Universal third-trimester ultrasonic screening using fetal macrosomia in the prediction of adverse perinatal outcome: A systematic review and meta-analysis of diagnostic test accuracy.

BACKGROUND: The effectiveness of screening for macrosomia is not well established. One of the critical elements of an effective screening program is the diagnostic accuracy of a test at predicting the condition. The objective of this study is to investigate the diagnostic effectiveness of universal ultrasonic fetal biometry in predicting the delivery of a macrosomic infant, shoulder dystocia, and associated neonatal morbidity in low- and mixed-risk populations. METHODS AND
FINDINGS: We conducted a predefined literature search in Medline, Excerpta Medica database (EMBASE), the Cochrane library and ClinicalTrials.gov from inception to May 2020. No language restrictions were applied. We included studies where the ultrasound was performed as part of universal screening and those that included low- and mixed-risk pregnancies and excluded studies confined to high risk pregnancies. We used the estimated fetal weight (EFW) (multiple formulas and thresholds) and the abdominal circumference (AC) to define suspected large for gestational age (LGA). Adverse perinatal outcomes included macrosomia (multiple thresholds), shoulder dystocia, and other markers of neonatal morbidity. The risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Meta-analysis was carried out using the hierarchical summary receiver operating characteristic (ROC) and the bivariate logit-normal (Reitsma) models. We identified 41 studies that met our inclusion criteria involving 112,034 patients in total. These included 11 prospective cohort studies (N = 9986), one randomized controlled trial (RCT) (N = 367), and 29 retrospective cohort studies (N = 101,681). The quality of the studies was variable, and only three studies blinded the ultrasound findings to the clinicians. Both EFW >4,000 g (or 90th centile for the gestational age) and AC >36 cm (or 90th centile) had >50% sensitivity for predicting macrosomia (birthweight above 4,000 g or 90th centile) at birth with positive likelihood ratios (LRs) of 8.74 (95% confidence interval [CI] 6.84-11.17) and 7.56 (95% CI 5.85-9.77), respectively. There was significant heterogeneity at predicting macrosomia, which could reflect the different study designs, the characteristics of the included populations, and differences in the formulas used. An EFW >4,000 g (or 90th centile) had 22% sensitivity at predicting shoulder dystocia with a positive likelihood ratio of 2.12 (95% CI 1.34-3.35). There was insufficient data to analyze other markers of neonatal morbidity.
CONCLUSIONS: In this study, we found that suspected LGA is strongly predictive of the risk of delivering a large infant in low- and mixed-risk populations. However, it is only weakly (albeit statistically significantly) predictive of the risk of shoulder dystocia. There was insufficient data to analyze other markers of neonatal morbidity.

Introduction

Macrosomia is usually defined as birthweight >4,000 g or >90th centile for sex and gestational age. Macrosomic birth weight is associated with the risk of adverse outcomes, including perinatal death [1] and injuries related to traumatic delivery [2]. Ultrasonic estimated fetal weight (EFW) was first described in 1975 [3]. The equation for EFW that is in most widespread use was published by Hadlock and colleagues in 1985 [4], and the distribution of EFW in relation to week of gestation was published in 1991 [5]. Hence, the diagnostic tools to identify small for gestational age (SGA) and large for gestational age (LGA) fetuses have been available for many years. One of the main complications associated with macrosomia is shoulder dystocia, and a Cochrane review of four randomized controlled trials (RCTs) including 1,190 women demonstrated that routine induction of labor (IOL) for suspected LGA may prevent this outcome [6]. However, it remains unclear whether screening and intervention for suspected LGA results in better outcomes.

