Neurological Manifestations of SARS-CoV-2 Infection: Protocol for a Sub-analysis of the COVID-19 Critical Care Consortium Observational Study
Bibliographic record
Abstract
Introduction: Neurological manifestations and complications in coronavirus disease-2019 (COVID-19) patients are frequent. Prior studies suggested a possible association between neurological complications and fatal outcome, as well as the existence of potential modifiable risk factors associated to their occurrence. Therefore, more information is needed regarding the incidence and type of neurological complications, risk factors, and associated outcomes in COVID-19. Methods: This is a pre-planned secondary analysis of the international multicenter observational study of the COVID-19 Critical Care Consortium (which collected data both retrospectively and prospectively from the beginning of COVID-19 pandemic) with the aim to describe neurological complications in critically ill COVID-19 patients and to assess the associated risk factors, and outcomes. Adult patients with confirmed COVID-19, admitted to Intensive Care Unit (ICU) will be considered for this analysis. Data collected in the COVID-19 Critical Care Consortium study includes patients' pre-admission characteristics, comorbidities, severity status, and type and severity of neurological complications. In-hospital mortality and neurological outcome were collected at discharge from ICU, and at 28-days. Ethics and Dissemination: The COVID-19 Critical Care Consortium main study and its amendments have been approved by the Regional Ethics Committee of participating sites. No further approval is required for this secondary analysis. Trial Registration Number: ACTRN12620000421932.
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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 | 0.036 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.036 | 0.009 |
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".