Antibiotic prescribing in neonatal sepsis: an Australian nationwide survey

OBJECTIVE

To evaluate quality and variation in antibiotic prescribing for neonatal sepsis.

DESIGN

We analysed prescribing in hospitalised neonates using the National Antimicrobial Prescribing Survey in Australian neonates from 1 January 2014 to 31 December 2018.

SETTING

Data from antibiotic point prevalence surveys performed in hospitals, ranging from rural hospitals to tertiary paediatric and maternity hospitals within Australia.

PATIENTS

Admitted neonates <28 days of age from participating hospitals.

MAIN OUTCOME MEASURES

Variation and appropriateness in prescribing for neonatal sepsis and variation in dosing for gentamicin and benzylpenicillin across hospitals.

RESULTS

A total of 415 prescriptions among 214 neonates from 39 different hospitals were included. The majority of prescriptions (342, 82.4%) were for neonates <7 days of age. The most commonly prescribed antibiotics were gentamicin and benzylpenicillin, with 323 (77.8%) prescriptions. Dosing variability was substantial, with doses ranging from 2 to 8 mg/kg for gentamicin (median 5 mg/kg, IQR 4-5) and from 45 to 72 mg/kg for benzylpenicillin (median 60 mg/kg, IQR 50-60), although only 13 (3.2%) and 19 (4.6%) prescriptions were locally assessed as inappropriate or non-compliant with guidelines, respectively. At time of audit, 22% of antibiotics had been given for more than 48 hours and 9% more than 72 hours, although microbiologically confirmed infection was documented in only nine (4.2%) neonates.

CONCLUSIONS

Prescribing for neonatal sepsis was dominated by use of benzylpenicillin and gentamicin with substantial variation in dosing. A small minority had culture-confirmed infection. Efforts to standardise antibiotic dosing and duration for suspected neonatal sepsis are recommended.

Impact of Skull Thickness on Cerebral NIRS Oximetry in Neonates: An in silico Study

Monitoring of cerebral tissue oxygen saturation (StO₂) by near-infrared spectroscopy (NIRS oximetry) has great potential to reduce the incidence of hypoxic and hyperoxic events and thus prevent long-term disabilities in preterm neonates. Since the light has to penetrate superficial layers (bone, skin and cerebrospinal fluid) before it reaches the brain, the question arises whether these layers influence cerebral StO₂ measurement. We assessed this influence on the accuracy of cerebral StO₂ values. For that purpose, we simulated light propagation with 'N-layered medium' software. It was found that with a superficial layer thickness of ≤6 mm, typical for term and preterm neonates, StO₂ accurately reflects cerebral tissue oxygenation.

Reducing False Alarm Rates in Neonatal Intensive Care: A New Machine Learning Approach

In neonatal intensive care units (NICUs), 87.5% of alarms by the monitoring system are false alarms, often caused by the movements of the neonates. Such false alarms are not only stressful for the neonates as well as for their parents and caregivers, but may also lead to longer response times in real critical situations. The aim of this project was to reduce the rates of false alarms by employing machine learning algorithms (MLA), which intelligently analyze data stemming from standard physiological monitoring in combination with cerebral oximetry data (in-house built, OxyPrem).

MATERIALS & METHODS

Four popular MLAs were selected to categorize the alarms as false or real: (i) decision tree (DT), (ii) 5-nearest neighbors (5-NN), (iii) naïve Bayes (NB) and (iv) support vector machine (SVM). We acquired and processed monitoring data (median duration (SD): 54.6 (± 6.9) min) of 14 preterm infants (gestational age: 26 6/7 (± 2 5/7) weeks). A hybrid method of filter and wrapper feature selection generated the candidate subset for training these four MLAs.

RESULTS

A high specificity of >99% was achieved by all four approaches. DT showed the highest sensitivity (87%). The cerebral oximetry data improved the classification accuracy.

DISCUSSION & CONCLUSION

Despite a (as yet) low amount of data for training, the four MLAs achieved an excellent specificity and a promising sensitivity. Presently, the current sensitivity is insufficient since, in the NICU, it is crucial that no real alarms are missed. This will most likely be improved by including more subjects and data in the training of the MLAs, which makes pursuing this approach worthwhile.

Comparison of tissue oximeters on a liquid phantom with adjustable optical properties: an extension

Cerebral near-infrared spectroscopy (NIRS) oximetry may help clinicians to improve patient treatment. However, the application of NIRS oximeters is increasingly causing confusion to the users due to the inconsistency of tissue oxygen haemoglobin saturation (StO2) readings provided by different oximeters. To establish a comparability of oximeters, in our study we performed simultaneous measurements on the liquid phantom mimicking properties of neonatal heads and compared the tested device to a reference NIRS oximeter (OxiplexTS). We evaluated the NIRS oximeters FORE-SIGHT, NIRO and SenSmart, and reproduced previous results with the INVOS and OxyPrem v1.3 oximeters. In general, linear relationships of the StO2 values with respect to the reference were obtained. Device specific hypoxic and hyperoxic thresholds (as used in the SafeBoosC study, www.safeboosc.eu) and a table allowing for conversion of StO2 values are provided.