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Enregistrement W3204113306 · doi:10.1002/uog.24784

Increased rate of miscarriage during second wave of <scp>COVID</scp>‐19 pandemic in India

2021· letter· en· W3204113306 sur OpenAlexaboutno aff
Rahul Gajbhiye, Arundhati Tilve, Shweta Kesarwani, Shayla Srivastava, Shailesh Kore, Kanchan Patil, Smita D. Mahale, Niraj N. Mahajan

Notice bibliographique

RevueUltrasound in Obstetrics and Gynecology · 2021
Typeletter
Langueen
DomaineMedicine
ThématiqueCOVID-19 Impact on Reproduction
Établissements canadiensnon disponible
Organismes subventionnairesIndian Council of Medical ResearchThe Wellcome Trust DBT India AllianceDepartment of Biotechnology, Ministry of Science and Technology, IndiaWellcome Trust
Mots-clésMedicineMiscarriagePandemicPregnancyObstetricsCohort studyCohortIncidence (geometry)CoronavirusPediatricsCoronavirus disease 2019 (COVID-19)DiseaseInternal medicineInfectious disease (medical specialty)

Résumé

récupéré en direct d'OpenAlex

The lack of reliable data on the risk of miscarriage due to coronavirus disease 2019 (COVID-19) is a concern for both patients and obstetricians. A recent meta-analysis demonstrated an increased risk of adverse pregnancy outcome in low-to-middle-income countries (LMICs) when compared with high-income countries1. The second wave of the COVID-19 pandemic was reported to be more fatal than the first wave, with increased disease severity and maternal mortality2. However, the impact of the second wave of COVID-19 in India on the rate of miscarriage is unknown. We report on the incidence of miscarriage in a cohort of pregnant and postpartum women with COVID-19 (n = 1630) admitted to BYL Nair Charitable Hospital (NCH), Mumbai, India, between 1 April 2020 and 4 July 2021, during the first (1 April 2020 to 31 January 2021) and second (1 February 2021 to 7 July 2021) waves of the COVID-19 pandemic (Figure 1). Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was confirmed using reverse transcription polymerase chain reaction of nasopharyngeal swabs, as per the national testing guidelines. The data of the cohort admitted during the COVID-19 pandemic were compared to those of 11 952 women admitted prior to the pandemic between 1 October 2016 and 30 September 2018. This prepandemic period was selected due to uninterrupted obstetric and gynecological services and data availability. Miscarriage was defined as spontaneous pregnancy loss before 20 weeks of gestation or delivery of a dead fetus weighing less than 500 g. Intrauterine fetal demise (IUFD) was defined as in-utero death of a fetus that was confirmed by ultrasound before delivery. The study was approved by the ethics committees of TNMC (ECARP/2020/63) and ICMR-NIRRH (IEC no. D/ICEC/Sci-53/55/2020) and registered with the Clinical Trial Registry of India (CTRI#2020-025423). The rate of miscarriage per 1000 births was significantly higher during the second wave of the COVID-19 pandemic than that during the first wave (82.6 vs 26.8; P < 0.001) or the prepandemic period (odds ratio, 1.7 (95% CI, 1.16–2.59); P = 0.006). The rate of miscarriage per 100 admissions during the second wave of the COVID-19 pandemic was also significantly higher than that during the first wave (P < 0.004) or the prepandemic period (P = 0.003) (Table 1). During the prepandemic period, the rate of miscarriage was significantly higher in the months February to July (in 2017 and 2018) (55.7 per 1000 births) compared with the months April to January (in 2016, 2017 and 2018) (42.8 per 1000 births) (P = 0.004). Even so, the rate of miscarriage during the second wave of the COVID-19 pandemic (February–July 2021) was significantly higher compared with the same months in the prepandemic period in 2017 and in 2018 at NCH (P = 0.044) (Tables S1 and S2). The rate of IUFD was significantly higher during the COVID-19 pandemic compared with that during the prepandemic period (P = 0.006). The incidence of first- and second-trimester IUFD during the COVID-19 pandemic was higher compared with that in the prepandemic period, but the difference did not reach statistical significance (P = 0.09). The rate of second-trimester miscarriage was significantly higher during the COVID-19 pandemic as compared to the prepandemic period (P < 0.001) (Table 1). A higher number of symptomatic women with COVID-19 and miscarriage were reported during the first wave (7/22 (31.8%)) as compared to the second wave (5/28 (17.9%)) of the COVID-19 pandemic. During the second wave of the COVID-19 pandemic, 96.4% (27/28) of women with miscarriage conceived spontaneously, as compared to a rate of 77.3% (17/22) during the first wave (P = 0.07). Our study demonstrates that the risk of miscarriage during the second wave of the COVID-19 pandemic was three times higher compared with the first wave of the pandemic and two times higher compared with the prepandemic period. Although seasonal variation was observed and the rate of miscarriage was higher during February–July compared to April–January in the prepandemic period, we observed a significantly higher rate of miscarriage during the same months in the second wave of the COVID-19 pandemic. This is the first study to report on the increased rate of miscarriage during the second wave of the COVID-19 pandemic in India. The observed increased risk of miscarriage in women with COVID-19 supports the findings of a study conducted in Turkey3 but is in contrast to the findings of the studies from the USA4 and Canada5. The findings of our study support the observations that COVID-19 could disproportionately affect pregnant women in LMICs1 and women from an Asian ethnic background. The increased miscarriage rate during the second wave of the pandemic could be due to the high infectivity and virulence of the Delta (B.1.617.2) variant of SARS-CoV-2, which was reported to be responsible for the second wave in India6, leading to more IUFDs in both trimesters. Higher COVID-19 rates, fewer antenatal care visits, reduced access to nutritious food and travel restrictions during the second wave could also account for the increased rate of miscarriage during the second wave of the pandemic. However, further studies are required to demonstrate the causal link between fetal death and COVID-19. Limitations of this study include the lack of SARS-CoV-2 testing of products of conception and data on genome sequencing of SARS-CoV-2 strains. In conclusion, our study provides evidence to support counseling of women wishing to become pregnant during the ongoing COVID-19 pandemic and of those who become infected during the first trimester of pregnancy. In our study, COVID-19 appeared to be associated with an increased risk of miscarriage, especially during the second wave of the pandemic. Our findings are important for public health policy, especially for prioritizing the vaccination of pregnant women in India and other LMICs in light of the predicted third wave of the COVID-19 pandemic. We thank Dr Periyasamy Kuppusamy for his assistance in statistical analysis. The study was funded by intramural grant of ICMR-NIRRH (No. ICMR-NIRRH/RA/1070/05-2021). R.K.G. is an awardee of the DBT Wellcome Trust India Alliance Clinical and Public Health Intermediate Fellowship (Grant no. IA/CPHI/18/1/503933). Data available on request due to privacy/ethical restrictions Table S1 Seasonal variation in the rate of miscarriage observed prior to vs during the COVID-19 pandemic Table S2 Number of births and miscarriages in the evaluated period prior to the COVID-19 pandemic (1 October 2016 to 31 September 2018), overall and according to month Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,197
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,196
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,197
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0020,002
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,026
Tête enseignante GPT0,274
Écart entre enseignants0,248 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2021
Routes d'admission1
Résumé présentoui

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