Evidence map›Paper›PMID 41415156›Full record

ReviewJournal of mid-life health

Statistical Glossaries and Biostatistical Aspects in Obstetrics and Gynecology.

Vanamail Perumal

Abstract readReview
In one paragraph

Review in Journal of mid-life health. 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

1 author.

Vanamail PerumalTrichy SRM Medical College Hospital and Research Centre, Tiruchirappalli, Tamil Nadu, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article emphasizes the transformative power of statistical glossaries and biostatistical methods in obstetrics and gynecology. These glossaries illuminate essential statistical terms and concepts, enriching our understanding of biostatistical techniques critical for analyzing maternal and reproductive health data. Such methodologies are not merely tools; they are keys that unlock insights into fertility, pregnancy complications, treatment effectiveness, and the broader spectrum of women's health. The review illuminates prevalent biostatistical approaches, including linear and logistic regression analyses, showcasing their profound impact on converting health data into meaningful, actionable insights. By establishing a robust framework for interpreting research findings, these techniques empower healthcare professionals and researchers to elevate patient care and shape public health strategies. Ultimately, applying biostatistics in obstetrics and gynecology advances individual patient outcomes while inspiring evidence-based practices and policymaking in maternal health. Statistical indices and models play a vital role in obstetrics and gynecology, serving as essential instruments for healthcare providers and researchers. They enhance our understanding of complex health issues and enable predictions leading to improved health outcomes for women and newborns. By integrating these statistical methodologies into clinical practice and research, we can make informed decisions that positively influence patient care. The ripple effect of these applications extends from individual patient interactions to large-scale public health initiatives, fostering a culture of evidence-based practice and informed policymaking. As we continue to advance our knowledge and use of biostatistical methods, we are ultimately dedicated to uplifting the standard of care for women, ensuring healthier futures for generations to come.

Indexed as

Biostatistical methodsobstetrics and gynecologystatistical glossaries

Identifiers

PMID41415156
PMCPMC12711187

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.