The importance of mid-trimester anomaly scans in a low-resource setting: a retrospective study of 7,615 mid-trimester anomaly scans at a tertiary maternity hospital in Nepal

The importance of mid-trimester anomaly scans in a low-resource setting: a retrospective study of 7,615 mid-trimester anomaly scans at a tertiary maternity hospital in Nepal | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The importance of mid-trimester anomaly scans in a low-resource setting: a retrospective study of 7,615 mid-trimester anomaly scans at a tertiary maternity hospital in Nepal Abhishek Shah, Dipesh Poudel, Manisha Bohora, Subaj Bhattarai, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8187679/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Congenital anomalies are a leading cause of perinatal mortality in low- and middle-income countries. While mid-trimester anomaly scans are standard in high-income settings, their utility in Nepal remains undocumented. This study evaluates the spectrum, frequency, and clinical significance of fetal anomalies detected during routine anomaly scans at Nepal’s largest maternity hospital. Methods A retrospective cross-sectional study was conducted at Paropakar Maternity and Women’s Hospital (PMWH), analyzing all mid-trimester anomaly scans (18–24 weeks) performed between January 2021 and April 2023. Anomalies were classified as major (structurally significant) or minor/soft markers (e.g., echogenic bowel, intracardiac echogenic focus). Data were summarized using descriptive statistics, and associations were assessed using Chi-square test. Results Of 7,615 anomaly scans, 2,807 (36.9%) detected at least one anomaly. The most common findings were hydronephrosis (27.1%), echogenic bowel (21.4%), and central nervous system variants (26.1%). Only 88 (3.1%) were major anomalies, including neural tube defects (n = 8), holoprosencephaly (n = 2), omphalocele, gastroschisis, and skeletal dysplasia. Soft markers were present in 1,380 (49.2%) of all anomaly cases. Critically, 68 (81.0%) of 84 major anomalies occurred in fetuses with ≥ 1 soft marker, compared to only 16 without. This association was highly significant (χ² = 42.6, p < 0.001; OR = 4.6, 95% CI: 2.6–8.1). Conclusions Mid-trimester anomaly scans in Nepal detect a substantial number of clinically significant fetal anomalies. The strong association between soft markers and major structural defects underscores their value as screening indicators, even in settings where advanced diagnostics are unavailable. These findings support the integration of standardized anomaly scans into routine antenatal care across similar low-resource regions. Anomaly scan Congenital anomalies Fetal ultrasound Soft markers Low-resource setting Nepal Prenatal diagnosis Mid-trimester scan Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Congenital anomalies affect an estimated 3–6% of live births globally and are a leading cause of neonatal mortality, particularly in low- and middle-income countries (LMICs) where access to prenatal screening and specialized care is limited ( 1 – 3 ). In Nepal, congenital malformations contribute significantly to infant mortality, with national estimates suggesting a prevalence of 52 per 10,000 live births ( 4 ). Despite this burden, systematic data on prenatal detection rates remain scarce, and routine anomaly screening is not yet standardized across the public health system. The mid-trimester anomaly scan (18–24 weeks’ gestation) is a cornerstone of prenatal care in high-income countries. International guidelines from the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) recommend a detailed anatomical survey during this window to detect structural abnormalities ( 5 ). In such settings, anomaly scans detect over 50% of major congenital malformations, enabling timely counseling, delivery planning, and postnatal intervention ( 6 ). In contrast, ultrasound services in LMICs like Nepal are often limited to basic biometry and placental assessment, with inconsistent attention to detailed fetal anatomy. Operator-dependent practices, lack of standardized protocols, and insufficient training further constrain diagnostic utility ( 7 – 9 ). As a result, many major anomalies go undetected until birth, missing critical opportunities for informed decision-making and perinatal management. Recent studies from South Asia suggest that even basic mid-trimester scans can detect 3–5% of major structural defects. In Nepal, Tamrakar and Shrestha (2020) reported a 3.02% detection rate of congenital anomalies using mid-trimester ultrasound, with 87.8% sensitivity for major malformations( 10 ). Similarly, Thapa et al. (2019) emphasized the value of second-trimester ultrasound in detecting structural defects and guiding clinical management in a Nepali cohort ( 11 ). However, neither study systematically evaluated the role of soft markers such as intracardiac echogenic foci, choroid plexus cysts, or mild ventriculomegaly in predicting major anomalies. While soft markers are often considered benign in high-resource settings, especially when isolated, their clinical significance in LMICs remains unclear. In contexts where advanced diagnostics (e.g., chromosomal microarray, exome sequencing, or fetal MRI) are unavailable, soft markers may serve as realistic red flags for underlying structural pathology ( 12 ). However, to date, no large-scale study from Nepal has systematically evaluated the spectrum of fetal anomalies detected during routine mid-trimester scans or assessed the clinical significance of soft markers in predicting major structural defects. Our study addresses this critical evidence gap by analyzing fetal anomalies detected during routine mid-trimester scans at Paropakar Maternity and Women’s Hospital (PMWH), Nepal’s largest public maternity hospital. Our objectives were to determine the incidence and types of anomalies detected, classify anomalies as major or minor and assess the association between soft markers and major structural defects. By doing so, we aim to provide evidence for national antenatal care guidelines and support the efficient use of limited ultrasound resources in Nepal and other low-resource settings. Methods Study design and setting This retrospective cross-sectional study was conducted at the Department of Radiodiagnosis, Paropakar Maternity and Women’s Hospital (PMWH), Kathmandu, Nepal, a tertiary public hospital performing approximately 12,000 deliveries annually. The study was approved by the Institutional Review Committee (IRC) of PMWH (Ref:65/2340) which granted a waiver of informed consent due to the retrospective and anonymized nature of the data. All patient identifiers were removed prior to analysis to ensure confidentiality. Sample size and data collection The sample size was determined using the standard formula for estimating a population proportion: n = (Z² × p × (1 − p )) / d ², where Z = 1.96 for a 95% confidence level, p = anticipated prevalence of congenital anomalies, and d = margin of error. Based on WHO estimates and regional literature, a conservative prevalence of 10% was