten patients were used in this study.

A national survey on the practice and outcomes of mechanical ventilation in Korean intensive care units.

A study was undertaken to describe the practice and outcomes of mechanical ventilation throughout Korea. This prospective cohort study was conducted over a three-month period enrolling patients (n = 519) who received mechanical ventilation for more than 72 hours in 21 university hospital intensive care units throughout Korea. The most common indication for mechanical ventilation was acute respiratory failure. The most common cause of acute-on-chronic respiratory failure was tuberculous lung disease. The most common initial mode for ventilation was volume-controlled ventilation. The mean tidal volume of acute respiratory distress syndrome patients was 7.6 ml/kg of the predicted body weight and the mean positive end-expiratory pressure was 9.4 cmH20. The weaning success rate at 28 days was 50.3%. Pressure support and the T-piece were most commonly used as initial and final weaning modes respectively. Preventive measures against deep vein thrombosis during mechanical ventilation were performed more frequently in intensive care units with full-time critical care physicians than those without such physicians. Multivariate analysis showed that the APACHE II score, indication for mechanical ventilation, respiratory rate at 72 hours, enteral feeding and prophylaxis of deep vein thrombosis were prognostic factors for survival. In Korean intensive care units, tuberculous lung disease remains an important cause for mechanical ventilation. The practice of mechanical ventilation in Korean intensive care units in general appeared to comply with the current international recommendations with regard to lung protection and weaning. However, intensive care units lacking critical care physicians seemed to be adopting fewer ancillary measures, such as deep vein thrombosis prophylaxis.

Analysis of epileptic EEG signals using higher order spectra.

The unpredictability of the occurrence of epileptic seizures contributes to the burden of the disease to a major degree. An automatic system that detects seizure onsets would allow patients or the people near them to take appropriate precautions, and could provide more insight into these phenomena, thereby revealing important clinical information. Thus, various methods have been proposed to predict the onset of seizures based on EEG recordings. A seemingly promising approach involves nonlinear features motivated by the higher order spectra (HOS). The goal in this paper is to find the different HOS features for normal, pre-ictal (background) and epileptic EEG signals. This may help in the detection of seizure onset as early as possible with maximal accuracy. In this work, 300 EEG data, each belonging to the three classes, are studied. Our results show that the HOS based measures show unique ranges for the different classes with high confidence level (p = 0.002).

Clinical course and lung function change of idiopathic nonspecific interstitial pneumonia.

Most studies of idiopathic nonspecific interstitial pneumonia (NSIP) have primarily studied mortality. In order to clarify the detailed outcome and prognostic markers in idiopathic NSIP, the clinical course with initial radiological and clinical features was analysed. The clinical course of 83 patients who were classified with idiopathic NSIP (72 fibrotic, 11 cellular; 27 males and 56 females; mean+/-sd age 54.4+/-10.1 yrs) was retrospectively analysed. In fibrotic NSIP, 16 (22%) patients died of NSIP-related causes with a median (range) follow-up of 53 (0.3-181) months. Despite the favourable survival (5-yr 74%), patients with fibrotic NSIP were frequently hospitalised with recurrence rate of 36%. Reduced forced vital capacity at 12 months was a predictor of mortality. On follow-up, lung function was improved or stable in approximately 80% of the patients. The extent of consolidation and ground-glass opacity on initial high-resolution computed tomography correlated significantly with serial changes of lung function, and the presence of honeycombing was a predictor of poor prognosis. During follow-up, eight (10%) patients developed collagen vascular disease. In conclusion, the overall prognosis of fibrotic nonspecific interstitial pneumonia was good; however, there were significant recurrences despite initial improvement and a subset of the patients did not respond to therapy. Some patients developed collagen vascular diseases at a later date.

Sequential organ failure assessment score and comorbidity: valuable prognostic indicators in chronically critically ill patients.

Chronically critically ill patients are defined as those who survive initial life-threatening, possibly reversible organ failure(s) but are unable to recover rapidly to a point at which they are fully independent of life support. Accordingly, these patients require mechanical ventilation and medical resources for a long time in an intensive care unit (ICU). The present study analysed demographic, clinical and survival data of chronically critically ill patients, to identify condition(s) related to poor prognosis. A total of 141 chronically critically ill patients were studied retrospectively over a two-year period (July 1, 2003 to June 30, 2005). Their mean lengths of stay in the ICU and in the hospital were 42.9+/-36.4 and 83.9+/-100.5 days respectively. ICU and six-month cumulative mortality rates were 42.6% and 75.9% respectively. Non-survivors had a significantly higher Sequential Organ Failure Assessment (SOFA) score than survivors on day 21 of ICU admission, as well as having significantly lower changes of SOFA scores between days three and 21. Multivariate analysis demonstrated that the SOFA score on day 21 and the Charlson Comorbidity Index were the best predictor of survival for six months after hospital discharge. The SOFA score on day 21 and comorbidity in the ICU appears to be a valuable prognostic indicators in chronically critically ill patients.

Computer-based analysis of cardiac state using entropies, recurrence plots and Poincare geometry.

Heart rate variability refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability is important because it provides a window to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computer-based intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Parameters are extracted from the heart rate signals and analysed using computers for diagnostics. This paper describes the analysis of normal and seven types of cardiac abnormal signals using approximate entropy (ApEn), sample entropy (SampEn), recurrence plots and Poincare plot patterns. Ranges of these parameters for various cardiac abnormalities are presented with an accuracy of more than 95%. Among the two entropies, ApEn showed better performance for all the cardiac abnormalities. Typical Poincare and recurrence plots are shown for various cardiac abnormalities.

Automated identification of diabetic retinopathy stages using digital fundus images.

Diabetic retinopathy (DR) is caused by damage to the small blood vessels of the retina in the posterior part of the eye of the diabetic patient. The main stages of diabetic retinopathy are non-proliferate diabetes retinopathy (NPDR) and proliferate diabetes retinopathy (PDR). The retinal fundus photographs are widely used in the diagnosis and treatment of various eye diseases in clinics. It is also one of the main resources for mass screening of diabetic retinopathy. In this work, we have proposed a computer-based approach for the detection of diabetic retinopathy stage using fundus images. Image preprocessing, morphological processing techniques and texture analysis methods are applied on the fundus images to detect the features such as area of hard exudates, area of the blood vessels and the contrast. Our protocol uses total of 140 subjects consisting of two stages of DR and normal. Our extracted features are statistically significant (p < 0.0001) with distinct mean +/- SD as shown in Table 1. These features are then used as an input to the artificial neural network (ANN) for an automatic classification. The detection results are validated by comparing it with expert ophthalmologists. We demonstrated a classification accuracy of 93%, sensitivity of 90% and specificity of 100%.

Cardiac state diagnosis using higher order spectra of heart rate variability.

Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart, by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computer-based intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are nonlinear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of nonlinear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and seven classes of arrhythmia. We present some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. We also extracted features from the HOS and performed an analysis of variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test.

Automatic identification of epilepsy by HOS and power spectrum parameters using EEG signals: a comparative study.

Epilepsy is characterized by the spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic system that detects seizure onsets would allow patients or the people near them to take appropriate precautions, and could provide more insight into these phenomena. The use of non-linear features motivated by the higher order spectra (HOS) had been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, the features are extracted from the power spectrum and the bispectrum. Their performance is studied by feeding them to a Gaussian mixture model (GMM) classifier. Results show that with selected HOS based features, we were able to achieve 93.11% compared to classification accuracy of 88.78% as that of features derived from PSD.