AI Blind-Sweep Ultrasound for Antenatal Screening by Non-Specialist Health Workers in Rural DR Congo (FS2)
Diagnostic Accuracy and Implementation Feasibility of AI-Assisted Blind Ultrasound Sweep (SPAQ E-con AI) for Antenatal Screening by Non-Specialist Health Workers in Rural Democratic Republic of the Congo
Descripción general del estudio
Estado
Estado
Condiciones
Condiciones
Intervención / Tratamiento
Intervención / Tratamiento
Descripción detallada
Study conduct is organised in Batches. Batch 1 (Centre de Sante CBCO, Kenge health zone, Kwango province) enrolled 80 participants, of whom 78 had complete datasets, and is closed. Batch 2 is planned at approximately 1,300 participants. The confirmatory analysis cut is approximately 130 to 160 cases acquired with a model frozen before collection, comprising a core set of 80 to 100, an early-gestation enrichment of 25 to 30, and an upper-gestational-age enrichment of 25 to 30. Enrolment may stop early once the pre-specified confidence-interval criteria for the two primary gestational-age outcomes are met. The registered enrolment ceiling of 3,000 is unchanged.
Sites are facilities of the Kenge health zone, Kwango province, within the perimeter already approved in the protocol (up to 6 facilities plus 2 to 5 village outreach sites).
Eligibility follows the protocol: pregnant women aged 18 years or older. Multiple pregnancies are eligible.
Two sub-cohorts address the bounds of the gestational-age range. The early sub-cohort (crown-rump length 7 to 84 mm, approximately under 14 weeks) draws on the same source population as Cohort B-2 and is recruited through community health worker (RECO) village outreach and neighbouring health facilities; it is reported descriptively. The upper-bound sub-cohort (35 weeks or more) is a separate validation subset, recruited in parallel and analysed separately; sensitivity and specificity are reported, and positive and negative predictive values are not reported because prevalence in this subset is artificial.
The registered Trimester 3 estimation window (28 to 36 weeks) is unchanged. In Batch 2, point estimates are reported for 28 to 34 weeks, and 35 to 36 weeks is handled as "to be confirmed / refer". This is an operational reporting restriction, not a change to the registered window.
The AI model is identified and frozen before each Batch and recorded in a model and application version registry under a pre-determined change control plan. Results are reported by frozen version. AI inference is not used for clinical decision-making.
Tipo de estudio
Tipo de estudio
Inscripción (Estimado)
Inscripción
Contactos y Ubicaciones
Estudio Contacto
Estudio Contacto
- Nombre: Kuniyuki Furuta
- Número de teléfono: +818099740409
- Correo electrónico: furuta@soik.co.jp
Ubicaciones de estudio
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Kwango
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Kenge, Kwango, República Democrática del Congo
- Reclutamiento
- Centre de Sante CBCO
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Contacto:
- Henoch Bulu
- Número de teléfono: +243812268392
- Correo electrónico: drhenochbulu@gmail.com
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Criterios de participación
Criterio de elegibilidad
Criterio de elegibilidad
Edades elegibles para estudiar
- Adulto
- Adulto Mayor
Acepta Voluntarios Saludables
Método de muestreo
Población de estudio
Descripción
Inclusion Criteria:
- Pregnant women aged 18 years or older
- Identified at a participating facility routine ANC visit or RECO village outreach within the Kenge health zone catchment
- Written informed consent obtained
Exclusion Criteria:
- Emergency presentation
- Duplicate re-registration of an already-enrolled woman
- Lacking capacity to consent
- Planned relocation outside Kwango province during the study period
- Refusal of consent
Plan de estudios
¿Cómo está diseñado el estudio?
Detalles de diseño
Número de grupos/cohortes
Cohortes e Intervenciones
Grupo / CohorteGrupo / Cohorte |
Intervención / TratamientoIntervención / Tratamiento |
|---|---|
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Cohort A
Natural enrollment / Description: Consecutive ANC attendees (natural prevalence)
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Smartphone-based 9-sweep obstetric ultrasound with AI estimation of gestational age, fetal presentation, and placenta location, operated by trained non-specialist health workers after 30-60 minutes of training.
