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The Cochrane Database of Systematic... Dec 2020Simulation-based obstetric team training focuses on building a system that will anticipate errors, improve patient outcomes and the performance of clinical care teams.... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Simulation-based obstetric team training focuses on building a system that will anticipate errors, improve patient outcomes and the performance of clinical care teams. Simulation-based obstetric team training has been proposed as a tool to improve the overall outcome of obstetric health care.
OBJECTIVES
To assess the effects of simulation-based obstetric team training on patient outcomes, performance of obstetric care teams in practice and educational settings, and trainees' experience.
SEARCH METHODS
The Cochrane Pregnancy and Childbirth Group's Trials Register, ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform (ICTRP) were searched (14 April 2020), together with references checking and hand searching the available proceedings of 2 international conferences.
SELECTION CRITERIA
We included randomised controlled trials (RCTs) (including cluster-randomised trials) comparing simulation-based obstetric team training with no, or other type of training.
DATA COLLECTION AND ANALYSIS
We used standard methodological procedures expected by Cochrane, to identify articles, assess methodological quality and extract data. Data from three cluster-randomised trials could be used to perform generic inverse variance meta-analyses. The meta-analyses were based on risk ratios (RRs) and mean differences (MDs) with 95% confidence intervals (CIs). We used the GRADE approach to rate the certainty of the evidence. We used Kirkpatrick's model of training evaluation to categorise the outcomes of interest; we chose Level 3 (behavioural change) and Level 4 (patient outcome) to categorise the primary outcomes.
MAIN RESULTS
We included eight RCTs, six of which were cluster-randomised trials, involving more than 1000 training participants and more than 200,000 pregnancies/births. Four studies reported on outcome measures on Kirkpatrick level 4 (patient outcome), three studies on Kirkpatrick level 3 (performance in practice), two studies on Kitkpatrick level 2 (performance in educational settings), and none on Kirkpatrick level 1 (trainees' experience). The included studies were from Mexico, the Netherlands, the UK and the USA, all middle- and high-income countries. Kirkpatrick level 4 (patient outcome) Simulation-based obstetric team training may make little or no difference for composite outcomes of maternal and/or perinatal adverse events compared with no training (3 studies; n = 28,731, low-certainty evidence, data not pooled due to different composite outcome definitions). We are uncertain whether simulation-based obstetric team training affects maternal mortality compared with no training (2 studies; 79,246 women; very low-certainty evidence). However, it may reduce neonatal mortality (RR 0.70, 95% CI 0.48 to 1.01; 2 studies, 79,246 pregnancies/births, low-certainty evidence). Simulation-based obstetric team training may have little to no effect on low Apgar score compared with no training (RR 0.99, 95% 0.85 to 1.15; 2 studies; 115,171 infants; low-certainty evidence), but it probably reduces trauma after shoulder dystocia (RR 0.50, 95% CI 0.25 to 0.99; 1 study; moderate-certainty evidence) and probably slightly reduces the number of caesarean deliveries (RR 0.79, 95% CI 0.67 to 0.93; 1 study; n = 50,589; moderate-certainty evidence) Kirkpatrick level 3 (performance in practice) We found that simulation-based obstetric team training probably improves the performance of the obstetric teams in practice, compared with no training (3 studies; 2398 obstetric staff members, moderate-certainty evidence, data not pooled due to different outcome definitions).
AUTHORS' CONCLUSIONS
Simulation-based obstetric team training may help to improve team performance of obstetric teams, and it might contribute to improvement of specific maternal and perinatal outcomes, compared with no training. However, high-certainty evidence is lacking due to serious risk of bias and imprecision, and the effect cannot be generalised for all outcomes. Future studies investigating simulation-based obstetric team training compared to training courses with a different instructional design should carefully consider how and when to measure outcomes. Particular attention should be paid to effect measurement at the level of patient outcome, taking into consideration the low incidence of adverse maternal and perinatal events.
Topics: Apgar Score; Bias; Cesarean Section; Clinical Competence; Confidence Intervals; Emergencies; Female; Humans; Infant; Infant Mortality; Infant, Newborn; Maternal Mortality; Medical Errors; Obstetrics; Patient Care Team; Pregnancy; Randomized Controlled Trials as Topic; Shoulder Dystocia; Simulation Training; Treatment Outcome
PubMed: 33325570
DOI: 10.1002/14651858.CD011545.pub2 -
The Cochrane Database of Systematic... Sep 2019Gestational diabetes mellitus (GDM) is a common medical condition that complicates pregnancy and causes adverse maternal and fetal outcomes. At present, most treatment...
