Severe maternal morbidity in women with high BMI in IVF and unassisted singleton pregnancies
Notice bibliographique
Résumé
STUDY QUESTION: Is there a synergistic risk of severe maternal morbidity (SMM) in overweight/obese women who conceived by IVF compared to normal-weight women without IVF? SUMMARY ANSWER: SMM was more common in IVF pregnancies, and among overweight/obese women, but we did not detect a synergistic effect of both factors. WHAT IS KNOWN ALREADY: While much is known about the impact of overweight and obesity on success rates after IVF, there is less data on maternal health outcomes. STUDY DESIGN, SIZE, DURATION: This is a population-based cohort study of 114 409 singleton pregnancies with conceptions dating from 11 January 2013 until 10 January 2014 in Ontario, Canada. The data source was the Canadian Assisted Reproductive Technologies Register (CARTR Plus) linked with the Ontario birth registry (BORN Information System). PARTICIPANTS/MATERIALS, SETTING, METHODS: We included women who delivered at ≥20 weeks gestation, and excluded those younger than 18 years or with twin pregnancies. Women were classified according to the mode of conception (IVF or unassisted) and according to pre-pregnancy BMI (high BMI (≥25 kg/m2) or low-normal BMI (<25 kg/m2)). The main outcome was SMM, a composite of serious complications using International Classification of Diseases, 10th revision (ICD-10) codes. Secondary outcomes were gestational hypertension, pre-eclampsia, gestational diabetes and cesarean delivery. Adjusted risk ratios (aRR) with 95% CI were estimated using log binomial regression, adjusted for maternal age, parity, education, income and baseline maternal comorbidity. MAIN RESULTS AND THE ROLE OF CHANCE: Of 114 409 pregnancies, 1596 (1.4%) were IVF conceptions. Overall, 41.2% of the sample had high BMI, which was similar in IVF and non-IVF groups. We observed 674 SMM events (rate: 5.9 per 1000 deliveries). IVF was associated with an increased risk of SMM (rate 11.3/1000; aRR 1.89, 95% CI: 1.06-3.39). High BMI was modestly associated with SMM (rate 7.0/1000; aRR 1.23, 95% CI: 1.04-1.45) There was no interaction between the two factors (P = 0.22). We noted supra-additive effects of high BMI and IVF on the risk of pre-eclampsia and gestational diabetes, but not gestational hypertension or cesarean delivery. LIMITATIONS, REASONS FOR CAUTION: We were unable to assess outcomes according to reason for treatment. Type II error (beta ~25%) may affect our results. WIDER IMPLICATIONS OF THE FINDINGS: Our results support previous data indicating a greater risk of SMM in IVF pregnancies, and among women with high BMI. However, these factors do not interact. Overweight and obese women who seek treatment with IVF should be counseled about pregnancy risks. The decision to proceed with IVF should be based on clinical judgment after considering an individual's chance of success and risk of complications. STUDY FUNDING/COMPETING INTEREST(S): This study was supported by the Research Institute of the McGill University Health Centre (grant 6291) and also supported by the Trio Fertility (formerly Lifequest) Research Fund. The authors report no competing interests. TRIAL REGISTRATION NUMBER: Not applicable.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».