assumed to account for potential underreporting in retrospective settings, with a margin of error set at 2% (0.02). This yielded a required sample size of 864 anomaly scans. However, given the availability of a larger dataset, all eligible cases were analyzed to improve precision. The study included all pregnant women who underwent a mid-trimester anomaly scan between 18 and 24 weeks of gestation from January 2021 to April 2023. Data were extracted from archived ultrasound reports in the radiology department using a structured data collection proforma. Records that were incomplete, illegible, or lacked essential documentation were excluded from the analysis. Data Analysis Each detected anomaly was systematically categorized by organ system (central nervous system, renal, gastrointestinal, cardiac, musculoskeletal, facial, or thoracic) and by clinical severity. Anomalies were classified as major if they represented structural defects likely to cause significant morbidity or mortality such as neural tube defects, omphalocele, gastroschisis, holoprosencephaly, major cardiac malformations or as minor/soft markers if they consisted of isolated findings with low predictive value, including intracardiac echogenic foci (IEF), echogenic bowel, choroid plexus cysts (CPC), mild ventriculomegaly (VM), and prominent or dilated cisterna magna. The presence of any soft marker was recorded as a binary variable (yes/no). This classification was performed in accordance with established guidelines from the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) and the American College of Obstetricians and Gynecologists (ACOG)( 13 , 14 ). Data was entered into Microsoft Excel 2016 and subsequently imported into IBM SPSS Statistics version 28 for analysis. Prior to analysis, the dataset underwent rigorous cleaning to ensure completeness, accuracy, and consistency; duplicate entries and incomplete records were excluded. Descriptive statistics were used to summarize the data: frequencies and percentages were reported for categorical variables (e.g., anomaly type, organ system, soft marker presence), while continuous variables such as maternal age and gestational age at scan were summarized using means, medians, and standard deviations where applicable. The distribution of anomaly types was categorized and presented using frequency tables. Cases were further stratified into major and minor anomalies to calculate their respective proportions. To assess associations, Chi-square tests were performed to evaluate the relationship between categorical variables, specifically focusing on the association between soft marker presence and the detection of major anomalies. A p -value of less than 0.05 was considered statistically significant. Odds ratios (OR) with 95% confidence intervals (CI) were calculated to quantify the strength of associations where relevant. Results Out of total 7,812 mid trimester anomaly scans performed at Paropakar Maternity and Women’s Hospital (PMWH), between January 2021 and April 2023, 7,615 mid-trimester anomaly scans were included in the study and remaining 197 scans were excluded due to lack of essential documentation. Of the 7,615 scans included, 2,807 (36.9%) detected at least one fetal anomaly. The annual number of anomaly scans increased progressively over the study period, although the detection rate (% of scans with anomalies) showed a slight decline from 2021 to 2023 (Table 1 ). Table 1 Distribution of Total Ultrasound Scans and Anomaly Scans Year Total Anomaly scans Total anomalies detected n(%) 2021 1,250 487 (39.0) 39.00% 2022 2,800 1080(38.6) 38.60% 2023 3,565 1240(34.8) 34.80% Total 7,615 2807 (36.9) 36.90% When stratified by the organ system involved, Renal anomalies (27.1%), Central nervous system (CNS) findings (26.1%), and gastrointestinal anomalies (21.4%) were most common (Table 2 ). Most of the anomalies recorded were minor anomalies or soft markers, including echogenic bowel (n = 589), intracardiac echogenic foci (n = 429), mild ventriculomegaly (n = 362) and prominent/dilated cisterna magna (n = 279) (Table 3 ). Most of the major anomalies identified were those involving cardiovascular system (Fig. 1 ), Craniofacial structures (Fig. 2 ), limb related anomalies (Fig. 3 ). Few cases of body wall defects like omphalocele and ectopia cordis (Fig. 4 ) were also identified. Table 2 Types and frequencies of anomalies detected. Anomaly Type n (%) Renal anomalies 760 (27.1%) CNS anomalies 732 (26.1%) Gastrointestinal anomalies 602 (21.4%) Cardiac anomalies 452 (16.1%) Multiple System involvement 148 (5.3%) Soft markers (isolated) 89 (3.2%) Facial clefts (CL/CP) 12 (0.4%) Musculoskeletal anomalies 10 (0.4%) Thoracic anomalies 2 (0.1%) Total 2,807 (100%) Table 3 Frequency of Each Specific Anomaly Anomaly Type Frequency (n) Renal Anomalies Hydronephrosis (any) 760 Hydronephrosis (Left) 406 Hydronephrosis (Right) 257 Hydronephrosis (B/L) 97 MCK (Multicystic Kidney) 5 Gastrointestinal Anomalies Echogenic Bowel 589 Gastroschisis 1 Omphalocele 1 CNS Anomalies Mild Ventriculomegaly (U/L) 362 Prominent Cisterna Magna 233 Dilated Cisterna Magna 46 Choroid Plexus Cyst (U/L) 27 Choroid Plexus Cyst (B/L) 6 Anencephaly 2 Encephalocele 2 Holoprosencephaly 2 Spina Bifida with Meningocele/Meningomyelocele 4 Microcephaly / Craniofacial Defect 1 Cardiac Anomalies Intracardiac Echogenic Focus (IEF) 429 Hypoplastic Left Heart 1 Pericardial Effusion (Minimal) 22 Musculoskeletal Anomalies Clubfoot 3 Skeletal Dysplasia 2 Absence of U/L Hand (Acheiria) 1 B/L Hands & Feet Abnormality 1 Facial Clefts Cleft Lip (U/L) 6 Cleft Lip (B/L) 3 Cleft Palate (with Cleft Lip) 1 Thoracic Anomalies CPAM (Congenital Pulmonary Airway Malformation) 1 Diaphragmatic Hernia 1 Soft Markers (Isolated) Single Umbilical Artery (SUA) 19 Two-Vessel Umbilical Cord 19 Mild Ventriculomegaly (B/L) 13 Prominent Lateral Ventricle (U/L) 124 Thickened Nuchal Fold 1 Compound Findings Hydronephrosis + IEF 12 Echogenic Bowel + IEF 17 Echogenic Bowel + CPC 6 Echogenic Bowel + VM 2 IEF + CPC 5 IEF + SUA 2 CPC + SUA 1 Out of the total anomalies detected, 88 (3.1%) were classified as major structural defects and 2,719 (96.9%) had minor anomalies. Critically, soft markers were found to be strongly associated with major anomalies. Of the 1,380 cases with ≥ 1 soft marker, 68 (4.9%) had a major anomaly, compared to only 16 (1.1%) among the 1,427 cases without soft markers (Table 4 ). This association was highly significant (χ² = 42.6, p < 0.001; OR = 4.6, 95% CI: 2.6–8.1). Table 4 Major vs Minor Anomalies Major Anomaly Present No Major Anomaly Total Soft marker present 68 1,312 1,380 Soft marker absent 16 1,411 1,427 Total 84 2,723 2,807 Discussion This study presents the first comprehensive analysis of fetal anomaly detection rates from Paropakar Maternity and Women’s Hospital, Nepal’s largest public maternity hospital. Across a 28-month period from January 2021 to April 2023, we identified 2807 fetal anomalies among 7615 mid-trimester anomaly scans, yielding an overall detection rate of 36.9 percent. While most of those findings were classified as minor