Probiotics for Prevention of Severe Necrotizing Enterocolitis: Experience of New Zealand Neonatal Intensive Care Units.

Introduction: Necrotizing enterocolitis (NEC) affects mainly preterm infants, has a multifactorial etiology and is associated with intestinal dysbiosis and disordered immunity. Use of probiotics for prophylaxis is beneficial with studies indicating reduction in NEC ≥ stage 2, late onset sepsis (LOS) and mortality. However, not all studies have shown a reduction, there are questions regarding which probiotic to use, whether infants <1,000 g benefit and the risk of probiotic sepsis. All neonatal intensive care units in New Zealand (NZ) use probiotics and contribute to an international database (Australian and New Zealand Neonatal Network or ANZNN). Objective: To use ANZNN data to investigate the experience of NZ neonatal units with probiotics for NEC prevention in a setting where the baseline incidence of severe NEC was low, to compare results of 2 commonly used probiotic regimes and report on the extremely low birth weight subgroup. Method: Outcomes before (Pre group 2007-2010) and after (Probiotic group 2013-2015) starting routine probiotics for preterm infants <1,500 g or <32 weeks were compared. Clinicians reviewed cases to ensure they met database criteria. Five units used Infloran (Bifidobacterium bifidum and Lactobacillus acidophilus) and 1 unit used Lactobacillus GG (LGG) and bovine lactoferrin (bLF). Results: Four thousand five hundred and twenty nine infants were included and Pre and Probiotic groups were well-balanced with regard to gestation, birth weight and gender. The incidence of NEC in the Probiotic group was 1.6 and 2.7% in the pre group (corrected OR 0.62 CI 0.41-0.94). There was one case of probiotic sepsis. There was no significant difference between the Infloran and LGG/bLF combinations in regard to observed NEC rates. Late onset sepsis rates were significantly lower in the Probiotic group (p < 0.01). Conclusions: Introduction of probiotics for preterm infants in NZ has been associated with significant reductions in NEC and late onset sepsis.

Plasma ammonia concentrations in extremely low birthweight infants in the first week after birth: secondary analysis from the ProVIDe randomized clinical trial.

BACKGROUND: Little is known about normative ammonia concentrations in extremely low birthweight (ELBW) babies and whether these vary with birth characteristics. We aimed to determine ammonia concentrations in ELBW babies in the first week after birth and relationships with neonatal characteristics and protein intake. METHODS: Arterial blood samples for the measurement of plasma ammonia concentration were collected within 7 days of birth from ProVIDe trial participants in six New Zealand neonatal intensive care units. RESULTS: Three hundred and twenty-two babies were included. Median (range) gestational age was 25.7 (22.7-31.6) weeks. Median (interquartile range (IQR)) ammonia concentration was 102 (80-131) µg/dL. There were no statistically significant associations between ammonia concentrations and birthweight or sex. Ammonia concentrations were weakly correlated with mean total (Spearman's rs = 0.11, P = 0.047) and intravenous (rs = 0.13, P = 0.02) protein intake from birth, gestational age at birth (rs = -0.13, P = 0.02) and postnatal age (rs = -0.13, P = 0.02). CONCLUSIONS: Plasma ammonia concentrations in ELBW babies are similar to those of larger and more mature babies and only weakly correlated with protein intake. Currently, recommended thresholds for investigation of hyperammonaemia are appropriate for ELBW babies. Protein intake should not be limited by concerns about potential hyperammonaemia.

Safe and effective glycaemic control in premature infants: observational clinical results from the computerised STAR-GRYPHON protocol.

