Detection of small for gestational age babies and perinatal outcomes following implementation of the Growth Assessment Protocol at a New Zealand tertiary facility: An observational intervention study

Clinical decision support systems for maternity care: a systematic review and meta-analysis

Background

The use of Clinical Decision Support Systems (CDSS) is increasing throughout healthcare and may be able to improve safety and outcomes in maternity care, but maternity care has key differences to other disciplines that complicate the use of CDSS. We aimed to identify evaluated CDSS and synthesise evidence of their impact on maternity care.

Methods

We conducted a systematic review for articles published before 24th May 2024 that described i) CDSS that ii) investigated the impact of their use iii) in maternity settings. Medline, CINAHL, CENTRAL and HMIC were searched for articles relating to evaluations of CDSS in maternity settings, with forward- and backward-citation tracing conducted for included articles. Risk of bias was assessed using the Mixed Methods Assessment Tool, and CDSS were described according to the clinical problem, purpose, design, and technical environment. Quantitative results from articles reporting appropriate data were meta-analysed to estimate odds of a CDSS achieving its desired outcome using a multi-level random effects model, first by individual CDSS and then across all CDSS. PROSPERO ID: CRD42022348157.

Findings

We screened 12,039 papers and included 87 articles describing 47 unique CDSS. 24 articles (28%) described randomised controlled trials, 30 (34%) described non-randomised interventional studies, 10 (11%) described mixed methods studies, 10 (11%) described qualitative studies, 7 (8%) described quantitative descriptive studies, and 7 (8%) described economic evaluations. 49 (56%) were in High-Income Countries and 38 (44%) in Low- and Middle-Income countries, with no CDSS trialled in both income categories. Meta-analysis of 35 included studies found an odds ratio for improved outcomes of 1.69 (95% confidence interval 1.24-2.30). There was substantial variation in effects, aims, CDSS types, context, study designs, and outcomes.

Interpretation

Most CDSS evaluations showed improvements in outcomes, but there was heterogeneity in all aspects of design and evaluation of systems. CDSS are increasingly important in delivering healthcare, and Electronic Health Records and mHealth will increase their availability, but traditional epidemiological methods may be limited in guiding design and demonstrating effectiveness due to rapid CDSS development lifecycles and the complex systems in which they are embedded. Development methods that are attentive to context, such as Human Centred Design, will help to meet this need.

Funding

None.

Outcome-based comparative analysis of five fetal growth velocity models to define slow growth

OBJECTIVE

Fetal growth surveillance includes assessment of size as well as rate of growth, and various definitions for slow growth have been adopted into clinical use. The aim of this study was to evaluate the effectiveness of different models to identify stillbirth risk, in addition to risk represented by the fetus being small-for-gestational age (SGA).

METHODS

This was a retrospective analysis of a routinely collected and anonymized dataset of pregnancies that had two or more third-trimester ultrasound measurements of estimated fetal weight (EFW). SGA was defined as EFW < 10th customized centile, and slow growth was defined according to five published models in clinical use: (1) a fixed velocity limit of 20 g per day (FVL20 ); (2) a fixed > 50 centile drop, regardless of scan-measurement interval (FCD50 ); (3) a fixed > 30 centile drop, regardless of scan interval (FCD30 ); (4) growth trajectory slower than the third customized growth-centile limit (GCL3 ); and (5) EFW at second scan below the projected optimal weight range (POWR), based on partial receiver-operating-characteristics-curve-derived  cut-offs specific to the scan interval.

RESULTS

The study cohort consisted of 164 718 pregnancies with 480 592 third-trimester ultrasound scans (mean ± SD, 2.9 ± 0.9). The last two scans in each pregnancy were performed at an average gestational age of 33 + 5 and 37 + 1 weeks. At the last scan, 12 858 (7.8%) EFWs were SGA, and of these, 9359 were also SGA at birth (positive predictive value, 72.8%). The rate at which slow growth was defined varied considerably (FVL20 , 12.7%; FCD50 , 0.7%; FCD30 , 4.6%; GCL3 , 19.8%; POWR, 10.1%), and there was varying overlap between cases identified as having slow growth and those identified as SGA at the last scan. Only the POWR method identified additional non-SGA pregnancies with slow growth (11 237/16 671 (67.4%)) that had significant stillbirth risk (relative risk, 1.58 (95% CI, 1.04-2.39)). These non-SGA cases resulting in stillbirth had a median EFW centile of 52.6 at the last scan and a median weight centile of 27.3 at birth. Subgroup analysis identified methodological problems with the fixed-velocity model because it assumes linear growth throughout gestation, and with the centile-based methods because the non-parametric distribution of centiles at the extremes does not reflect actual difference in weight gain.

