
==== Front
Am J Physiol Heart Circ Physiol
Am J Physiol Heart Circ Physiol
AJPHEART
American Journal of Physiology - Heart and Circulatory Physiology
0363-6135
1522-1539
American Physiological Society Rockville, MD

38758122
H-00056-2024
H-00056-2024
10.1152/ajpheart.00056.2024
Review
cardiovascular-complications-of-pregnancyCardiovascular Complications of PregnancyReduced uterine perfusion pressure as a model for preeclampsia and fetal growth restriction in murine: a systematic review and meta-analysis
A SYSTEMATIC REVIEW AND META-ANALYSIS: MURINE RUPP MODEL
https://orcid.org/0000-0001-8454-3851
van Kammen Caren M. 1
Taal Seija E. L. 2
Wever Kimberley E. 3
Granger Joey P. 4
Lely A. Titia 2
https://orcid.org/0000-0002-6587-1320
Terstappen Fieke 2
1Division of Nanomedicine, Department CDL Research, https://ror.org/0575yy874 University Medical Center Utrecht , Utrecht, The Netherlands
2Department of Woman and Baby, University Medical Center Utrecht , Wilhelmina Children’s Hospital, Utrecht, The Netherlands
3Department of Anesthesiology, Pain, and Palliative Medicine, Radboud University Medical Center , Nijmegen, The Netherlands
4Department of Physiology and Biophysics, Cardiovascular-Renal Research Center, University of Mississippi Medical Center , Jackson, Mississippi, United States
Correspondence: C. M. van Kammen (c.m.vankammen@umcutrecht.nl).
1 7 2024
17 5 2024
17 5 2024
327 1 H89H107
31 1 2024
6 5 2024
7 5 2024
Copyright © 2024 The Authors.
2024
The Authors.
https://creativecommons.org/licenses/by/4.0/ Licensed under Creative Commons Attribution CC-BY 4.0. Published by the American Physiological Society.

The reduced uterine perfusion pressure (RUPP) model is frequently used to study preeclampsia and fetal growth restriction. An improved understanding of influential factors might improve reproducibility and reduce animal use considering the variability in RUPP phenotype. We performed a systematic review and meta-analysis by searching Medline and Embase (until 28 March, 2023) for RUPP studies in murine. Primary outcomes included maternal blood pressure (BP) or proteinuria, fetal weight or crown-rump length, fetal reabsorptions, or antiangiogenic factors. We aimed to identify influential factors by meta-regression analysis. We included 155 studies. Our meta-analysis showed that the RUPP procedure results in significantly higher BP (MD = 24.1 mmHg; [22.6; 25.7]; n = 148), proteinuria (SMD = 2.3; [0.9; 3.8]; n = 28), fetal reabsorptions (MD = 50.4%; [45.5; 55.2]; n = 42), circulating soluble FMS-like tyrosine kinase-1 (sFlt-1) (SMD = 2.6; [1.7; 3.4]; n = 34), and lower fetal weight (MD = −0.4 g; [−0.47; −0.34]; n = 113. The heterogeneity (variability between studies) in primary outcomes appeared ≥90%. Our meta-regression identified influential factors in the method and time point of BP measurement, randomization in fetal weight, and type of control group in sFlt-1. The RUPP is a robust model considering the evident differences in maternal and fetal outcomes. The high heterogeneity reflects the observed variability in phenotype. Because of underreporting, we observed reporting bias and a high risk of bias. We recommend standardizing study design by optimal time point and method chosen for readout measures to limit the variability. This contributes to improved reproducibility and thereby eventually improves the translational value of the RUPP model.

fetal growth restriction
; placental insufficiency
; preeclampsia
pregnancy
; reduced uterine perfusion pressure
; ZonMw (Netherlands Organisation for Health Research and Development) 10.13039/501100001826 40-42600-98-476 Joey P. GrangerCall for PapersTrue
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pmcINTRODUCTION

Cardiovascular disease (CVD) is the primary cause of maternal deaths during pregnancy, with mounting evidence suggesting a significant link between pregnancy complications and the later development of CVD (1–3). Preeclampsia (PE) and fetal growth restriction (FGR) are such cardiovascular pregnancy complications that majorly impact maternal and fetal morbidity and mortality. Placental insufficiency forms the common etiology of these complex syndromes. Currently, there is no treatment available for this multifactorial disease. The search for a safe and effective therapy for this cardiovascular complication during pregnancy requires the use of animal models.

A commonly used animal model to understand the pathophysiology of PE and FGR is the reduced uterine perfusion pressure (RUPP) (Fig. 1), a surgical model introduced by Granger et al. in 2006 (4), as a modification of the preexisting model by Eder and McDonald in 1987 (5). The induction occurs by placing a clip around a pregnant rat’s abdominal aorta, below the renal arteries, during early to midgestation. The placement of a clip on the right and left ovarian arteries at the uterine arcade just before the first segmental artery prevents an adaptive increase in uterine blood flow via the ovarian artery. Most studies applied the RUPP model in rats, but the procedure has also been adapted for several other species including mice, dogs, rabbits, sheep, and primates. The rat model mimics many of the prominent human characteristics of PE and FGR secondary to placental ischemia including proteinuria, endothelial dysfunction, hypertension in the mother, and restricted growth in the fetus (6). Furthermore, recent research shows the presence of cardiovascular and metabolic remodeling of the maternal and fetal heart (7–9). This suggests a strong association between preeclampsia and cardiovascular disease.

Figure 1. Schematic overview of reduced uterine perfusion pressure model. A surgical model induced in most cases (*) placing a clip (as illustrated in the picture) or a ligature around the abdominal aorta of a pregnant mouse or rat, below the renal arteries, during early to midgestation. The placement of a clip or ligature on the right and left ovarian arteries at the uterine arcade just before the first segmental artery prevents an adaptive increase in uterine blood flow via the ovarian artery.

Murine (rats and mice) subjected to RUPP appears to have a variable degree of severity in the manifestation of PE/FGR phenotype. Multiple study characteristics potentially influence the response to RUPP. The extent to which these variables influence the severity of PE and FGR remains uncertain. The years of experience with the RUPP model in mainly rats have yielded an abundance of data that allow the identification of influential factors.

Accordingly, this systematic review and meta-analysis aimed to assess the impact of animal characteristics and methodological differences of the RUPP model on the preeclamptic and fetal growth-restricted phenotype. This may offer a perspective of influential factors on the heterogeneity (variability between studies) in phenotypical outcome and quality of published studies which could assist in optimizing the RUPP model and experimental design of future studies and thereby eventually improve the translational value of the RUPP model. Primary outcomes consist of maternal mean blood pressure or proteinuria, fetal weight or crown-rump length, and percentage of fetal reabsorptions; secondary outcome entails the level of the circulating soluble FMS-like tyrosine kinase-1 (sFlt-1) as the most studied antiangiogenic factor in PE. Furthermore, we set out to analyze influential factors by subgroup analysis, including species, strain, age, pairing details, method and time point of measurements, anesthesia during surgery and measurements, and the type of control group in the RUPP model.

