Long-Term Neurodevelopmental, Mental, and Cardiometabolic Health in Individuals Conceived with Assisted Reproductive Technology: A Literature Review
Bibliographic record
Abstract
Background: Assisted reproductive technology (ART) has revolutionised fertility treatments since 1978 and, while its immediate perinatal outcomes have been extensively studied, its long-term health effects require exploration. Method: PubMed database was searched for studies spanning 2016 to 2023 to conduct this literature review of the long-term neurodevelopmental, mental, and cardiometabolic health of ART-conceived individuals. Results: A total of 49 studies were included in this review. ART-conceived individuals revealed mostly positive neurodevelopmental and mental health impacts. However, children conceived via intracytoplasmic sperm injection (ICSI) demonstrated an increased risk of neurodevelopmental disorders, including autism spectrum disorder, intellectual disability, and psychological and neurological development delays, while frozen embryo transfer was linked to an increased risk of language delay. Additionally, children born via ART as multiples or prematurely showed an elevated risk of cerebral palsy. While ART generally demonstrated a favourable impact on cardiometabolic health, there were concerns about increased risk of high blood pressure, altered lipid profiles, obesity, insulin resistance, premature vascular aging, and adverse metabolic changes. Specifically, ICSI-conceived individuals were more prone to adiposity and insulin resistance, while frozen embryo transfer was associated with type 1 diabetes. Conclusion: While ART-conceived individuals generally exhibit favourable health, specific subgroups may face elevated risks for certain neurodevelopmental disorders and long-term cardiometabolic issues, warranting further research. ART may be associated with metabolic alterations at a young age, potentially increasing the risk of chronic diseases such as metabolic syndrome, type 2 diabetes, and cardiovascular disease later in life. Continued long-term monitoring and targeted interventions are recommended to mitigate these risks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".