variants or soft markers, the identification of 88 major structural anomalies highlights the clinical utility of routine anomaly scanning even in a resource-constrained setting. Our findings carry significant implications for prenatal care policy, sonographer training, and referral systems in Nepal and similar low- and middle-income countries. A striking feature of our dataset is the high prevalence of soft markers such as intracardiac echogenic foci, echogenic bowel, mild ventriculomegaly, and prominent cisterna magna. It reflects both the sensitivity of routine scanning and the lack of standardized reporting criteria in low-resource settings. While these findings are often isolated and benign in high-income countries, our data show they are strongly predictive of major anomalies in Nepal (OR = 4.6). It indicates that fetuses with at least one soft marker were 4.6 times more likely to have a major anomaly compared to those without, with a 95 percent confidence interval of 2.6 to 8.1 and a p value less than 0.001. This suggests that in settings where advanced diagnostics (e.g., fetal MRI, chromosomal microarray, exome sequencing) are unavailable, soft markers should not be dismissed but rather used as triggers for detailed re-evaluation, counseling, delivery planning and, when appropriate, referral to tertiary care centers. The 3.1% detection rate of major anomalies in our cohort aligns closely with prior regional studies. Tamrakar and Shrestha reported a 3.02% anomaly detection rate in a Nepali population using mid-trimester scans, with high sensitivity for structural defects( 10 ). Similarly, studies from India, Pakistan and Bangladesh have documented comparable rates, suggesting a consistent pattern across South Asia( 15 – 17 ). Detection rates in high-income countries may be higher, a gap likely attributable to differences in sonographer training, adherence to standardized scanning protocols such as those recommended by the International Society of Ultrasound in Obstetrics and Gynecology, and access to follow-up imaging. Nevertheless, the absolute number of major anomalies detected in our study, though small in proportion, is clinically significant. These include life-limiting or surgically correctable conditions such as neural tube defects, holoprosencephaly, omphalocele, gastroschisis, congenital diaphragmatic hernia, and skeletal dysplasia. Early identification of such conditions enables informed decision-making by families, facilitates planned delivery at facilities equipped for neonatal surgery, and ultimately reduces perinatal mortality and long-term disability. From a policy perspective, our findings strongly support the integration of standardized anomaly scanning into Nepal’s national antenatal care package. Currently, ultrasound services in most public hospitals are often limited to basic biometry and placental localization, with inconsistent attention to detailed fetal anatomy. Our findings directly inform three key policy priorities in Nepal. First, there is a need for standardized training, which can be achieved by introducing ISUOG-aligned anomaly scan modules into radiology and obstetrics residency programs to ensure consistent and high-quality fetal anomaly detection. Second, the development of a national Nepal Fetal Anomaly Screening Protocol is essential to define clear reporting thresholds for soft markers and guide clinical interpretation in resource-limited settings. Third, establishing well-structured referral pathways with explicit criteria for transferring patients from district hospitals to tertiary centers such as Paropakar Maternity and Women’s Hospital will facilitate timely diagnosis, counseling, and management of pregnancies affected by major structural anomalies. Such measures align with the World Health Organization’s 2023 recommendations for strengthening antenatal ultrasound services in low-resource settings as a cost-effective strategy to reduce perinatal mortality. ( 18 ) This study has several strengths, including its large sample size, real-world setting in a high-volume public hospital, and rigorous classification of anomalies using internationally accepted criteria. However, it also has limitations. The retrospective design precludes postnatal confirmation of prenatal diagnoses, raising the possibility of both over- and under-diagnosis. The single-center nature of the study may limit generalizability to rural or private-sector settings. Additionally, the lack of outcome data such as pregnancy termination rates, neonatal survival, or surgical interventions prevents a full assessment of the clinical impact of anomaly detection. Future research should address these gaps through prospective cohort studies with postnatal follow-up, cost-effectiveness analyses of anomaly screening in Nepal’s public health system, and exploration of community-level barriers to timely antenatal care. Emerging technologies such as artificial intelligence-assisted ultrasound interpretation may also offer scalable solutions to support sonographers in low-resource environments. To sum up, mid-trimester anomaly scans are both feasible and clinically valuable in Nepal’s public maternity hospitals. The strong association between soft markers and major structural defects emphasize their utility as screening tools in settings where advanced diagnostics are unavailable. We recommend the national adoption of standardized anomaly scanning protocols to enhance early detection, improve counseling, and optimize perinatal outcomes across Nepal and similar low-resource regions. Conclusions Finding of the study showed that mid-trimester anomaly scans are feasible, informative, and clinically valuable in Nepal’s public maternity hospitals. The strong association between soft markers and major structural defects supports their use as screening indicators in settings lacking advanced diagnostics. We recommend national adoption of standardized anomaly scanning protocols to improve early detection, counseling, and perinatal outcomes across Nepal and similar low-resource regions. Abbreviations PMWH Paropakar Maternity and Women’s Hospital IEF Intracardiac echogenic focus CPC Choroid plexus cyst VM Ventriculomegaly NTD Neural tube defect HLHS Hypoplastic left heart syndrome ISUOG International Society of Ultrasound in Obstetrics and Gynecology ACOG American College of Obstetricians and Gynecologists Declarations Ethics approval and consent to participate : Approved by the Institutional Review Committee (IRC) of Paropakar Maternity and Women’s Hospital, Kathmandu, Nepal. Waiver of informed consent granted due to retrospective design. Consent for publication : Not applicable. Competing interests: The authors declare that they have no competing interests. Funding: This research received no specific grant. It was self-funded by the authors. Author Contribution AS: Conceptualization, supervision, manuscript review. DP: Data analysis, statistical interpretation, manuscript drafting. MB, SB, PP, AR, AG, JS, BK, DS: Data collection and validation, critical revision. All authors read and approved the final manuscript. Acknowledgement We thank Department of Radiodiagnosis, PMWH and the staff for their cooperation and support throughout the study. Data Availability The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. References Christianson AL, Howson CP, Modell B. Global report on birth defects: the hidden toll of dying and disabled children. White Plains (NY): March of Dimes Birth Defects Foundation; 2006. Centers for Disease Control and Prevention (CDC). Data and Statistics on Birth Defects. https://www.cdc.gov/birth-defects/data-research/facts-stats/index.html . Accessed 24 October 2025. European Platform on Rare Disease Registration. EU RD Platform. https://eu-rd-platform.jrc.ec.europa.eu . Accessed 24 October 2025. Bhandari S, Sayami JT, KC RR, Banjara MR. Prevalence of congenital defects including selected neural tube defects in Nepal: results from a health survey. 