Haemodynamic instability after cardiac surgery: nurses` perceptions of clinical decision-making

Background. Cardiac surgical patients are distinguished by their potential for instability in the early postoperative period, highly invasive haemodynamic monitoring technologies and unique clinical presentations as a result of undergoing cardiopulmonary bypass. Little is known about nurses’ perceptions of assuming responsibility for such patients. An nderstanding of nurses’ perceptions may identify areas of practice that can be improved and assist in determining the adequacy of current decision supports.

Aim. The aim of this study was to describe critical care nurses’ perceptions of assuming responsibility for the nursing management of cardiac patients in the initial two-hour postoperative period. Design. An exploratory descriptive study based on naturalistic decision-making.

Methods. Thirty-eight nurses were interviewed immediately following a two-hour observation of their clinical practice. Content analysis and a systematic thematic analysis process called ‘Framework’ were used to analyse the interview transcripts.

Results. Nurses described their perceptions of managing patients in terms of how they felt about making decisions for complex cardiac surgical patients and in terms of how clinical processes unique to the admission phase impacted their decision-making. Nurses felt either daunted or stimulated and challenged when making decisions. Nurses identified handover from anaesthetists, settling in procedures and forms of
collegial assistance as important processes that impacted their decision-making.

Conclusion. Nurses’ previous experiences with similar patients influenced how they felt about making decisions during the initial two-hour postoperative period, but did not alter their views about processes important for patient safety during this time. Relevance to clinical practice. Feelings expressed by nurses in this study highlight the need for clinical supervision and appropriate allocation of resources during the immediate recovery period after cardiac surgery. Nurses identified ways to improve clinical processes that impacted their decision-making during the immediate recovery of cardiac surgical patients.

Critical care nurses' haemodynamic decision making

For cardiac surgical patients, the immediate 2-hour recovery period is distinguished by potentially life-threatening haemodynamic instability. To ensure optimum patient outcomes, nurses of varying levels of experience must make rapid and accurate decisions in response to episodes of haemodynamic instability. Decision complexity, nurses’ characteristics, and environmental characteristics, have each been found to influence nurses' decision making in some form. However, the effect of the interplay between these influences on decision outcomes has not been investigated. The aim of the research reported in this thesis was to explore variability in critical care nurses' haemodynamic decision making as a function of interplay between haemodynamic decision complexity, nurses' experience, and specific environmental characteristics by applying a naturalistic decision making design. Thirty-eight nurses were observed recovering patients in the immediate 2-hour period after cardiac surgery. A follow-up semi-structured interview was conducted. A naturalistic decision making approach was used. An organising framework for the goals of therapy related to maintaining haemodynamic stability after cardiac surgery was developed to assist the observation and analysis of practice. The three goals of therapy were the optimisation of cardiovascular performance, the promotion of haemostasia, and the reestablishment of normothermia. The research was conducted in two phases. Phase One explored issues related to observation as method, and identified emergent themes. Phase Two incorporated findings of Phase 1, investigating the variability in nurses' haemodynamic decision making in relation to the three goals of therapy. The findings showed that patients had a high acuity after cardiac surgery and suffered numerous episodes of haemodynamic instability during the immediate 2-hour recovery period. The quality of nurses' decision making in relation to the three goals of therapy was influenced by the experience of the nurse and social interactions with colleagues. Experienced nurses demonstrated decision making that reflected the ability to recognise subtle changes in haemodynamic cues, integrate complex combinations of cues, and respond rapidly to instability. The quality of inexperienced nurses' decision making varied according to the level and form of decision support as well as the complexity of the task. When assistance was provided by nursing colleagues during the reception and recovery of patients, the characteristics of team decision making were observed. Team decision making in this context was categorised as either integrated or non integrated. Team decision making influenced nurses' emotions and actions and decision making practices. Findings revealed nurses' experience affected interactions with other team members and their perceptions of assuming responsibility for complex patients. Interplay between decision complexity, nurses' experience, and the environment in which decisions were made influenced the quality of nurses' decision making and created an environment of team decision making, which, in turn, influenced nurses' emotional responses and practice outcomes. The observed variability in haemodynamic decision making has implications for nurse education, nursing practice, and system processes regarding patient allocation and clinical supervision.

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.

Intravascular device administration sets: Replacement after standard versus prolonged use in hospitalised patients--a study protocol for a randomised controlled trial (The RSVP Trial)

Introduction Vascular access devices (VADs), such as peripheral or central venous catheters, are vital across all medical and surgical specialties. To allow therapy or haemodynamic monitoring, VADs frequently require administration sets (AS) composed of infusion tubing, fluid containers, pressure-monitoring transducers and/or burettes. While VADs are replaced only when necessary, AS are routinely replaced every 3–4 days in the belief that this reduces infectious complications. Strong evidence supports AS use up to 4 days, but there is less evidence for AS use beyond 4 days. AS replacement twice weekly increases hospital costs and workload. Methods and analysis This is a pragmatic, multicentre, randomised controlled trial (RCT) of equivalence design comparing AS replacement at 4 (control) versus 7 (experimental) days. Randomisation is stratified by site and device, centrally allocated and concealed until enrolment. 6554 adult/paediatric patients with a central venous catheter, peripherally inserted central catheter or peripheral arterial catheter will be enrolled over 4 years. The primary outcome is VAD-related bloodstream infection (BSI) and secondary outcomes are VAD colonisation, AS colonisation, all-cause BSI, all-cause mortality, number of AS per patient, VAD time in situ and costs. Relative incidence rates of VAD-BSI per 100 devices and hazard rates per 1000 device days (95% CIs) will summarise the impact of 7-day relative to 4-day AS use and test equivalence. Kaplan-Meier survival curves (with log rank Mantel-Cox test) will compare VAD-BSI over time. Appropriate parametric or non-parametric techniques will be used to compare secondary end points. p Values of <0.05 will be considered significant.

