Observational studyBMC infectious diseases2025
Pertussis risk assessment in children: a retrospective study of blood parameters from two medical centers.
Observational study in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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Who cites it
1 citing paper in PubMed.
- Complete Blood Count-Derived Inflammatory Markers in Pediatric Lower Respiratory Tract Infection: A Narrative Review.Pathogens (Basel, Switzerland) · 2026Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesPertussis is an important contributor to respiratory morbidity and mortality and remains underdiagnosed since pertussis re-emergence becomes a global public health concern in recent years. This multi-center retrospective observational study aimed to develop a diagnostic prediction model based on laboratory blood parameters to identify children with pertussis.
methodsA total of 545 children with suspected pertussis from the hospital between January 2024 and June 2024 were identified and randomly split into training (n = 381), and validation group (n = 164). A model was generated based on Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analysis identifying potential predictors of pertussis. Model performance was assessed using receiver-operating characteristic (ROC), calibration plots and decision curve analysis (DCA). External validation was conducted on an independent cohort from another hospital (n = 594).
resultsBased on LASSO and multivariate analysis, a model was formulated incorporating four predictors, including age, CRP level, lymphocyte count, and hematocrit (ROC: 0.741 for the training cohort, 0.694 for the internal validation cohort and 0.675 for the external validation cohort). Calibration curve and DCA validated the fitness and clinical application value of this nomogram.
conclusionsThe model developed in this multicenter cohort study exhibits high accuracy in predicting the probability of pertussis in children. This model can be very helpful for clinicians when making decisions.
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