ArticleItalian journal of pediatrics2026
A nomogram for early prediction of pertussis-associated pneumonia in children: a retrospective clinical study.
Article in Italian journal of pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundPertussis, an acute respiratory infection caused by Bordetella pertussis, has recently shown a global resurgence. Pneumonia represents one of its most frequent and severe complications. The present study aimed to identify risk factors for pertussis-associated pneumonia and to develop a predictive model for early identification of high-risk pediatric patients.
methodsA retrospective analysis was performed on 123 children hospitalized with pertussis at the Children's Hospital Affiliated to Zhengzhou University between 1 June 2024 and 31 December 2024(training cohort). Using univariate analysis, least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analysis, identified the predictors for pertussis-associated pneumonia. An independent cohort enrolled between 1 January 2025 and 31 July 2025, was used for external validation cohort. Receiving operating characteristic curve (ROC), calibration plots, decision curve analysis (DCA), and clinical impact curves (CIC) were used to evaluate the performance of the model.
resultsWe identified five independent predictors of pertussis-associated pneumonia: white blood cell count (WBC; OR = 1.112, 95% CI: 1.012-1.221), interleukin-6 (IL-6; OR = 1.153, 95% CI: 1.049-1.267), lymphocyte percentage (Lym%; OR = 1.045, 95% CI: 1.013-1.078), interleukin-17a (IL-17a; OR = 1.209, 95% CI: 1.024-1.427), and Co-infection (OR = 3.096, 95% CI: 1.260-7.610). The area under the receiver operating characteristic curve (AUC) was 0.824 (95% CI: 0.747-0.900) in the training cohort and 0.792 (95% CI: 0.718-0.865) in the external validation cohort. The Hosmer-Lemeshow test indicated good calibration (P = 0.590 in the training cohort; P = 0.735 in the external validation cohort). Decision curve analysis and clinical impact curves confirmed clinical utility.
conclusionA clinically useful nomogram model was developed for early prediction of pertussis-associated pneumonia in children. Application of this model may assist clinicians in promptly identifying high-risk patients and implementing timely interventions to improve outcomes.Notably, this study had a small sample size (n = 123) relative to the five predictors, and the external validation cohort was from the same center, which may limit the model's generalizability to heterogeneous clinical settings.
Indexed as
Identifiers
What 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.