OBJECTIVE: Previous studies examine clinical outcomes of insulin therapy in neonatal intensive care units (NICUs), without first developing safe and effective control protocols. This research quantifies the safety and performance of a computerised model-based control algorithmSTAR-GRYPHON (Stochastic TARgeted Glucose Regulation sYstem to Prevent Hyper- and hypO-glycaemia in Neonates). DESIGN: Retrospective observational study of glycaemic control in very/extremely low birthweight infants treated with insulin from Christchurch Women's Hospital NICU between January 2013 and June 2017. Blood glucose (BG) outcomes and control performance is compared with retrospective data (n=22) and literature. INTERVENTIONS: Insulin infusion doses were calculated from 3 to 4 hourly BG measurements using a computerised model-based control algorithm, STAR-GRYPHON. MAIN OUTCOME MEASURES: Mean BG, time in targeted range and incidence of hypoglycaemia. RESULTS: STAR-GRYPHON (n=35) had lower mean BG concentration (7.0mmol/L vs 7.9 mmol/L), higher %BG within the 4.0-8.0 mmol/L target range (71.1% vs 50.9%) and lower %BG <4.0 mmol/L (0.6% vs 2.1%). There were only 2 BG <2.6 mmol/L (over n=2, 5.5% of patients, 0.03% of all BG outcomes), one of which may be attributed to clinical error. These results show better control to target and lower incidence of hypoglycaemia than most literature results from intensive insulin therapy protocols or study groups in children and infants. CONCLUSIONS: Model-based protocols can safely and effectively control BG in very premature infants and should be used in future studies to determine the effect of insulin therapy on clinical outcomes.

A multifaceted programme to reduce the rate of tongue-tie release surgery in newborn infants: Observational study.

OBJECTIVES: A programme was introduced in Canterbury, New Zealand to evaluate the diagnosis and treatment of frenulum releases in newborn infants with suspected tongue-tie (ankyloglossia). The primary goals were to support breastfeeding and ensure that unnecessary surgery was avoided. METHODS: Local healthcare professionals reached consensus on a pathway for improving management of infants with tongue-tie and breast-feeding difficulties. This embedded an expert breast-feeding review and assessment of lingual function using a validated method, the Bristol Tongue-tie Assessment Tool (BTAT). Infants with breastfeeding problems related to tongue-tie had a frenotomy at a hospital outpatient clinic. An education programme was developed to support introduction of the new clinical pathway and included seminars and online information for healthcare professionals and the general public. RESULTS: Frenotomy intervention rate reduced markedly from 11.3% in 2015 to 3.5% by mid-2017. Feeding methods were not different before or after surgery between infants who received a frenotomy and those who did not. Initially, the BTAT threshold for frenotomy was set at ≤5, however the final clinical pathway combined a breastfeeding assessment and a BTAT threshold of ≤4. The education programs assisted with the changes in practice, while increased use of the clinician guidance and public health information websites confirmed growing awareness of tongue-tie and community breastfeeding support. CONCLUSIONS: Establishing consistent multidisciplinary assessment of tongue-tie in infants with feeding difficulties led to a marked reduction in frenotomy intervention rate. 23% of the frenotomy group in the 2016 audit showed a significant improvement in the ability to breastfeed, but overall there was no difference in the feeding pattern of infants who either received or were declined a frenotomy. The development of a supportive education programme and availability of online information about tongue-tie for health professionals and consumers contributed to successful uptake of the new clinical pathway.

Model-based glycaemic control: methodology and initial results from neonatal intensive care.

Very/extremely premature infants often experience glycaemic dysregulation, resulting in abnormally elevated (hyperglycaemia) or low (hypoglycaemia) blood glucose (BG) concentrations, due to prematurity, stress, and illness. STAR-GRYPHON is a computerised protocol that utilises a model-based insulin sensitivity parameter to directly tailor therapy for individual patients and their changing conditions, unlike other common insulin protocols in this cohort. From January 2013 to January 2015, 13 patients totalling 16 hyperglycaemic control episodes received insulin under STAR-GRYPHON. A significant improvement in control was achieved in comparison to a retrospective cohort, with a 26% absolute improvement in BG within the targeted range and no hypoglycaemia. This improvement was obtained predominantly due to the reduction of hyperglycaemia (%BG>10.0 mmol/l: 5.6 vs. 17.7%, p<0.001), and lowering of the median per-patient BG [6.9 (6.1-7.9) vs. 7.8 (6.6-9.1) mmol/l, p<0.001, Mann-Witney U test]. While cohort-wide control results show good control overall, there is high intra-patient variability in BG behaviour, resulting in overly conservative treatments for some patients. Patient insulin sensitivity differs between and within patients over time, with some patients having stable insulin sensitivity, while others change rapidly. These results demonstrate the trade-off between safety and performance in a highly variable and fragile cohort.

Brain mass estimation by head circumference and body mass methods in neonatal glycaemic modelling and control.

