Evidence map›Paper›PMID 28427805›Full record

ArticleAmerican journal of obstetrics and gynecology2017

Confounding, causality, and confusion: the role of intermediate variables in interpreting observational studies in obstetrics.

Cande V Ananth, Enrique F Schisterman

Open access · greenAbstract read
In one paragraph

Article in American journal of obstetrics and gynecology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 145 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
145citing papers in PubMed, 6 pooled it
24.2field-weighted citation impact, top 1% of its field
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

145 citing papers in PubMed, 6 syntheses or guidelines pooled it, 309 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Trial
  8. Trial
  9. Observational
  10. Article
  11. Association between annual twin delivery volume and severe postpartum hemorrhage in twin pregnancies.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2026
    Observational
  12. Article
  13. Article
  14. Beyond the Headlines: Examining the Evidence Around Acetaminophen and Autism Risk.The journal of pediatric pharmacology and therapeutics : JPPT : the official journal of PPAG · 2026
    Article
  15. Article
  16. Article
  17. Neighborhood socioeconomic disadvantage and chorioamnionitis.Journal of perinatology : official journal of the California Perinatal Association · 2026
    Article
  18. Article
  19. Article
  20. Article

85 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Cande V AnanthDepartment of Obstetrics and Gynecology, College of Physicians and Surgeons, Columbia University, New York, NY; Department of Epidemiology, Joseph L. Mailman School of Public Health, Columbia University, New York, NY. Electronic address: cande.ananth@columbia.edu.
Enrique F SchistermanEpidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD.
Columbia University · USNational Institutes of Health · US

Funding

ROC Curve MethodologyZIAHD008761 · NICHD · EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT · PI SCHISTERMAN, ENRIQUE F. · 2009 to 2021
$2.1M
Intramural NIH HHS ZIA HD008761
6 · The paper itself

Abstract

Prospective and retrospective cohorts and case-control studies are some of the most important study designs in epidemiology because, under certain assumptions, they can mimic a randomized trial when done well. These assumptions include, but are not limited to, properly accounting for 2 important sources of bias: confounding and selection bias. While not adjusting the causal association for an intermediate variable will yield an unbiased estimate of the exposure-outcome's total causal effect, it is often that obstetricians will want to adjust for an intermediate variable to assess if the intermediate is the underlying driver of the association. Such a practice must be weighed in light of the underlying research question and whether such an adjustment is necessary should be carefully considered. Gestational age is, by far, the most commonly encountered variable in obstetrics that is often mislabeled as a confounder when, in fact, it may be an intermediate. If, indeed, gestational age is an intermediate but if mistakenly labeled as a confounding variable and consequently adjusted in an analysis, the conclusions can be unexpected. The implications of this overadjustment of an intermediate as though it were a confounder can render an otherwise persuasive study downright meaningless. This commentary provides an exposition of confounding bias, collider stratification, and selection biases, with applications in obstetrics and perinatal epidemiology.

Indexed as

CausalityConfounding Factors, EpidemiologicData Interpretation, StatisticalFemaleHumansObservational Studies as TopicObstetricsPregnancySelection Biascausal pathwaycollider stratification biasconfounderdescending proxyinappropriate adjustmentintermediate variableoveradjustmentperinatal paradoxselection biasunmeasured confounding

Identifiers

PMID28427805
PMCPMC5545051
OpenAlexW2605728932

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.