MATERIALS AND METHODS

Study Protocol

This systematic review is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (Supplemental Table S1). Before starting, we registered a review protocol for animal studies on PROSPERO (CRD42022335776). Key elements of this protocol on PROSPERO are described in the following paragraphs. The few amendments (Supplemental Table S2) to the preregistered protocol are reported in the Supplemental Data and referred to as post hoc analyses.

Data Source and Search Strategy

On March 28, 2023, we performed a systematic literature search in the databases “Embase” and “Medline” through Ovid to identify studies using the RUPP model in murine which also reported on phenotypical outcomes of the preeclampsia and fetal growth restriction. No restrictions on language or publication date were applied (Supplemental Table S3). Search results were deduplicated using Rayyan (https://www.rayyan.ai/).

Study Selection: Inclusion and Exclusion Criteria

Two independent researchers (Cv.K. and S.T.) screened the retrieved studies using Rayyan. Screening for eligibility was first performed based on title and abstract, followed by screening for final inclusion based on full text. In case of disagreement, a third independent investigator was consulted (K.W.). Studies were considered eligible when all of the following inclusion criteria applied: 1) the study was a primary animal study; 2) the study used the species of interest (rats or mice); 3) the RUPP model was applied; 4) a relevant control group was used; 5) at least one of the outcome measures was reported: namely, maternal blood pressure (BP), proteinuria, percentage of fetal reabsorptions, fetal weight, fetal crown-to-rump length, and levels of circulating antiangiogenic factors. We defined the RUPP model as surgical induction by partially clamping both the abdominal aorta and the two ovarian arteries; other strategies of induction were excluded. We excluded publications that lacked original data (e.g., conference abstracts and reviews), as well as studies using genetically modified animals and those lacking an untreated control group and/or untreated RUPP group.

Data Extraction

Two independent reviewers (Cv.K. and S.T.) extracted data in duplicate on subject characteristics (including species, strain, dam age, pairing, and time point of induction of RUPP), study design (including randomization, experimental unit fetus or dam, number of animals per group, number of animals per assay), method and timing of measurements. Our primary outcomes were maternal blood pressure (MAP, systolic BP, and diastolic BP), proteinuria, the percentage of fetal reabsorptions, fetal weight, and fetal crown-to-rump length. In addition, we extracted data on levels of circulating antiangiogenic factors as a secondary outcome. When outcome data were only presented in figures, we extracted them using a digital tool (http://automeris.io/WebPlotDigitizer/). For each outcome, we extracted means (SD) and number of subjects per experimental group.

Assessment of Risk of Bias and Study Quality

Two reviewers (Cv.K. and S.T.) independently assessed the risk of bias for each included study, using SYRCLE’s risk of bias tool for animal studies (10). Both reviewers resolved discrepancies through discussion. If no consensus could be achieved, a third researcher (F.T.) served in two cases as an arbiter.

Data Synthesis

Meta-analysis was performed when the prespecified required minimum of 20 studies was reached for an outcome, using the online R software (https://posit.co/cloud) with the meta and metafor package (v.4.2-0, Auckland, New Zealand). Meta-analysis methodology was performed according to gold-standard guidelines (11, 12). The mean difference (MD) and 95% confidence intervals (CIs) were calculated to compare the blood pressure in mmHg, fetal weight in grams, and fetal reabsorptions in percentage between control and RUPP groups. For blood pressure analysis, we used MAP and when not available SBP was used, a post hoc sensitivity analysis was performed to justify the pooling of the MAP and SBP.

The percentage of reabsorptions in some studies needed to be calculated from, e.g., the difference in litter size between gestational day (GD) 14 and GD19, or from the survival rate. In such cases, no SD could be recalculated because of the lack of individual data points. We therefore calculated the mean SD of all other comparisons and imputed this in the aforementioned cases. We assessed the robustness of this method by performing a post hoc sensitivity analysis in which all comparisons with an imputed SD were omitted from the analysis. Proteinuria and circulating antiangiogenic factor were synthesized using the standardized mean difference (SMD [95% CI]) to correct for the use of different units of measurements and assay kits.

When studies measured on multiple time points, we extracted all the measurements but eventually included only the most frequently reported time point for the outcome in the meta-analysis. In addition, a post hoc analysis of the type of control [sham vs. normal pregnant (NP)] was performed. For studies that used both NP and sham animals as control groups, only the sham group was included in the meta-analysis. In four rat studies, a correction of plug control in outcome measures was applied, i.e., the vaginal plug confirmation was reported as GD1 instead of GD0 or 0.5 and thereby extrapolating that the measurement also occurred a day earlier than described. In fetal weight analysis, we excluded studies using the individual fetus as the unit of analysis instead of the litter (n = 4).

To investigate potential sources of heterogeneity (stratified), meta-regression was performed on predefined subgrouping variables, provided that at least two subgroup categories contained at least 10 studies. The variables considered were (as per protocol) species (mice vs. rat); strain (Sprague–Dawley rat vs. Wistar rat vs. balb/c mouse vs. C57bl6 mouse vs. other); dam age [early young adults 8–10 wk vs. young adult 11–13 wk (i.e., at the plateau phase of their growth curve) vs. later age]; parity (primiparous vs. multiparous); time point of RUPP (early mouse GD <13 vs. standard 13 vs. late > 13); (early rat GD <14 vs. standard 14 vs. late > 14); method of blood pressure measurement [conscious restrained vs. conscious free (telemetry) vs. under anesthesia]; method of proteinuria measurement (spot vs. 24 h continuous measurement); time point of measurement at the gestational day of pregnancy (using in linear regression), and randomization (randomization vs. not reported vs. not randomized).

To account for expected between-study heterogeneity, a random effects model was used. A two-sided P value < 0.05 was considered significant for all overall analyses. For subgroup analysis, this significance level was adjusted for multiple comparisons using the Bonferroni–Holmes correction. To quantify the degree of heterogeneity across the included studies, the I2 statistic was used. The I2 statistic describes the degree of heterogeneity across studies in the outcome of the RUPP animal model, with the absence of heterogeneity being defined as 0%, whereas we declare >0–50, >50, and >80% as indicators of low, moderate, and high degrees of heterogeneity, respectively. Publication bias was investigated for each outcome reported in ≥20 studies, using visual inspection of funnel plots and Egger’s regression.

RESULTS

Study Selection and Overall Study Characteristics

The search yielded a total of 2,071 studies after duplicate removal (Fig. 2). The majority of the exclusions (n = 376) after title and abstract screening were based on the use of a different animal model, or the record not being a primary animal study. Our analysis after full-text screening incorporated a total of 155 studies reporting relevant outcomes in the RUPP model. We performed meta-analyses on maternal blood pressure (BP), proteinuria, percentage of fetal reabsorptions, fetal weight (FW), and levels of circulating sFlt-1 as an antiangiogenic factor (Table 1). Data extraction per outcome is reported in a Supplemental Excel overview E1. The number of studies reporting fetal crown-to-rump length and other antiangiogenic factors did not meet the prespecified threshold of 20 studies required for meta-analysis.

Figure 2. Flowchart of identification and selection process according to Preferred Reporting Items for systematic reviews and Meta-Analyses (PRISMA). The search strategy retrieved 2,071 unique hits via Embase and MEDLINE using OVID, of which we included 155 studies reporting relevant outcomes in the reduced uterine perfusion pressure (RUPP) model.