INTRODUCTION: Hyperglycaemia is a common complication of stress and prematurity in extremely low-birth-weight infants. Model-based insulin therapy protocols have the ability to safely improve glycaemic control for this group. Estimating non-insulin-mediated brain glucose uptake by the central nervous system in these models is typically done using population-based body weight models, which may not be ideal. METHOD: A head circumference-based model that separately treats small-for-gestational-age (SGA) and appropriate-for-gestational-age (AGA) infants is compared to a body weight model in a retrospective analysis of 48 patients with a median birth weight of 750g and median gestational age of 25 weeks. Estimated brain mass, model-based insulin sensitivity (SI) profiles, and projected glycaemic control outcomes are investigated. SGA infants (5) are also analyzed as a separate cohort. RESULTS: Across the entire cohort, estimated brain mass deviated by a median 10% between models, with a per-patient median difference in SI of 3.5%. For the SGA group, brain mass deviation was 42%, and per-patient SI deviation 13.7%. In virtual trials, 87-93% of recommended insulin rates were equal or slightly reduced (Δ<0.16mU/h) under the head circumference method, while glycaemic control outcomes showed little change. CONCLUSION: The results suggest that body weight methods are not as accurate as head circumference methods. Head circumference-based estimates may offer improved modelling accuracy and a small reduction in insulin administration, particularly for SGA infants.

On the problem of patient-specific endogenous glucose production in neonates on stochastic targeted glycemic control.

BACKGROUND: Both stress and prematurity can induce hyperglycemia in the neonatal intensive care unit, which, in turn, is associated with worsened outcomes. Endogenous glucose production (EGP) is the formation of glucose by the body from substrates and contributes to blood glucose (BG) levels. Due to the inherent fragility of the extremely low birth weight (ELBW) neonates, true fasting EGP cannot be explicitly determined, introducing uncertainty into glycemic models that rely on quantifying glucose sources. Stochastic targeting, or STAR, is one such glycemic control framework. METHODS: A literature review was carried out to gather metabolic and EGP values on preterm infants with a gestational age (GA) <32 weeks and a birth weight (BW) <2 kg. The data were analyzed for EGP trends with BW, GA, BG, plasma insulin, and glucose infusion (GI) rates. Trends were modeled and compared with a literature-derived range of population constant EGP models using clinically validated virtual trials on retrospective clinical data. RESULTS: No clear relationship was found for EGP and BW, GA, or plasma insulin. Some evidence of suppression of EGP with increasing GI or BG was seen. Virtual trial results showed that population-constant EGP models fit clinical data best and gave tighter control performance to a target band in virtual trials. CONCLUSIONS: Variation in EGP cannot easily be quantified, and EGP is sufficiently modeled as a population constant in the neonatal intensive care insulin-nutrition-glucose model. Analysis of the clinical data and fitting error suggests that ELBW hyperglycemic preterm neonates have unsuppressed EGP in the higher range than that seen in literature.

Nasogastric aspiration as an indicator for feed absorption in model-based glycemic control in neonatal intensive care.

BACKGROUND: STAR (stochastic targeted) is a glycemic control model-based framework for critically ill neonates that has shown benefits in reducing hypoglycemia and hyperglycemia. STAR uses a stochastic matrix method to forecast future changes in a patient's insulin sensitivity and then applies this result to a physiological model to select an optimal insulin treatment. Nasogastric aspiration may be used as an indicator to suggest periods of care when enteral feed absorption is compromised, improving the performance of glycemic control. An analysis has been carried out to investigate the effect of poorly absorbed feeds on glycemic control. METHOD: Clinical data were collected from eight patients on insulin therapy and enteral feed, which included large or significantly milky aspirates. Patients had a median gestational age of 25 weeks and postnatal age of 5.5 days. Virtual patients were created using the NICING model, and insulin sensitivity (SI) profiles were fit. Alternative feed profiles were generated whereby enteral feed absorption was redistributed with time to account for poor feed absorption. The effect of poor feed absorption, as indicated by aspirates, is investigated. RESULTS: The average percentage change of SI 4 h before a significant aspirate was 1.16%, and 1.49% in the 4 h following the aspirate. No distinct relationship was found between the fractional change in SI and the volume of the aspirate. Accounting for aspirates had a clinically negligible impact on glycemic control in virtual trials. CONCLUSION: Accounting for aspirates by manipulating enteral feed profiles had a minimal influence on both modeling and controlling glycemia in neonates. The impact of this method is clinically insignificant, suggesting that a population constant for the rate of glucose absorption in the gut adequately models feed absorption within the STAR framework.