BACKGROUND
Gestational diabetes mellitus (GDM) is a common medical condition that complicates pregnancy and causes adverse maternal and fetal outcomes. At present, most treatment strategies focus on normalisation of maternal blood glucose values with use of diet, lifestyle modification, exercise, oral anti-hyperglycaemics and insulin. This has been shown to reduce the incidence of adverse outcomes, such as birth trauma and macrosomia. However, this involves intensive monitoring and treatment of all women with GDM. We propose that using medical imaging to identify pregnancies displaying signs of being affected by GDM could help to target management, allowing low-risk women to be spared excessive intervention, and facilitating better resource allocation.
OBJECTIVES
We wanted to address the following question: in women with gestational diabetes, does the use of fetal imaging plus maternal blood glucose concentration to indicate the need for medical management compared with glucose concentration alone reduce the risk of adverse perinatal outcomes?
SEARCH METHODS
We searched Cochrane Pregnancy and Childbirth's Trials Register (29 January 2019), ClinicalTrials.gov, the World Health Organization International Clinical Trials Registry Platform (ICTRP) (both on 29 January 2019), and reference lists of retrieved studies.
SELECTION CRITERIA
Randomised controlled trials, including those published in abstract form only. Studies using a cluster-randomised design and quasi-randomised controlled trials were both eligible for inclusion, but we didn't identify any. Cross-over trials were not eligible for inclusion in our review.We included women carrying singleton pregnancies who were diagnosed with GDM, as defined by the trials' authors. The intervention of interest was the use of fetal biometry on imaging methods in addition to maternal glycaemic values for indicating the use of medical therapy for GDM. The control group was the use of maternal glycaemic values alone for indicating the use of such therapy.
DATA COLLECTION AND ANALYSIS
Two review authors independently assessed trials for inclusion and assessed risk of bias. Two review authors extracted data and checked them for accuracy.
MAIN RESULTS
Three randomised controlled trials met the inclusion criteria for our systematic review - the studies randomised a total of 524 women.We assessed the three included studies as being at a low to moderate risk of bias; the nature of the intervention made it difficult to achieve blinding of participants and personnel and none of the trial reports contained information about methods of allocation concealment (and were therefore assessed as being at an unclear risk of selection bias).In all studies, the intervention was the use of fetal biometry on ultrasound to identify fetuses displaying signs of fetal macrosomia, and the use of this information to indicate the use of medical anti-hyperglycaemic treatments. Those pregnancies were subject to more stringent blood glucose targets than those without signs of fetal macrosomia.Maternal outcomesThe use of fetal biometry in addition to maternal blood glucose concentration (compared with maternal blood glucose concentration alone) may make little or no difference to the incidence of caesarean delivery (risk ratio (RR) 0.81, 95% confidence interval (CI) 0.59 to 1.10; 2 trials, 428 women; low-certainty evidence). We are unclear about the results for hypertensive disorders of pregnancy (RR 0.80, 95% CI 0.34 to 1.89; 2 trials, 325 women) due to very low-certainty evidence. The included trials did not report on development of type 2 diabetes in the mother or maternal hypoglycaemia.Fetal and neonatal outcomesThe use of fetal biometry may make little or no difference to the incidence of neonatal hypoglycaemia (RR 0.90, 95% CI 0.57 to 1.42; 3 trials, 524 women; low-certainty evidence). Very low-certainty evidence means that we are unclear about the results for large-for-gestational age (RR 0.81, 95% CI 0.38 to 1.74; 3 trials, 524 women); shoulder dystocia (RR 0.33, 95% CI 0.01 to 7.98; 1 trial, 96 women); a composite measure of perinatal morbidity or mortality (RR 1.00, 95% CI 0.21 to 4.71; 1 study, 96 women); or perinatal mortality (RR 0.33, 95% CI 0.01 to 7.98; 1 trial, 96 women).
AUTHORS' CONCLUSIONS
This review is based on evidence from three trials involving 524 women. The trials did not report some important outcomes of interest to this review, and the majority of our secondary outcomes were also unreported. The available evidence ranged from low- to very low-certainty, with downgrading decisions based on limitations in study design, imprecision and inconsistency.There is insufficient evidence to evaluate the use of fetal biometry (in addition to maternal blood glucose concentration values) to assist in guiding the medical management of GDM, on either maternal or perinatal health outcomes, or the associated costs.More research is required, ideally larger randomised studies which report the maternal and infant short- and long-term outcomes listed in this review, as well as those outcomes relating to financial and resource implications.
Topics: Biometry; Diabetes, Gestational; Female; Fetal Macrosomia; Humans; Insulin; Pregnancy; Pregnancy Complications; Pregnancy Outcome; Randomized Controlled Trials as Topic
PubMed: 31476798
DOI: 10.1002/14651858.CD012544.pub2