Evidence map›Paper›PMID 38082281›Full record

Trial reportBMC musculoskeletal disorders2023

Predicting efficacy and guiding procedure choice in non-vascularized bone grafting: a CT Radiomics and clinical predictor approach.

Hao Chen, Peng Xue, Hongzhong Xi, Shuai He, Guangquan Sun, Xin Liu, Bin Du

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in BMC musculoskeletal disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. 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

7 authors at 1 institution in 1 country.

Hao ChenAffiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, China.
Peng XueAffiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, China.
Hongzhong XiAffiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, China.
Shuai HeAffiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, China.
Guangquan SunAffiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, China.
Xin LiuAffiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, China.
Bin DuAffiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, China. fsyy00608@njucm.edu.cn.
Nanjing University of Chinese Medicine · CN

Funding

A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions No.035062005001Jiangsu Graduate Practice and Innovation Plan No. SJCX22_0769National Natural Science Foundation of China 82074471
6 · The paper itself

Abstract

objectivesThere is no practical approach for accurately predicting the efficacy of non-vascularized bone grafting (NVBG) and guiding its optimal procedure. MATERIALS AND

methodsThis study enrolled 153 patients with 182 hips that underwent NVBG procedures. The patients were randomly divided into a training cohort (n = 130) and a validation cohort (n = 52). In the training cohort, radiomics model, clinical model, and combined radiomics-clinical (C-R) model were constructed using Rad-scores and clinical predictors to predict the efficacy of NVBG. The optimal model was visualized by a nomogram and assessed by decision curve analysis (DCA). 128 hips that underwent successful NVBG were then randomized into a new training cohort (n = 92) and a new validation cohort (n = 36), and three models were constructed and validated to predict the choice of NVBG procedure.

resultsJapanese Investigation Committee (JIC) classification, exposure to risk factors postoperative, and Rad-scores consisting of four radiomics features were independent predictors for the efficacy of NVBG (P < 0.05). The C-R model provided better performance in both the training cohort (AUC: 0.818) and validation cohort (AUC: 0.747). To predict the choice of NVBG procedure, the C-R model built by JIC classification and Rad-scores consisting of five radiomics features showed the finest performance in both cohorts (AUC: 0.860 and 0.800, respectively). DCA showed great benefit using the C-R model for the choice of NVBG procedure.

conclusionThe approach integrated by CT radiomics and clinical predictors can be visually and quantitatively applied to predict the efficacy and guide the choice of NVBG procedure with great predictive accuracy.

Indexed as

Bone TransplantationHumansNomogramsPostoperative PeriodTomography, X-Ray ComputedCT radiomicsHip preservationNon-vascularized bone graftingOsteonecrosis of femoral head

Identifiers

PMID38082281
PMCPMC10712171
OpenAlexW4389571161

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.