Table 1. Overview of reported outcomes per included study using the RUPP model

Author (et al.), Year (Ref. No.)	Species, Strain	Type of Control	Maternal BP	Maternal Proteinuria	Fetal Reabsorptions	Fetal Weight	Circulating sFlt-1	
Akhaphong, 2018 (13)	Rat, Sd	Sham	✓	–	✓	✓1	–	
Alexander, 2001 (14)	Rat, Sd	Sham	✓	–		✓	–	
Alexander, 2001 (15)	Rat, Sd	NP	✓	–	–	✓	–	
Alexander, 2001 (16)	Rat, Sd	Sham	✓	✓	–	–	–	
Alexander, 2004 (17)	Rat, Sd	Sham	✓	–	–	✓	–	
Amaral, 2013 (18)	Rat, Wistar	Sham	✓	–	–	–	–	
Amaral, 2015 (19)	Rat, Sd	NP	✓	–	–	✓	–	
Amaral, 2017 (20)	Rat, Sd	NP	✓	–	–	✓	✓	
Anderson, 2005 (21)	Rat, Sd	Sham	✓	–	–	✓	–	
Ashraf, 2022 (22)	Rat, Sd	Sham	–	–	✓	✓	–	
Bakrania, 2019 (23)	Rat, Sd	Sham	✓	–	–		✓	
Balta, 2011 (24)	Rat, Sd	Sham	✓	✓	–	✓	–	
Gilbert, 2012 (25)	Rat, Sd	NP	✓	–	–	✓	✓	
Banek, 2013 (26)	Rat, Sd	NP and Sham2	✓	–	✓	✓	✓	
Barron, 2001 (27)	Rat, Sd	Sham	✓	–	–	–	–	
Bauer, 2013 (28)	Rat, Sd	Sham	✓	–	–	✓	✓	
Brennan, 2016 (29)	Rat, Sd	Sham	✓	–	–	✓	–	
Chang, 2005 (30)	Rat, Sd	Sham	✓	–	–	✓	–	
Chatre, 2022 (31)	Rat, Sd	Sham	✓	–	–	✓3	–	
Chen, 2008 (32)	Rat, Sd	Sham		–	–	✓	–	
Chen, 2017 (33)	Rat, Sd	Sham	✓	–	–	✓	–	
Chen, 2019 (34)	Rat, Sd	NP	✓	–	–	✓	–	
Coats, 2021 (35)	Rat, Sd	Sham	–	–	–	✓4	–	
Coats, 2021 (36)	Rat, Sd	Sham	–	–	✓	✓	–	
Cornelius, 2013 (37)	Rat, Sd	NP	✓	–	–	✓	–	
Cornelius, 2015 (38)	Rat, Sd	NP	✓	–	–	✓	–	
Cornelius, 2016 (39)	Rat, Sd	NP	✓	–	–	✓	–	
Cottrell, 2019 (40)	Rat, Sd	NP	✓	–	–	✓	–	
Cottrell, 2021 (41)	Rat, Sd	NP	✓	–	–	✓	–	
Crews, 2000 (42)	Rat, Sd	Sham	✓	–	–	–	–	
Cunningham, 2018 (43)	Rat, Sd	NP	✓	–	–	✓	✓	
Cunningham, 2020 (44)	Rat, Sd	NP	✓	–	–	✓	–	
Cunningham, 2021 (45)	Rat, Sd	NP	✓	–	✓	✓	–	
Darby, 2013 (46)	Rat, Sd	NP	✓	–	–	–	–	
Deer, 2021 (47)	Rat, Sd	NP	✓	–	–	✓	–	
Deer, 2021 (48)	Rat, Sd	NP	✓	–	✓	✓	–	
Deng, 2022 (49)	Rat, Sd	Sham	✓	✓	✓	–	✓	
Dias-Junior, 2017 (50)	Rat, Sd	Sham	✓	–	–	✓	✓	
Ding, 2018 (51)	Rat, Sd	Sham	✓	–	–	–	–	
Duncan, 2020 (52)	Rat, Sd	NP	✓	–	–	–	–	
Eddy, 2020 (53)	Rat, Sd	Sham	✓	–	✓	✓	–	
Elfarra, 2017 (54)	Rat, Sd	NP	✓	–	–	✓	–	
Elfarra, 2020 (55)	Rat, Sd	NP and Sham1	✓	–	–	✓	–	
El-Saka, 2019 (56)	Rat, Wistar	Sham	✓	✓	–	✓	✓	
Cristóvão Escouto, 2018 (57)	Rat, Wistar	NP	✓	–	–	–	–	
Faulkner, 2016 (58)	Rat, Sd	NP	✓	–	✓	✓	✓	
Faulkner, 2018 (59)	Rat, Sd	NP	✓	–	–	–	–	
Fraser, 2015 (60)	Rat, Sd	Sham	✓	–	–	–	–	
Gadonski, 2006 (61)	Rat, Sd	NP	✓	–	–	–	–	
George, 2011 (62)	Rat, Sd	NP	✓	–	–	✓	✓	
George, 2013 (63)	Rat, Sd	NP	✓	–	–	✓	–	
George, 2014 (64)	Rat, Sd	Sham	✓	–	–	✓	–	
Giambrone, 2019 (65)	Rat, Sd	Sham	✓	–	–	✓	–	
Giardina, 2002 (66)	Rat, Sd	Sham	✓	–	–	–	–	
Gilbert, 2007 (67)	Rat, Sd	NP	✓	–	–	✓3	–	
Gilbert, 2007 (68)	Rat, Sd	NP	✓	–	✓	✓	✓	
Gilbert, 2009 (69)	Rat, Sd	NP	✓	–	–	✓	–	
Gilbert, 2010 (70)	Rat, Sd	NP	✓	–	–	✓	✓	
Gilbert, 2012 (71)	Rat, Sd	Sham	✓	–	–	✓	–	
Gilbert, 2012 (25)	Rat, Sd	Sham	✓	–	–	✓	–	
Gutkowska, 2011 (72)	Rat, Sd	NP	✓	–	–	–	–	
Haase, 2020 (73)	Rat, Sd	Sham	✓	✓	–	✓	–	
Han, 2018 (74)	Rat, Sd	Sham	✓	–	–	✓	✓	
Harmon, 2015 (75)	Rat, Sd	NP	✓	–	–	✓	–	
Hassanzadeh-Taheri, 2022 (76)	Rat, Wistar	Sham	✓	✓	–	✓5	–	
Heltemes, 2010 (77)	Rat, Sd	NP	✓	–	–	✓	–	
Herrock, 2023 (78)	Rat, Sd	NP	✓	–	✓	✓	–	
Herrock, 2023 (79)	Rat, Sd	NP	✓	–	–	✓	–	
Herse, 2012 (80)	Rat, Sd	NP	✓	–	–	✓	–	
Hines, 2007 (81)	Rat, Sd	Sham	✓	–	✓	–	–	
Huang, 2021 (82)	Rat, Sd	Sham	✓	–	–	✓	✓	
Ibrahim, 2017 (83)	Rat, Sd	NP	✓	–	–	✓	–	
Intapad, 2014 (84)	Mouse, C57BL/6J	Sham	✓	✓	✓	✓	✓	
Isler, 2003 (85)	Rat, Sd	Sham	✓	–	–	✓	–	
Issotina Zibrila, 2021 (86)	Rat, Sd	Sham	✓	✓	–	–	–	
Issotina Zibrila, 2021 (87)	Rat, Sd	Sham	✓	✓	✓	✓	–	
Javadian, 2013 (88)	Rat, Sd	Sham	✓	✓	–	✓	–	
Joyner, 2007 (89)	Rat, Sd	Sham	✓	✓	–	✓4	–	
Kiprono, 2013 (90)	Rat, Sd	NP	✓	–	✓	✓	–	
LaMarca, 2005 (91)	Rat, Sd	NP	✓	–	–	–	–	
LaMarca, 2008 (92)	Rat, Sd	NP	✓	–	–	–	–	
LaMarca, 2008 (93)	Rat, Sd	NP	✓	–	–	✓	–	
Lamarca, 2011 (94)	Rat, Sd	NP	✓	–	–	✓	–	
Laule, 2017 (95)	Rat, Sd	Sham	✓	–	✓	✓	–	
Laule, 2019 (96)	Rat, Sd	Sham	✓	–	–	✓	–	