Electrolytes in sick neonates - which sodium is the right answer?

INTRODUCTION: Hypoproteinaemia leads to spuriously high-sodium values when measured by indirect ion-selective electrodes (ISE) as used in main laboratory analysers compared with direct ISE employed in point-of-care analysers (POCT). The authors, therefore, investigated the occurrence of hypoalbuminaemia and its effect on measured sodium from POCT and the main laboratory analyser of neonatal intensive-care samples. METHOD: Sodium, in paired retrospective samples, measured by the main laboratory and neonatal unit blood-gas (POCT) analysers were compared. RESULTS: Hypoalbuminaemia (<30 g/l) was present in 1400/2420 paired results. Sodium was higher when measured by laboratory analyser, the difference increased with decreasing albumin; sodium (laboratory - POCT)=7.6 (±1.1)-0.22 (±0.04)×albumin. A difference >3 mmol/l was present in 31% and consequently underestimated (9.4%) hyponatraemia and overestimated (3.8%) hypernatraemia. CONCLUSION: Hypoalbuminaemia is common in sick neonates and monitoring electrolytes using POCT and laboratory analysers frequently yield significantly different results with consequent misclassification. In these patients, measurement of electrolytes by direct ISE (blood-gas analyser) may be more accurate.

Impact of variation in patient response on model-based control of glycaemia in critically ill patients.

Critically ill patients commonly experience stress-induced hyperglycaemia, and several studies have shown tight glycaemic control (TGC) can reduce patient mortality. However, tight control is often difficult to achieve due to conflicting drug therapies and evolving patient condition. Thus, a number of studies have failed to achieve consistently safe and effective TGC possibly due to the use of fixed insulin dosing protocols over adaptive patient-specific methods. Model-based targeted glucose control can adapt insulin and dextrose interventions to match identified patient insulin sensitivity. This study explores the impact on glycaemic control of assuming patient response to insulin is constant, as many protocols do, versus time-varying. Validated virtual trial simulations of glucose control were performed on adult and neonatal virtual patient cohorts. Results indicate assumptions of constant insulin sensitivity can lead to six-fold increases in incidence of hypoglycaemia, similar to literature reports and a commonly cited issue preventing increased adoption of TGC in critical care. It is clear that adaptive, patient-specific, approaches are better able to manage inter- and intra-patient variability than typical, fixed protocols.

Pilot study of a model-based approach to blood glucose control in very-low-birthweight neonates.

BACKGROUND: Hyperglycemia often occurs in premature, very low birthweight infants (VLBW) due to immaturity of endogenous regulatory systems and the stress of their condition. Hyperglycemia in neonates has been linked to increased morbidities and mortality and occurs at increasing rates with decreasing birthweight. In this cohort, the emerging use of insulin to manage hyperglycemia has carried a significant risk of hypoglycemia. The efficacy of blood glucose control using a computer metabolic system model to determine insulin infusion rates was assessed in very-low-birth-weight infants. METHODS: Initial short-term 24-hour trials were performed on 8 VLBW infants with hyperglycemia followed by long-term trials of several days performed on 22 infants. Median birthweight was 745 g and 760 g for short-term and long-term trial infants, and median gestational age at birth was 25.6 and 25.4 weeks respectively. Blood glucose control is compared to 21 retrospective patients from the same unit who received insulin infusions determined by sliding scales and clinician intuition. This study was approved by the Upper South A Regional Ethics Committee, New Zealand (ClinicalTrials.gov registration NCT01419873). RESULTS: Reduction in hyperglycemia towards the target glucose band was achieved safely in all cases during the short-term trials with no hypoglycemic episodes. Lower median blood glucose concentration was achieved during clinical implementation at 6.6 mmol/L (IQR: 5.5 - 8.2 mmol/L, 1,003 measurements), compared to 8.0 mmol/L achieved in similar infants previously (p < 0.01). No significant difference in incidence of hypoglycemia during long-term trials was observed (0.25% vs 0.25%, p = 0.51). Percentage of blood glucose within the 4.0 - 8.0 mmol/L range was increased by 41% compared to the retrospective cohort (68.4% vs 48.4%, p < 0.01). CONCLUSIONS: A computer model that accurately captures the dynamics of neonatal metabolism can provide safe and effective blood glucose control without increasing hypoglycemia. TRIAL REGISTRATION: ClinicalTrials.gov registration NCT01419873.