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Epidemiological study of congenital anomalies and risk factors in newborn infants at a tertiary care hospital in Bangladesh. Newborn. 2023;2(3):185–90. https://doi.org/10.5005/jp-journals-11002-0071 . World Health Organization. WHO recommendations on antenatal care for a positive pregnancy experience. Geneva: World Health Organization. 2016. https://www.who.int/publications/i/item/9789241549912 . Accessed 24 October 2025. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8187679","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":563694454,"identity":"0c87b3b7-ef64-403d-bb16-436dba65143c","order_by":0,"name":"Abhishek Shah","email":"","orcid":"","institution":"Paropakar Maternity and Women’s Hospital (PMWH)","correspondingAuthor":false,"prefix":"","firstName":"Abhishek","middleName":"","lastName":"Shah","suffix":""},{"id":563694455,"identity":"6ac5f0cc-1c40-41f8-9fc5-167f7d2a4961","order_by":1,"name":"Dipesh 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00:19:30","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":83789,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8187679/v1/681ce89e985756e77561f3bc.html"},{"id":99317118,"identity":"db173aa1-a7db-4d29-98af-9c814abed3d1","added_by":"auto","created_at":"2025-12-31 16:29:40","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":443451,"visible":true,"origin":"","legend":"\u003cp\u003eUSG images showing various cardiac anomalies detected\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8187679/v1/2fd27a143df13a7437439af3.jpeg"},{"id":99316037,"identity":"0fedfa86-dcdd-409a-8ec4-6ef9c183ddf7","added_by":"auto","created_at":"2025-12-31 16:27:37","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1445321,"visible":true,"origin":"","legend":"\u003cp\u003eUSG images showing various craniofacial anomalies\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8187679/v1/5546504e8328bbe02acfcdaa.jpeg"},{"id":99317830,"identity":"e091ef0f-755b-4f5b-af0d-d92abd62f30e","added_by":"auto","created_at":"2025-12-31 16:30:46","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":444246,"visible":true,"origin":"","legend":"\u003cp\u003eUSG images \u0026nbsp;showing some limb anomalies\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8187679/v1/29ed28f9307411ce482926e1.jpeg"},{"id":99188562,"identity":"89301bb3-a93b-4b6f-96af-656b4313730a","added_by":"auto","created_at":"2025-12-30 00:19:30","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":864736,"visible":true,"origin":"","legend":"\u003cp\u003eUSG images showing some miscellaneous findings in different patients\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8187679/v1/25604cf0e1c9537c7d9f3a77.jpeg"},{"id":99323665,"identity":"3376330c-2b4f-45c3-ad47-3630d42b28d5","added_by":"auto","created_at":"2025-12-31 16:45:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3901911,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8187679/v1/7a4d2547-4ddf-451b-9322-b597d805db6b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The importance of mid-trimester anomaly scans in a low-resource setting: a retrospective study of 7,615 mid-trimester anomaly scans at a tertiary maternity hospital in Nepal","fulltext":[{"header":"Background","content":"\u003cp\u003eCongenital anomalies affect an estimated 3\u0026ndash;6% of live births globally and are a leading cause of neonatal mortality, particularly in low- and middle-income countries (LMICs) where access to prenatal screening and specialized care is limited (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In Nepal, congenital malformations contribute significantly to infant mortality, with national estimates suggesting a prevalence of 52 per 10,000 live births (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Despite this burden, systematic data on prenatal detection rates remain scarce, and routine anomaly screening is not yet standardized across the public health system.\u003c/p\u003e \u003cp\u003eThe mid-trimester anomaly scan (18\u0026ndash;24 weeks\u0026rsquo; gestation) is a cornerstone of prenatal care in high-income countries. International guidelines from the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) recommend a detailed anatomical survey during this window to detect structural abnormalities (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In such settings, anomaly scans detect over 50% of major congenital malformations, enabling timely counseling, delivery planning, and postnatal intervention (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In contrast, ultrasound services in LMICs like Nepal are often limited to basic biometry and placental assessment, with inconsistent attention to detailed fetal anatomy. Operator-dependent practices, lack of standardized protocols, and insufficient training further constrain diagnostic utility (\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). As a result, many major anomalies go undetected until birth, missing critical opportunities for informed decision-making and perinatal management.\u003c/p\u003e \u003cp\u003eRecent studies from South Asia suggest that even basic mid-trimester scans can detect 3\u0026ndash;5% of major structural defects. In Nepal, Tamrakar and Shrestha (2020) reported a 3.02% detection rate of congenital anomalies using mid-trimester ultrasound, with 87.8% sensitivity for major malformations(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Similarly, Thapa et al. (2019) emphasized the value of second-trimester ultrasound in detecting structural defects and guiding clinical management in a Nepali cohort (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). However, neither study systematically evaluated the role of soft markers such as intracardiac echogenic foci, choroid plexus cysts, or mild ventriculomegaly in predicting major anomalies. While soft markers are often considered benign in high-resource settings, especially when isolated, their clinical significance in LMICs remains unclear. In contexts where advanced diagnostics (e.g., chromosomal microarray, exome sequencing, or fetal MRI) are unavailable, soft markers may serve as realistic red flags for underlying structural pathology (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). However, to date, no large-scale study from Nepal has systematically evaluated the spectrum of fetal anomalies detected during routine mid-trimester scans or assessed the clinical significance of soft markers in predicting major structural defects.