Evidence map›Paper›PMID 42733116›Full record

ArticleBMC musculoskeletal disorders2026

Construction and validation of a nomogram model incorporating the systemic immune-inflammation index for preoperative deep vein thrombosis risk in patients with traumatic lower limb fractures.

Ailing Yang, Yamin Feng, Yang Shen, Sitong Liu, Huaiping Zhao, Hongli Guo, Tiantian Ren, Xiaoli Guan, Zhihong Wei

Abstract readValidation Study
In one paragraph

Article in BMC musculoskeletal disorders, 2026. 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

9 authors.

Ailing Yang *Department of Orthopedics, Lanzhou University Second Hospital, Lanzhou, China.
Yamin Feng *Department of Psychological Health, Lanzhou University Second Hospital, Lanzhou, China.
Yang ShenDepartment of Orthopedics, Lanzhou University Second Hospital, Lanzhou, China.
Sitong LiuDepartment of Orthopedics, Lanzhou University Second Hospital, Lanzhou, China.
Huaiping ZhaoDepartment of Orthopedics, Lanzhou University Second Hospital, Lanzhou, China.
Hongli GuoDepartment of Orthopedics, Lanzhou University Second Hospital, Lanzhou, China.
Tiantian RenPaediatric Surgery, Lanzhou University Second Hospital, Lanzhou, China.
Xiaoli GuanGeneral Surgery, Lanzhou University Second Hospital, Lanzhou , China.
Zhihong WeiOutpatient Department, Lanzhou University Second Hospital, No. 82, Cuiyingmen, Chengguan District, Lanzhou, China. 1806174019@qq.com.

Funding

Lanzhou Science and Technology Development Guidance Plan Project 2023-ZD-76Lanzhou University Second Hospital's Cuiying Science and Technology Innovation Program CY2022-HL-A05the Natural Science Foundation of Gansu Province 23JRRA0987
6 · The paper itself

Abstract

backgroundThis study aimed to explore the risk factors for preoperative deep vein thrombosis (DVT) in patients with traumatic lower-extremity fracture (TLEF), analyze the correlation and predictive efficacy of the systemic immune-inflammation index (SII) in DVT development, and establish a corresponding nomogram prediction model.

methodThis study retrospectively analyzed the clinical data of 950 patients who underwent surgery for TLEF at our hospital between May 2022 and April 2024. The enrolled patients were randomly divided into the training group (665 cases) and the validation group (285 cases) at a 7:3 ratio. We performed univariate and multivariate logistic regression analyses in the training dataset to screen independent risk factors for preoperative DVT in TLEF patients. R Studio was used to construct the nomogram model. The goodness-of-fit test and ROC curve were adopted to evaluate the efficacy of the model.

resultsAge, fracture site, SII, D-dimer and APTT were identified as independent predictive factors for preoperative DVT. The nomogram exhibited good agreement with the ideal model in both the training and validation datasets.

conclusionsThe nomogram prediction model for preoperative DVT risk in TLEF patients was developed by incorporating SII and other risk factors. It can assist clinical practitioners in early assessment of DVT development.

Indexed as

Fractures, BoneInflammationLower ExtremityNomogramsVenous ThrombosisAdultAgedFemaleHumansMaleMiddle AgedRetrospective StudiesRisk AssessmentRisk FactorsDeep vein thrombosisRisk prediction modelSystemic immune-inflammation indexTraumatic lower extremity fractures

Identifiers

PMID42733116
PMCPMC13573360

What OpenQuestion holds

Textmetadata
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.