BCS1L gene mutation presenting with GRACILE-like syndrome and complex III deficiency.

The clinical presentation of a neonate with GRACILE-like syndrome, complex III deficiency and BCS1L mutations is discussed. This case is compared and contrasted with the original Finnish reports of GRACILE syndrome and other cases with a similar phenotype. This case confirms the pathogenicity of the BCS1L gene mutation c.166C>T, and provides support for the pathogenicity of a sequence variation, c.-588T>A, previously reported.

Are gentamicin and/or vancomycin associated with ototoxicity in the neonate? A retrospective audit.

BACKGROUND: Aminoglycoside-induced ototoxicity has been reported in neonates but its incidence is poorly defined, whereas vancomycin-induced ototoxicity has not been reported in neonates. OBJECTIVE: To compare hearing test results in infants in a neonatal intensive care unit (NICU) who were or were not treated with extended interval gentamicin dosing and/or standard vancomycin dosing. METHOD: A database of otoacoustic emissions (OAE), over a 5-year period of NICU admissions, was combined with databases of gentamicin and vancomycin dosing to compare patients treated or not treated with these antibiotics. RESULTS: A total of 2,347 OAE results was available. OAE failure rates were: no gentamicin and no vancomycin (noGnoV), 7% (85/1,233); gentamicin but no vancomycin (GnoV), 4% (42/949); vancomycin but no gentamicin (VnoG), 22% (9/41) and gentamicin and vancomycin (GandV), 14% (17/124). Compared to noGnoV there was a decreased risk of OAE failure in GnoV (p = 0.022, OR 0.64, 95% CI 0.44-0.94) and an increased risk in VnoG (p = 0.003, OR 3.46, 95% CI 1.54-7.75) and GandV, (p = 0.006, OR 2.20, 95% CI 1.26-3.83). CONCLUSIONS: Gentamicin, as used and evaluated in this audit, showed no evidence of an increased risk of ototoxicity; what was observed was a statistically significant decrease in OAE failure rate. Vancomycin, by contrast, was associated with ototoxicity.

Development of blood glucose control for extremely premature infants.

Extremely premature neonates often experience hyperglycaemia, which has been linked to increased mortality and worsened outcomes. Insulin therapy can assist in controlling blood glucose levels and promoting needed growth. This study presents the development of a model-based stochastic targeted controller designed to adapt insulin infusion rates to match the unique and changing metabolic state and control parameters of the neonate. Long-term usage of targeted BG control requires successfully forecasting variations in neonatal metabolic state, accounting for differences in clinical practices between units, and demonstrating robustness to errors that can occur in everyday clinical usage. Simulation studies were used to evaluate controller ability to target several common BG ranges and evaluate controller sensitivity to missed BG measurements and delays in control interventions on a virtual patient cohort of 25 infants developed from retrospective data. Initial clinical pilot trials indicated model performance matched expected performance from simulations. Stochastic targeted glucose control developed using validated patient-specific virtual trials can yield effective protocols for this cohort. Long-term trials show fundamental success, however clinical interface design appears as a critical factor to ensuring good compliance and thus good control.

Modeling the glucose regulatory system in extreme preterm infants.

BACKGROUND: Premature infants represent a significant proportion of the neonatal intensive care population. Blood glucose homeostasis in this group is often disturbed by immaturity of endogenous regulatory systems and the stress of their condition. Hypo- and hyperglycemia are frequently reported in very low birth weight infants, and more mature infants often experience low levels of glycemia. A model capturing the unique fundamental dynamics of the neonatal glucose regulatory system could be used to develop better blood glucose control methods. METHODS: A metabolic system model is adapted from adult critical care to the unique physiological case of the neonate. Integral-based fitting methods were used to identify time-varying insulin sensitivity and non-insulin mediated glucose uptake profiles. The clinically important predictive ability of the model was assessed by assuming insulin sensitivity was constant over prediction intervals of 1, 2 and 4h forward and comparing model-simulated versus actual clinical glucose values for all recorded interventions. The clinical data included 1091 glucose measurements over 3567 total patient hours, along with all associated insulin and nutritional infusion data, for N=25 total cases. Ethics approval was obtained from the Upper South A Regional Ethics Committee for this study. RESULTS: The identified model had a median absolute percentage error of 2.4% [IQR: 0.9-4.8%] between model-fitted and clinical glucose values. Median absolute prediction errors at 1-, 2- and 4-h intervals were 5.2% [IQR: 2.5-10.3%], 9.4% [IQR: 4.5-18.4%] and 13.6% [IQR: 6.3-27.6%] respectively. CONCLUSIONS: The model accurately captures and predicts the fundamental dynamic behaviors of the neonatal metabolism well enough for effective clinical decision support in glycemic control. The adaptation from adult to a neonatal case is based on the data from the literature. Low prediction errors and very low fitting errors indicate that the fundamental dynamics of glucose metabolism in both premature neonates and critical care adults can be described by similar mathematical models.