\u003c/p\u003e \u003cp\u003eOur study addresses this critical evidence gap by analyzing fetal anomalies detected during routine mid-trimester scans at Paropakar Maternity and Women\u0026rsquo;s Hospital (PMWH), Nepal\u0026rsquo;s largest public maternity hospital. Our objectives were to determine the incidence and types of anomalies detected, classify anomalies as major or minor and assess the association between soft markers and major structural defects. By doing so, we aim to provide evidence for national antenatal care guidelines and support the efficient use of limited ultrasound resources in Nepal and other low-resource settings.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eThis retrospective cross-sectional study was conducted at the Department of Radiodiagnosis, Paropakar Maternity and Women\u0026rsquo;s Hospital (PMWH), Kathmandu, Nepal, a tertiary public hospital performing approximately 12,000 deliveries annually. The study was approved by the Institutional Review Committee (IRC) of PMWH (Ref:65/2340) which granted a waiver of informed consent due to the retrospective and anonymized nature of the data. All patient identifiers were removed prior to analysis to ensure confidentiality.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample size and data collection\u003c/h3\u003e\n\u003cp\u003eThe sample size was determined using the standard formula for estimating a population proportion: \u003cem\u003en\u003c/em\u003e = (Z\u0026sup2; \u0026times; \u003cem\u003ep\u003c/em\u003e \u0026times; (1\u0026thinsp;\u0026minus;\u0026thinsp;\u003cem\u003ep\u003c/em\u003e)) / \u003cem\u003ed\u003c/em\u003e\u0026sup2;, where \u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.96 for a 95% confidence level, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;anticipated prevalence of congenital anomalies, and \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;margin of error. Based on WHO estimates and regional literature, a conservative prevalence of 10% was assumed to account for potential underreporting in retrospective settings, with a margin of error set at 2% (0.02). This yielded a required sample size of 864 anomaly scans. However, given the availability of a larger dataset, all eligible cases were analyzed to improve precision. The study included all pregnant women who underwent a mid-trimester anomaly scan between 18 and 24 weeks of gestation from January 2021 to April 2023. Data were extracted from archived ultrasound reports in the radiology department using a structured data collection proforma. Records that were incomplete, illegible, or lacked essential documentation were excluded from the analysis.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eEach detected anomaly was systematically categorized by organ system (central nervous system, renal, gastrointestinal, cardiac, musculoskeletal, facial, or thoracic) and by clinical severity. Anomalies were classified as major if they represented structural defects likely to cause significant morbidity or mortality such as neural tube defects, omphalocele, gastroschisis, holoprosencephaly, major cardiac malformations or as minor/soft markers if they consisted of isolated findings with low predictive value, including intracardiac echogenic foci (IEF), echogenic bowel, choroid plexus cysts (CPC), mild ventriculomegaly (VM), and prominent or dilated cisterna magna. The presence of any soft marker was recorded as a binary variable (yes/no). This classification was performed in accordance with established guidelines from the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) and the American College of Obstetricians and Gynecologists (ACOG)(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eData was entered into Microsoft Excel 2016 and subsequently imported into IBM SPSS Statistics version 28 for analysis. Prior to analysis, the dataset underwent rigorous cleaning to ensure completeness, accuracy, and consistency; duplicate entries and incomplete records were excluded. Descriptive statistics were used to summarize the data: frequencies and percentages were reported for categorical variables (e.g., anomaly type, organ system, soft marker presence), while continuous variables such as maternal age and gestational age at scan were summarized using means, medians, and standard deviations where applicable. The distribution of anomaly types was categorized and presented using frequency tables. Cases were further stratified into major and minor anomalies to calculate their respective proportions. To assess associations, Chi-square tests were performed to evaluate the relationship between categorical variables, specifically focusing on the association between soft marker presence and the detection of major anomalies. A \u003cem\u003ep\u003c/em\u003e-value of less than 0.05 was considered statistically significant. Odds ratios (OR) with 95% confidence intervals (CI) were calculated to quantify the strength of associations where relevant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOut of total 7,812 mid trimester anomaly scans performed at Paropakar Maternity and Women\u0026rsquo;s Hospital (PMWH), between January 2021 and April 2023, 7,615 mid-trimester anomaly scans were included in the study and remaining 197 scans were excluded due to lack of essential documentation. Of the 7,615 scans included, 2,807 (36.9%) detected at least one fetal anomaly. The annual number of anomaly scans increased progressively over the study period, although the detection rate (% of scans with anomalies) showed a slight decline from 2021 to 2023 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of Total Ultrasound Scans and Anomaly Scans\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Anomaly scans\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal anomalies detected n(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e487 (39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e39.00%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1080(38.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e38.60%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1240(34.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e34.80%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2807 (36.