- ICH GCP
- Rejestr badań klinicznych w USA
- Badanie kliniczne NCT07677670
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
Przegląd badań
Status
Interwencja / Leczenie
Szczegółowy opis
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.
Typ studiów
Zapisy (Szacowany)
Kontakty i lokalizacje
Kontakt w sprawie studiów
- Nazwa: Kuniyuki Furuta
- Numer telefonu: +818099740409
- E-mail: furuta@soik.co.jp
Lokalizacje studiów
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Kwango
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Kenge, Kwango, Demokratyczna Republika Kongo
- Rekrutacyjny
- Centre de Sante CBCO
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Kontakt:
- Henoch Bulu
- Numer telefonu: +243812268392
- E-mail: drhenochbulu@gmail.com
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-
Kryteria uczestnictwa
Kryteria kwalifikacji
Wiek uprawniający do nauki
- Dorosły
- Starszy dorosły
Akceptuje zdrowych ochotników
Metoda próbkowania
Badana populacja
Opis
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 studiów
Jak projektuje się badanie?
Szczegóły projektu
Kohorty i interwencje
Grupa / Kohorta |
Interwencja / Leczenie |
|---|---|
|
Cohort A
Natural enrollment / Description: Consecutive ANC attendees (natural prevalence)
|
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.
|
|
Cohort B-1 Placenta/malpresentation enriched
Enriched validation subset for placenta praevia and fetal malpresentation
|
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.
|
|
Cohort B-2 - Trimester 1 (CRL/GS) enriched
Enriched trimester 1 cases for CRL/GS gestational age models
|
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.
|
|
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.
|
|
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.
|
Co mierzy badanie?
Podstawowe miary wyniku
Miara wyniku |
Opis środka |
Ramy czasowe |
|---|---|---|
|
Gestational age mean absolute error (MAE), Trimester 2 (14-27 weeks)
Ramy czasowe: Through study completion, up to 12 months
|
MAE in days vs reference standard, with 95% CI; target MAE ≤7 days and upper 95% CI ≤10 days
|
Through study completion, up to 12 months
|
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Gestational age mean absolute error (MAE), Trimester 3 (28-36 weeks)
Ramy czasowe: Through study completion, up to 12 months
|
MAE in days vs reference standard, with 95% CI; target MAE ≤10 days and upper 95% CI ≤14 days
|
Through study completion, up to 12 months
|
|
AI confidence calibration - Expected Calibration Error (ECE)
Ramy czasowe: 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
Ramy czasowe: At Batch 1 closure, up to 8 weeks
|
Brier score of AI confidence versus reference-standard agreement; target <=0.20
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At Batch 1 closure, up to 8 weeks
|
Miary wyników drugorzędnych
Miara wyniku |
Opis środka |
Ramy czasowe |
|---|---|---|
|
Trimester 1 gestational age MAE (CRL and GS models)
Ramy czasowe: Through study completion, up to 12 months
|
Integrated Cohort A T1 + Cohort B-2, N=30; CRL model MAE ≤5 days or GS model MAE ≤7 days
|
Through study completion, up to 12 months
|
|
Placenta praevia and fetal malpresentation sensitivity and specificity
Ramy czasowe: Through study completion, up to 12 months
|
Observed sensitivity/specificity with 95% CI (Clopper-Pearson) on enriched validation subset (Cohort B-1, target N=20-25); reported as observed values
|
Through study completion, up to 12 months
|
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Inter-rater reliability of gestational age - Intraclass Correlation Coefficient (ICC)
Ramy czasowe: During the inter-rater assessment window, up to 1 week
|
ICC(2,1) between two independent readers for gestational age in days
|
During the inter-rater assessment window, up to 1 week
|
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Inter-rater reliability of placenta praevia classification - Cohen's kappa
Ramy czasowe: During the inter-rater assessment window, up to 1 week
|
Cohen's kappa for placenta praevia (yes/no) between two independent readers
|
During the inter-rater assessment window, up to 1 week
|
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Inter-rater reliability of fetal presentation classification - weighted kappa
Ramy czasowe: During the inter-rater assessment window, up to 1 week
|
Linear weighted kappa for fetal presentation category between two independent readers
|
During the inter-rater assessment window, up to 1 week
|
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Acceptability - Acceptability of Intervention Measure (AIM) score
Ramy czasowe: Through study completion, up to 12 months
|
Mean AIM score (4-item, 5-point Likert) among health workers
|
Through study completion, up to 12 months
|
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Feasibility - ultrasound throughput (scans per device per day)
Ramy czasowe: Through study completion, up to 12 months
|
Number of scans completed per device per day; target >=15
|
Through study completion, up to 12 months
|
|
Fidelity - protocol adherence rate (5-item checklist)
Ramy czasowe: Through study completion, up to 12 months
|
Percentage adherence on a 5-item fidelity checklist; target >=80%
|
Through study completion, up to 12 months
|
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Penetration - proportion of eligible women screened
Ramy czasowe: Through study completion, up to 12 months
|
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
Ramy czasowe: At study completion, up to 12 months
|
Percentage of staff reporting intention to continue use at the end-of-study interview
|
At study completion, up to 12 months
|
Współpracownicy i badacze
Sponsor
Śledczy
- Główny śledczy: Kuniyuki Furuta, SOIK Corporation
Daty zapisu na studia
Główne daty studiów
Rozpoczęcie studiów (Rzeczywisty)
Zakończenie podstawowe (Szacowany)
Ukończenie studiów (Szacowany)
Daty rejestracji na studia
Pierwszy przesłany
Pierwszy przesłany, który spełnia kryteria kontroli jakości
Pierwszy wysłany (Rzeczywisty)
Aktualizacje rekordów badań
Ostatnia wysłana aktualizacja (Rzeczywisty)
Ostatnia przesłana aktualizacja, która spełniała kryteria kontroli jakości
Ostatnia weryfikacja
Więcej informacji
Terminy związane z tym badaniem
Słowa kluczowe
Dodatkowe istotne warunki MeSH
Inne numery identyfikacyjne badania
- SOIK-FS2-2026
Plan dla danych uczestnika indywidualnego (IPD)
Planujesz udostępniać dane poszczególnych uczestników (IPD)?
Informacje o lekach i urządzeniach, dokumenty badawcze
Bada produkt leczniczy regulowany przez amerykańską FDA
Bada produkt urządzenia regulowany przez amerykańską FDA
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