Evidence map›Paper›PMID 42890885›Full record

ArticleFrontiers in pediatrics2026

Development and validation of a nomogram for stratifying severe

Zhongying Chen, Wugao Ding, Zhengyan Gao

Abstract read
In one paragraph

Article in Frontiers in 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.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Zhongying ChenDepartment of Pediatrics, Second People's Hospital of Futian District, Shenzhen, China.
Wugao DingDepartment of Pediatrics, Second People's Hospital of Futian District, Shenzhen, China.
Zhengyan GaoDepartment of Pediatrics, Second People's Hospital of Futian District, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to develop and validate a clinically applicable diagnostic predictive model to facilitate early identification of severe Methods: Clinical data from children with MPP hospitalized from January 2023 to December 2023, were retrospectively collected as the training set. Patients were classified into general MPP (GMPP) or SMPP groups based on whether SMPP occurred within 24 h of admission. After comparing the differences in clinical data between the two groups at admission, multivariate logistic regression was used to identify risk indicators for SMPP and construct a diagnostic predictive model. A nomogram was developed to visualize the model. Subsequently, data from children with MPP hospitalized between January 2024 and December 2024 were collected to conduct temporal external validation of the model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curves, Hosmer-Lemeshow goodness-of-fit test, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). Results: In total, 412 children with MPP were included, with 222 cases within the training set (119 SMPP, 53.60%) and 190 within the temporal external validation set (129 SMPP, 67.89%). Independent risk indicators for the occurrence of SMPP included the duration of fever before admission (OR = 2.019, 95% CI: 1.387-2.938), shortness of breath (OR = 111.599, 95% CI: 11.512-1,081.834), unresponsive to macrolide before admission (OR = 3.687, 95% CI: 1.529-8.892), interleukin-6 (IL-6) (OR = 1.052, 95% CI: 1.010-1.095), and pulmonary consolidation (OR = 31.634, 95% CI: 11.643-85.948) (all Conclusion: The model developed in this study provides valuable reference for early risk stratification of pediatric SMPP and timely, individualized clinical decision-making in children with MPP. However, extensive external validation is required.

Indexed as

childrenIL-6nomogrampredictive modelsevere Mycoplasma pneumoniae pneumonia

Identifiers

PMID42890885
PMCPMC13672552

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.