ArticleTherapeutic advances in respiratory disease
Development of a clinical prediction model for cough variant asthma.
Article in Therapeutic advances in respiratory disease. 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
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCough variant asthma (CVA) is a common cause of chronic cough but remains underdiagnosed due to limited access to bronchial provocation test.
objectiveTo develop a clinical prediction model for CVA based on more accessible indicators.
designA single-center retrospective cohort study.
methodsA retrospective cohort of patients with chronic cough from January 2024 to December 2024 was included. The patients were randomly divided into a training set and an internal validation set at a ratio of 7:3. Univariable and multivariable logistic regression analyses were used to identify independent predictors of CVA. A nomogram prediction model was constructed based on these factors. The predictive performance of the nomogram was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).
resultsA total of 323 patients with chronic cough were included, with 226 assigned to the training set (45 with CVA, 181 with non-CVA) and 97 to the internal validation set (23 with CVA, 74 with non-CVA). Multivariable logistic regression analysis identified increased eosinophils in induced sputum, elevated peripheral blood eosinophil count (PBEC), raised FeNO
conclusionThe CVA clinical prediction model based on induced sputum cytology, PBEC, FeNO
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.