Evidence map›Paper›PMID 38075035›Full record

ArticleOpen medicine (Warsaw, Poland)2023

Impact of COVID-19 lockdown on glycemic levels during pregnancy: A retrospective analysis.

Erika Di Zazzo, Sergio Davinelli, Serena Panichella, Giovanni Scapagnini, Mariano Intrieri, Silvio Garofalo

Open access · goldAbstract read
In one paragraph

Article in Open medicine (Warsaw, Poland), 2023. 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, top 69% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 1 institution in 1 country.

Erika Di ZazzoUOC Laboratorio Analisi, Ospedale "A. Cardarelli", 86100 Campobasso, Italy.
Sergio DavinelliDepartment of Medicine and Health Sciences "V. Tiberio", University of Molise, 86100 Campobasso, Italy.
Serena PanichellaDepartment of Medicine and Health Sciences "V. Tiberio", University of Molise, 86100 Campobasso, Italy.
Giovanni ScapagniniDepartment of Medicine and Health Sciences "V. Tiberio", University of Molise, 86100 Campobasso, Italy.
Mariano IntrieriDepartment of Medicine and Health Sciences "V. Tiberio", University of Molise, 86100 Campobasso, Italy.
Silvio GarofaloDepartment of Medicine and Health Sciences "V. Tiberio", University of Molise, 86100 Campobasso, Italy.
University of Molise · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studies on the COVID-19 pandemic effects on gestational diabetes mellitus (GDM) remain limited and controversial. This study aimed to investigate the impact of the COVID-19 lockdown on the glycemic balance of pregnant women and GDM risk. To this aim, a single-center retrospective cohort analysis assessing glucose homeostasis using the oral glucose tolerance test in 862 pregnant women before (from March 9, 2019 to March 8, 2020 - Group 1), during (from March 9, 2020 to March 8, 2021 - Group 2), and after (from March 9, 2021 to March 8, 2022 - Group 3) the COVID-19 lockdown in Molise, a region of central Italy, was conducted. We observed that the blood glucose concentration of pregnant women was significantly lower during the COVID-19 lockdown than during the previous and following years at all time points evaluated (time 0, 60', and 120'). Specifically, at time 0, it was 82.14 mg/dl for group 2 vs 85.94 for group 1 (

Indexed as

COVID-19gestational diabetes mellitusglycemialockdownoral glucose tolerance testpregnancy

Identifiers

PMID38075035
PMCPMC10710209
OpenAlexW4389438334

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.