134 Virus kinetics and biochemical derangements in children with Ebolavirus disease
Bibliographic record
Abstract
Abstract Primary Subject area Infectious Diseases Background In the second largest outbreak of Ebolavirus disease (EVD) on record (Democratic Republic of Congo, 2018-2020), 3470 cases were confirmed, 29% of them among children under 18 years of age. Objectives To describe virologic and biochemical characteristics of pediatric patients with EVD, and to compare these to a control group of adults with EVD. Design/Methods Retrospective medical record review of children < 16 years old from two treatment centres in North Kivu, DRC. A control group of patients 16-44 years old was included as a reference comparator group. Patient demographics, serial measurements of viral load, serial biochemistry panel, and frequent point-of-care glucose test results were abstracted from the chart record. Funding provided by the Association for Health Innovation in Africa (AFHIA). Results Seventy-three children and 234 adults were included, admitted from April 24 to October 14, 2019. Pediatric patients commonly had electrolyte imbalances (36% hypokalemia, 52% hyperkalemia, and 74% hyponatremia), AKI (51%), elevated liver enzymes (median peak ALT 380 IU/L and AST 570 IU/L), and rhabdomyolysis (48%). Viral load at admission (7.2 versus 6.5 log10copies/mL, p=0.0001), peak viral load (7.5 versus 6.7 log10copies/mL, p<0.0001), and time to clearance of viremia (16 versus 12 days p<0.0001) were significantly different in children. Duration of hospital stay (20 versus 16 days, p<0.0001) was prolonged in children, a direct consequence of slower clearance of viremia. There was no significant difference between groups in other laboratory values. Factors including ALT >525 U/L, viral load (VL) >7.6 log10copies/mL, BUN >7.5 mmol/L, and CRP >100 mg/L were associated with mortality in children, as in adults. In a multivariable logistic regression model, ALT and VL remained statistically significant independent predictors of mortality. Conclusion Pediatric patients with EVD, like adults, experience multi-organ involvement with life-threatening kidney and liver injury, rhabdomyolysis, and electrolyte imbalances. Pediatric patients have significantly higher viral loads throughout the course of EVD than adults.
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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".