Liv Merete Reinar

Prognostic value of the labour admission test and its effectiveness compared with auscultation only: a systematic review

Objective  To assess the effectiveness of the labour admission test in preventing adverse outcomes, compared with auscultation only, and to assess the tests prognostic value in predicting adverse outcomes.

ST waveform analysis vs. cardiotocography alone for intrapartum fetal monitoring: A systematic review and meta-analysis of randomized trials

ST waveform analysis was introduced to reduce metabolic acidosis at birth and avoid unnecessary operative deliveries relative to conventional cardiotocography. Our objective was to quantify the efficacy of ST waveform analysis vs. cardiotocography and assess the quality of the evidence using the Grading of Recommendations Assessment, Development and Evaluation tool.

Development of a complex intervention to improve health literacy skills.

Background Providing insight into the developmental processes involved in building interventions is an important way to ensure methodological transparency and inform future research efforts. The objective of this study was to describe the development of a web portal designed to improve health literacy skills among the public. Methods The web portal was tailored to address three key barriers to obtaining information, using the conceptual frameworks of shared decision-making and evidence-based practice and based on explicit criteria for selecting the content and form of the intervention. Results The web portal targeted the general public and took the form of structured sets of tools. Content included: an introduction to research methods, help on how to find evidence-based health information efficiently based on the steps of evidence-based practice, an introduction to critical appraisal, information about patient participation rights in decision-making, and a decision aid for consultations. Conclusions The web portal was designed in a systematic and transparent way and address key barriers to obtaining and acting upon reliable health information. The web portal provides open access to the tools and can be used independently by health care users, or during consultations with health professionals.

STAN technology, surrogate outcomes and possible sources of bias

Sir, We appreciate the comments from Olofsson (1) and Kessler et al. (2). We investigated several outcomes in our review, and two (risk of metabolic acidosis and operative vaginal delivery) showed statistically significant differences in favor of STAN. (3). Two other high quality meta-analyses were published almost simultaneously (4,5), and neither reported significant differences in rates of metabolic acidosis. Saccone et al. (4) and Neilson (5) used risk ratio (RR) and random effect models, whereas we used peto odds ratio (OR) and fixed effect model for outcomes with an incidence <1%. Both approaches have pros and cons and we hesitate to define either one as superior. Olofsson argues that we did the most correct metaanalysis (3). Positive feedback is always welcome, but it is tempting to ask whether this judgment is related to the fact that our metaanalysis shows positive results for metabolic acidosis, whereas the others do not. We once again emphasize the need to view all results in context, particularly when the only interesting effect manifests itself in a surrogate outcome with uncertain clinical validity. Surrogate outcomes are used to predict the risk of future serious events, thus shortening the size, duration and cost of trials. Unfortunately, this is associated with pitfalls and bias (6,7). The uncertain validity of metabolic acidosis is demonstrated in an individual patient data review (4) investigating a composite endpoint (at least one of the following: intrapartum fetal death, neonatal death, Apgar score ≤3 at five minutes, neonatal seizures, metabolic acidosis, intubation for ventilation at delivery or neonatal encephalopathy) without finding a difference between STAN and CTG. Hence, we disagree with Kessler et al. and Olofsson, who seem to take the validity of metabolic acidosis for granted. Kessler et al. assume that 10.3% of all babies born with metabolic acidosis have severe adverse outcomes due to an intrapartum hypoxic event. Their calculation presupposes that the risk reductions for metabolic acidosis and for serious adverse events are linearly related. We find this inference speculative, and wonder why one should trust estimates based on assumption rather than direct data. Direct data suggest that that STAN might be associated with reduced survival (3–5). Kessler et al. estimated that STAN will prevent 493 operative vaginal deliveries in Norway each year. This estimate is based on the questionable assumption that all delivery units use STAN on all laboring women, and they ask whether we regard this reduction as unimportant. We welcome efforts to reduce operative deliveries without compromising neonatal outcomes, but this should involve other approaches rather than STAN. Olofsson further argues that our GRADE assessments are influenced by culture, norms and other preferences. This is of course true. The use of GRADE does not guarantee consensus, but we note that the Cochrane meta-analysis (5) arrived at very similar conclusions. Olofsson states that relying more on negative than positive evidence is a part of being human, suggesting that our conclusions are prone to bias. We believe that confirmation bias, conflicts of interest and uncritical embracement of new technology (8) are the most potent sources of bias in this field. We do not see any reasons why we could be more exposed to this type of bias than others. As an extension of the latter argument, it is tempting to refer to the criticism of the recently published US study (9). This study was funded with 3 million USD and supported by Neoventa AB (10). The STAN algorithm was different from that used in Europe, but the algorithm was the same as used by Neoventa for their FDA approval (10). In 2014, Olofsson, Kessler, Yli and others published a review (11) and concluded: “The results of the ongoing multicenter RCT in the United States are some months away. Certainly the contribution of the USA data will help to determine whether the addition of ST analysis to conventional CTG results in improved perinatal outcomes.” After the US study showed negative results, Kessler, Yli and others published a statement with severe objections to this study on the Neoventa homepage (12). It is tempting to speculate whether this criticism would have been raised if the US study had published positive results.