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e36.90%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhen stratified by the organ system involved, Renal anomalies (27.1%), Central nervous system (CNS) findings (26.1%), and gastrointestinal anomalies (21.4%) were most common (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Most of the anomalies recorded were minor anomalies or soft markers, including echogenic bowel (n\u0026thinsp;=\u0026thinsp;589), intracardiac echogenic foci (n\u0026thinsp;=\u0026thinsp;429), mild ventriculomegaly (n\u0026thinsp;=\u0026thinsp;362) and prominent/dilated cisterna magna (n\u0026thinsp;=\u0026thinsp;279) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Most of the major anomalies identified were those involving cardiovascular system (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), Craniofacial structures (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), limb related anomalies (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Few cases of body wall defects like omphalocele and ectopia cordis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) were also identified.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTypes and frequencies of anomalies detected.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnomaly Type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e760 (27.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCNS anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e732 (26.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastrointestinal anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e602 (21.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiac anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e452 (16.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple System involvement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoft markers (isolated)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacial clefts (CL/CP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMusculoskeletal anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThoracic anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,807 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFrequency of Each Specific Anomaly\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnomaly Type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency (n)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal Anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHydronephrosis (any)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e760\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHydronephrosis (Left)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e406\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHydronephrosis (Right)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e257\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHydronephrosis (B/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMCK (Multicystic Kidney)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastrointestinal Anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEchogenic Bowel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e589\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGastroschisis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOmphalocele\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCNS Anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild Ventriculomegaly (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e362\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProminent Cisterna Magna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e233\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDilated Cisterna Magna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChoroid Plexus Cyst (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChoroid Plexus Cyst (B/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnencephaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEncephalocele\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHoloprosencephaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpina Bifida with Meningocele/Meningomyelocele\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMicrocephaly / Craniofacial Defect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiac Anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntracardiac Echogenic Focus (IEF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e429\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHypoplastic Left Heart\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePericardial Effusion (Minimal)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMusculoskeletal Anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClubfoot\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSkeletal Dysplasia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbsence of U/L Hand (Acheiria)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB/L Hands \u0026amp; Feet Abnormality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacial Clefts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCleft Lip (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCleft Lip (B/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCleft Palate (with Cleft Lip)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThoracic Anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCPAM (Congenital Pulmonary Airway Malformation)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiaphragmatic Hernia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoft Markers (Isolated)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle Umbilical Artery (SUA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTwo-Vessel Umbilical Cord\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild Ventriculomegaly (B/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProminent Lateral Ventricle (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThickened Nuchal Fold\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound Findings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHydronephrosis\u0026thinsp;+\u0026thinsp;IEF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEchogenic Bowel\u0026thinsp;+\u0026thinsp;IEF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEchogenic Bowel\u0026thinsp;+\u0026thinsp;CPC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEchogenic Bowel\u0026thinsp;+\u0026thinsp;VM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIEF\u0026thinsp;+\u0026thinsp;CPC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIEF\u0026thinsp;+\u0026thinsp;SUA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCPC\u0026thinsp;+\u0026thinsp;SUA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOut of the total anomalies detected, 88 (3.1%) were classified as major structural defects and 2,719 (96.9%) had minor anomalies.\u003c/p\u003e \u003cp\u003eCritically, soft markers were found to be strongly associated with major anomalies. Of the 1,380 cases with \u0026ge;\u0026thinsp;1 soft marker, 68 (4.9%) had a major anomaly, compared to only 16 (1.1%) among the 1,427 cases without soft markers (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This association was highly significant (χ\u0026sup2; = 42.6, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; OR\u0026thinsp;=\u0026thinsp;4.6, 95% CI: 2.6\u0026ndash;8.1).