Evidence map›Paper›PMID 42656316›Full record

ArticleAJOG global reports2026

Digital and AI-assisted approaches across the preeclampsia care pathway: a scoping review.

Ova Emilia, Susaldi Susaldi, Yova Agustini, Meita Dhamayanti, Fanni Hanifa, Hardinsyah Hardinsyah, Triagung Yuliyana, Salma Widya Azhari

Abstract read
In one paragraph

Article in AJOG global reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ova EmiliaDepartment of Obstetrics and Gynecology, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia (Emilia).
Susaldi SusaldiFaculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia (Susaldi, Agustini).
Yova AgustiniFaculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia (Susaldi, Agustini).
Meita DhamayantiFaculty of Medicine, Universitas Padjadjaran, Bandung, Indonesia (Dhamayanti, Hanifa).
Fanni HanifaFaculty of Health Sciences, Universitas Indonesia Maju, Jakarta, Indonesia (Hanifa, Yuliyana).
Hardinsyah HardinsyahFaculty of Medicine and Nutrition, IPB University, Bogor, Indonesia (Hardinsyah, Yuliyana, Azhari).
Triagung YuliyanaFaculty of Health Sciences, Universitas Indonesia Maju, Jakarta, Indonesia (Hanifa, Yuliyana).
Salma Widya AzhariFaculty of Medicine and Nutrition, IPB University, Bogor, Indonesia (Hardinsyah, Yuliyana, Azhari).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo map peer-reviewed evidence across four linked functions of digital and AI-assisted preeclampsia care-risk prediction, patient education, remote blood pressure monitoring, and clinician-directed escalation-and determine whether these functions have been evaluated together as an integrated clinical service. DATA SOURCES: PubMed, Scopus, and ScienceDirect were searched for records published from January 2010 to May 11, 2026. STUDY ELIGIBILITY CRITERIA: Peer-reviewed original empirical and technical studies of artificial intelligence, machine learning, clinical decision support, telemedicine, mobile health, remote monitoring, digital education, or care escalation for preeclampsia or hypertensive disorders of pregnancy were eligible. Reviews, protocols, conference abstracts without a full report, editorials, and opinion articles were excluded. STUDY APPRAISAL AND SYNTHESIS

methodsThe review followed PRISMA-ScR and Joanna Briggs Institute guidance. Two reviewers independently screened records. One reviewer charted data and a second independently verified them. Findings were organized by the four predefined functions and synthesized thematically. Formal critical appraisal was not performed; the synthesis therefore describes the evidence map rather than certainty or implementation readiness.

resultsThe searches identified 1396 records. After 313 duplicates were removed, 1083 records were screened, and 320 full-text articles were assessed; 286 full-text articles were excluded, and 34 studies conducted in diverse single- and multicountry settings were included. Prediction models reported favorable discrimination estimates, but calibration, independent validation, and equity assessment were inconsistent. Remote monitoring findings were mixed: BUMP 1 did not show earlier clinic-recorded detection of hypertension, whereas some replacement-care models reduced visits or admissions without an observed increase in adverse outcomes. Education studies mainly examined hypothetical responses or communication gaps rather than measured behavior change. Adoption surveys and qualitative implementation studies did not establish clinical effectiveness. No study prospectively evaluated all four functions as a coordinated service; this was treated as a descriptive observation, not evidence of effectiveness or novelty.

conclusionComponent evidence supports staged study, not routine implementation of an integrated pathway. Searching three electronic information sources, excluding gray literature, and not performing formal appraisal may have omitted relevant implementation evidence. Future codesigned prospective studies should evaluate calibration, safety, workload, equity, and maternal and perinatal outcomes.

Indexed as

antenatal servicesclinical decision supportdigital healthhealth equityhypertensive disorders of pregnancyimplementation sciencematernal healthmobile healthpatient educationrisk prediction

Identifiers

PMID42656316
PMCPMC13506530

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.