The AI model is frozen before each Batch and managed in a version registry under a pre-determined change control plan (PCCP); AI inference is not used for clinical decision-making.
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Cohort B-1 Placenta/malpresentation enriched
Enriched validation subset for placenta praevia and fetal malpresentation
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Smartphone-based 9-sweep obstetric ultrasound with AI estimation of gestational age, fetal presentation, and placenta location, operated by trained non-specialist health workers after 30-60 minutes of training.
The AI model is frozen before each Batch and managed in a version registry under a pre-determined change control plan (PCCP); AI inference is not used for clinical decision-making.
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Cohort B-2 - Trimester 1 (CRL/GS) enriched
Enriched trimester 1 cases for CRL/GS gestational age models
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Smartphone-based 9-sweep obstetric ultrasound with AI estimation of gestational age, fetal presentation, and placenta location, operated by trained non-specialist health workers after 30-60 minutes of training.
The AI model is frozen before each Batch and managed in a version registry under a pre-determined change control plan (PCCP); AI inference is not used for clinical decision-making.
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Cohort B-3 - Early gestation (CRL 7-84 mm) enriched
Early-gestation enrichment sub-cohort: crown-rump length 7-84 mm, approximately under 14 weeks of gestation.
Drawn from the same source population as Cohort B-2 and recruited through community health worker (RECO) village outreach and neighbouring health facilities.
Reported descriptively.
|
Smartphone-based 9-sweep obstetric ultrasound with AI estimation of gestational age, fetal presentation, and placenta location, operated by trained non-specialist health workers after 30-60 minutes of training.
The AI model is frozen before each Batch and managed in a version registry under a pre-determined change control plan (PCCP); AI inference is not used for clinical decision-making.
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Cohort B-4 - Upper gestational-age bound (>=35 weeks) validation subset
Validation subset at the upper bound of the gestational-age range (35 weeks of gestation or more), recruited in parallel with the main cohort and analysed separately.
Sensitivity and specificity are reported.
Positive and negative predictive values are not reported, because prevalence in this subset is artificial.
|
Smartphone-based 9-sweep obstetric ultrasound with AI estimation of gestational age, fetal presentation, and placenta location, operated by trained non-specialist health workers after 30-60 minutes of training.
The AI model is frozen before each Batch and managed in a version registry under a pre-determined change control plan (PCCP); AI inference is not used for clinical decision-making.
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¿Qué mide el estudio?
Medidas de resultado primarias
Medidas de resultado primarias
Medida de resultado |
Medida Descripción |
Periodo de tiempo |
|---|---|---|
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Gestational age mean absolute error (MAE), Trimester 2 (14-27 weeks)
Periodo de tiempo: Through study completion, up to 12 months
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MAE in days vs reference standard, with 95% CI; target MAE ≤7 days and upper 95% CI ≤10 days
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Through study completion, up to 12 months
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Gestational age mean absolute error (MAE), Trimester 3 (28-36 weeks)
Periodo de tiempo: Through study completion, up to 12 months
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MAE in days vs reference standard, with 95% CI; target MAE ≤10 days and upper 95% CI ≤14 days
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Through study completion, up to 12 months
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AI confidence calibration - Expected Calibration Error (ECE)
Periodo de tiempo: At Batch 1 closure, up to 8 weeks
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Expected Calibration Error from the reliability diagram of AI confidence versus reference-standard agreement; target <=0.05
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At Batch 1 closure, up to 8 weeks
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AI confidence calibration - Brier score
Periodo de tiempo: At Batch 1 closure, up to 8 weeks
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Brier score of AI confidence versus reference-standard agreement; target <=0.20
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At Batch 1 closure, up to 8 weeks
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Medidas de resultado secundarias
Medidas de resultado secundarias
Medida de resultado |
Medida Descripción |
Periodo de tiempo |
|---|---|---|
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Trimester 1 gestational age MAE (CRL and GS models)
Periodo de tiempo: Through study completion, up to 12 months
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Integrated Cohort A T1 + Cohort B-2, N=30; CRL model MAE ≤5 days or GS model MAE ≤7 days
