Kliničke i laboratorijske osobitosti pandemijske i sezonske influence u djece
Bibliographic record
Abstract
Several studies carried out in recent years have provided increasing evidence for the great disease burden of influenza in children. During annual outbreaks, the attack rates of influenza are highest in children. Influenza frequently gives rise to bacterial complications such as acute otitis media, and young children are hospitalized for influenza-related illnesses at rates comparable to those seen in the elderly. Children also have a central role in the spread of influenza in the community, and the socioeconomic impact of pediatric influenza on children and on their household members is substantial. The great impact of influenza on children calls for increased attention to effective management of this illness in the youngest age groups. Influenza vaccination of young children is currently recommended in some countries (eg, the United States, Canada, and Finland) but despite the recommendations the vaccination rates remain low in many areas. For the treatment of influenza, the neuraminidase inhibitor oseltamivir is licensed for use in children 1 year of age or older. When started within 48 hours of the onset of symptoms, oseltamivir treatment shortens the duration of influenza by 1.5 days and reduces the development of acute otitis media as a complication by more than 40%. Neuraminidase inhibitors are also effective for postcontact prophylaxis of influenza in the family setting. The difficulty of diagnosing influenza on clinical grounds alone is an important limiting factor for the institution of antiviral treatment in young children. This is particularly true for the primary care where the routine use of influenza rapid tests for all febrile patients during a busy epidemic period may not be feasible.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".