Respiratory syncytial virus - associated intensive care unit admission in children in Southern China
Bibliographic record
Abstract
BACKGROUND: There are incomplete data on the global burden of viral lower respiratory tract infection, in particular the role of Respiratory Syncytial Virus, in children requiring health services. FINDINGS: In this study set in a large urban area of southern China from 1 January 2007 to 31 December 2010, children 1 month to 14 years of age with RSV-associated "severe" or "very severe pneumonia" according to World Health Organization definitions, and meeting local criteria for admission to the pediatric intensive care unit, were followed for the course of their admission. The median age was 3 months and 79% (135/171) of children with RSV were under six months of age. All children needed supplemental oxygen, and 22% required mechanical ventilatory support. The mortality rate was 3.5%. In multivariate analysis, congenital heart disease and Trisomy 21 were associated with death. CONCLUSIONS: Children admitted to an intensive care unit with RSV-associated severe/very pneumonia in a large urban setting in southern China were most commonly ≤ six months old and almost one quarter of these had respiratory failure. The overall mortality rate was 3.5%. RSV vaccine strategies that would protect children from early infancy are urgently needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".