Association of pediatric COVID‐19 and subarachnoid hemorrhage
Bibliographic record
Abstract
Neuroinvasive Potential of SARS-CoV2 May Play a Role in the Respiratory Failure of COVID-19 Patients." Here, we describe subarachnoid hemorrhage (SAH) as a severe neurological manifestation associated with pediatric COVID-19. A 9-year-old boy presented with cardiopulmonary arrest and low Glasgow Coma Scale (GCS) and COVID-19 symptoms, including respiratory insufficiency, fever, nausea, abdominal pain, headache, anorexia, and fatigue. He had no past medical history and close contact with a person who tested positive for COVID-19. Reverse transcriptionpolymerase chain reaction (RT-PCR) from nasopharyngeal swab specimens confirmed positive COVID-19. Laboratory testing (Table 1) revealed the development of nonoliguric renal failure due to a fourfold increase in creatinine. The patient blood-type was A+. He received intravenous dopamine for low blood pressure and fresh frozen plasma (FFP) in addition to meropenem, vancomycin, azithromycin, oseltamivir, levofloxacin, lopinavir/ritonavir, and hydroxychloroquine. Chest computed tomography (CT) scan (Figure 1) was performed two times: On the first day of hospitalization, the scan exhibited consolidation at posterior basal segments of both lungs with air bronchogram sign and on the second day, it revealed a consolidation with the progression of air bronchogram and a mild right-sided pleural effusion occurred. Due to fixed and dilated pupils on the second day, the brain CT scan (Figure 1F) uncovered the hyperdensity at basal cisterns, interhemispheric and bilateral Sylvian fissures in favor of SAH, and reduction of white matter density in favor of brain edema. The World Federation of Neurologic Surgeons grading scale for SAH was 5. Timely follow-up chest CT along with RT-PCR confirmed COVID-19
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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".