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Through study completion, up to 12 months
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Placenta praevia and fetal malpresentation sensitivity and specificity
Periodo de tiempo: Through study completion, up to 12 months
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Observed sensitivity/specificity with 95% CI (Clopper-Pearson) on enriched validation subset (Cohort B-1, target N=20-25); reported as observed values
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Through study completion, up to 12 months
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Inter-rater reliability of gestational age - Intraclass Correlation Coefficient (ICC)
Periodo de tiempo: During the inter-rater assessment window, up to 1 week
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ICC(2,1) between two independent readers for gestational age in days
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During the inter-rater assessment window, up to 1 week
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Inter-rater reliability of placenta praevia classification - Cohen's kappa
Periodo de tiempo: During the inter-rater assessment window, up to 1 week
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Cohen's kappa for placenta praevia (yes/no) between two independent readers
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During the inter-rater assessment window, up to 1 week
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Inter-rater reliability of fetal presentation classification - weighted kappa
Periodo de tiempo: During the inter-rater assessment window, up to 1 week
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Linear weighted kappa for fetal presentation category between two independent readers
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During the inter-rater assessment window, up to 1 week
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Acceptability - Acceptability of Intervention Measure (AIM) score
Periodo de tiempo: Through study completion, up to 12 months
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Mean AIM score (4-item, 5-point Likert) among health workers
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Through study completion, up to 12 months
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Feasibility - ultrasound throughput (scans per device per day)
Periodo de tiempo: Through study completion, up to 12 months
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Number of scans completed per device per day; target >=15
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Through study completion, up to 12 months
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Fidelity - protocol adherence rate (5-item checklist)
Periodo de tiempo: Through study completion, up to 12 months
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Percentage adherence on a 5-item fidelity checklist; target >=80%
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Through study completion, up to 12 months
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Penetration - proportion of eligible women screened
Periodo de tiempo: Through study completion, up to 12 months
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Percentage of eligible women in the catchment screened with AI ultrasound
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Through study completion, up to 12 months
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Sustainability - intention to continue use
Periodo de tiempo: At study completion, up to 12 months
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Percentage of staff reporting intention to continue use at the end-of-study interview
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At study completion, up to 12 months
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Colaboradores e Investigadores
Patrocinador
Patrocinador
Investigadores
Investigadores
- Investigador principal: Kuniyuki Furuta, SOIK Corporation
Fechas de registro del estudio
Fechas importantes del estudio
Inicio del estudio (Actual)
Inicio del estudio
Finalización primaria (Estimado)
Finalización primaria
Finalización del estudio (Estimado)
Finalización del estudio
Fechas de registro del estudio
Enviado por primera vez
Enviado por primera vez
Primero enviado que cumplió con los criterios de control de calidad
Primero enviado que cumplió con los criterios de control de calidad
Publicado por primera vez (Actual)
Publicado por primera vez
Actualizaciones de registros de estudio
Última actualización publicada (Actual)
Última actualización publicada
Última actualización enviada que cumplió con los criterios de control de calidad
Última actualización enviada que cumplió con los criterios de control de calidad
Última verificación
Última verificación
Más información
Términos relacionados con este estudio
Palabras clave
Términos MeSH relevantes adicionales
Otros números de identificación del estudio
Otros números de identificación del estudio
- SOIK-FS2-2026
Plan de datos de participantes individuales (IPD)
¿Planea compartir datos de participantes individuales (IPD)?
Información sobre medicamentos y dispositivos, documentos del estudio
Estudia un producto farmacéutico regulado por la FDA de EE. UU.
Estudia un producto de dispositivo regulado por la FDA de EE. UU.
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