Sonologist's characteristics related to a higher quality in fetal nuchal translucency measured in primary antenatal care centers

Torrent, Anna; Manrique, Gemma; Gómez‐Castelló, Teresa; Baldrich, E.; Cahuana, Marc Josep; Manresa, Josep María; Borrell, Antoni

doi:10.1002/pd.5512

Cited by 2 publications

(1 citation statement)

References 29 publications

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“…We were able to confirm the previously described effect of ultrasound equipment characteristics on fetal cardiac assessment [ 25 ]. Other factors potentially affecting image quality are gestational age, time constraint and sonographers experience [ 19 , 26 ]. A limitation of the study is that logbook evaluation should have ideally occurred prospectively.…”

Section: Discussionmentioning

confidence: 99%

Organ-specific learning curves of sonographers performing first-trimester anatomical screening and impact of score-based evaluation on ultrasound image quality

et al. 2023

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Introduction First-trimester anatomical screening (FTAS) by ultrasound has been introduced in many countries as screening for aneuploidies, but also as early screening for fetal structural abnormalities. While a lot of emphasis has been put on the detection rates of FTAS, little is known about the performance of quality control programs and the sonographers’ learning curve for FTAS. The aims of the study were to evaluate the performance of a score-based quality control system for the FTAS and to assess the learning curves of sonographers by evaluating the images of the anatomical planes that were part of the FTAS protocol. Methods Between 2012–2015, pregnant women opting for the combined test in the North-Netherlands were also invited to participate in a prospective cohort study extending the ultrasound investigation to include a first-trimester ultrasound performed according to a protocol. All anatomical planes included in the protocol were documented by pictures stored for each examination in logbooks. The logbooks of six sonographers were independently assessed by two fetal medicine experts. For each sonographer, logbooks of examination 25-50-75 and 100 plus four additional randomly selected logbooks were scored for correct visualization of 12 organ-system planes. A plane specific score of at least 70% was considered sufficient. The intra-class correlation coefficient (ICC), was used to measure inter-assessor agreement for the cut-off scores. Organ-specific learning curves were defined by single-cumulative sum (CUSUM) analysis. Results Sixty-four logbooks were assessed. Mean duration of the scan was 22 ± 6 minutes and mean gestational age was 12+6 weeks. In total 57% of the logbooks graded as sufficient. Most sufficient scores were obtained for the fetal skull (88%) and brain (70%), while the lowest scores were for the face (29%) and spine (38%). Five sonographers showed a learning curve for the skull and the stomach, four for the brain and limbs, three for the bladder and kidneys, two for the diaphragm and abdominal wall and one for the heart and spine and none for the face and neck. Conclusion Learning curves for FTAS differ per organ system and per sonographer. Although score-based evaluation can validly assess image quality, more dynamic approaches may better reflect clinical performance.

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Section: Discussionmentioning

confidence: 99%

Organ-specific learning curves of sonographers performing first-trimester anatomical screening and impact of score-based evaluation on ultrasound image quality

et al. 2023

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Magnitude, disparity, and predictors of poor-quality antenatal care service: A systematic review and meta-analysis

Demissie,

Molla,

Tiruneh Tiyare

et al. 2024

SAGE Open Medicine

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Background: Antenatal care is directed toward ensuring healthy pregnancy outcomes. Quality antenatal care increases the likelihood of receiving an effective intervention to maintain maternal, fetal, and neonatal well-being, while poor quality is linked to poor pregnancy outcomes. However, owing to the complex nature of quality, researchers have followed several approaches to systematically measure it. The evidence from these variable approaches appears inconsistence and poses challenges to programmers and policymakers. Hence, it is imperative to obtain a pooled estimate of the quality of antenatal care. Therefore, considering the scarcity of evidence on the quality of antenatal care, this study aimed to review, synthesize, and bring pooled estimates of accessible evidence. Objective: This study aimed to estimate the pooled magnitude and predictors of quality of antenatal care services and compare regional disparity. Method: We conducted a comprehensive systematic three-step approach search of published and unpublished sources from 2002 to 2022. The methodological quality of eligible studies was checked using Joanna Briggs Institute critical appraisal tool for cross-sectional studies. Meta-analysis was carried out using STATA version 16. Statistical heterogeneity was assessed using Cochran’s Q test. In the presence of moderate heterogeneity ( I2 more than 50%), sensitivity and subgroup analyses were conducted and presented in a forest plot. Effect size was reported using standardized mean difference and its 95% confidence interval. Funnel plots and Egger’s regression test were used to measure publication bias at the 5% significance level. A trim-and-fill analysis was conducted to adjust for publication bias. Pooled estimates were computed using random-effects models and weighted using the inverse variance method in the presence of high heterogeneity among studies. A 95% CI and 5% significance level were considered to declare significance variables. Results: The global pooled poor-quality antenatal care was 64.28% (95% CI: 59.58%−68.98%) ( I2 = 99.97%, p = 0.001). The identified pooled predictors of good-quality antenatal care service were: number of antenatal care visits (fourth and above antenatal care visit) (Adjusted odds ratio (AOR) = 2.6, 95% CI: 1.37–3.84), family wealth index (AOR = 2.72, 95% CI: 1.89–3.55), maternal education attainment (AOR = 3.03, 95% CI: 2.24–3.82), residence (urban dwellers) (AOR = 4.06, 95% CI: 0.95–7.17), and confidentiality antenatal care (AOR = 2.23, 95% CI: −0.36 to −4.82). Conclusions: The study found regional and country-level disparities in the quality of antenatal care services for pregnant women, where poor-quality antenatal care services were provided for more than two-thirds to three-fourths of antenatal care attendants. Therefore, policymakers and health planners should put a great deal of emphasis on addressing the quality of antenatal care services.

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Sonologist's characteristics related to a higher quality in fetal nuchal translucency measured in primary antenatal care centers

Cited by 2 publications

References 29 publications

Organ-specific learning curves of sonographers performing first-trimester anatomical screening and impact of score-based evaluation on ultrasound image quality

Organ-specific learning curves of sonographers performing first-trimester anatomical screening and impact of score-based evaluation on ultrasound image quality

Magnitude, disparity, and predictors of poor-quality antenatal care service: A systematic review and meta-analysis

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