Lawrence, 2019 (97)	Rat, Sd	Sham	✓	✓	–	✓	–	
Lawrence, 2022 (98)	Rat, Sd	NP	✓	✓	–	–	–	
Li, 2017 (99)	Rat, Sd	Sham	✓	–	–	✓	–	
Lillegard, 2013 (100)	Rat, Sd	Sham	✓	–	✓	–	✓	
Lillegard, 2014 (101)	Rat, Sd	Sham	✓	–	✓	✓	–	
Lin, 2020 (102)	Rat, Sd	Sham	✓	–	–	✓	–	
Liu, 2022 (103)	Rat, Sd	NP and Sham1	✓	✓	–	✓	✓	
Llinás, 2002 (104)	Rat, Sd	NP	✓	–	–	–	–	
Alexander, 2004 (17)	Rat, Sd	Sham	✓	–	–	–	–	
Logue, 2017 (105)	Rat, Sd	Sham	✓	✓	✓	✓	✓	
Ma, 2017 (106)	Rat, Sd	Sham	✓	✓	–	–	✓	
Porcello Marrone, 2014 (107)	Rat, Wistar	NP	✓	–	–	–	–	
Mazzuca, 2014 (108)	Rat, Sd	Sham	✓	–	–	✓	–	
Mazzuca, 2023 (109)	Rat, Sd	Sham	✓	–	–	–	–	
McCarthy, 2011 (110)	Rat, Sd	NP	✓	✓	–	✓	✓	
Moore, 2003 (111)	Rat, Sd	Sham	–	–	–	✓	–	
Morton, 2012 (112)	Rat, Sd	Sham	✓	–	–	✓	–	
Morton, 2015 (113)	Rat, Sd	Sham	✓	–	–	✓	–	
Morton, 2019 (114)	Rat, Sd	Sham	✓	✓	✓	✓4	–	
Murphy, 2015 (115)	Rat, Sd	Sham	✓	–	–	–	✓	
Neves, 2008 (116)	Rat, Sd	Sham	✓	✓	✓	✓4	–	
Novotny, 2012 (117)	Rat, Sd	NP	✓	–	–	✓	–	
Novotny, 2013 (118)	Rat, Sd	NP	✓	–	–	✓	–	
Ojeda, 2016 (119)	Rat, Sd	NP	–	–	–	✓	–	
Ou, 2020 (120)	Rat, Wistar	NP and Sham1	✓	–	–	–	–	
Paauw, 2017 (121)	Rat, Sd	NP	✓	✓	✓	✓	✓	
Palei, 2021 (122)	Rat, Sd	NP	✓		✓	✓	–	
Pang, 2023 (123)	Rat, unknown	NP	✓	–	–	–	–	
Ramirez, 2011 (124)	Rat, Sd	NP	✓	–	✓	✓	–	
Regal, 2016 (125)	Rat, Sd	NP	✓	–	–	✓	–	
Laule, 2017 (95)	Rat, Sd	NP	✓	–	✓	✓	–	
Regal, 2019 (126)	Rat, Sd	NP	✓	–	–	✓	–	
Reho, 2011 (127)	Rat, Sd	NP	✓	–	✓	✓	–	
Ren, 2018 (128)	Rat, Sd	NP	✓	–	–	✓	✓	
Ren, 2021 (129)	Rat, Sd	NP	✓	–	–	✓	–	
Richards, 2021 (8)	Rat, Sd	NP	✓	–	✓	✓	–	
Ryan, 2011 (130)	Rat, Sd	NP	✓	–	–	–	–	
Santiago-Font, 2016 (131)	Rat, Sd	NP	✓	–	–	✓	✓	
Sedeek, 2008 (132)	Rat, Sd	Sham	✓	–	–	✓	–	
Sholook, 2007 (133)	Rat, Sd	Sham	✓	–	–	–	–	
Spradley, 2016 (134)	Rat, Sd	NP	✓	–	✓	✓	✓	
Spradley, 2018 (135)	Rat, Wistar	Sham	✓	–	✓	✓	–	
Spradley, 2019 (136)	Rat, Sd	Sham	✓	–	✓	✓	–	
Sun, 2020 (137)	Rat, Sd	Sham	✓	–	✓	✓3	✓	
Tam, 2011 (138)	Rat, Sd	NP	✓	–	✓	✓	–	
Tian, 2016 (139)	Rat, Sd	Sham	✓	✓	✓	✓	–	
Travis, 2020 (140)	Rat, Sd	NP	✓	–	✓	✓	✓	
Travis, 2021 (141)	Rat, Sd	Sham	✓	–	–	✓ 4	✓	
Travis, 2021 (142)	Rat, Sd	NP	✓	–	✓	✓	✓	
Travis, 2021 (143)	Rat, Sd	Sham	✓	–	✓	✓	✓	
Ushida, 2016 (144)	Rat, Sd	Sham	✓	✓	✓	✓3	✓	
Vaka, 2018 (145)	Rat, Sd	NP	✓	–	–	✓	–	
Vaka, 2019 (146)	Rat, Sd	NP	✓	–	–	–	–	
Veillon, 2009 (147)	Rat, Sd	NP	✓	–	–	✓	–	
Walsh, 2009 (148)	Rat, Sd	NP and Sham1	✓	–	–	✓	–	
Walsh, 2012 (149)	Rat, Sd	NP	✓	–	–	✓	–	
Wang, 2017 (33)	Rat, Sd	Sham	✓	✓	–	–	–	
Wang, 2023 (150)	Rat, Sd	Sham	✓	–	✓	✓	–	
Warrington, 2015 (151)	Rat, Sd	NP	✓	–	–	–	–	
Li, 2014 (152)	Rat, Sd	Sham	✓	–	–	✓	–	
Wei, 2021 (153)	Mouse, C57BL/6J	Sham	✓	–	–	–	–	
Williamson, 2020 (154)	Rat, Sd	Sham	✓	✓	–	✓	✓	
Yang, 2019 (155)	Rat, Sd	Sham	✓	✓	–	✓	–	
Yang, 2023 (156)	Mouse, BALB/c	Sham	✓	✓	✓	–	✓	
Younes, 2020 (157)	Rat, Sd	Sham	✓	–	✓	✓4	–	
Zhang, 2016 (158)	Rat, Sd	NP	✓	–	✓	✓	–	
Zhang, 2020 (159)	Rat, Sd	Sham	✓	✓	–	–	–	
Zhang, 2021 (160)	Rat, Sd	Sham	✓	–	–	–	–	
Zhang, 2022 (161)	Rat, Sd	N/S	–	–	–	✓	–	
Zheng, 2022 (162)	Rat, Sd	Sham	✓	✓	✓	✓	–	
Main study characteristics and reported outcomes of included studies in alphabetical order. BP, blood pressure; Sd, Sprague-Dawley; NP, normal pregnant; N/S, not specified; sFlt-1, soluble FMS-like tyrosine kinase-1; RUPP, reduced uterine perfusion pressure. 1Sex differences were pooled for meta-analysis. 3Reporting fetus as experimental unit data, not included in the meta-analysis. 2In the case of reporting both NP and sham as a control group in one study, we only used the sham data in meta-analysis. 4Authors also conducted measurements on fetal crown-to-rump length; however, because of the limited number of studies available, we were unable to perform a meta-analysis. 5Data were exclusively presented in Hassanzadeh-Taheri et al. (76), Fig. 2, as we did not have the capability to measure individual data points; consequently, these data were not included in the meta-analysis.