Tight glycemic control in critical care--the leading role of insulin sensitivity and patient variability: a review and model-based analysis.

Tight glycemic control (TGC) has emerged as a major research focus in critical care due to its potential to simultaneously reduce both mortality and costs. However, repeating initial successful TGC trials that reduced mortality and other outcomes has proven difficult with more failures than successes. Hence, there has been growing debate over the necessity of TGC, its goals, the risk of severe hypoglycemia, and target cohorts. This paper provides a review of TGC via new analyses of data from several clinical trials, including SPRINT, Glucontrol and a recent NICU study. It thus provides both a review of the problem and major background factors driving it, as well as a novel model-based analysis designed to examine these dynamics from a new perspective. Using these clinical results and analysis, the goal is to develop new insights that shed greater light on the leading factors that make TGC difficult and inconsistent, as well as the requirements they thus impose on the design and implementation of TGC protocols. A model-based analysis of insulin sensitivity using data from three different critical care units, comprising over 75,000h of clinical data, is used to analyse variability in metabolic dynamics using a clinically validated model-based insulin sensitivity metric (S(I)). Variation in S(I) provides a new interpretation and explanation for the variable results seen (across cohorts and studies) in applying TGC. In particular, significant intra- and inter-patient variability in insulin resistance (1/S(I)) is seen be a major confounder that makes TGC difficult over diverse cohorts, yielding variable results over many published studies and protocols. Further factors that exacerbate this variability in glycemic outcome are found to include measurement frequency and whether a protocol is blind to carbohydrate administration.

Blood glucose prediction using stochastic modeling in neonatal intensive care.

Hyperglycemia is a common metabolic problem in premature, low-birth-weight infants. Blood glucose homeostasis in this group is often disturbed by immaturity of endogenous regulatory systems and the stress of their condition in intensive care. A dynamic model capturing the fundamental dynamics of the glucose regulatory system provides a measure of insulin sensitivity (S(I)). Forecasting the most probable future S(I) can significantly enhance real-time glucose control by providing a clinically validated/proven level of confidence on the outcome of an intervention, and thus, increased safety against hypoglycemia. A 2-D kernel model of S(I) is fitted to 3567 h of identified, time-varying S(I) from retrospective clinical data of 25 neonatal patients with birth gestational age 23 to 28.9 weeks. Conditional probability estimates are used to determine S(I) probability intervals. A lag-2 stochastic model and adjustments of the variance estimator are used to explore the bias-variance tradeoff in the hour-to-hour variation of S(I). The model captured 62.6% and 93.4% of in-sample S(I) predictions within the (25th-75th) and (5th-95th) probability forecast intervals. This overconservative result is also present on the cross-validation cohorts and in the lag-2 model. Adjustments to the variance estimator found a reduction to 10%-50% of the original value provided optimal coverage with 54.7% and 90.9% in the (25th-75th) and (5th-95th) intervals. A stochastic model of S(I) provided conservative forecasts, which can add a layer of safety to real-time control. Adjusting the variance estimator provides a more accurate, cohort-specific stochastic model of S(I) dynamics in the neonate.

Blood glucose controller for neonatal intensive care: virtual trials development and first clinical trials.

