P. R. F. Dear

Central Venous Catheter Tip in the Right Atrium: A Risk Factor for Neonatal Cardiac Tamponade

Fatal cardiac tamponade is a well recognised complication of the use of central venous catheters in neonatal patients. There is controversy over optimum catheter tip position to balance catheter performance against risk of adverse events. We report a series of five cases of tamponade occurring in one neonatal unit over a 4-year period, related to catheter tip placement in the right atrium. Right atrial catheter angulation, curvature or looping (CA) was present in all five cases on plain radiograph. It was infrequently seen in other patients over the same period. Review of the literature indicates that CA was present in 6 of the 11 previous cases where the presence or absence of CA can be determined. Where right atrial catheter tip placement is accepted, clinicians should be aware of this characteristic catheter configuration, which is a major risk factor for cardiac tamponade. We recommend that catheter tips should not be placed in the right atrium to avoid risk of tamponade.

Using cognitive task analysis to facilitate the integration of decision support systems into the neonatal intensive care unit

OBJECTIVE New medical systems may be rejected by staff because they do not integrate with local practice. An expert system, FLORENCE, is being developed to help staff in a neonatal intensive care unit (NICU) make decisions about ventilator settings when treating babies with respiratory distress syndrome. For FLORENCE to succeed it must be clinically useful and acceptable to staff in the context of local work practices. The aim of this work was to identify those contextual factors that would affect FLORENCEs success. METHODS A cognitive task analysis (CTA) of the NICU was performed. First, work context analysis was used to identify how work is performed in the NICU. Second, the critical decision method (CDM) was used to analyse how staff make decisions about changing the ventilator settings. Third, naturalistic observation of staffs use of the ventilator was performed. RESULTS A. The work context analysis identified the NICUs hierarchical communication structure and the importance of numerous types of record in communication. B. It also identified important ergonomic and practical requirements for designing the displays and positioning the computer. C. The CDM interviews suggested instances where problems can arise if the data used by FLORENCE, which is automatically read, is not manually verified. D. Observation showed that most alarms cleared automatically. When FLORENCE raises an alarm, staff will normally be required to intervene and make a clinical judgement, even if the ventilator settings are not subsequently changed. CONCLUSIONS FLORENCE must not undermine the NICUs hierarchical communication channels (A). The re-design of working practices to incorporate FLORENCE, reinforced through its user interface, must ensure that expert help is called on when appropriate (A). The procedures adopted with FLORENCE should ensure that the data the advice is based upon is valid (C). For example, FLORENCE could prompt staff to manually verify the data before implementing any suggested changes. FLORENCEs audible alarm should be clearly distinguishable from other NICU alarms (D); new procedures should be established to ensure that FLORENCE alarms receive attention (D), and false alarms from FLORENCE should be minimised (B, D). FLORENCE should always provide the data and reasoning underpinning its advice (A, C, D). The methods used in the CTA identified several contextual issues that could affect FLORENCEs acceptance. These issues, which extend beyond FLORENCEs capability to suggest changes to the ventilator settings, are being addressed in the design of the user interface and plans for FLORENCEs subsequent deployment.

An expert system to assist neonatal intensive care

An expert system for neonatal intensive care (ESNIC) for the management of mechanically ventilated neonates on intermittent positive pressure ventilation (IPPV) has been developed. The system uses the rule based expert system shell XiPlus (Inference Inc.) and runs on an IBM-compatible PC. The rules have been derived from the knowledge of two consultant paediatricians. The inputs to the system are the current ventilator settings, blood gas tensions and pH. The output of the system is a set of suggested new ventilator settings. The aim of the system is to provide ventilator settings which will maintain the arterial blood gas tensions within an acceptable range, reducing pressures whenever feasible and increasing pressures only as a last resort. In addition, ESNIC provides data archiving, graphical displays of all parameters, ventilation and discharge summaries. With the 63 patients in the study ESNIC was consulted for 76% of all ventilator adjustments and the advice given was accepted on 83% of these occasions.

Placement of neonatal central venous catheter tips in the right atrium: a practice to be avoided?

