Risk factors for severe respiratory syncytial virus infection during the first year of life: development and validation of a clinical prediction model
Bibliographic record
Abstract
ABSTRACT Background Novel immunisation methods against respiratory syncytial virus (RSV) are emerging, but knowledge of risk factors for severe RSV disease is insufficient for their optimal targeting. We aimed to identify predictors for RSV hospitalisation, and to develop and validate a clinical prediction model to guide RSV immunoprophylaxis for under 1-year-old infants. Methods In this retrospective cohort study using nationwide registries, we studied all infants born in 1997-2020 in Finland (n = 1 254 913) and in 2006-2020 in Sweden (n = 1 459 472), and their parents and siblings. We screened 1 510 candidate predictors and we created a logistic regression model with 16 predictors and compared its performance to a machine learning model (XGboost) using all 1 510 candidate predictors. Findings In addition to known predictors such as severe congenital heart defects (CHD, adjusted odds ratio (aOR) 2·89, 95% confidence interval 2·28-3·65), we identified novel predictors for RSVH, most notably esophageal malformations (aOR 3·11, 1·86-5·19) and lower complexity CHDs (aOR 1·43, 1·25-1·63). In validation data from 2018-2020, the C-statistic was 0·766 (0·742-0·789) in Finland and 0·737 (0·710-0·762) in Sweden. The clinical prediction model’s performance was similar to the machine learning model (C-statistic in Finland 0·771, 0·754-0·788). Calibration varied according to epidemic intensity. Model performance was similar across different strata of parental income. The infants in the 90th percentile of predicted RSVH probability hospitalisation had 3·3 times higher observed risk than the population’s average. Assuming 60% effectiveness, immunisation in this top 10% of infants at highest risk would have a number needed to treat of 23 in Finland and 40 in Sweden in preventing hospitalisations. Interpretation The identified predictors and the prediction model can be used in guiding RSV immunoprophylaxis in infants. Funding Sigrid Jusélius Foundation, European Research Council, Pediatric Research Foundation (for complete list of funding sources, see Acknowledgements).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".