CONCLUSION

Comparative analysis of five clinically used methods to define slow fetal growth has shown that only the measurement-interval-specific POWR model can identify non-SGA fetuses with slow growth that are at increased risk of stillbirth. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Characteristics associated with antenatally unidentified small-for-gestational-age fetuses: prospective cohort study nested within DESiGN randomized controlled trial

OBJECTIVE

To identify the clinical characteristics and patterns of ultrasound use amongst pregnancies with an antenatally unidentified small-for-gestational-age (SGA) fetus, compared with those in which SGA is identified, to understand how to design interventions that improve antenatal SGA identification.

METHODS

This was a prospective cohort study of singleton, non-anomalous SGA (birth weight < 10th centile) neonates born after 24 + 0 gestational weeks at 13 UK sites, recruited for the baseline period and control arm of the DESiGN trial. Pregnancy with antenatally unidentified SGA was defined if there was no scan or if the final scan showed estimated fetal weight (EFW) at the 10th centile or above. Identified SGA was defined if EFW was below the 10th centile at the last scan. Maternal and fetal sociodemographic and clinical characteristics were studied for associations with unidentified SGA using unadjusted and adjusted logistic regression models. Ultrasound parameters (gestational age at first growth scan, number and frequency of ultrasound scans) were described, stratified by presence of indication for serial ultrasound. Associations of unidentified SGA with absolute centile and percentage weight difference between the last scan and birth were also studied on unadjusted and adjusted logistic regression, according to time between the last scan and birth.

RESULTS

Of the 15 784 SGA babies included, SGA was not identified antenatally in 78.7% of cases. Of pregnancies with unidentified SGA, 47.1% had no recorded growth scan. Amongst 9410 pregnancies with complete data on key maternal comorbidities and antenatal complications, the risk of unidentified SGA was lower for women with any indication for serial scans (adjusted odds ratio (aOR), 0.56 (95% CI, 0.49-0.64)), for Asian compared with white women (aOR, 0.80 (95% CI, 0.69-0.93)) and for those with non-cephalic presentation at birth (aOR, 0.58 (95% CI, 0.46-0.73)). The risk of unidentified SGA was highest among women with a body mass index (BMI) of 25.0-29.9 kg/m2 (aOR, 1.15 (95% CI, 1.01-1.32)) and lowest in those with underweight BMI (aOR, 0.61 (95% CI, 0.48-0.76)) compared to women with BMI of 18.5-24.9 kg/m2 . Compared to women with identified SGA, those with unidentified SGA had fetuses of higher SGA birth-weight centile (adjusted odds for unidentified SGA increased by 1.21 (95% CI, 1.18-1.23) per one-centile increase between the 0th and 10th centiles). Duration between the last scan and birth increased with advancing gestation in pregnancies with unidentified SGA. SGA babies born within a week of the last growth scan had a mean difference between EFW and birth-weight centiles of 19.5 (SD, 13.8) centiles for the unidentified-SGA group and 0.2 (SD, 3.3) centiles for the identified-SGA group (adjusted mean difference between groups, 19.0 (95% CI, 17.8-20.1) centiles).

CONCLUSIONS

Unidentified SGA was more common amongst women without an indication for serial ultrasound, and in those with cephalic presentation at birth, BMI of 25.0-29.9 kg/m2 and less severe SGA. Ultrasound EFW was overestimated in women with unidentified SGA. This demonstrates the importance of improving the accuracy of SGA screening strategies in low-risk populations and continuing performance of ultrasound scans for term pregnancies. © 2022 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Evaluating the Growth Assessment Protocol for stillbirth prevention: progress and challenges

Many stillbirths are associated with fetal growth restriction, and are hence potentially avoidable. The Growth Assessment Protocol (GAP) is a multidisciplinary program with an evidence based care pathway, training in risk assessment, fetal growth surveillance with customised charts and rolling audit. Antenatal detection of small for gestational age (SGA) has become an indicator of quality of care. Evaluation is essential to understand the impact of such a prevention program. Randomised trials will not be effective if they cannot ensure proper implementation before assessment. Observational studies have allowed realistic evaluation in practice, with other factors excluded that may have influenced the outcome. An award winning 10 year study of stillbirth data in England has been able to assess the effect of GAP in isolation, and found a strong, causal association with improved antenatal detection of SGA babies, and the sustained decline in national stillbirth rates. The challenge now is to apply this program more widely in low and middle income settings where the main global burden of stillbirth is, and to adapt it to local needs and resources.

Impact of introduction of the growth assessment protocol in a South Indian tertiary hospital on SGA detection, stillbirth rate and neonatal outcome

OBJECTIVES

India has a high rate of stillbirths, and many deaths are due to fetal growth restriction and potentially preventable. Screening and identification of the small for gestational age (SGA) fetus during the antenatal period has been shown to reduce stillbirths. We set out to evaluate the impact of implementing the Growth Assessment Protocol (GAP), a programme designed for screening for SGA.