Animal and Study Characteristics

In the 155 included studies, a comparison was made between the experimental group exposed to RUPP surgery versus the NP group (n = 70) or undergoing sham surgery (n = 80) (Supplemental Excel overview E1). Five studies used both NP and sham as a control group. Most studies used Sprague Dawley rats (Sd) (n = 145) and only a few used Wistar rats (n = 7), C57BL/6 mice (n = 2), or balb/c mice (n = 1). The median maternal age at the day of delivery for both rats and mice was 12 wk (range, 6– 16 wk; reported in n = 45). The median body weight in rats was 238 g (range, 180–312 g; reported in n = 34) and for mice, one study reported body weight (range, 18–22 g; reported in n = 1). In both species, the median age at day of surgery (reported in n = 6) lies at 12 wk (range, 9–22 wk). On the day of surgery, the median body weight reported was 225 g in rats (range, 220–362 g; reported in n = 18). Only a few studies (n = 16) described details on parity.

Surgery Characteristics

The majority of RUPP surgeries were performed on GD14 (n = 137) in the rat studies (n = 152) and GD13 in two of the three mice studies (Supplemental Excel overview E1). In the four rat studies that reported vaginal plug conformation as GD1 instead of GD0, the RUPP surgery was corrected to GD13 instead of the reported GD14. Mainly, isoflurane (n = 126) was used as an anesthetic during the surgery, with other types of used anesthesia being chloral hydrate 10% (n = 2), ketamine and xylazine (n = 3), pentobarbital (n = 2), or unknown (n = 23). The RUPP model was mostly induced by placing a silver clip around the lower abdominal aorta and the ovarian arteries (n = 142). Still, others used surgical clips (no material described, n = 3), plastic clips (n = 1), silk sutures (n = 10), or did not report induction method (n = 2). The diameter of the restriction was reported in 146 studies with the used clip or suture inner diameter (ID) in mm. Predominantly, an ID of 0.203-mm abdominal aorta clip in rats was used and 0.100-mm clip for ovarian arteries, other IDs ranged from 0.023 to 0.33 mm for abdominal aorta and 0.06 mm to 0.33 for ovarian arteries. In two of the three mice studies, an abdominal aorta clip of ID 0.1 mm and ovarian arteries clips of 0.05 mm were used. After surgery, follow-up time ranged from 8 h to 5 days, with mainly the outcome end point on GD19 (range, GD17 and GD22) or delivery of pups for fetal growth restriction follow-up.

Meta-Analysis and Meta-Regression per Outcome

Overall, our meta-analysis showed increased maternal blood pressure (BP), proteinuria, fetal reabsorptions, circulating sFlt-1, and a decrease in fetal weight per litter in RUPP compared with control (Table 2). We will discuss these results in more detail per outcome (see Maternal blood pressure, Maternal proteinuria, Percentage of fetal reabsortions, Fetal growth restriction, and Circulating sFlt-1).

Table 2. Overall effect of performed meta-analysis of included studies using the RUPP model

	No. Comp	Pooled Estimate (MD/SMD)	95% CI	I2, %	P Value	Egger’s Regression P Value	
Maternal blood pressure, mmHg	148	24.1 MD	[22.6; 25.7]	92	<0.0001	0.11	
Proteinuria	28	2.3 SMD	[0.9; 3.8]	92	<0.0021	0.54	
Fetal reabsorptions (%)1	42	50.4 MD	[45.5; 55.2]	92	<0.0001	0.27	
Fetal weight, g	113	−0.4 MD	[−0.47; −0.34]	90	<0.0001	0.0032	
Circulating sFlt-1	34	2.6 SMD	[1.7; 3.4]	84	<0.0001	0.43	
Values are pooled estimates expressed in mean difference (MD) or standardized mean difference (SMD) with a 95% confidence interval [CI] using a random effect model. RUPP, reduced uterine perfusion pressure. 1In nine studies, data with imputed SD of the mean SDs were used. No. Comp, experimental comparisons; I2, heterogeneity; sFlt-1, circulating soluble FMS-like tyrosine kinase-1.

Maternal blood pressure.

Our meta-analysis on blood pressure showed an increase of 24.1 mmHg [22.6; 25.7; I2 = 92%; P < 0.0001; Supplemental Fig. S1] in RUPP animals (n = 1,659) compared with control animals (n = 1,575). First and foremost, artery cannulation (n = 138) was applied to measure maternal BP in the 148 included studies.

We observed a significant effect in the meta-regression of the method of BP measurement [R2 = 5%; P < 0.01, Fig. 3A]; however, the effect is predominantly due to the much lower effect in the small stratum of two comparisons using telemetry. Predominantly, BP measurements were performed consciously (n = 120; of which CA is n = 110, tail-cuff n = 8, telemetry n = 2). In some of these cases, anesthesia was used on the day of BP measurement (n = 8) using isoflurane and in most cases after a minimal recovery of 1 h. Unconscious BP measurements under anesthesia (n = 16) were obtained in part of the studies that used artery cannulation. Meta-regression on the state of consciousness in animals during measurement showed no significant effect of this variable on the outcome (Fig. 3B). MAP is reported in most studies (n = 135). In other studies, SBP was used (n = 13), mainly the tail-cuff studies used SBP. Reporting the time point of BP at the gestational day of pregnancy was registered in 145 studies, the most used time point is GD19 (n = 123). A linear regression on time of measurement indicated a decrease in the effect of RUPP on BP over time [R2 = 1.53%; P < 0.05, Fig. 4]. Meta-regression on pairing (Fig. 3C); type of control (Fig. 3D); and reporting of randomization (Fig. 3E) showed no significant effect of these variables on the outcome.