Propofol sedation administered by cardiologists for patients undergoing catheter ablation for ventricular tachycardia

AIMS Propofol sedation has been shown to be safe for atrial fibrillation ablation and internal cardioverter-defibrillator implantation but its use for catheter ablation (CA) of ventricular tachycardia (VT) has yet to be evaluated. Here, we tested the hypothesis that VT ablation can be performed using propofol sedation administered by trained nurses under a cardiologist's supervision. METHODS AND RESULTS Data of 205 procedures (157 patients, 1.3 procedures/patient) undergoing CA for sustained VT under propofol sedation were analysed. The primary endpoint was change of sedation and/or discontinuation of propofol sedation due to side effects and/or haemodynamic instability. Propofol cessation was necessary in 24 of 205 procedures. These procedures (Group A; n = 24, 11.7%) were compared with those with continued propofol sedation (Group B; n = 181, 88.3%). Propofol sedation was discontinued due to hypotension (n = 22; 10.7%), insufficient oxygenation (n = 1, 0.5%), or hypersalivation (n = 1, 0.5%). Procedures in Group A were significantly longer (210 [180-260] vs. 180 [125-220] min, P = 0.005), had a lower per hour propofol rate (3.0 ± 1.2 vs. 3.8 ± 1.2 mg/kg of body weight/h, P = 0.004), and higher cumulative dose of fentanyl administered (0.15 [0.13-0.25] vs. 0.1 [0.05-0.13] mg, P < 0.001), compared with patients in Group B. Five (2.4%) adverse events occurred. CONCLUSION Sedation using propofol can be safely performed for VT ablation under the supervision of cardiologists. Close haemodynamic monitoring is required, especially in elderly patients and during lengthy procedures, which carrying a higher risk for systolic blood pressure decline.

Central venous oxygen saturation monitoring

It has been established that mixed venous oxygen saturation (SvO2) reflects the balance between systemic oxygen deliver y and consumption. Literature indicates that it is a valuable clinical indicator and has good prognostic value early in patient course. This article aims to establish the usefulness of SvO2 as a clinical indicator. A secondary aim was to determine whether central venous oxygen saturation (ScvO2) and SvO2 are interchangeable. Of particular relevance to cardiac nurses is the link between decreased SvO2 and cardiac failure in patients with myocardial infarction, and with decline in myocardial function, clinical shock and arrhythmias. While absolute values ScvO2 and SvO2 are not interchangeable, ScvO2 and SvO2are equivalent in terms of clinical course. Additionally, ScvO2 monitoring is a safer and less costly alternative to SvO2 monitoring. It can be concluded that continuous ScvO2 monitoring should potentially be undertaken in patients at risk of haemodynamic instability.

Topographic, haemodynamic and psychophysical investigation of glaucomatous optic neuropathy

Loss of optic nerve head (ONH) axons in primary open angle glaucoma (POAG) has been attributed to both mechanical and vascular factors. Confocal scanning laser ophthalmoscopy (cSLO) provides a promising tool for the topographic follow-up of the ONH in glaucoma, while scanning laser Doppler flowmetry (SLDF) facilitates the rapid non-invasive assessment of retinal capillary blood flow. The purposes of these investigations were to optimise the techniques and explore their potential to classify and monitor disease. Preliminary investigations explored the reproducibility and validity of cSLO and SLDF and showed that: For cSLO: In a model eye, measurements are accurate over a range of axial lengths. For best reproducibility, seven images per visit are required, with a contour line located on Elschnig's scleral ring and transferred automatically between images. For SLDF: Three perfusion images are required for optimum reproducibility. Physiological changes induced by gas perturbation can be measured. Cross-sectional comparison of groups of normal subjects and early POAG patients showed that: cSLO parameters differentiate the early POAG group. Blood volume measured by SLDF showed group differences in superior nasal retina only. Longitudinal investigation of ONH topography, haemodynamic and visual field indices in normal subjects and POAG patients showed that: cSLO detects topographical change over time more frequently in the POAG group. Important parameters include: C:D area ratio, cup and rim area, mean depth in contour, volumes above and below reference and surface. Factor analysis identified "cup" and "rim" factors that can be used to detect change over time in individual patients. Blood flow changes were most apparent in the inferior nasal peripapillary retina of the POAG group. Perimetry is of clinical value for the identification of glaucoma but is less sensitive than cSLO for monitoring glaucomatous change.