An RCT of IOL in women with an ultrasonically suspected LGA infant is in progress in the United Kingdom (The Big Baby trial, ISRCTN18229892). However, the women recruited to this trial will have been scanned because they were high risk for some reason, as the National Institute for Health and Care Excellence (NICE) has recommended that women should not be routinely scanned in late pregnancy [7]. Although the trial will confirm whether IOL is effective in high-risk women, it will not determine whether screening women without risk factors and intervening results in net benefit. It is often the case that screening and intervention programs that work well in high-risk groups do not work as well in low-risk populations, and one explanation for this can be that the screening test is less informative in low- and mixed-risk populations due to the lower prior risk of disease. In this study, we sought to quantify the diagnostic effectiveness of screening for fetal macrosomia and associated complications using universal ultrasonic fetal biometry in late pregnancy.

Methods

Sources

The protocol for this review was prospectively written and registered with PROSPERO (the International Prospective Register of Systematic Reviews), and the registration number was CRD42017064093. We searched the literature systematically using the Cochrane Database of Systematic Reviews (CDSR), Cochrane Central Register of Controlled Trials (CENTRAL), Medline, EMBASE, and ClinicalTrials.gov from inception to August 2019. An update search was done on May 28, 2020. We applied no restrictions on the language of the report or the location of the study. The studies were identified using a combination of words related to “ultrasound,” “pregnancy,” “estimated fetal weight,” “EFW,” “birthweight,” “macrosomia,” “large for gestational age,” “shoulder dystocia,” and “brachial plexus injury.” The exact search strategy is presented in S1 Text.

Study selection

We set out to include cohort studies where an ultrasound scan was performed ≥24 weeks’ gestation (wkGA), excluding multiple pregnancies. We included studies of low-risk populations, universal screening, and mixed-risk populations (i.e., included both high-risk and low-risk pregnancies). Studies that included only high-risk women, such as patients with preexisting or gestational diabetes, and those in which the ultrasound was performed during labor were excluded. Studies were not selected on the basis of the definition of the index test, i.e., the formula and the threshold used. Finally, we included both blinded and unblinded studies.

Index tests and outcomes

For the purposes of the meta-analysis, we defined suspected LGA as a fetus with an EFW >4,000 g or >90th centile or with an abdominal circumference (AC) >36 cm or >90th centile. However, we have also documented other thresholds used. The outcomes studied included macrosomic birth weight (>4,000 g or >90th centile) and severe macrosomic birth weight (>4,500 g or >97th centile); shoulder dystocia; and perinatal morbidity (neonatal unit admission, 5-minute Apgar score of six or less, metabolic acidosis, neonatal hypoglycaemia, and neonatal jaundice).

Quality assessment

Two authors (AAM and NS) independently performed the literature search, using the software package Review Manager 5.3. Any differences were addressed in consultation with the senior author (GCS). The Quality Assessment of Diagnostic Accuracy Studies (QUADAS 2) tool was used to assess the risk of biases, following the Cochrane Handbook of Diagnostic Test Accuracy Studies [8]. The QUADAS 2 tool was employed to assess potential biases in patient selection, index test, reference standard, and flow and timing. In relation to flow and timing, we assessed the risk from the perspective of universal ultrasound screening near term (i.e., around 36 wkGA). Flow and timing are based on the timing of the ultrasound scan, the timing of delivery, and the length of the interval between scan and delivery. A standardized data extraction form was employed to obtain information on the characteristics of the study (publication year, location, setting, study design, blinding), the participants (inclusion and exclusion rules and number, including inclusion or exclusion of women with diabetes, either preexisting or gestational), the index test (range of wkGA when the scan was conducted, the EFW equation employed, and the threshold for screen positive), reference standard (outcome, wkGA at delivery, and the scan-to-delivery interval).

