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Record W4413095378 · doi:10.1016/j.nurpra.2025.105476

Nurse Practitioners Driving Virtual Postpartum Care

2025· article· en· W4413095378 on OpenAlexfundno aff
Leah Spiro, Galen Cook‐Wiens, Wei-Ti Chen, Nancy Jo Bush, Margo Minissian

Bibliographic record

VenueThe Journal for Nurse Practitioners · 2025
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
FundersUniversity of California, Los AngelesCommission de la santé mentale du Canada
KeywordsNurse practitionersNursingMedicineHealth carePolitical science

Abstract

fetched live from OpenAlex

Hypertensive disorders of pregnancy account for 2.5% to 4.6% of readmissions within 6 weeks postpartum (PP). A standardized approach to hypertensive disorders of pregnancy using remote patient monitoring may improve outcomes through optimized PP blood pressure (BP) management. The feasibility of a standardized nurse practitioner (NP)–driven remote patient monitoring protocol was measured to optimize BPs in the immediate PP period and was successfully demonstrated in a pilot sample (n = 30) at 0.767 (CI = 0.577-0.885; P = .0027) using an exact binomial test. Overall participant adherence was 91.23%, and overall satisfaction was 92%. Future work to improve systems innovation for BP optimization in PP patients is needed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.090
Threshold uncertainty score0.302

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0900.028

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.332
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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