Toward Personalized Medicine: The Effect of Treatment of Chronic Enterovirus Diarrhea in an Immunocompromised Patient and the Correlation With In Vitro Models
Bibliographic record
Abstract
Enteroviruses (EV) usually cause acute, mild, self-limiting disease. Chronic infections with EVs are rare, and typically occur in patients with immunodeficiency, posing a high risk of severe outcomes. We report a rare case of chronic diarrhea caused by coxsackievirus A1 (CVA1) (from EV-C species) infection in a patient with a common variable immunodeficiency, who was on treatment with pooled intravenous immunoglobulin (IVIG) from the Netherlands. To explore treatment options, we assessed the presence of neutralizing antibodies (nAbs) against CVA1 in pooled IVIG from South Africa, where EV-Cs are prevalent, and tested the antiviral efficacy of US Food and Drug Administration-approved drugs like fluoxetine, itraconazole, ribavirin, and remdesivir (RDV) against CVA1 in vitro. Both Dutch and South African IVIG showed low nAb titers against CVA1. The patient, treated with Dutch IVIG, also received a combination of amantadine and fluoxetine, which were discontinued due to side effects. Among the drugs tested, only RDV significantly inhibited CVA1 replication in rhabdomyosarcoma (RD) cells. This in vitro efficacy was not reflected by a favorable clinical response after treatment of the patient with RDV. In concordance with unfavorable antiviral response in the patient, preliminary tests on a co-culture model containing isogenic human intestinal cells and intestinal fibroblasts showed no significant reduction in CVA1 RNA copies after RDV administration. In conclusion, our results showed that repurposing of drugs that have shown in vitro efficacy does not translate well to the patients, and this is also reflected in a more physiologically relevant model of the human intestine.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".