Data extraction and synthesis

Sensitivity, specificity, positive and negative likelihood ratios (LRs) [9] were calculated from standard two-by-two tables, which had been extracted for each study by tabulating each of the different definitions of screen positive with each of the different outcomes studied. The “hierarchical summary receiver–operating characteristics” (HSROC) model of Rutter and Gatsonis [10] was utilized for data synthesis. This method allows the results of studies to be combined despite variation between studies in the threshold employed for screen positive. The bivariate logit-normal (Reitsma) model [11] was used to calculate average estimates of sensitivity and specificity and respective variances, at a specific threshold, in analyses in which data were available from at least four studies. We also used meta-analysis to obtain a summary of the diagnostic odds ratios (DORs) [12]. Publication bias was assessed using the Deeks’ funnel plot asymmetry test when data was available from a sufficient number of studies. Significant asymmetry was assumed at P < 0.05 [13]. Statistical analyses were performed using STATA version 14 (StataCorp LP, College Station, Texas), specifically, its METANDI, METAN, and MIDAS packages. Analysis and reporting was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (S1 PRISMA Checklist) [14].

Results

Study characteristics

Fig 1 is the literature search PRISMA flowchart. Out of 9,811 unique titles and 72 full paper reviews, we identified 41 studies [15-55] fulfilling the inclusion criteria, including a total of 112,034 participants. The study characteristics are presented in S1 Table. Six studies [18,27,33,36,37,52] (N = 53,935) included unselected pregnancies, nine [23,29,31-33,35,43,45,53,54] (N = 6,436) were confined to low-risk pregnancies, and 26 [15–17, 9–22,24–26,28,30,34,38–42,44,46–51,55] (N = 51,663) recruited pregnancies at mixed risk. The list of the excluded studies and the reasons for the exclusion are presented in S2 Table.

Fig 1

PRISMA flow diagram.

The risk of bias, as assessed by the QUADAS-2 tool, is summarized in Fig 2 and presented in detail in S1 Fig. The Galvin 2017 study [29] was published as an abstract; hence, we used a different study from the same cohort (GENESIS study) [56] to assess the risk of bias. Two of the included studies [51,52] have been authored by some of the coauthors of this paper. We used the same criteria for the quality assessment and analysis. Only three studies—Sovio 2018 [52] (Pregnancy Outcome Prediction study), Galvin 2017 [29] (GENESIS study), and Peregrine 2007 [47]—blinded the results to the clinicians. Hence, the large majority of studies were at risk of bias in relation to the reference standard. The second most common risk of bias was in relation to flow and timing, as six studies [19,24,36,39,47,55] performed the ultrasound either prior to IOL or less than 72 hours before delivery, resulting in a very short interval between the scan and delivery. Conversely, two studies [18,27] had a very long interval (ultrasound <33 wkGA). Two studies [17,20] did not present data on the gestational age at delivery. Finally, three studies [23,48,54] were confined to pregnancies progressing beyond 41 wkGA and were classified as having “high applicability concerns due to patient selection”.

Fig 2

Summary of bias assessment using the QUADAS-2 tool of the studies included in the meta-analysis.

QUADAS 2, Quality Assessment of Diagnostic Accuracy Studies.

Meta-analysis results

Full details of the summary diagnostic performance are presented in Table 1. In summary, both definitions of ultrasonically suspected macrosomia (i.e., either EFW >4,000 g or >90th percentile) had >50% sensitivity for predicting LGA at birth. Many associations were similar regardless of the formula employed, but the positive LRs for the Hadlock formulae (ranging between 7.5 and 12) tended to be higher than for the Shepard formula (around 5). The performance of definitions using just the AC was similar to using an ultrasonic EFW. The sensitivity for predicting severe macrosomia at birth of suspected LGA was around 70%. However, macrosomia (EFW >4,000 g or >90th centile) had a lower (22%) sensitivity for predicting shoulder dystocia, although the association was statistically significant and the positive LR was approximately 2.

Table 1

Summary diagnostic performance of suspected LGA to predict adverse perinatal outcome.

