Evidence map›Paper›PMID 39759350›Full record

ArticleHeliyon2024

Development and validation of a nomogram for predicting sleep disturbance in pregnant and postpartum women: A pilot study.

Yingyu Zhong, He Wang, Yueyun Wang

Abstract read
In one paragraph

Article in Heliyon, 2024. 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
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.

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

3 authors.

Yingyu ZhongShenzhen Maternity and Child Healthcare Hospital, China.
He WangShenzhen Maternity and Child Healthcare Hospital, China.
Yueyun WangShenzhen Maternity and Child Healthcare Hospital, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sleep disturbances are common in pregnant and postpartum women, impacting their health. Predictive tools for timely intervention are scarce. Objective: To develop and validate a nomogram predicting sleep disturbance risk in this demographic. Methods: We enrolled unipara with singleton pregnancies from Shenzhen hospitals in 2022, with complete data and survey cooperation. Data collected included demographics, pregnancy stage, systemic health, sleep status, and emotional state. Subjects were randomly assigned to training (70 %) and validation (30 %) groups. Risk factors were identified via logistic regression, and the nomogram was evaluated using calibration, ROC curves, and DCA. Results: The study involved 727 women. Identified risk factors for sleep disturbance included education, income, and various systemic and emotional symptoms. The nomogram demonstrated strong predictive accuracy in both groups (AUC: 0.93 and 0.91), with calibration and DCA confirming its reliability. Conclusion: The nomogram accurately predicts sleep disturbance risk, aiding early detection and improving sleep quality in pregnant and postpartum women. Its broader applicability will be confirmed in future studies.

Indexed as

Early interventionNomogramPredictive modelPregnant and postpartum womenSleep disturbance

Identifiers

PMID39759350
PMCPMC11697565

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.