Norovirus‐associated gastroenteritis, Pernambuco, Northeast Brazil, 2014‐2017
Bibliographic record
Abstract
Norovirus (NoV) is currently the leading cause of nonbacterial gastroenteritis. In Brazil, few studies have characterized the molecular, epidemiological and clinical features of NoV-associated gastroenteritis. This study aimed to describe the molecular and clinicoepidemiological findings of NoV infections in patients of all ages throughout Pernambuco state, Northeast Brazil. Thus, 1135 stool samples were analyzed from patients with gastroenteritis from Pernambuco state. NoV was detected by enzyme immunoassay in 125 (11.01%) samples. Regarding gender distribution, 55 (44.00%) patients were female and 70 (56.00%) male. Their ages ranged from 5 days to 87 years, and the group most affected by NoV infection (88.00%) was children under 3 years. Complete clinical information was available for 88 out of 125 NoV-positive patients. Diarrhea was present in all patients and vomiting was reported in 60 patients (68.68%). Nine patients (10.22%) had bloody stools and 46 (52.27%) had a fever, with temperatures ranging from 37.90°C to 39.90°C (mean 38.20°C). NoV was detected mainly in the summer-autumn seasons. Genome sequencing and phylogenetic analyses identified four different NoV GII genotypes circulating in this area of the country. Therefore, our study provided valuable information about the clinics and epidemiology of NoV infection in tropical settings and will assist health authorities to develop better control strategies against this important pathogen.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".