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMajor vs Minor Anomalies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMajor Anomaly Present\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo Major Anomaly\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoft marker present\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,380\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoft marker absent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,427\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2,807\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study presents the first comprehensive analysis of fetal anomaly detection rates from Paropakar Maternity and Women\u0026rsquo;s Hospital, Nepal\u0026rsquo;s largest public maternity hospital. Across a 28-month period from January 2021 to April 2023, we identified 2807 fetal anomalies among 7615 mid-trimester anomaly scans, yielding an overall detection rate of 36.9 percent. While most of those findings were classified as minor variants or soft markers, the identification of 88 major structural anomalies highlights the clinical utility of routine anomaly scanning even in a resource-constrained setting. Our findings carry significant implications for prenatal care policy, sonographer training, and referral systems in Nepal and similar low- and middle-income countries.\u003c/p\u003e \u003cp\u003eA striking feature of our dataset is the high prevalence of soft markers such as intracardiac echogenic foci, echogenic bowel, mild ventriculomegaly, and prominent cisterna magna. It reflects both the sensitivity of routine scanning and the lack of standardized reporting criteria in low-resource settings. While these findings are often isolated and benign in high-income countries, our data show they are strongly predictive of major anomalies in Nepal (OR\u0026thinsp;=\u0026thinsp;4.6).\u003c/p\u003e \u003cp\u003eIt indicates that fetuses with at least one soft marker were 4.6 times more likely to have a major anomaly compared to those without, with a 95 percent confidence interval of 2.6 to 8.1 and a p value less than 0.001. This suggests that in settings where advanced diagnostics (e.g., fetal MRI, chromosomal microarray, exome sequencing) are unavailable, soft markers should not be dismissed but rather used as triggers for detailed re-evaluation, counseling, delivery planning and, when appropriate, referral to tertiary care centers.\u003c/p\u003e \u003cp\u003eThe 3.1% detection rate of major anomalies in our cohort aligns closely with prior regional studies. Tamrakar and Shrestha reported a 3.02% anomaly detection rate in a Nepali population using mid-trimester scans, with high sensitivity for structural defects(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Similarly, studies from India, Pakistan and Bangladesh have documented comparable rates, suggesting a consistent pattern across South Asia(\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Detection rates in high-income countries may be higher, a gap likely attributable to differences in sonographer training, adherence to standardized scanning protocols such as those recommended by the International Society of Ultrasound in Obstetrics and Gynecology, and access to follow-up imaging. Nevertheless, the absolute number of major anomalies detected in our study, though small in proportion, is clinically significant. These include life-limiting or surgically correctable conditions such as neural tube defects, holoprosencephaly, omphalocele, gastroschisis, congenital diaphragmatic hernia, and skeletal dysplasia. Early identification of such conditions enables informed decision-making by families, facilitates planned delivery at facilities equipped for neonatal surgery, and ultimately reduces perinatal mortality and long-term disability.\u003c/p\u003e \u003cp\u003eFrom a policy perspective, our findings strongly support the integration of standardized anomaly scanning into Nepal\u0026rsquo;s national antenatal care package. Currently, ultrasound services in most public hospitals are often limited to basic biometry and placental localization, with inconsistent attention to detailed fetal anatomy. Our findings directly inform three key policy priorities in Nepal. First, there is a need for standardized training, which can be achieved by introducing ISUOG-aligned anomaly scan modules into radiology and obstetrics residency programs to ensure consistent and high-quality fetal anomaly detection. Second, the development of a national Nepal Fetal Anomaly Screening Protocol is essential to define clear reporting thresholds for soft markers and guide clinical interpretation in resource-limited settings. Third, establishing well-structured referral pathways with explicit criteria for transferring patients from district hospitals to tertiary centers such as Paropakar Maternity and Women\u0026rsquo;s Hospital will facilitate timely diagnosis, counseling, and management of pregnancies affected by major structural anomalies. Such measures align with the World Health Organization\u0026rsquo;s 2023 recommendations for strengthening antenatal ultrasound services in low-resource settings as a cost-effective strategy to reduce perinatal mortality. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThis study has several strengths, including its large sample size, real-world setting in a high-volume public hospital, and rigorous classification of anomalies using internationally accepted criteria. However, it also has limitations. The retrospective design precludes postnatal confirmation of prenatal diagnoses, raising the possibility of both over- and under-diagnosis. The single-center nature of the study may limit generalizability to rural or private-sector settings. Additionally, the lack of outcome data such as pregnancy termination rates, neonatal survival, or surgical interventions prevents a full assessment of the clinical impact of anomaly detection.\u003c/p\u003e \u003cp\u003eFuture research should address these gaps through prospective cohort studies with postnatal follow-up, cost-effectiveness analyses of anomaly screening in Nepal\u0026rsquo;s public health system, and exploration of community-level barriers to timely antenatal care. Emerging technologies such as artificial intelligence-assisted ultrasound interpretation may also offer scalable solutions to support sonographers in low-resource environments.\u003c/p\u003e \u003cp\u003eTo sum up, mid-trimester anomaly scans are both feasible and clinically valuable in Nepal\u0026rsquo;s public maternity hospitals. The strong association between soft markers and major structural defects emphasize their utility as screening tools in settings where advanced diagnostics are unavailable. We recommend the national adoption of standardized anomaly scanning protocols to enhance early detection, improve counseling, and optimize perinatal outcomes across Nepal and similar low-resource regions.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eFinding of the study showed that mid-trimester anomaly scans are feasible, informative, and clinically valuable in Nepal\u0026rsquo;s public maternity hospitals. The strong association between soft markers and major structural defects supports their use as screening indicators in settings lacking advanced diagnostics. We recommend national adoption of standardized anomaly scanning protocols to improve early detection, counseling, and perinatal outcomes across Nepal and similar low-resource regions.