Diagnostic test	Studies	Patients	Summary sensitivity	Summary specificity	Positive LR(95% CI)	Negative LR(95% CI)
			(95% CI)	(95% CI)
Outcome: Birthweight >4,000 g (or 90th centile)
EFW (any) >4,000 g (or 90th centile)	30	80,045	53.2%	93.9%	8.74	0.50
			(47.2%–59.1%)	(91.9%–95.5%)	(6.84–11.17)	(0.44–0.56)
EFW (Hadlock-AC/FL/HC/BPD)	9	22,073	63.1%	94.3%	11.13	0.39
			(49.1%–75.2%)	(90.9%–96.5%)	(8.24–15.04)	(0.28–0.55)
EFW (Hadlock- AC/FL/BPD)	10	17,110	55.1%	92.9%	7.77	0.48
			(44.1%–65.7%)	(89.7%–95.2%)	(5.55–10.89)	(0.38–0.61)
EFW (Hadlock- AC/FL/HC)	7	60,648	55.2%	94.9%	11.84	0.47
			(45.7%–64.2%)	(92.4%–96.6%)	(7.46–15.74)	(0.39–0.58)
EFW (Hadlock- AC/FL)	9	16,736	60.5%	92.0%	7.54	0.43
			(50.7%–69.5%)	(89.4%–93.7%)	(6.13–9.29)	(0.34–0.54)
EFW (Hadlock- AC/BPD)	6	13,617	62.9%	93.7%	9.99	0.40
			(36.1%–83.5%)	(85.9%–97.3%)	(6.40–15.58)	(0.21–0.75)
EFW (Shepard)	7	14,060	73.7%	85.1%	4.96	0.31
			(54.4%–86.9%)	(76.5%–90.9%)	(3.29–7.48)	(0.17–0.56)
AC >36cm (or 90th centile)	5	10,543	57.8%	92.3%	7.56	0.46
			(39.6%–74.2%)	(88.7%–94.9%)	(5.85–9.77)	(0.30–0.68)
Outcome: Birthweight >4,500 g (or 97th centile)
EFW (any) >4,000 g (or 90th centile)	5	51,686	67.5%	89.7%	6.58	0.36
			(47.8%–82.6%)	(79.1%–95.3%)	(2.78–15.58)	(0.20–0.65)
Outcome: Shoulder dystocia
EFW (any) >4,000 g (or 90th centile)	6	26,264	22.0%	89.6%	2.12	0.87
			(9.9%–42.0%)	(80.8%–94.6%)	(1.34–3.35)	(0.74–1.02)

Abbreviations: AC, abdominal circumference; BPD, Biparietal diameter; CI, confidence interval; EFW, estimated fetal weight; FL, femur length; HC, head circumference; LR, likelihood ratio

Fig 3 has summary ROC curves for shoulder dystocia and macrosomia. For the prediction of macrosomia at birth, most of the large studies were close to the point estimate, and only a few small studies were outside the prediction intervals. For shoulder dystocia, most studies reported sensitivities below 30%, and only one study [55] reported a sensitivity of >50%. However, in this study, the total number of shoulder dystocia cases was very small (n = 3). Fig 4 and Fig 5 present graphs of the pooling of DORs for macrosomia and shoulder dystocia, respectively. There was significant heterogeneity for the prediction of macrosomia but not for the prediction of shoulder dystocia.

Fig 3

Summary ROC curves for the diagnostic performance of EFW >4,000 g (or 90th centile) at predicting (A) macrosomia at birth (birthweight above 4,000 g or above the 90th centile) and (B) shoulder dystocia. EFW, estimated fetal weight.

Fig 4

Diagnostic performance of EFW >4,000 g (or 90th centile) at predicting macrosomia at birth (birthweight above 4,000 g or above the 90th centile).

EFW, estimated fetal weight.

Fig 5

Diagnostic performance of EFW >4,000 g (or 90th centile) at predicting shoulder dystocia.

EFW, estimated fetal weight.