Editor—Following the recent media interest in pericardial tamponade complicating the use of percutaneous central venous catheters in neonatal patients, we wish to alert readers to our experience. Our previous policy was to accept right atrial placement of percutaneous central venous catheter tips. This was in line with published recommendations1-3 and is still considered acceptable practice in some …

An advisory system for artificial ventilation of the newborn utilizing a neural network

A neural network has been developed to manage ventilated neonates. The network inputs are the current ventilator settings (inspiratory and expiratory times, peak inspiratory and positive end-expiratory pressures and inspired oxygen concentration), partial pressures of arterial blood gases and pH. Two hidden layers comprising 50 nodes each are employed in the network, which utilizes a standard back-propagation algorithm. The network provides the new ventilator settings as five outputs that represent the most appropriate ventilator settings projected to maintain blood gases within an acceptable range. The network has been trained using a data set derived from a rule-based expert system developed for the same purpose. Performances of both systems have been compared. The neural network is capable of learning and adapting to the individual patients response, which in principle offers significant advantages over the rule-based system.

EFFECTS OF TRANSFUSION IN ANEMIA OF PREMATURITY

The authors aimed to test the hypothesis that blood transfusions depress hematopoiesis in healthy infants with anemia of prematurity (AOP). They also set out to find markers that predict recovery from AOP. Thirty-nine premature babies underwent weekly and post-transfusion measurements of hemoglobin concentrations, reticulocyte counts (RCC), and erythropoietin levels (EPO). RCC and EPO dropped significantly 7 days after a blood transfusion but had normalized after 14 days. Elevated RCC or EPO levels were not predictive of an increase in hemoglobin. Postnatal HbFg/dL was higher in babies who had received transfusions. The authors conclude that blood transfusions depress erythropoiesis in infants with AOP and stimulate HbF synthesis but this effect is not sustained. Reticulocyte counts and erythropoietin levels are unhelpful in predicting recovery from AOP.

To PEEP or not to PEEP

It is well recognised that reducing positive end expiratory pressure (PEEP) leads to an increase in the tidal volume and minute volume in ventilated neonates. The magnitude of this effect is perhaps not commonly appreciated, however. Effectively, PEEP is four times as potent as peak inflation pressure (PIP) in bringing about changes in tidal volume. The influence of changes in PEEP and PIP on tidal volume and the relative magnitude of each are considered. Twenty one preterm infants were studied on 38 separate occasions. All were sedated, paralysed, and ventilated, 19 for hyaline membrane disease. A 1 cm H2O reduction in PEEP was twice as potent as a 2 cm H2O increase in PIP in achieving an increase in tidal volume (14 v 7%). Similarly, increasing PEEP by 1 cm H2O was twice as effective as a 2 cm H2O decrease in PIP in reducing tidal volume (13 v 6%). Small (0.5-1 cm H2O) changes in PEEP can often be used to improve ventilation and carbon dioxide elimination. Levels of PEEP of 4-5 cm H2O may, at times, impair gas exchange and contribute to overdistension.

Comparison of neural networks and statistical models to predict gestational age at birth

The aim of this study was to produce models for the prediction of high risk pregnancies, with particular emphasis on pre-term delivery. Neural network and logistic regression models have been developed utilising pregnancy and delivery data spanning a period of seven years. Five input factors were used as explanatory variables: age, number of previous still births, gestational age at first clinical assessment, diabetes and a measure of socio-economic status. There was little difference between average model performance for the two techniques: optimal neural network performance was achieved with a fully connected feed forward network comprising a single hidden layer of three nodes and single output node. This produced a Receiver Operating Characteristic (ROC) curve area of 0.700. The ROC area for logistic regression models was 0.695. The performance of these models reflected weak associations within the data. However, performance is encouraging given the relatively limited number of predictive inputs.

Response to the Proposal of a Template for Defining a Causal Relation between Acute Intrapartum Events and Cerebral Palsy

After major placental abruption at 41 weeks ofgestation, severe abnormalities on the CTC lead to immediate Caesarean section. The infant is in a very poor condition, needs advanced resuscitation and starts breathing at 16 minutes of age. No cord gas is taken. Over thefirstfew days, the infant suffers from an acute encephalopathic illness with seizures as well as acute renal failure. At six years ofage, he has cerebral palsy.

A mathematical model of CO2 variation in the ventilated neonate.

A mathematical model of the variation of partial pressure of carbon dioxide in the arterial blood of a ventilated neonate is developed. The model comprises alveolar, arterial, pulmonary, venous and tissue compartments, with gas exchange in the lung determined by inspiration and expiration terms. Gas exchange is modelled through diffusion and convective transfer. Carbon dioxide is produced in the tissue by a metabolic term. Shunting is modelled by allowing blood flow to bypass the pulmonary compartment in which diffusion takes place. The model predicts changes in the carbon dioxide partial pressures that occur following abrupt changes in the ventilation settings, and show broad agreement with actual data obtained from novel sensing technology.