Rabies in humans: A treatment approach
Bibliographic record
Abstract
BACKGROUND: Only few rabies survivors have been described in the medical literature, of whom most suffered severe neurological sequelae. Published treatment protocols have not been applied successfully. Yet, experimental treatments may be of benefit when factors associated with survival are present. Here, we describe two patients who were hospitalised at Amsterdam UMC with clinical rabies and who died despite experimental treatments. METHODS: We describe the clinical course and medical decisions in the treatment of two rabies patients at our hospital and compared this approach with published data on the treatment of clinical rabies, depending on the presence or absence of prognostic factors associated with survival, and regarded this information in the context of clinical practice. RESULTS: The most important factor associated with survival - the presence of high antibody titres in serum or cerebrospinal fluid (CSF) at the time of diagnosis - was not present in either of the two cases at our hospital. In addition to supportive treatment, both of our patients were treated unsuccesfully with a novel treatment approach with intrathecal and intravenous monoclonal rabies antibodies, which barely increased serum and CSF antibody levels. CONCLUSIONS: Higher-dosed treatments with monoclonal antibodies in serum may be needed to yield an effect. Any experimental treatment may be most promising in patients who have other factors associated with survival. In the absence of these, initiation of palliative care still seems to remain the most rational strategy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".