Only three studies—Crimmins 2018 [25], Galvin 2017 [29], and Sovio 2018 [52]—reported neonatal unit admission as an outcome, and a meta-analysis was not feasible. However, none of the studies reported statistically significant results with positive LRs of 0.73 (95% confidence interval [CI] 0.36–1.48), 1.39 (95% CI 0.97–2.00), and 1.33 (95% CI 0.80–2.22), respectively. Only the Sovio 2018 [52] study reported on 5-minute Apgar score of less than 7 and neonatal metabolic acidosis with positive LRs of 1.94 (95% CI 0.66–5.75) and 1.08 (95% CI 0.28–4.18), respectively. Moreover, the Sovio 2018 study was the only one that reported on neonatal hypoglycaemia and neonatal jaundice with positive LRs of 1.9 (95% CI 1.1–3.4) and 1.2 (95% CI 0.6–2.4), respectively.

The analysis demonstrated no significant evidence of publication bias (P = 0.57) when evaluated using Deeks’ funnel plot asymmetry test (S2 Fig).

Discussion

The main conclusion of this analysis is that an ultrasonic EFW indicating an increased risk of a large baby was strongly associated with delivering a macrosomic infant, but it was only weakly associated with the risk of shoulder dystocia. When the EFW was calculated using the widely employed Hadlock method, the positive LRs for macrosomia were in the region of 7 to 12, whereas they were approximately 2 in relation to the risk of shoulder dystocia.

This is the largest systematic review on the prediction of macrosomia and the only study that was focused on low- and mixed-risk populations from the perspective of using third-trimester ultrasound as routine screening in all pregnancies. We reported on multiple ultrasound markers and formulas. Moreover, we also reported on the prediction of shoulder dystocia, which is a major perinatal complication, the prevention of which would be a major aim of the routine ultrasound screening. The main limitation of this study is that there was significant heterogeneity between the studies in the ability to predict a macrosomic infant, as the forest plot of DORs indicates. The source of this heterogeneity is unclear, but it could relate to differences in the quality of the performance of the diagnostic test, such as the quality of the imaging equipment, the skill and training of sonographers, and the characteristics of the population. Finally, despite the large amount of studies included, only three studies [25, 29, 52] reported any outcomes of neonatal morbidity, and a meta-analysis was not feasible.

In the current study, we incorporated previously published data from the POP study (Sovio 2018) [52], which included nulliparous women who had a research scan at 36 wkGA, which was blinded in most cases to the clinicians. We found that the DOR (95% CI) from the POP study was very similar to the summary DOR derived from all of the other studies, which suggests that the results from the POP study are likely to be generalizable. The POP study was one of only a few identified that blinded the ultrasound result. Another blinded study, conducted in seven centers across Ireland between 2012 and 2015, the GENESIS study (Galvin 2017) [29], was a prospective cohort study of 2,772 nulliparous pregnant women. The results of the GENESIS study have only been published in conference proceedings [29] and include the outcome of shoulder dystocia but not macrosomia. Interestingly, neither the POP study nor the GENESIS study observed a statistically significant association between ultrasonic LGA and shoulder dystocia. When blinded and unblinded studies were combined, the meta-analysis demonstrated that ultrasound may be predictive of shoulder dystocia, albeit weakly. However, the associations observed in the other studies may be due to ascertainment bias. Specifically, if the fetus is suspected to be large on the basis of the EFW, the staff attending the delivery may have a lower threshold for using maneuvers for shoulder dystocia in the event of any delay. They may also be more likely to document a given delay as being due to shoulder dystocia. Hence, unblinded studies could result in stronger associations with shoulder dystocia through ascertainment bias. The fact that ultrasonic EFW is relatively poor as a predictor of shoulder dystocia is not unexpected, given that the actual birth weight of the baby is also not strongly predictive of the outcome: the majority of cases of shoulder dystocia involve a normal birth weight infant [57].

Finally, ultrasonic suspicion of a large baby is a clinical situation where there is evidence that knowledge of the scan result may itself cause complications. Multiple studies have demonstrated that women who have a false positive diagnosis of fetal macrosomia based on EFW are more likely to be delivered by emergency caesarean section [58,59]. This finding underlines the potential for harm caused by screening low-risk women. Research studies in which the results of the scan are revealed could lead to associations with adverse outcomes that were caused by an iatrogenic harm from a false positive result. Conversely, analysis of studies in which the scan was revealed may fail to show true associations with adverse outcome as knowledge of the scan result led to interventions that mitigated the risk.