METHODS

Observational study comparing two-time epochs; before (years 2011-2014) and after (years 2015-2018) introduction of GAP. The programme includes identification of risk factors, risk categorization, serial fundal height measurement, customised fetal growth charts and appropriate referral protocols. Fetal growth charts and birth centiles were generated based on the hospital database of normal outcome pregnancies, customised to women's ethnicity, parity, height, and weight. The protocol was introduced following training of obstetric and midwifery care providers. We evaluated SGA detection rates, stillbirth rates (from 28 weeks) and neonatal morbidity at term.

RESULTS

There were 26,199 and 31,498 births, with 115 and 108 stillbirths in the pre and post-GAP implementation periods, respectively. SGA detection rates increased from 51.1 to 67.1%, representing a 31% improvement (p<0.001). Overall stillbirth rates declined from 4.4 to 3.4 per 1000 births (RR 0.78 CI 95% 0.60-1.02) and at term from 1.5 to 0.6 (RR 0.37 CI 95% 0.20-0.66). Neonatal intensive care admission and neonatal encephalopathy in term neonates also decreased significantly.

CONCLUSIONS

Introduction of the GAP programme in an Indian tertiary maternity service was associated with improved antenatal detection of SGA and reduced stillbirth rates and neonatal morbidity.

Evaluation of the Growth Assessment Protocol (GAP) for antenatal detection of small for gestational age: The DESiGN cluster randomised trial

BACKGROUND

Antenatal detection and management of small for gestational age (SGA) is a strategy to reduce stillbirth. Large observational studies provide conflicting results on the effect of the Growth Assessment Protocol (GAP) in relation to detection of SGA and reduction of stillbirth; to the best of our knowledge, there are no reported randomised control trials. Our aim was to determine if GAP improves antenatal detection of SGA compared to standard care.

METHODS AND FINDINGS

This was a pragmatic, superiority, 2-arm, parallel group, open, cluster randomised control trial. Maternity units in England were eligible to participate in the study, except if they had already implemented GAP. All women who gave birth in participating clusters (maternity units) during the year prior to randomisation and during the trial (November 2016 to February 2019) were included. Multiple pregnancies, fetal abnormalities or births before 24+1 weeks were excluded. Clusters were randomised to immediate implementation of GAP, an antenatal care package aimed at improving detection of SGA as a means to reduce the rate of stillbirth, or to standard care. Randomisation by random permutation was stratified by time of study inclusion and cluster size. Data were obtained from hospital electronic records for 12 months prerandomisation, the washout period (interval between randomisation and data collection of outcomes), and the outcome period (last 6 months of the study). The primary outcome was ultrasound detection of SGA (estimated fetal weight <10th centile using customised centiles (intervention) or Hadlock centiles (standard care)) confirmed at birth (birthweight <10th centile by both customised and population centiles). Secondary outcomes were maternal and neonatal outcomes, including induction of labour, gestational age at delivery, mode of birth, neonatal morbidity, and stillbirth/perinatal mortality. A 2-stage cluster-summary statistical approach calculated the absolute difference (intervention minus standard care arm) adjusted using the prerandomisation estimate, maternal age, ethnicity, parity, and randomisation strata. Intervention arm clusters that made no attempt to implement GAP were excluded in modified intention to treat (mITT) analysis; full ITT was also reported. Process evaluation assessed implementation fidelity, reach, dose, acceptability, and feasibility. Seven clusters were randomised to GAP and 6 to standard care. Following exclusions, there were 11,096 births exposed to the intervention (5 clusters) and 13,810 exposed to standard care (6 clusters) during the outcome period (mITT analysis). Age, height, and weight were broadly similar between arms, but there were fewer women: of white ethnicity (56.2% versus 62.7%), and in the least deprived quintile of the Index of Multiple Deprivation (7.5% versus 16.5%) in the intervention arm during the outcome period. Antenatal detection of SGA was 25.9% in the intervention and 27.7% in the standard care arm (adjusted difference 2.2%, 95% confidence interval (CI) -6.4% to 10.7%; p = 0.62). Findings were consistent in full ITT analysis. Fidelity and dose of GAP implementation were variable, while a high proportion (88.7%) of women were reached. Use of routinely collected data is both a strength (cost-efficient) and a limitation (occurrence of missing data); the modest number of clusters limits our ability to study small effect sizes.

CONCLUSIONS

In this study, we observed no effect of GAP on antenatal detection of SGA compared to standard care. Given variable implementation observed, future studies should incorporate standardised implementation outcomes such as those reported here to determine generalisability of our findings.

TRIAL REGISTRATION

This trial is registered with the ISRCTN registry, ISRCTN67698474.