Evidence map›Paper›PMID 42160455›Full record

Observational studyPLoS medicine2026

Associations between hematologic dynamics during pregnancy and obstetric complications: A retrospective observational study.

Veronica Tozzo, Rachel Petherbridge, Kaitlyn James, Sarah Hsu, Deepti Pant, Chloe Michalopoulos, Brody H Foy, Tanayott Thaweethai, Christopher Mow, Jacqueline Maya and 6 more

Abstract readObservational Study
In one paragraph

Observational study in PLoS medicine, 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

5 · Who and what money

Authors and funding

16 authors.

Veronica TozzoDepartment of Pathology and Center for Systems Biology, Massachusetts General Hospital, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0000-0001-8538-9198
Rachel PetherbridgeDepartment of Pathology and Center for Systems Biology, Massachusetts General Hospital, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0000-0002-3236-5587
Kaitlyn JamesDepartment of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Sarah HsuDiabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0000-0001-9823-9711
Deepti PantBiostatistics Center, Division of Clinical Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0000-0002-6890-081X
Chloe MichalopoulosDiabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0000-0002-6912-8622
Brody H FoyDepartment of Pathology and Center for Systems Biology, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Tanayott ThaweethaiBiostatistics Center, Division of Clinical Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0000-0003-0613-4176
Christopher MowDepartment of Pathology and Center for Systems Biology, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Jacqueline MayaDiabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Carolina Batlle CameroUniversity of Puerto Rico, School of Medicine, San Juan, Puerto Rico.ORCID https://orcid.org/0009-0007-0715-6744
Lydia ShookDepartment of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0000-0002-5859-8610
Kathryn J GrayDepartment of Obstetrics and Gynecology, University of Washington School of Medicine, Seattle, Washington, United States of America.
Logan MauneyDepartment of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0000-0002-3493-0869
John M HigginsDepartment of Pathology and Center for Systems Biology, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Camille E PoweDepartment of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, Massachusetts, United States of America.

Funding

Glycemic Observation Using A1C for Gestational Diabetes DiagnosisR01HD104756 · NICHD · MASSACHUSETTS GENERAL HOSPITAL · PI John Matthew Higgins, Camille Elise Powe · 2022 to 2026
$3.5M
Mentoring Underrepresented Researchers in Diabetes and Pregnancy InvestigationK26DK138346 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI Camille Elise Powe · 2023 to 2026
$529k
NICHD NIH HHS R01 HD104756NIDDK NIH HHS K26 DK138346
6 · The paper itself

Abstract

backgroundPregnancy alters hematologic state as measured by complete blood count (CBC), but the longitudinal changes in CBC indices that define healthy pregnancies are not well established. In a large cohort based at an academic health system in the United States, we aimed to define reference intervals and typical longitudinal changes in CBC indices during pregnancy. We then tested for associations between extreme CBC values for gestational age or extreme longitudinal changes in CBC indices and obstetric complications. METHODS AND

findingsWe studied nine CBC indices in individuals with singleton pregnancies who delivered after 30 weeks' gestation and presented for prenatal care prior to 20 weeks. The electronic health record (EHR)-based Maternal Health Cohort (Massachusetts General Hospital; 1998-2016) formed our discovery cohort of 45,992 pregnancies, 18% of which had relevant complications. We developed a validation cohort of 48,868, 27% with complications from EHR data in the Mass General Brigham healthcare system from 2016 to 2024. In pregnancies without complications in the discovery cohort, we derived gestational-age-specific reference intervals (2.5th-97.5th percentile) and established typical intra-pregnancy longitudinal changes. In the validation cohort, we then tested CBC values outside of the 26-29 weeks' gestation reference interval and CBC rare changes (uncommon changes in magnitude and direction) between 7-14 and 26-29 weeks' gestation for association with a composite outcome (hypertensive disorders of pregnancy, small for gestational age birthweight, preterm birth) and its individual components using generalized estimating equations. Derived reference intervals differed from those in the literature for mean red cell volume, mean red cell hemoglobin, red cell count, and mean red cell hemoglobin concentration; reference intervals for other indices were similar to those previously published. In validation, hematocrit, hemoglobin, and red cell count values above their gestational-age specific reference intervals were associated with increased risk of the composite obstetric outcome: odds ratios (ORs) of 1.4 (95% CI [1.2, 1.5] p < 0.0001) for hematocrit; 1.6 (95% CI [1.4, 1.8] p < 0.0001) for hemoglobin; and 1.6 (95% CI [1.4, 1.7] p < 0.0001) for red cell count. Uncommon increases in hemoglobin (>0.67 g/dL) or red cell count (>0.07 106/mm3) between 7-14 weeks' and 26-29 weeks' gestation were associated with increased risk for preterm birth, OR for hemoglobin 1.9 (95% CI [1.5, 2.5] p < 0.0001) and red cell count 2.1 (95% CI [1.7, 2.6] p < 0.0001). Limitations include the retrospective nature of the study and the exclusion of pregnancies without prenatal care prior to 20 weeks' and pregnancies delivered before 29 weeks' gestation.

conclusionsElevated red blood cell-related measurements and unusually large intra-pregnancy increases in those measures are associated with subsequent obstetric complications.

Indexed as

Pregnancy ComplicationsAdultBlood Cell CountFemaleGestational AgeHumansPregnancyReference ValuesRetrospective Studies

Identifiers

PMID42160455
PMCPMC13215607

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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.