We conclude that ultrasonically suspected LGA in the general population has quite good diagnostic effectiveness for macrosomic birth weight. However, it is not strongly predictive of the risk of associated complications, such as shoulder dystocia. Similar observations have been made in relation to ultrasonically suspected SGA [60, 61]. That study indicated that reduced fetal abdominal growth velocity helped discriminate between healthy SGA babies and those that were at increased risk of complications. Interestingly, the analogous finding is also true in LGA babies, in whom the combination of LGA and accelerated abdominal growth velocity was associated with the risk of neonatal morbidity [52]. We believe that future studies should address the other factors which help differentiate those suspected LGA fetuses which are at the greatest risk of complications.

PRISMA checklist.

(DOC)

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Literature search strategy for Medline and EMBASE (from inception to May 2020).

(DOCX)

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Characteristics of the studies included in the meta-analysis.

(DOCX)

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List of studies excluded from the meta-analysis and reason for exclusion.

(DOCX)

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Risk of bias assessment using the QUADAS 2 tool.

(TIFF)

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Deeks’ funnel plot asymmetry test.

(TIFF)

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15 Jan 2020

Dear Dr Smith,

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9 Apr 2020

Dear Gordon,

Thank you very much for submitting your manuscript "Universal third trimester ultrasonic screening using fetal macrosomia in the prediction of adverse perinatal outcome, a systematic review and meta-analysis of diagnostic test accuracy." (PMEDICINE-D-20-00081R1) for consideration at PLOS Medicine. Please accept my sincere apologies for the unusual delay in getting back to you about it. One of the reviewers was very late submitting.

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In light of these reviews, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

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Requests from the editors:

Title – Please insert a colon before the study descriptor in Universal third trimester ultrasonic screening using fetal macrosomia in the prediction of adverse perinatal outcome, a systematic review and meta-analysis of diagnostic test accuracy.

Abstract – please use p values, where possible, where 95%Cis are used (also elsewhere, as needed) and please add a sentence on the study’s limitations as the final sentence of the abstract

Thank you for providing the PRISMA checklist – please use sections and paragraphs instead of page numbers as these can change on formatting and revision.

Comments from the reviewers:

Reviewer #1: The study question (3rd trimester US screening for macrosomia) is a well-known, but not evidence based answered one. It is an important problem to the community of clinical obstetricians in the high- and middle-income countries.

The design and the mothodology of the study is well organized. The results are clearly written and the consequnezes for the day-to-day work of obstetrical clinicians and for future scientific study questions are mentioned.

The manuscript can be published without revision, may I ask for correction of some typing errors (like in the short running title marcosomia - macrosomia!).

Reviewer #2: See attachment

Michael Dewey

Reviewer #3: Overall: a well written paper: clear and concise, easy to read, clinically relevant.

Abstract: In the abstract there is a reference to ultrasound screening and breech. Why, this is not incorporated in the introduction, nor is a reference given. Seems a bit out of place.

The aim is clear and well defined. Moreover, the authors address an important clinical problem: can shoulder dystocia be predicted?.

I have only one concern. I miss information on the inclusion of just abstracts (i.e. non-peer reviewed studies) in this systematic review and meta-analysis (since the abstract of Galvin 2017 is included) . Did the authors check if study protocols were published in a registry or were authors contacted in order to assess the risk of bias? If authors are unable to share their protocol, their study should not included. Please add.

Any attachments provided with reviews can be seen via the following link:

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Submitted filename: moraitis.pdf

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1 May 2020

Submitted filename: PMEDICINE-D-20-0008R1- response to reviewers.docx

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27 May 2020

Dear Dr. Smith,

Thank you very much for re-submitting your manuscript "Universal third trimester ultrasonic screening using fetal macrosomia in the prediction of adverse perinatal outcome: a systematic review and meta-analysis of diagnostic test accuracy." (PMEDICINE-D-20-00081R2) for review by PLOS Medicine.