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePMWH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eParopakar Maternity and Women\u0026rsquo;s Hospital\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIEF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntracardiac echogenic focus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCPC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChoroid plexus cyst\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVentriculomegaly\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNTD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNeural tube defect\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHLHS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHypoplastic left heart syndrome\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eISUOG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Society of Ultrasound in Obstetrics and Gynecology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACOG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmerican College of Obstetricians and Gynecologists\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003e \u003cb\u003eEthics approval and consent to participate\u003c/b\u003e:\u003c/strong\u003e \u003cp\u003eApproved by the Institutional Review Committee (IRC) of Paropakar Maternity and Women\u0026rsquo;s Hospital, Kathmandu, Nepal. Waiver of informed consent granted due to retrospective design.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003e \u003cb\u003eConsent for publication\u003c/b\u003e:\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests:\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis research received no specific grant. It was self-funded by the authors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAS: Conceptualization, supervision, manuscript review. DP: Data analysis, statistical interpretation, manuscript drafting. MB, SB, PP, AR, AG, JS, BK, DS: Data collection and validation, critical revision. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank Department of Radiodiagnosis, PMWH and the staff for their cooperation and support throughout the study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChristianson AL, Howson CP, Modell B. Global report on birth defects: the hidden toll of dying and disabled children. White Plains (NY): March of Dimes Birth Defects Foundation; 2006.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCenters for Disease Control and Prevention (CDC). 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WHO recommendations on antenatal care for a positive pregnancy experience. Geneva: World Health Organization. 2016. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/9789241549912\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/9789241549912\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 24 October 2025.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Anomaly scan, Congenital anomalies, Fetal ultrasound, Soft markers, Low-resource setting, Nepal, Prenatal diagnosis, Mid-trimester scan","lastPublishedDoi":"10.21203/rs.3.rs-8187679/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8187679/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCongenital anomalies are a leading cause of perinatal mortality in low- and middle-income countries. While mid-trimester anomaly scans are standard in high-income settings, their utility in Nepal remains undocumented. This study evaluates the spectrum, frequency, and clinical significance of fetal anomalies detected during routine anomaly scans at Nepal\u0026rsquo;s largest maternity hospital.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA retrospective cross-sectional study was conducted at Paropakar Maternity and Women\u0026rsquo;s Hospital (PMWH), analyzing all mid-trimester anomaly scans (18\u0026ndash;24 weeks) performed between January 2021 and April 2023. Anomalies were classified as major (structurally significant) or minor/soft markers (e.g., echogenic bowel, intracardiac echogenic focus). Data were summarized using descriptive statistics, and associations were assessed using Chi-square test.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOf 7,615 anomaly scans, 2,807 (36.9%) detected at least one anomaly. The most common findings were hydronephrosis (27.1%), echogenic bowel (21.4%), and central nervous system variants (26.1%). Only 88 (3.1%) were major anomalies, including neural tube defects (n\u0026thinsp;=\u0026thinsp;8), holoprosencephaly (n\u0026thinsp;=\u0026thinsp;2), omphalocele, gastroschisis, and skeletal dysplasia. Soft markers were present in 1,380 (49.2%) of all anomaly cases. Critically, 68 (81.0%) of 84 major anomalies occurred in fetuses with \u0026ge;\u0026thinsp;1 soft marker, compared to only 16 without. This association was highly significant (χ\u0026sup2; = 42.6, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; OR\u0026thinsp;=\u0026thinsp;4.6, 95% CI: 2.6\u0026ndash;8.1).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMid-trimester anomaly scans in Nepal detect a substantial number of clinically significant fetal anomalies. The strong association between soft markers and major structural defects underscores their value as screening indicators, even in settings where advanced diagnostics are unavailable. These findings support the integration of standardized anomaly scans into routine antenatal care across similar low-resource regions.\u003c/p\u003e","manuscriptTitle":"The importance of mid-trimester anomaly scans in a low-resource setting: a retrospective study of 7,615 mid-trimester anomaly scans at a tertiary maternity hospital in Nepal","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-30 00:19:25","doi":"10.21203/rs.3.rs-8187679/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-06T16:05:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-01T21:27:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-30T15:50:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"66241685566020980667655663221083799805","date":"2025-12-21T16:21:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"66720073824777263173553784397199035762","date":"2025-12-21T12:12:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-19T11:34:27+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-25T10:50:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-25T10:29:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-25T10:27:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2025-11-23T21:03:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6d9f6126-03e0-4d7d-bca3-f1d4193dad73","owner":[],"postedDate":"December 30th, 2025","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-06T16:05:59+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-17T02:53:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-30 00:19:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8187679","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8187679","identity":"rs-8187679","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}