Trial reportInfection2023
Diagnostic nomogram to differentiate between epididymal tuberculosis and bacterial epididymitis.
Trial report in Infection, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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.
Who cites it
5 citing papers in PubMed.
- Development and application of a risk prediction nomogram for sarcopenia one year after surgery in early-stage non-small cell lung cancer patients.Frontiers in medicine · 2026Article
- Construction and Validation of a Prediction Model for Sustained Smoking Cessation in Patients with Chronic Obstructive Pulmonary Disease.International journal of chronic obstructive pulmonary disease · 2026Article
- A Novel Nomogram to Differentiate Between Renal Tuberculosis and Nontuberculous Renal Infection.Infection and drug resistance · 2025Article
- A Novel Differentiation Nomogram Model for Brucellar Spondylitis and Tuberculous Spondylitis.Infection and drug resistance · 2024Article
- Atlas of patient-reported outcome measures, nomograms and scoring systems used in simple and complicated urinary tract infections: a systematic review.Therapeutic advances in infectious diseaseReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeWe developed and validated a diagnostic nomogram for differentiating epididymal tuberculosis (TB) from bacterial epididymitis.
methodsIn this retrospective study, we developed a prediction model based on demographics and clinical characteristics. Eligible patients were randomly divided into derivation and validation cohorts (ratio 7:3). Univariate and multivariate regression analyses were used to filter variables and select predictors. Multivariate logistic regression was used to construct the nomogram. Concordance index (C-index), calibration plots, and decision curves analysis (DCA) were used to assess the discrimination, calibration, and clinical usefulness of the nomogram.
resultsWe included 147 patients (epididymal TB, 93; bacterial epididymitis, 54). The derivation cohort included 66 patients with epididymal TB and 38 with bacterial epididymitis; the validation cohort included 27 patients with epididymal TB and 16 with bacterial epididymitis. One regression model was built from three differential variables: body mass index, purified protein derivative, and chronic infection. Accordingly, one nomogram was developed. The model had good discrimination and calibration. C-indexes of the derivation and validation cohorts were 0.89 and 0.98 (95% confidence intervals, 0.83-0.95 and 0.94-1.01), respectively. DCA showed that the proposed nomogram was useful for differentiation.
conclusionThe nomogram can differentiate between epididymal TB and bacterial epididymitis.
Indexed as
Identifiers
36114385What OpenQuestion holds
Registered trials
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.