Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

A grounded theory study of technology appropriation in anaesthesia

The human-technology nexus is a strong focus of Information Systems (IS) research; however, very few studies have explored this phenomenon in anaesthesia. Anaesthesia has a long history of adoption of technological artifacts, ranging from early apparatus to present-day information systems such as electronic monitoring and pulse oximetry. This prevalence of technology in modern anaesthesia and the rich human-technology relationship provides a fertile empirical setting for IS research. This study employed a grounded theory approach that began with a broad initial guiding question and, through simultaneous data collection and analysis, uncovered a core category of technology appropriation. This emergent basic social process captures a central activity of anaesthestists and is supported by three major concepts: knowledge-directed medicine, complementary artifacts and culture of anaesthesia. The outcomes of this study are: (1) a substantive theory that integrates the aforementioned concepts and pertains to the research setting of anaesthesia and (2) a formal theory, which further develops the core category of appropriation from anaesthesia-specific to a broader, more general perspective. These outcomes fulfill the objective of a grounded theory study, being the formation of theory that describes and explains observed patterns in the empirical field. In generalizing the notion of appropriation, the formal theory is developed using the theories of Karl Marx. This Marxian model of technology appropriation is a three-tiered theoretical lens that examines appropriation behaviours at a highly abstract level, connecting the stages of natural, species and social being to the transition of a technology-as-artifact to a technology-in-use via the processes of perception, orientation and realization. The contributions of this research are two-fold: (1) the substantive model contributes to practice by providing a model that describes and explains the human-technology nexus in anaesthesia, and thereby offers potential predictive capabilities for designers and administrators to optimize future appropriations of new anaesthetic technological artifacts; and (2) the formal model contributes to research by drawing attention to the philosophical foundations of appropriation in the work of Marx, and subsequently expanding the current understanding of contemporary IS theories of adoption and appropriation.

Cardiac safety concerns for ondansetron, an antiemetic commonly used for nausea linked to cancer treatment and following anaesthesia

Introduction: Ondansetron is a 5-HT3 receptor antagonist commonly used as an anti-emetic to prevent the nausea and vomiting associated with anti-cancer drugs, cancer radiotherapy, or postoperatively. Recently, the US Food and Drug Administration (FDA) issued a warning for ondansetron due to a potential for prolongation of the QT interval of the electrocardiogram (ECG), a phenomenon that is associated with an increased risk of the potentially fatal arrhythmia torsade de pointes. Areas covered: We undertook a review of the cardiac safety of ondansetron. Our primary sources of information were PubMed (with downloading of full articles), and the internet. Expert opinion: The dose of ondansetron that the FDA has concerns about is 32 mg iv (or several doses that are equivalent to this), which is only used in preventing nausea and vomiting associated with cancer chemotherapy. This suggests that ondansetron may be safe in the lower doses used to prevent the nausea and vomiting in radiation treatment or postoperatively. However, as there is a report that a lower dose of ondansetron prolonged the QT interval in healthy volunteers, this needs to be clarified by the FDA. More research needs to be undertaken of the relationship between QT prolongation and torsades in order that the FDA can produce clear-cut evidence of pro-arrhythmic risk when introducing warnings for this.

Depth of anaesthesia monitoring during procedural sedation and analgesia: A systematic review protocol