I have discussed the paper with my colleagues and the academic editor and it was also seen again by xxx reviewers. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.

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***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file.

Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. If you haven't already, we ask that you provide a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract.

We expect to receive your revised manuscript within 1 week. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

We ask every co-author listed on the manuscript to fill in a contributing author statement. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT.

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

If you have any questions in the meantime, please contact me or the journal staff on plosmedicine@plos.org.

We look forward to receiving the revised manuscript by Jun 03 2020 11:59PM.

Sincerely,

Adya Misra, PhD

Senior Editor

PLOS Medicine

plosmedicine.org

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Requests from Editors:

Please update your literature search to the end of April to ensure no recent publications have been missed.

Abstract

Please add a sentence, say, to the abstract to summarize the included studies - for example, quoting the range of study dates and categories of study design (e.g., X RCTs, Y cohort studies ...).

Please add a new final sentence to the "methods and findings" subsection of your abstract, to quote 2-3 of the study's main limitations.

In your abstract and throughout the paper, please add p values alongside 95% CI, where available

Author summary

Please rephrase level 1 evidence here as it may not be accessible to all readers. You may wish to include this as a second bullet point

Please rephrase lines 90-96 using more accessible language

Please break the first subsection of the "author summary" down into 2-3 individual points.

Introduction

Please can you add a space between text and reference brackets

References

Please format the bibliography in Vancouver style

Competing Interests- please add a sentence to note GS is an Academic Editor at PLOS Medicine

At line 70, please begin the sentence, "In this study, we found that ..." or similar.

Please refer to the attached PRISMA checklist in the methods section of your main text.

To the discussion section of your main text, please add a concise discussion of study strengths and limitations.

Please remove the funding and competing interest information from the end of the text (this will appear in the metadata in the event of publication, via the submission form).

Please avoid "P=0.000" in the figures.

Comments from Reviewers:

Reviewer #1: The revised paper is ready for publication.

Reviewer #2: The authors have addressed my points.

Michael Dewey

Any attachments provided with reviews can be seen via the following link:

[LINK]

9 Sep 2020

Dear Prof. Smith,

On behalf of my colleagues and the academic editor, Dr. Eva Pajkrt, I am delighted to inform you that your manuscript entitled "Universal third trimester ultrasonic screening using fetal macrosomia in the prediction of adverse perinatal outcome: a systematic review and meta-analysis of diagnostic test accuracy." (PMEDICINE-D-20-00081R3) has been accepted for publication in PLOS Medicine.

PRODUCTION PROCESS

Before publication you will see the copyedited word document (in around 1-2 weeks from now) and a PDF galley proof shortly after that. The copyeditor will be in touch shortly before sending you the copyedited Word document. We will make some revisions at the copyediting stage to conform to our general style, and for clarification. When you receive this version you should check and revise it very carefully, including figures, tables, references, and supporting information, because corrections at the next stage (proofs) will be strictly limited to (1) errors in author names or affiliations, (2) errors of scientific fact that would cause misunderstandings to readers, and (3) printer's (introduced) errors.

If you are likely to be away when either this document or the proof is sent, please ensure we have contact information of a second person, as we will need you to respond quickly at each point.

PRESS

A selection of our articles each week are press released by the journal. You will be contacted nearer the time if we are press releasing your article in order to approve the content and check the contact information for journalists is correct. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact.

PROFILE INFORMATION

Now that your manuscript has been accepted, please log into EM and update your profile. Go to https://www.editorialmanager.com/pmedicine, log in, and click on the "Update My Information" link at the top of the page. Please update your user information to ensure an efficient production and billing process.

Thank you again for submitting the manuscript to PLOS Medicine. We look forward to publishing it.

Best wishes,

Adya Misra, PhD

Senior Editor

PLOS Medicine

plosmedicine.org