ArticlePloS one2020
Nomogram for pneumonia prediction among children and young people with cerebral palsy: A population-based cohort study.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Poor handling of continuous predictors in clinical prediction models using logistic regression: a systematic review.Journal of clinical epidemiology · 2023Pooled it
- Risk of pneumonia and mortality after routine dental scaling in patients with moderate-to-severe cerebral palsy: A nationwide cohort study.Journal of dental sciences · 2026Article
- Trajectories of medication use and polypharmacy among children with cerebral palsy.Journal of managed care & specialty pharmacy · 2023Article
- Article
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- Nomogram to predict 3-month unfavorable outcome after thrombectomy for stroke.BMC neurology · 2022Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPneumonia is the leading cause of death among children and young people (CYP) with severe cerebral palsy (CP). Only a few studies used nomogram for assessing risk factors and the probability of pneumonia. Therefore, we aimed to identify risk factors and devise a nomogram for identifying the probability of severe pneumonia in CYP with severe CP.
methodsThis retrospective nationwide population-based cohort study examined CYP with newly diagnosed severe CP before 18 years old between January 1st, 1997 and December 31st, 2013 and followed them up through December 31st, 2013. The primary endpoint was defined as the occurrence of severe pneumonia with ≥ 5 days of hospitalization. Logistic regression analysis was used for determining demographic factors and comorbidities associated with severe pneumonia. These factors were assigned integer points to create a scoring system to identify children at high risk for severe pneumonia.
resultsAmong 6,356 CYP with newly diagnosed severe CP, 2,135 (33.59%) had severe pneumonia. Multivariable logistic regression analysis revealed that seven independent predictive factors, namely age <3 years, male sex, and comorbidities of pressure ulcer, gastroesophageal reflux, asthma, seizures, and perinatal complications. A nomogram was devised by employing these seven significant predictive factors. The prediction model presented favorable discrimination performance.
conclusionsThe nomogram revealed that age, male sex, history of pressure ulcer, gastroesophageal reflux, asthma, seizures, and perinatal complications were potential risk factors for severe pneumonia among CYP with severe CP.
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