Evidence map›Paper›PMID 41244769›Full record

ArticleFrontiers in medicine2025

Utility of a Caprini-combined prediction model in patients with gynecological venous thromboembolism in China.

Lijuan Ma, Lei Mao, Peipei Jia, Lin Wang, Lili Han, Xiumin Zhang, Ming Hou, Haiyan Ren, Chunyan Yan, Qingfeng Tang and 2 more

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

12 authors.

Lijuan Ma *Department of Gynecology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.
Lei Mao *Department of Medical, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.
Peipei JiaDepartment of Gynecology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.
Lin WangDepartment of Gynecology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.
Lili HanDepartment of Gynecology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.
Xiumin ZhangDepartment of Nursing, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.
Ming HouDepartment of Nursing, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.
Haiyan RenDepartment of Endocrinology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.
Chunyan YanDepartment of Dermatology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.
Qingfeng TangXinjiang Emergency Center, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.
Tao HanDepartment of Gynecology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.
Kereman YakufuDepartment of Gynecology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Explored the risk factors for venous thromboembolism in gynecological inpatients in western China, and developed an improved model to predict the VTE of this patient population. Methods: The records of 6897 patients hospitalized in the Gynecology Department of Xinjiang Autonomous Region People's Hospital were retrospectively reviewed, during January 1, 2021 to July 31, 2022 and meet the inclusion criteria are selected. The efficacy of the Caprini-combined prediction model was evaluated, and the Caprini-combined prediction model and independent risk factor-combined prediction model for predicting VTE were assessed using receiver operating characteristic (ROC) curve analysis. Results: The study cohort was divided into two groups: a VTE group ( Conclusion: Our study constructed a nomogram for predicting the risk of VTE based on age, BMI, Caprini scale score, respiratory/heart failure, length of hospital stay, PLT, serum albumin, and D-dimer levels. This model has good discrimination and prediction effects, and has certain clinical value.

Indexed as

Caprini scalegynecological patientsnomogramprediction modelvenous thromboembolism

Identifiers

PMID41244769
PMCPMC12615426

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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.