Background Procedural sedation and analgesia (PSA) is used to attenuate the pain and distress that may otherwise be experienced during diagnostic and interventional medical or dental procedures. As the risk of adverse events increases with the depth of sedation induced, frequent monitoring of level of consciousness is recommended. Level of consciousness is usually monitored during PSA with clinical observation. Processed electroencephalogram-based depth of anaesthesia (DoA) monitoring devices provide an alternative method to monitor level of consciousness that can be used in addition to clinical observation. However, there is uncertainty as to whether their routine use in PSA would be justified. Rigorous evaluation of the clinical benefits of DoA monitors during PSA, including comprehensive syntheses of the available evidence, is therefore required. One potential clinical benefit of using DoA monitoring during PSA is that the technology could improve patient safety by reducing sedation-related adverse events, such as death or permanent neurological disability. We hypothesise that earlier identification of lapses into deeper than intended levels of sedation using DoA monitoring leads to more effective titration of sedative and analgesic medications, and results in a reduction in the risk of adverse events caused by the consequences of over-sedation, such as hypoxaemia. The primary objective of this review is to determine whether using DoA monitoring during PSA in the hospital setting improves patient safety by reducing the risk of hypoxaemia (defined as an arterial partial pressure of oxygen below 60 mmHg or percentage of haemoglobin that is saturated with oxygen [SpO2] less than 90 %). Other potential clinical benefits of using DoA monitoring devices during sedation will be assessed as secondary outcomes. Methods/design Electronic databases will be systematically searched for randomized controlled trials comparing the use of depth of anaesthesia monitoring devices with clinical observation of level of consciousness during PSA. Language restrictions will not be imposed. Screening, study selection and data extraction will be performed by two independent reviewers. Disagreements will be resolved by discussion. Meta-analyses will be performed if suitable. Discussion This review will synthesise the evidence on an important potential clinical benefit of DoA monitoring during PSA within hospital settings.

Optimal management of the critically Ill: Anaesthesia, monitoring, data capture, and point-of-care technological practices in ovine models of critical care

Animal models of critical illness are vital in biomedical research. They provide possibilities for the investigation of pathophysiological processes that may not otherwise be possible in humans. In order to be clinically applicable, the model should simulate the critical care situation realistically, including anaesthesia, monitoring, sampling, utilising appropriate personnel skill mix, and therapeutic interventions. There are limited data documenting the constitution of ideal technologically advanced large animal critical care practices and all the processes of the animal model. In this paper, we describe the procedure of animal preparation, anaesthesia induction and maintenance, physiologic monitoring, data capture, point-of-care technology, and animal aftercare that has been successfully used to study several novel ovine models of critical illness. The relevant investigations are on respiratory failure due to smoke inhalation, transfusion related acute lung injury, endotoxin-induced proteogenomic alterations, haemorrhagic shock, septic shock, brain death, cerebral microcirculation, and artificial heart studies. We have demonstrated the functionality of monitoring practices during anaesthesia required to provide a platform for undertaking systematic investigations in complex ovine models of critical illness.

Detection of renal dysfunction during and after anaesthesia and surgery - evaluation of the influence of inorganic fluoride, ketorolac and clonidine

