Evidence map›Paper›PMID 41029127›Full record

Observational studyMedicine2025

Nomogram for predicting poor outcomes after hysteroscopic endometrial polypectomy in menstrual disorders.

Chunzhi Sheng, Zhaobo Yan, Fanrong Zhao

Abstract readObservational Study
In one paragraph

Observational study in Medicine, 2025. 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.

Chunzhi ShengGynecology Department, Wenling Hospital of Traditional Chinese Medicine, Wenling City, Zhejiang Province, China.
Zhaobo Yan

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patients with endometrial polyps often exhibit irregular menstrual symptoms, and even after hysteroscopic removal of endometrial polyps, some patients' menstrual disorders do not show significant improvement. This study retrospectively included 450 patients, with 355 patients showing significant improvement in menstrual disorders and 95 patients showing no significant improvement. Analyze the demographic, clinical characteristics, and surgical related factors of patients in these 2 situations, as well as the differences in hormone levels before and after treatment. Further, support vector machine can be used to screen the influencing factors of poor efficacy and construct a risk model. Perform multivariate regression analysis to examine the impact of the risk model and its interaction on poor efficacy. Construct a nomogram to further analyze the risk of poor therapeutic efficacy. The top 5 important features selected by support vector machine include progesterone changes, luteinizing hormone changes, polyp morphology, polyp type, and polyp location. The AUC (area under curve) of the constructed risk model is 0.701, indicating high predictive ability. In addition to the risk model, age, BMI (body mess index), menstrual duration, endometrial thickness, polyp size, and follicle stimulating hormone changes are also significant independent factors for poor therapeutic efficacy. The interaction indicates that the risk model performs better in patients with longer menstrual periods or larger polyps. Nomogram have high accuracy and clinical application value. The risk model we constructed has a good ability to predict poor therapeutic efficacy, and the nomogram provides a reference for clinical doctors' decision-making.

Indexed as

HysteroscopyMenstruation DisturbancesNomogramsPolypsUterine DiseasesAdultEndometriumFemaleHumansMiddle AgedRetrospective StudiesTreatment Outcomehysteroscopic endometrial polypectomymenstrual disorderspostoperative complicationsrisk model

Identifiers

PMID41029127
PMCPMC13593214

What OpenQuestion holds

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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.