Statistical significance is not necessarily equal to clinical significance.

Sir, We thank Vayssiere et al. for their comment (1). Vayssiere et al. state that there were contradictory findings regarding neonatal metabolic acidosis between the three recently published meta-analyses on STAN vs. CTG alone (2–4). We disagree, as all three meta-analyses reported a decrease but only one reached statistical significance. Further, Vayssiere et al. state that only we used revised data from previous trials appropriately, and they have performed new analyses using different methods based on the numbers used in our study (2). All their new analyses reached statistical significance, and Vayssiere et al. conclude that that the STAN method reduces metabolic acidosis by one-third and conclude that it is beneficial. We reported a statistically significant difference (relative risk reduction 36%, absolute risk reduction 0.25%). The significance was lost when we used peto OR in combination with a randomeffect model rather than a fixed-effect model. We argued that the result should be interpreted with caution because metabolic acidosis is a surrogate endpoint with a questionable relation to harder outcomes and because we did not observe similar effects in other clinical outcomes. In addition, the statistically significant result disappeared when using another method, which underpins the need for caution. We have previously argued carefully for our view (2,5) and will not repeat the arguments here. Vayssiere et al. (1) state that metabolic acidosis is one of the best indicators available at birth for the immediate assessment – without providing any arguments as to why it makes metabolic acidosis a predictive indicator for adverse fetal outcomes in this setting. If they could provide studies showing good correlations between metabolic acidosis and adverse outcomes, it would be useful. No long-term outcomes, as cerebral palsy, are published from the randomized controlled trials using the STAN technology. After publishing our meta-analysis, we have experienced that supporters of STAN conclude that we used the most appropriate methods and the right data – but criticized us for our conclusions. They are unwilling to discuss the problem about use of surrogate outcomes and risk of bias (6,7), or the low absolute risk reduction of 0.25%. Based on data from six trials of good quality, with more than 26 000 women included, there is currently no evidence to conclude that STAN improves neonatal outcomes compared with CTG alone. We are now discussing whether small changes in numbers extracted from the primary studies or slightly different methods can change results and conclusions in the three recent meta-analyses. It is unlikely that future trials comparing STAN with CTG alone will be funded, and it is unlikely that evidence from observational studies can change the conclusions from the meta-analyses based on RCTs. It is time to consider whether the resources (human and economic) available can be used better to improve perinatal outcomes than just focusing on the STAN technology. Ellen Blix, Kjetil Gundro Brurberg, Eirik Reierth, Liv Merete Reinar and P al Øian Faculty of Health Sciences, Oslo and Akershus University College of Applied Sciences, Oslo, The Norwegian Knowledge Centre for the Health Services, Oslo, Centre for Evidence Based Practice, Bergen University College, Bergen, Science and Health Library, University Library, UiT The Arctic University of Norway, Tromsø, Department of Obstetrics and Gynecology, University Hospital of North Norway, Tromsø, and Department of Clinical Medicine, UiT The Arctic University of Norway, Tromsø, Norway