Figure 3. Stratified meta-regressions for the outcome of maternal blood pressure. A: method of blood pressure measurement. B: state of consciousness of animal during blood pressure measurement. C: pairing. D: type of control. E: study design on randomization. Data represent pooled estimates expressed as mean difference (MD) with a 95% confidence interval (CI) using a random effect model; n, number of independent comparisons in the stratum. RUPP, reduced uterine perfusion pressure.

Figure 4. Time depending on the effect of maternal blood pressure measurement. Regression time-point bubble plot of maternal blood pressure measurement, time-point gestational days (GDs) 17–21. On the time-points GD20 (n = 11) and GD21 (n = 3), effect of blood pressure (BP) is lower and revealed a significant regression R2 = 1.53%. P < 0.05.

Visual inspection of the funnel plots suggested no publication bias in BP (Supplemental Fig. S9A) which was supported by Egger’s regression test (Supplemental Fig. S9B).

Maternal proteinuria.

Meta-analysis on proteinuria showed increased levels of 2.3 of the SMD [0.9; 3.8; I2 = 92%; P = 0.0021; Supplemental Fig. S2] in animals subjected to RUPP (n = 301) referenced to control animals (n = 269), derived from 28 comparisons. Two different methods were used to collect urine samples, metabolic cage, or separate cage over 24-h collection (n = 17), or urine spot sample (n = 7) was collected directly from bladder, and four studies did not describe the collection method. To determine proteinuria, multiple assays were used, which measured concentrations of total protein (n = 14) or albumin (n = 3), or ratio of albumin and creatinine (n = 5), and five not specified assays.

The timing of proteinuria collection (varying from GD17 to GD20) did not influence the overall estimate (Supplemental Fig. S8A). Meta-regression of reporting of randomization (Supplemental Fig. S6) also showed no significant effect of this variable on the outcome.

Visual inspection of the funnel plots and Egger’s regression test suggested no publication bias in proteinuria (Supplemental Fig. S9, C and D).

Percentage of fetal reabsorptions.

The meta-analysis on the percentage of fetal reabsorptions showed an increase of 50.4% [45.5; 55.2; I2 = 92%; P < 0.0001; Supplemental Fig. S3] in dams subjected to RUPP (n = 520) compared with control dams (n = 458) based on 42 comparisons. Within this meta-analysis, most studies (n = 33) reported the exact percentages, as the difference between viable pups at GD14 and day of euthanization or as the differences in reabsorbed fetuses between GD14 and day of euthanization. In the cases where normal pregnant animals were used as the control group, researchers calculated implantation sites and reabsorption due to no surgery to determine the number of viable pups at GD14. In nine studies, the percentage of fetal reabsorptions had to be calculated because other ways of reporting were chosen.

Meta-regression on the timing of measurement (varying from GD18 to GD22) showed no effect of this variable on the outcome (Supplemental Fig. S8B). Meta-regression on type of control (Supplemental Fig. S7A) and reporting of randomization (Supplemental Fig. S7B) both showed no significant effects.

Visual inspection of the funnel plots suggested no publication bias in the percentage of fetal reabsorptions (Supplemental Fig. S9, E and F) which was confirmed by Egger’s regression test.

Fetal growth restriction.

The meta-analysis of fetal weight displayed a decrease of 0.4 g [−0.47; −0.34; I2 = 90%; P < 0.0001; Supplemental Fig. S4] in dams subjected to RUPP (n = 1,301) compared with control dams (n = 1,198) from a total of 113 comparisons. The decrease of 0.4-g MD is in line with our observation with a mean percent fetal weight loss of ∼16 ± 9% in RUPP compared with sham.

The time point of euthanasia to measure fetal weight showed a variation between GD18 and GD22, with the majority of the data reported on GD19 (n = 84); however, meta-regression did not reveal an effect of the timing on the outcome (Supplemental Fig. S8C). Meta-regression analysis revealed a smaller fetal weight difference between RUPP and control in studies that mentioned randomization versus those not reporting randomization [R2 = 3.9%; P < 0.024, Fig. 5C]. Meta-regressions on parity (Fig. 5A) and type of control (Fig. 5B) showed no effect of these variables on the outcome.

Figure 5. Stratified meta-regressions for the outcome of fetal weight. A–C: meta-regression on fetal weight as follows: pairing (A), type of control (B), and study design on randomization (C). Data represent pooled estimates expressed as mean difference (MD) with a 95% confidence interval (CI) using a random effect model; n, number of independent comparisons in the stratum. RUPP, reduced uterine perfusion pressure.

Visual inspection of the funnel plots suggested publication bias in fetal weight (Supplemental Fig. S9K); Egger’s regression test confirmed this (Supplemental Fig. S9L) (P < 0.0032, Table 2).

Circulating sFlt-1.

The meta-analysis of levels of sFlt-1, as the most studied antiangiogenic factor, showed an increased SMD of 2.6 [1.7; 3.4; I2 = 84%; P < 0.0001; Supplemental Fig. S5]. The meta-analysis combined results from the 155 independent studies from a total of 34 comparisons including animals subjected to RUPP (n = 343) compared with control animals (n = 332). All the reported studies used ELISA kits to measure sFlt-1 (n = 34), only the manufacturer of ELISA kits and the intra-assay and inter-assay precision with a coefficient of variability differed between studies or was not reported.

Meta-regression on type of control demonstrated a higher effect in normal pregnant compared with sham animals [R2 = 5.2%; P < 0.05, Fig. 6A]. Meta-regression of the timing of measurement (Supplemental Fig. S8D) and study design reporting on randomization (Fig. 6B) showed no effect of these variables.

Figure 6. Stratified meta-regressions for the outcome circulating soluble FMS-like tyrosine kinase-1 (sFlt-1). A: type of control. B: study design on randomization. Data represent pooled estimates expressed as standardized mean difference (SMD) with a 95% confidence interval (CI) using a random effect model; n, number of independent comparisons in the stratum. RUPP, reduced uterine perfusion pressure.

Visual inspection of the funnel plots suggested no publication bias in sFlt-1 (Supplemental Fig. S9I), which was supported by Egger’s regression test (Supplemental Fig. S9J).

Sensitivity analyses.

Two sensitivity analyses were performed to assess the influence of two important methodological decisions on the outcome of our meta-analyses. First, we assessed the effect of imputed SDs on the meta-analysis of fetal weight, by omitting all comparisons with an imputed SD from the analysis. Doing so did not significantly change the pooled estimate (original MD = 50.4% [45.5; 55.2]; I2 = 92% vs. sensitivity analysis MD = 49.7% [43.7; 55.6]; I2 = 93%). Subgroup analysis results remained unchanged (Supplemental Table S4).

