Evidence map›Paper›PMID 38720714›Full record

ArticleHeliyon2024

Prediction model of deep vein thrombosis risk after lower extremity orthopedic surgery.

Jiannan Zhang, Yang Shao, Hongmei Zhou, Ronghua Li, Jie Xu, Zhongzhou Xiao, Lu Lu, Liangyu Cai

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. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

8 authors.

Jiannan ZhangDepartment of Anesthesiology, Wuxi TCM Hospital, Wuxi, 214071, PR China.
Yang ShaoDepartment of Anesthesiology, Wuxi TCM Hospital, Wuxi, 214071, PR China.
Hongmei ZhouDepartment of Anesthesiology, Wuxi TCM Hospital, Wuxi, 214071, PR China.
Ronghua LiDepartment of Anesthesiology, Wuxi TCM Hospital, Wuxi, 214071, PR China.
Jie XuShanghai Artificial Intelligence Laboratory, Shanghai, 200030, PR China.
Zhongzhou XiaoShanghai Artificial Intelligence Laboratory, Shanghai, 200030, PR China.
Lu LuShanghai Artificial Intelligence Laboratory, Shanghai, 200030, PR China.
Liangyu CaiDepartment of Anesthesiology, Wuxi TCM Hospital, Wuxi, 214071, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This investigation was conceived to engineer and appraise a pioneering clinical nomogram, crafted to bridge the extant chasm in literature regarding the postoperative risk stratification for deep vein thrombosis (DVT) in the aftermath of lower extremity orthopedic procedures. This novel tool offers a sophisticated and discerning algorithm for risk prediction, heretofore unmet by existing methodologies. Methods: In this retrospective observational study, clinical records of hospitalized patients who underwent lower extremity orthopedic surgery were collected at the Wuxi TCM Hospital Affiliated to the Nanjing University of Chinese Medicine between Jan 2017 and Oct 2019. The univariate and multivariate analysis with the backward stepwise method was applied to select features for the predictive nomogram. The performance of the nomogram was evaluated with respect to its discriminant capability, calibration ability, and clinical utility. Result: A total of 5773 in-hospital patients were eligible for the study, with the incidence of deep vein thrombosis being approximately 1 % in this population. Among 31 variables included, 5 of them were identified to be the predictive features in the nomogram, including age, mean corpuscular hemoglobin concentration (MCHC), D-dimer, platelet distribution width (PDW), and thrombin time (TT). The area under the receiver operating characteristic (ROC) curve in the training and validation cohort was 85.9 % (95%CI: 79.96 %-90.04 %) and 85.7 % (95%CI: 78.96 %-90.69 %), respectively. Both the calibration curves and decision curve analysis demonstrated the overall satisfactory performance of the model. Conclusion: Our groundbreaking nomogram is distinguished by its unparalleled accuracy in discriminative and calibrating functions, complemented by its tangible clinical applicability. This innovative instrument is set to empower clinicians with a robust framework for the accurate forecasting of postoperative DVT, thus facilitating the crafting of bespoke and prompt therapeutic strategies, aligning with the rigorous standards upheld by the most esteemed biomedical journals.

Indexed as

D-dimerDeep venous thrombosisLower extremity orthopedic surgeryRisk prediction

Identifiers

PMID38720714
PMCPMC11076659

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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.