Evidence map›Paper›PMID 30782942›Full record

ArticleBMJ open2019

Maternity Log study: a longitudinal lifelog monitoring and multiomics analysis for the early prediction of complicated pregnancy.

Junichi Sugawara, Daisuke Ochi, Riu Yamashita, Takafumi Yamauchi, Daisuke Saigusa, Maiko Wagata, Taku Obara, Mami Ishikuro, Yoshiki Tsunemoto, Yuki Harada and 19 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

4 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

29 authors at 2 institutions in 1 country.

Junichi SugawaraTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.ORCID 0000-0001-8026-2550
Daisuke OchiTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Riu YamashitaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Takafumi YamauchiTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Daisuke SaigusaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Maiko WagataTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Taku ObaraTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Mami IshikuroTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Yoshiki TsunemotoResearch Laboratories, NTT DoCoMo, Inc, Yokosuka, Japan.
Yuki HaradaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Tomoko ShibataTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Takahiro MimoriTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Junko KawashimaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Fumiki KatsuokaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Takako Igarashi-TakaiTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Soichi OgishimaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Hirohito MetokiTohoku Medical and Pharmaceutical University, Sendai, Japan.
Hiroaki HashizumeTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Nobuo FuseTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Naoko MinegishiTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Seizo KoshibaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Osamu TanabeTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Shinichi KuriyamaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Kengo KinoshitaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Shigeo KureTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Nobuo YaegashiTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Masayuki YamamotoTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Satoshi HiyamaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Masao NagasakiTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Tohoku University · JPTohoku Medical and Pharmaceutical University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeA prospective cohort study for pregnant women, the Maternity Log study, was designed to construct a time-course high-resolution reference catalogue of bioinformatic data in pregnancy and explore the associations between genomic and environmental factors and the onset of pregnancy complications, such as hypertensive disorders of pregnancy, gestational diabetes mellitus and preterm labour, using continuous lifestyle monitoring combined with multiomics data on the genome, transcriptome, proteome, metabolome and microbiome.

participantsPregnant women were recruited at the timing of first routine antenatal visits at Tohoku University Hospital, Sendai, Japan, between September 2015 and November 2016. Of the eligible women who were invited, 65.4% agreed to participate, and a total of 302 women were enrolled. The inclusion criteria were age ≥20 years and the ability to access the internet using a smartphone in the Japanese language. FINDINGS TO DATE: Study participants uploaded daily general health information including quality of sleep, condition of bowel movements and the presence of nausea, pain and uterine contractions. Participants also collected physiological data, such as body weight, blood pressure, heart rate and body temperature, using multiple home healthcare devices. The mean upload rate for each lifelog item was ranging from 67.4% (fetal movement) to 85.3% (physical activity), and the total number of data points was over 6 million. Biospecimens, including maternal plasma, serum, urine, saliva, dental plaque and cord blood, were collected for multiomics analysis. FUTURE PLANS: Lifelog and multiomics data will be used to construct a time-course high-resolution reference catalogue of pregnancy. The reference catalogue will allow us to discover relationships among multidimensional phenotypes and novel risk markers in pregnancy for the future personalised early prediction of pregnancy complications.

Indexed as

Life StyleMetabolomeMicrobiotaProteomeTranscriptomeAdultComputational BiologyFemaleHumansJapanMiddle AgedPregnancyPregnancy ComplicationsProspective StudiesYoung AdultProteomecomplicated pregnancylifelogmulti-omics analysisprediction

Identifiers

PMID30782942
PMCPMC6398744
OpenAlexW2912831328

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.