BACKGROUND: Premature neonates often experience hyperglycemia, which has been linked to worsened outcomes. Insulin therapy can assist in controlling blood glucose (BG) levels. However, a reliable, robust control protocol is required to avoid hypoglycemia and to ensure that clinically important nutrition goals are met. METHODS: This study presents an adaptive, model-based predictive controller designed to incorporate the unique metabolic state of the neonate. Controller performance was tested and refined in virtual trials on a 25-patient retrospective cohort. The effects of measurement frequency and BG sensor error were evaluated. A stochastic model of insulin sensitivity was used in control to provide a guaranteed maximum 4% risk of BG < 72 mg/dl to protect against hypoglycemia as well as account for patient variability over 1-3 h intervals when determining the intervention. The resulting controller is demonstrated in two 24 h clinical neonatal pilot trials at Christchurch Women's Hospital. RESULTS: Time in the 72-126 mg/dl BG band was increased by 103-161% compared to retrospective clinical control for virtual trials of the controller, with fewer hypoglycemic measurements. Controllers were robust to BG sensor errors. The model-based controller maintained glycemia to a tight target control range and accounted for interpatient variability in patient glycemic response despite using more insulin than the retrospective case, illustrating a further measure of controller robustness. Pilot clinical trials demonstrated initial safety and efficacy of the control method. CONCLUSIONS: A controller was developed that made optimum use of the very limited available BG measurements in the neonatal intensive care unit and provided robustness against BG sensor error and longer BG measurement intervals. It used more insulin than typical sliding scale approaches or retrospective hospital control. The potential advantages of a model-based approach demonstrated in simulation were applied to initial clinical trials.

Cord and placenta arterial gas analysis: the accuracy of delayed sampling.

AIM: To determine the accuracy of delayed arterial gas sampling (1) from the umbilical cord and (2) from the placental surface at room temperature. METHODS: Term deliveries were classified a priori into three groups: normal vaginal deliveries, elective caesarean sections and high risk deliveries. The cord was double clamped and paired arterial samples were taken from the cord and the placenta at 0, 30, 60 and 90 min. RESULTS: 90 placentas were sampled with 30 cases per group. At time 0 the mean cord pH 7.207 (+/-0.08) was significantly lower than the placenta pH 7.240 (+/-0.08). The cord pH dropped significantly: by 0.050 (95% CI 0.036 to 0.063) at 30 min, 0.087 (95% CI 0.069 to 0.105) at 60 min, and 0.112 (95% CI 0.086 to 0.138) at 90 min. The placenta pH fell at twice the rate of the cord pH over 90 min. At time 0 the mean cord base excess -7.0 mmol/l (+/-4.1) was significantly lower than the placenta base excess -6.3 mmol/l (+/-3.6). The cord base excess fell at 30 min by 4.1 mmol/l (95% CI 3.4 to 4.7), at 60 min by 7.1 mmol/l (95% CI 6.1 to 8.0), and at 90 min by 9.0 mmol/l (95% CI 7.9 to 10.0). The pH and base excess rate of fall was similar for each of the three delivery groups despite differing starting values. CONCLUSION: Arterial blood gases should be taken as soon as possible after delivery from the umbilical cord. However, when this is not possible, the arterial pH and base excess from a delayed sample from a clamped cord at room temperature can be used to estimate the values at birth.

Amino-terminal proCNP: a putative marker of cartilage activity in postnatal growth.

Recent evidence from rodents and humans shows that C-type natriuretic peptide (CNP) plays an essential role in endochondral bone growth. We recently identified a stable product of proCNP, amino-terminal proCNP (NT-proCNP), which unlike CNP is readily measurable in human and ovine plasma. Hypothesizing that plasma NT-proCNP concentrations reflect in part CNP synthesis within growth plates of rapidly growing cartilage, we studied levels of CNP forms in both children and lambs and related these to age, growth velocity, and biochemical markers of bone turnover. Plasma NT-proCNP levels were elevated at birth and fell progressively with age. Significant associations between plasma NT-proCNP and height velocity, alkaline phosphatase, and type 1 collagen C telopeptide were identified in children (aged 5-18 y). In longitudinal animal studies, elevated plasma concentration of NT-proCNP in 1-wk-old lambs fell progressively to mature adult levels at age 27 wk. Plasma NT-proCNP showed a highly significant association with alkaline phosphatase and metacarpal growth velocity. Glucocorticoids, a treatment known to inhibit cartilage proliferation, reduced metacarpal growth elongation in 4-wk-old lambs and markedly lowered circulating NT-proCNP levels during the treatment period. In summary, NT-proCNP levels in blood show a strong association with growth velocity and markers of bone formation and may well serve as a useful marker of growth plate activity in humans and other mammals.