Drugs and surgical techniques may have harmful renal effects during the perioperative period. Traditional biomarkers are often insensitive to minor renal changes, but novel biomarkers may more accurately detect disturbances in glomerular and tubular function and integrity. The purpose of this study was first, to evaluate the renal effects of ketorolac and clonidine during inhalation anesthesia with sevoflurane and isoflurane, and secondly, to evaluate the effect of tobacco smoking on the production of inorganic fluoride (F-) following enflurane and sevoflurane anesthesia as well as to determine the effect of F- on renal function and cellular integrity in surgical patients. A total of 143 patients undergoing either conventional (n = 75) or endoscopic (n = 68) inpatient surgery were enrolled in four studies. The ketorolac and clonidine studies were prospective, randomized, placebo controlled and double-blinded, while the cigarette smoking studies were prospective cohort studies with two parallel groups. As a sign of proximal tubular deterioration, a similar transient increase in urine N-acetyl-beta-D-glucosaminidase/creatinine (U-NAG/crea) was noted in both the ketorolac group and in the controls (baseline vs. at two hours of anesthesia, p = 0.015) with a 3.3 minimum alveolar concentration hour sevoflurane anesthesia. Uncorrelated U-NAG increased above the maximum concentration measured from healthy volunteers (6.1 units/l) in 5/15 patients with ketorolac and in none of the controls (p = 0.042). As a sign of proximal tubular deterioration, U-glutathione transferase-alpha/crea (U-GST-alpha/crea) increased in both groups at two hours after anesthesia but a more significant increase was noted in the patients with ketorolac. U-GST-alpha/crea increased above the maximum ratio measured from healthy volunteers in 7/15 patients with ketorolac and in 3/15 controls. Clonidine diminished the activation of the renin-angiotensin aldosterone system during pneumoperitoneum; urine output was better preserved in the patients treated with clonidine (1/15 patients developed oliguria) than in the controls (8/15 developed oliguria (p=0.005)). Most patients with pneumoperitoneum and isoflurane anesthesia developed a transient proximal tubular deterioration, as U-NAG increased above 6.1 units/L in 11/15 patients with clonidine and in 7/15 controls. In the patients receiving clonidine treatment, the median of U-NAG/crea was higher than in the controls at 60 minutes of pneumoperitoneum (p = 0.01), suggesting that clonidine seems to worsen proximal tubular deterioration. Smoking induced the metabolism of enflurane, but the renal function remained intact in both the smokers and the non-smokers with enflurane anesthesia. On the contrary, smoking did not induce sevoflurane metabolism, but glomerular function decreased in 4/25 non-smokers and in 7/25 smokers with sevoflurane anesthesia. All five patients with S-F- ≥ 40 micromol/L, but only 6/45 with S-F- less than 40 micromol/L (p = 0.001), developed a S-tumor associated trypsin inhibitor concentration above 3 nmol/L as a sign of glomerular dysfunction. As a sign of proximal tubulus deterioration, U-beta 2-microglobulin increased in 2/5 patients with S-F- over 40 micromol/L compared to 2/45 patients with the highest S-F- less than 40 micromol/L (p = 0.005). To conclude, sevoflurane anesthesia may cause a transient proximal tubular deterioration which may be worsened by a co-administration of ketorolac. Clonidine premedication prevents the activation of the renin-angiotensin aldosterone system and preserves normal urine output, but may be harmful for proximal tubules during pneumoperitoneum. Smoking induces the metabolism of enflurane but not that of sevoflurane. Serum F- of 40 micromol/L or higher may induce glomerular dysfunction and proximal tubulus deterioration in patients with sevoflurane anesthesia. The novel renal biomarkers warrant further studies in order to establish reference values for surgical patients having inhalation anesthesia.

Effects of extracts of dried seeds of Toloache, Datura innoxia as anaesthesia on the African catfish Clarias gariepinus fingerlings

The effects of crude extract, pure extract, aqueous, fraction of pure and lipid fraction of pure extract of dried seeds of toloache. Datura innoxia as anaesthesia on the African catfish. Clarias gariepinus fingerlings were studied. The fish were exposed to various doses of the extract in aquaria tanks and the time taken for each fish to reach anaesthesia was recorded. The fish were anaesthetized up to 3.00g/l fingerlings reached anaesthesia is significantly (P<0.05) shorter time (1.004 minutes at 0.05gl) in pure unseparated extract than in crude extract (58.50 minutes at 3.00g/l concentrated). The time to reach anaesthesia decreased with an increase in concentration of the seed extract. Out the two fractions the lipid fraction had significantly (P>0.05) better anaesthetic on the fish. The control produced no observable anaesthetic effect on the fish within three hours. This suggests that the anaesthetizing active ingredent resided in the lipid fraction. All fish recovered from anaesthesia, swam and fed actively and no mortality was observed throughout the exposure period and thereafter. It is therefore recommended for use on C. gariepinus fingerlings

Differential effects of ageing on the EEG during pentobarbital and ketamine anaesthesia

Background and objectives: Pentobarbital and ketamine are commonly used in animal experiments, including studies on the effects of ageing on the central nervous system. The electroencephalogram is a sensitive measure of brain activity. The present study i