Second, to assess the effect of our decision to pool MAP and SBP in the meta-analysis of blood pressure, we re-ran the analysis using MAP data only. Doing so did not significantly change the pooled estimate (original MD = 24.1 [22.6; 25.7]; I2 = 92% vs. sensitivity analysis SMD = 23.5 [22.0; 25.0]; I2 = 89%). Subgroup analysis results remained unchanged, except for the use of anesthetics during the blood pressure measurement, which was no longer significant. This is likely the result of collinearity between the blood pressure measurement method (tail-cuff vs. cannulation vs. telemetry), the use of anesthesia, and the type of measurement performed (MAP vs. SBP) (Supplemental Table S4).

Reporting of Key Study Quality Indicators and Risks of Bias

The reporting of key indicators of study quality showed ample room for improvement in most of the included articles (Fig. 7A and Supplemental Table S5). The majority of studies reported a conflict-of-interest statement (n = 120), where most of the authors declared to have no conflict of interest (n = 110). However, the vast majority failed to mention randomization (reported in n = 65), provide any information on a sample size calculation (reported in n = 4), or mention any blinding of the investigators during the study (reported in n = 22). Of note, reporting of blinding was even less prevalent for our predefined outcome measures (reported in n = 5).

Figure 7. Risk of bias assessment. A and B: assessment of reporting of key study quality indicators (A) and risks of bias (B), according to SYRCLE’s risk of bias tool.

Our assessment of internal validity shows that most studies are at unclear risk of several types of bias (Fig. 7B and Supplemental Table S5). This is mainly due to the absence of concrete measures to reduce bias and poor reporting of baseline characteristics of the animals. We considered all studies to be at unclear risk of performance bias for the domain “blinded interventions” (item 5) because no study mentioned blinding during this phase. However, this likely is an underestimation of the risk of bias in many cases (specifically for the non-sham control group), since the surgical procedures come with a visible postoperative appearance (sutures and effect on body wt) that sets RUPP apart from control animals. No study mentioned taking any extra precautions to prevent this bias (e.g., the surgeon not participating in subsequent phases of the experiment, or precautions to ensure blinding of the animal caretakers). A high risk of attrition bias (item 8) was observed in several studies because of unexplained dropouts. When considering other types of bias (item 10), we assessed studies at high risk of bias because of a possible conflict of interest (12 studies). We scored a high risk of bias in studies using the individual fetus as the unit of analysis instead of the litter (four studies). Using the individual pups as the unit of analysis is considered as a unit of analysis error since this artificially inflates the number of independent subjects in the analysis and can bias the results.

DISCUSSION

This systematic review and meta-analysis support the use of the long-established murine RUPP model to study placental ischemia-induced PE and FGR. The maternal PE phenotype in RUPP is confirmed by significantly increased primary outcomes of hypertension and proteinuria, as well as the secondary outcome of circulating sFlt-1, together with the FGR phenotype through primary outcome of limited fetal growth and increased fetal resorptions. The presence of the high heterogeneity in all these outcomes makes it challenging to reproduce with a stable phenotype; however, this high heterogeneity reflects the complexities of the human condition. We discuss the observed heterogeneity in outcomes relating them to differences in characteristics and methods in Influential Factors in Maternal Outcome and Influential Factors in Fetal Outcome.

Influential Factors in Maternal Outcome

Maternal blood pressure.

Our meta-analysis shows a significant increase of BP after RUPP induction, which is most pronounced in early pregnancy. The effect also appears to be modified by anesthetic use and the type and method of blood pressure measurement, but collinearity of these variables prevented us from pinpointing the contribution of each of these individual factors.

Although all BP measuring methods-, intra-arterial, telemetry, and tail-cuff, show a significant increase in BP in the RUPP model, the most optimal method is debatable and situation-dependent considering their specific advantages and disadvantages (163–165). The highest effect is measured in studies using tail-cuff, although also accompanied by the widest confidence interval. Tail-cuff is in general considered a much less reliable method to measure BP which requires adequate training of animals. Beyond that, our biggest concern in RUPP specifically is that the tail-cuff relies on sensor detection of blood flow instead of detection of the pulse (166, 167). Inherent to RUPP surgery, partly clamping of an artery affects distal flow through the tail, and thereby considerably impacts the tail-cuff BP measurements.

In the same line of reasoning, considering the clipping site, the carotid artery is the preferred and most reliable location for intra-arterial catheters in RUPP model to accurately measure blood pressure, surpassing the femoral artery. Altogether, it is logical that the majority of studies in our meta-analysis used carotid artery catheters. Although this method can detect small changes in BP, the drawback of this method lies in the need for anesthesia close to the time of recording (usually during or within 24 h of the measurement). Conjointly, analgesics are used to invasively insert the catheter, together with the administration of anticoagulants to keep the catheter patent. In our meta-regression, anesthesia during BP measurement was applied in only a small group of the intra-artery cannulation method (n = 16). It is known that each individual anesthetic has a unique impact on the cardiovascular system (168). The expected impact of anesthetics overall has not been observed in our meta-regression, possibly because of a diverse range of used anesthetics (n = 5), which cancel each other out. Moreover, we speculate that the anesthetic effect of each individual anesthetic might be divergent in control animals, which could be attributed to endothelial activation in the RUPP model. In addition, the effect of the model itself is among others reliant on the angiotensin II mechanism in the central nervous system (5).

The time point dependent effect on blood pressure matches the results of a within-study effect using telemetry (114). Both show a higher blood pressure difference during GD17 and GD19 compared with GD20 and GD21 in the rat RUPP model. This is most likely due to the first mechanistic effect of ischemic reperfusion diminishes by readaptation of vascular homeostasis (169). This also relates to healthy pregnancies, whereas the increased nitric oxide-mediated vasodilation results in decreased systemic vascular resistance and blood pressure in mid and late pregnancy (170–173).

Notably, the elevated effect in our meta-regression is much lower in telemetry compared with the other two methods. The use of telemetry allows us to accurately measure BP unrestrained and unanesthetized over a period of time, implying that factors such as anesthesia and stress of restrained animals influence measurement. Of note, the rat telemetry study showed only an increased blood pressure in RUPP during the active phase at night (114), highlighting the importance of timing of measurement during the day/night cycle. With this in mind and because of underreporting of the time of measurement, heterogeneity might be induced by variation of timing of measurement during the day, assuming measurements were conducted during working hours (inactive phase). Possibly, measuring BP in the active phase with a reversed day-night rhythm in a specific time window could improve reproducibility in future studies.

Maternal proteinuria.

Although the RUPP procedure results in proteinuria when looking at the overall meta-analysis, more than half of individual studies observed no effect and proteinuria also appears to be the phenotypical outcome with the highest variability. This is in line with the early observations described in the review by Granger et al. and comparable to the within-study variability of multiple time points (4, 24, 155, 156, 162). The variability might be caused by the variety of sampling methods and assays with different units of measurement. Another reason for the high between-study heterogeneity could be the relatively short exposure to placental ischemia used in the studies (maximum 5 days). Of note, the time window in the murine RUPP studies may be too short to measure an effect on proteinuria, as the RUPP procedure in baboons does not lead to an increase in protein excretion until weeks 2 and 3 (174, 175). Unfortunately, the existing evidence is too heterogeneous to formulate advice on the most optimal assay or study design.

Circulating antiangiogenic factor sFlt-1.

