Risk Assessment at 11–14-Week Antenatal Visit: A Tertiary Referral Center Experience from South India

Vellamkondu, Anusha; Vasudeva, Akhila; Bhat, Rani Akhil; Kamath, Asha; Amin, Sapna Vinit; Rai, Lavanya; Kumar, Pratap

doi:10.1007/s13224-017-0985-4

Cited by 5 publications

(16 citation statements)

References 16 publications

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“…Model developers varied candidate predictors because of their availability in the setting of intended use 20,21 or to investigate the contribution of novel predictors to model performance. 22,23 Three groups developed models using data derived from low-resource settings, 20,21,24 and the remainder were developed in higher-resource settings. Most included all women presenting for routine pregnancy care.…”

Section: Resultsmentioning

confidence: 99%

“…In some studies the full set of candidate predictors was not clear. 24,32 The most frequently included predictor was ethnicity. Ethnicity was identified as a predictor of stillbirth in both univariable and multivariable analyses in every study that evaluated it, but it was highly variable in classification, even among datasets from the same country and city (Table S2).…”

Section: Resultsmentioning

confidence: 99%

“…In all, 16 distinct stillbirth outcomes were reported across the 69 models (Table S3). The most common gestational cut off was >24 weeks (range [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34]. Most studies excluded pregnancies affected by congenital anomaly and several excluded women who delivered spontaneously <24 weeks from the development dataset.…”

Section: Resultsmentioning

confidence: 99%

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Can risk prediction models help us individualise stillbirth prevention? A systematic review and critical appraisal of published risk models

Townsend

Manji

Allotey

et al. 2020

BJOG

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Background Stillbirth prevention is an international priorityrisk prediction models could individualise care and reduce unnecessary intervention, but their use requires evaluation. Objectives To identify risk prediction models for stillbirth, and assess their potential accuracy and clinical benefit in practice. Search strategy MEDLINE, Embase, DH-DATA and AMED databases were searched from inception to June 2019 using terms relevant to stillbirth, perinatal mortality and prediction models. The search was compliant with Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Selection criteria Studies developing and/or validating prediction models for risk of stillbirth developed for application during pregnancy. Data collection and analysis Study screening and data extraction were conducted in duplicate, using the CHARMS checklist. Risk of bias was appraised using the PROBAST tool. Results The search identified 2751 citations. Fourteen studies reporting development of 69 models were included. Variables consistently included were: ethnicity, body mass index, uterine artery Doppler, pregnancy-associated plasma protein and placental growth factor. For almost all models there were significant concerns about risk of bias. Apparent model performance (i.e. in the development dataset) was highest in models developed for use later in pregnancy and including maternal characteristics, and ultrasound and biochemical variables, but few were internally validated and none were externally validated. Conclusions Almost all models identified were at high risk of bias. There are first-trimester models of possible clinical benefit in early risk stratification; these require validation and clinical evaluation. There were few later pregnancy models but, if validated, these could be most relevant to individualised discussions around timing of birth.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Can risk prediction models help us individualise stillbirth prevention? A systematic review and critical appraisal of published risk models

Townsend

Manji

Allotey

et al. 2020

BJOG

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“…Vellamkondu A et al, conducted a study on risk assessment at 11-14 weeks gestation and observed that 8.63% of patient had deranged blood sugar levels. 10 Present study has reported 20% of the participants with raised liver enzyme values (SGOT > 50, U/L SGPT > 50 U/L). Elbishry GM et al, conducted a study in which they reported that 22% of the patients with preeclampsia had deranged LFT.…”

Section: Sensitivity Specificitymentioning

confidence: 46%

“…9 Uterine artery doppler waveform analysis also has the best predictability at 22-26 weeks period of gestation. 10 Resistance to blood flow within uteroplacental circulation is transmitted upstream to the uterine arteries. 11 Faulty trophoblastic invasion of the spiral arteries results in diminished placental perfusion and upstream increased uterine artery resistance; resulting in increased uterine artery pulsatility index (PI) or resistance index (RI) and persistence of early diastolic notch.…”

Section: Introductionmentioning

confidence: 99%

Comparative study of sFlt-1/Plgf ratio with uterine artery doppler indices in prediction of preeclampsia at 22-24 weeks period of gestation

Gupta

Sharma

Arora

et al. 2020

Int J Reprod Contracept Obstet Gynecol

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Background: Hypertensive disorders like pre-eclampsia along with hemorrhage and infection, contributes greatly to maternal morbidity and mortality. Various pro and antiangiogenic factors like sFlt-1 and Plgf have been linked to the etiopathogenesis of placental vascular disease and their combination with uterine artery doppler studies may improve the prediction accuracy. Present study was conducted to analyze sFlt-1/Plgf ratio and uterine artery doppler indices among high risk patients and to compare these in prediction of preeclampsia.Methods: A prospective observational study was conducted from September 2017 to February 2019 in which 100 patients giving consent and satisfying inclusion criteria were evaluated for various risk factors and were subjected to sFlt-1/Plgf ratio test and uterine artery doppler study at 22-24 weeks period of gestation. They were followed up and maternal outcome was analysed.Results: Among the cohort of 100 women with high risk factors, 35% of the study participants developed pre-eclampsia. Using sFlt-1/Plgf ratio 40% of them were screened positive for pre-eclampsia. This percentage of screened positive was 40%, 43%, and 53% using uterine artery RI, PI, and SD respectively. sFlt-1/Plgf was found to have a sensitivity of 91.4% and specificity of 87.7%. ROC curve analysis showed highest area under curve (AUC) for sFlt-1/Plgf (0.858).Conclusions: sFlt-1/Plgf ratio was found to be a better predictable biomarker than uterine artery Doppler indices in prediction of pre-eclampsia at 22-24 weeks period of gestation.

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Diagnostic accuracy of ultrasound screening for fetal structural abnormalities during the first and second trimester of pregnancy in low-risk and unselected populations

Buijtendijk,

Bet,

Leeflang

et al. 2024

Cochrane Database of Systematic Reviews

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Risk Assessment at 11–14-Week Antenatal Visit: A Tertiary Referral Center Experience from South India

Abstract: Majority of fetal abnormalities can be detected, and majority adverse pregnancy outcomes can be predicted at 11-14-week antenatal visit, although this study shows high screen positivity and low specificity in a tertiary referral unit.

Cited by 5 publications

References 16 publications

Can risk prediction models help us individualise stillbirth prevention? A systematic review and critical appraisal of published risk models

Can risk prediction models help us individualise stillbirth prevention? A systematic review and critical appraisal of published risk models

Comparative study of sFlt-1/Plgf ratio with uterine artery doppler indices in prediction of preeclampsia at 22-24 weeks period of gestation

Diagnostic accuracy of ultrasound screening for fetal structural abnormalities during the first and second trimester of pregnancy in low-risk and unselected populations

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