Background: Studies have inconsistently observed that children conceived by IVF or ICSI have higher blood pressure compared to children not conceived by these ARTs.
Objective And Rationale: The aim was to perform a systematic review and meta-analysis of blood pressure measures of offspring conceived by ART and those conceived naturally. Resolving the suspicion of ART as a risk factor of higher blood pressure, and therefore of heart disease, has public health and clinical implications.
Search Methods: A biomedical librarian searched the Embase, PubMed, and Web of Science databases. Searches were limited to records published in English since 1978. Grey literature was searched. Inclusion criteria were humans born via infertility treatment (vs no treatment) who underwent a blood pressure assessment. Exclusion criteria were non-human participants, non-quantitative studies, absence of a control group, and specialty populations (e.g. cancer patients only). Two reviewers independently screened each record's title and abstract and full text using Covidence, extracted data using Excel, and assessed bias using the National Heart, Lung, and Blood Institute's Quality Assessment Tool for cohort studies.
Outcomes: Of 5082 records identified, 79 were included in the systematic review and 36 were included in the meta-analysis of systolic blood pressure (SBP) and diastolic blood pressure (DBP) in ART and non-ART groups. Overall, 34 reports including 40 effect sizes from 25 unique cohorts, compared blood pressure between ART (N = 5229) and non-ART (N = 8509, reference) groups with no covariate adjustment. No standardized mean differences (SMD) in SBP (0.06 per SD of mmHg, 95% CI = -0.05, 0.18) or DBP (0.11, 95% CI = -0.04, 0.25) by treatment were found, but the heterogeneity was considerable (I2=76% for SBP and 87% for DBP). Adjusted analyses were presented in 12 reports, representing 28 effect sizes from 21 unique cohorts (N = 2242 treatment vs N = 37 590 non-treatment). Studies adjusted for varied covariates including maternal (e.g. age, education, body mass index, smoking, pregnancy complications), child (e.g. sex, age, physical activity, BMI, height), and birth characteristics (e.g. birth weight and gestational age). Adjusted results similarly showed no SMD for SBP (-0.03, 95% CI = -0.13, 0.08) or DBP (0.02, 95% CI = -0.12, 0.16), though heterogeneity remained high (I2 = 64% and 86%). Funnel plots indicated a slight publication bias, but the trim and fill approach suggested no missing studies. Removal of five studies which adjusted for birth outcomes (potentially over-adjusting for mediators) made no material difference. Type of treatment (e.g. IVF vs ICSI), period effects by birth year (≤2000 vs >2000), offspring age group (<8, 8-14, 15+), or study location (e.g. Europe) did not modify the results.
Wider Implications: In conclusion, conception by ART was not associated with offspring blood pressure in a meta-analysis, although considerable heterogeneity was observed. Given the increasing number of children born using ART, perpetuating a difference in blood pressure would mean unnecessary risk screening for many children/adults on a population level. At a clinical level, couples considering these reproductive technologies have some reassurance that there is no evidence of strong vascular 'programming' due to the techniques used.
Registration Number: PROSPERO No. CRD42022374232.
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http://dx.doi.org/10.1093/humupd/dmae029 | DOI Listing |
Circ Genom Precis Med
January 2025
Mary and Steve Wen Cardiovascular Division, Department of Medicine, University of California, Los Angeles. (W.F., N.D.W.).
Background: Lp(a; Lipoprotein[a]) is a predictor of atherosclerotic cardiovascular disease (ASCVD); however, there are few algorithms incorporating Lp(a), especially from real-world settings. We developed an electronic health record (EHR)-based risk prediction algorithm including Lp(a).
Methods: Utilizing a large EHR database, we categorized Lp(a) cut points at 25, 50, and 75 mg/dL and constructed 10-year ASCVD risk prediction models incorporating Lp(a), with external validation in a pooled cohort of 4 US prospective studies.
Hypertension
January 2025
Department of Nephrology, Medical Faculty, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Germany (S.A.P., I.Q., D. Arifaj, M.K., D. Argov, L.C.R., J.S.).
Background: Ciliary neurotrophic factor (CNTF), mainly known for its neuroprotective properties, belongs to the IL-6 (interleukin-6) cytokine family. In contrast to IL-6, the effects of CNTF on the vasculature have not been explored. Here, we examined the role of CNTF in AngII (angiotensin II)-induced hypertension.
View Article and Find Full Text PDFWounds from gunshots and other explosive devices are a source of loss of substances directly or secondary to a well- conducted debridement. In addition, these types of wounds are by definition contaminated. The major challenge in this context for any surgeon remains coverage.
View Article and Find Full Text PDFJHEP Rep
February 2025
Department of Gastroenterology and Hepatology, Hospital Universitario Ramón y Cajal, Instituto Ramon y Cajal de Investigación Sanitaria (IRYCIS), Universidad de Alcalá, Madrid, Spain.
Background & Aims: Systemic inflammation is a driver of decompensation in cirrhosis with unclear relevance in the compensated stage. We evaluated inflammation and bacterial translocation markers in compensated cirrhosis and their dynamics in relation to the first decompensation.
Methods: This study is nested within the PREDESCI trial, which investigated non-selective beta-blockers for preventing decompensation in compensated cirrhosis and clinically significant portal hypertension (CSPH: hepatic venous pressure gradient ≥10 mmHg).
Front Public Health
January 2025
Department of Computer Science, College of Engineering and Computer Science, Jazan University, Jazan, Saudi Arabia.
Introduction: The growing demand for real-time, affordable, and accessible healthcare has underscored the need for advanced technologies that can provide timely health monitoring. One such area is predicting arterial blood pressure (BP) using non-invasive methods, which is crucial for managing cardiovascular diseases. This research aims to address the limitations of current healthcare systems, particularly in remote areas, by leveraging deep learning techniques in Smart Health Monitoring (SHM).
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