Evidence map›Paper›PMID 23395644›Full record

ArticleAmerican journal of obstetrics and gynecology2013

Patterns of obstetric infection rates in a large sample of US hospitals.

Sarah L Goff, Penelope S Pekow, Jill Avrunin, Tara Lagu, Glenn Markenson, Peter K Lindenauer

Open access · bronzeAbstract read
In one paragraph

Article in American journal of obstetrics and gynecology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 11% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
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  3. Observational
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Sarah L GoffDepartment of Medicine, Baystate Medical Center, Springfield, MA, USA. Sarah.Goffmd@baystatehealth.org
Penelope S Pekow
Jill Avrunin
Tara Lagu
Glenn Markenson
Peter K Lindenauer
Baystate Medical Center · USTufts University · US

Funding

Tufts Clinical and Translational Science Institute (K12)KL2RR025751 · NCRR · TUFTS UNIVERSITY BOSTON · PI SELKER, HARRY P. · 2008 to 2011
$596k
Tufts Clinical and Translational Science Institute (K12)KL2TR000074 · NCATS · TUFTS UNIVERSITY BOSTON · PI SELKER, HARRY P. · 2012 to 2013
$149k
NCATS NIH HHS KL2 TR000074NCRR NIH HHS KL2 RR025751
6 · The paper itself

Abstract

objectiveMaternal infection is a common complication of childbirth, yet little is known about the extent to which infection rates vary among hospitals. We estimated hospital-level risk-adjusted maternal infection rates (RAIR) in a large sample of US hospitals and explored associations between RAIR and select hospital features. STUDY

designThis retrospective cohort study included hospitals in the Perspective database with >100 deliveries over 2 years. Using a composite measure of infection, we estimated and compared RAIR across hospitals using hierarchical generalized linear models. We then estimated the amount of variation in RAIR attributable to hospital features.

resultsOf the 1,001,189 deliveries at 355 hospitals, 4.1% were complicated by infection. Patients aged 15-19 years were 50% more likely to experience infection than those aged 25-29 years. Rupture of membranes >24 hours (odds ratio [OR], 3.0; 95% confidence interval [CI], 3.24-3.5), unengaged fetal head (OR, 3.11; 95% CI, 2.97-3.27), and blood loss anemia (OR, 2.42; 95% CI, 2.34-2.49) had the highest OR among comorbidities commonly found in patients with infection. RAIR ranged from 1.0-14.4% (median, 4.0%; interquartile range, 2.8-5.7%). Hospital features such as geographic region, teaching status, urban setting, and higher number of obstetric beds were associated with higher infection rates, accounting for 14.8% of the variation observed.

conclusionObstetric RAIR vary among hospitals, suggesting an opportunity to improve obstetric quality of care. Hospital features such as region, number of obstetric beds, and teaching status account for only a small portion of the observed variation in infection rates.

Indexed as

AdolescentAdultAge FactorsCohort StudiesCross-Sectional StudiesFemaleHospital AdministrationHospitalsHumansObstetrics and Gynecology Department, HospitalPregnancyPregnancy Complications, InfectiousRetrospective StudiesRisk AssessmentUnited StatesYoung Adult

Identifiers

PMID23395644
PMCPMC3670964
OpenAlexW2061278548

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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.