Evidence map›Paper›PMID 41758454›Full record

ArticleInfection2026

Development and validation of a nomogram for predicting mortality in patients with vertebral osteomyelitis.

Jianlong Li, Yingxin Zhao, Yongrui Yang, Wenkai Ruan, Rongpan Dang, Wentao Zhao, Huigang An, Liang Xu, Hongdong Tan, Xue Guo and 1 more

Abstract readValidation Study
PubMed Publisher
In one paragraph

Article in Infection, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Jianlong LiShandong Public Health Clinical Center, Shandong University, Jinan, 250013, Shandong, China.
Yingxin ZhaoShandong Public Health Clinical Center, Shandong University, Jinan, 250013, Shandong, China.
Yongrui YangShandong Public Health Clinical Center, Shandong University, Jinan, 250013, Shandong, China.
Wenkai RuanShandong Public Health Clinical Center, Shandong University, Jinan, 250013, Shandong, China.
Rongpan DangShandong Public Health Clinical Center, Shandong University, Jinan, 250013, Shandong, China.
Wentao ZhaoShandong Public Health Clinical Center, Shandong University, Jinan, 250013, Shandong, China.
Huigang AnShandong Public Health Clinical Center, Shandong University, Jinan, 250013, Shandong, China.
Liang XuShandong Public Health Clinical Center, Shandong University, Jinan, 250013, Shandong, China.
Hongdong TanShandong Public Health Clinical Center, Shandong University, Jinan, 250013, Shandong, China. tanhd_1218@163.com.
Xue GuoShandong Public Health Clinical Center, Shandong University, Jinan, 250013, Shandong, China.
Dongmei WangShandong Public Health Clinical Center, Shandong University, Jinan, 250013, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

STUDY

designRetrospective study.

methodsFrom January 2019 to January 2025, patients diagnosed with vertebral osteomyelitis at Shandong Public Health Clinical Center were enrolled. Clinical data were analyzed using Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariable logistic regression to identify risk factors. A prognostic nomogram was developed and evaluated for discrimination using the area under the receiver operating characteristic curve (AUC), calibration using the Hosmer-Lemeshow test and calibration curves, clinical utility through decision curve analysis, and robustness with 500 bootstrap resamples for internal validation. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated at the optimal cutoff.

resultsOf 248 patients, 55 (22.17%) died within 1 year. Eight independent risk factors were identified: renal insufficiency, higher Charlson Comorbidity Index, elevated C-reactive protein and white blood cell levels, multifocal vertebral osteomyelitis, pneumonia, poor cardiac function, and poor wound healing. The nomogram demonstrated excellent discrimination (AUC: 0.957; 95% CI 0.929-0.985), confirmed by bootstrap validation (AUC: 0.946; 95% CI 0.915-0.977). At a cutoff of 0.135, it achieved 82.5% sensitivity, 93.3% specificity, 88.7% positive predictive value, 81.9% negative predictive value, and 92.7% accuracy. Calibration was adequate (Hosmer-Lemeshow P = 0.750), and decision curve analysis confirmed clinical benefit.

conclusionsThis pioneering nomogram accurately predicts 1-year mortality in vertebral osteomyelitis, facilitating personalized clinical management.

Indexed as

NomogramsOsteomyelitisSpinal DiseasesAgedFemaleHumansMaleMiddle AgedPredictive Value of TestsPrognosisRetrospective StudiesRisk FactorsROC CurveSensitivity and SpecificityMortalityNomogramPrediction modelVertebral osteomyelitis

Identifiers

PMID41758454

What OpenQuestion holds

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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.