Evidence map›Paper›PMID 27449415›Full record

ArticleAmerican journal of epidemiology2016

Circulating Influenza Virus and Adverse Pregnancy Outcomes: A Time-Series Study.

Deshayne B Fell, David L Buckeridge, Robert W Platt, Jay S Kaufman, Olga Basso, Kumanan Wilson

Open access · bronzeAbstract read
In one paragraph

Article in American journal of epidemiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

9 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
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  3. Maternal-Newborn Health System Changes and Outcomes in Ontario, Canada, During Wave 1 of the COVID-19 Pandemic-A Retrospective Study.Journal of obstetrics and gynaecology Canada : JOGC = Journal d'obstetrique et gynecologie du Canada : JOGC · 2022
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Deshayne B Fell
David L Buckeridge
Robert W Platt
Jay S Kaufman
Olga Basso
Kumanan Wilson

Funding

CIHR
6 · The paper itself

Abstract

Individual-level epidemiologic studies of pregnancy outcomes after maternal influenza are limited in number and quality and have produced inconsistent results. We used a time-series design to investigate whether fluctuation in influenza virus circulation was associated with short-term variation in population-level rates of preterm birth, stillbirth, and perinatal death in Ontario between 2003 and 2012. Using Poisson regression, we assessed the association between weekly levels of circulating influenza virus and counts of outcomes offset by the number of at-risk gestations during 3 gestational exposure windows. The rate of preterm birth was not associated with circulating influenza level in the week preceding birth (adjusted rate ratio = 1.01, 95% confidence interval: 1.00, 1.02) or in any other exposure window. These findings were robust to alternate specifications of the model and adjustment for potential confounding. Stillbirth and perinatal death rates were similarly not associated with gestational exposure to influenza circulation during late pregnancy. We could not assess mortality outcomes relative to early gestational exposure because of missing dates of conception for many stillbirths. In this time-series study, population-level influenza circulation was not associated with short-term variation in rates of preterm birth, stillbirth, or perinatal death.

Indexed as

AdolescentAdultBirth CertificatesFemaleHumansInfant, NewbornInfluenza A Virus, H1N1 SubtypeInfluenza, HumanMaternal AgeMaternal HealthMedical Record LinkageMiddle AgedOntarioPerinatal DeathPoisson DistributionPopulation Surveillanceinfluenzapregnancypreterm birthstillbirthtime-series study

Identifiers

PMID27449415
PMCPMC4967597
OpenAlexW2486796397

What OpenQuestion holds

Textmetadata
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.