We showed that the increase in sFlt-1 after RUPP is more pronounced in studies using normal pregnant animals as controls than in those using sham-operated animals. This difference might be linked to an inflammatory response to surgery. Rats that underwent sham surgery (including telemetry probe implantation) showed elevated levels of cytokines similar to the RUPP group (114), which might indicate that elevations of cytokines in both groups are likely due to a systemic inflammatory response to the surgeries. In turn, this could influence the expression of sFlt-1 in endothelial cells and placental trophoblasts (176–178). Moreover, inflammation activates neutrophils, which can release proteases and reactive oxygen species that may play a role in cleavage of Flt-1 and increase sFlt-1 levels (179–183). The very wide CI might be due to the higher resorption rate since placental ischemia induces a higher release of sFlt-1. Other possible causes of heterogeneity involve the many different manufacturers and the sensitivity of the ELISA kits. Standardization provides more insight into the absolute effect of sFlt-1 in the RUPP model.

Influential Factors on Fetal Outcome

Fetal growth restriction.

The effect on weight loss in the RUPP model is a relatively large effect compared with the human condition (184). An overestimation of the effect might be in play considering the observed publication bias. In addition, selection bias may have led to unequal baseline characteristics of the animals in the RUPP and control groups, especially since we cannot rule out that animals were assigned to a group based on litter size on the day of surgery. Litter size can affect FW and was underreported as a baseline characteristic. The gestational day of the measured FW did not affect the outcome in our analysis; nevertheless, we speculate that later time points result in more accurate readings. This speculation is based on the understanding that fetuses tend to increase in weight as they develop over time. Therefore, measurements taken at later time points may provide more accurate readings of the absolute values. In addition, the longer exposure to the model at later time points could potentially result in a more pronounced difference in weight between the RUPP and control groups. This, combined with the already subtle differences, may allow for a more accurate measurement of the differences between the two groups.

Sex differences in the fetal outcome of the RUPP model could be relevant in fetal weight and eventually in long-term outcome effects. As reported, the placental response to oxidative stress appears to be different in males compared with females (185, 186). Only one study reported sex-specific fetal weight outcomes and showed no significant effect that males are more affected in the RUPP model, while an opposite trend in females is seen (13). The low reporting of sex differences could be due to difficulties in determining the sexes of small fetuses visually. This can be done easily by PCR as used in other studies (187).

Percentage of fetal resorptions.

Our meta-analysis showed a significant increase in the percentage of resorptions, with a high heterogeneity which could not be explained by any of our predefined subgrouping variables. The source of this heterogeneity therefore remains unclear, warranting further research. Theoretically, a varying amount of fetal reabsorptions could cause a higher level of inflammatory and antiangiogenic factors, which could in turn affect the severity of the RUPP model (188) Furthermore, a higher resorption rate could influence fetal growth in the RUPP model, assuming that the individual RUPP fetuses take in more of the available oxygen and nutrients when the litter size is smaller (189, 190).

Modifiable Factors in Animal and Surgery Characteristics

Unfortunately, we could not evaluate all the possible modifiable factors (such as strain, parity, and clipping details) for every outcome measure, because of the small subgroups or poor reporting. These factors might explain (part of) the heterogeneity of the RUPP model.

Strengths and Limitations

To the best of our knowledge, this is the first systematic review with meta-analysis in the RUPP model, which provides a complete overview of the maternal and fetal phenotypes. The relatively large sample size creates a high power in the meta-analysis which allows examination of many characteristics as possible influential factors. In BP, we were able to indicate two influential factors, namely, method and timing of BP measurement. One influential factor in sFlt-1 was indicated to the type of control and in FW randomization was indicated as an influential factor. Furthermore, our assessment of reporting of key study quality indicators and risks of bias reveals essential points of improvement for future research; namely, more rigorous implementation and reporting of vital experimental details and measures to reduce bias. Of note, the predominantly unclear risk of bias observed in the included studies may have led to an overestimation of effect sizes, which decreases the confidence we can have in the meta-analysis results. The subgroup analyses in particular must be regarded as hypothesis generating.

A limitation of this systematic review is that our assessment of sources of heterogeneity was hampered by the underreporting of certain study characteristics. This prevented us from performing all our predefined subgroup analyses for all outcomes. Although we investigated the RUPP effect only in the murine RUPP model, chosen specifically to reduce variables, investigation of the RUPP effect between species and between multiple RUPP methods would be worthwhile. However, both are not within the scope of this systematic review.

Perspectives and Significance

The RUPP model is of relevant use in research on cardiovascular complications during pregnancy regarding PE and FGR, considering the evident differences in maternal and fetal outcomes between RUPP and control. The RUPP model provides insight into particular aspects of this complex and multifactorial cardiovascular disease and contributes to our understanding of PE. However, high heterogeneity is observed in the model, and several factors can influence the severity of the RUPP model. Knowing these influential factors and limitations could contribute to improving comprehension of findings in future research using the RUPP model. Of course, this depends on the research question as pathophysiological mechanistic questions require a broad phenotype conform to the human condition, whereas research questions on novel therapeutics would benefit from an animal model with high reproducibility and small heterogeneity to detect potential small effects without needing a large group of animals. Based on this systematic review and meta-analysis of the RUPP model, we formed recommendations about the influential factors and limitations that can be considered when designing a study with RUPP. First, we advise BP measurements performed with intra-artery cannulation in the carotid artery with readout time point under GD20 or telemetry method until at least GD20. Second, the use of NP animals as a control group is justifiable depending on the study design. Third, proteinuria in RUPP rat is not of additional value as an outcome measure for future research, as the proteinuria outcome resulted in not being the most stable outcome measure. Possibly only in large groups, it could give enough power to show increased proteinuria in RUPP. If you are specifically interested in proteinuria as an outcome, an alternative PE model could be chosen, such as the Dahl rat. Fourth, fetal weight should be considered in light of viable litter size and sexes of fetuses. Another consideration to explore is the genetic differences and sensitivity to the RUPP in Sd and Wistar animals. Lastly, we strongly recommend improving the reporting of study design, e.g., according to the ARRIVE (Animal Research Reporting of In Vivo Experiments) guidelines, to improve study quality and to reduce the risk of bias.

SUPPLEMENTAL DATA

10.6084/m9.figshare.25452043 Supplemental Tables S1–S5, Supplemental Figs. S1–S9, and Supplemental Excel file E1: https://doi.org/10.6084/m9.figshare.25452043.

GRANTS

This study was supported by Meer Kennis Minder Dieren Grant 40-42600-98-476, from Netherlands Organization for Health Research and Development (ZonMw).

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the authors.

AUTHOR CONTRIBUTIONS

A.T.L. conceived and designed research; C.M.v.K. and S.E.L.T. performed experiments; C.M.v.K. and S.E.L.T. analyzed data; C.M.v.K., K.E.W., and F.T. interpreted results of experiments; C.M.v.K. and K.E.W. prepared figures; C.M.v.K. drafted manuscript; S.E.L.T., K.E.W., J.P.G., and F.T. edited and revised manuscript; S.E.L.T., K.E.W., J.P.G., A.T.L., and F.T. approved final version of manuscript.
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