Does C1 esterase inhibitor play a role in post COVID-19 neurological symptoms? A randomized, double-blind, placebo-controlled, crossover, proof-of-concept study
Bibliographic record
Abstract
Background: Many patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection experience neurologic changes post-infection, which has been hypothesized to be due to dysregulation in the infectious-immune axis that leads to a neuro-immune response. This immune dysfunction has been termed "Alzheimer's of the Immune System" or AIS and there are several immune factors that may play a key role. These include, among others, complement activation due to low levels of C1-esterase inhibitor (C1-INH) and function, and a decrease in signaling of Toll-like receptor (TLR)-3. We propose that C1-INH replacement may upregulate the immune dysfunction, thereby improving neurological symptoms. Methods: In this randomized, double-blind, placebo-controlled, crossover, proof-of-concept study, adults experiencing SARS-CoV-2 post-viral fatigue syndrome for >4 weeks post-recovery from coronavirus disease 2019 (COVID-19) infection were randomized 1:1 to two arms: Arm 1 (C1-INH for 8 weeks, then placebo for 8 weeks) or to Arm 2 (placebo for 8 weeks, then C1-INH for 8 weeks). Patients were assessed for adult executive function, abnormal cognitive decline, depression [Beck Depression Inventory-II (BDI-II)], migraine, fatigue [Fatigue Severity Scale (FSS)] and pain (Short-form McGill Pain Questionnaire). Percent change in TLR signaling in response to zymosan was compared with controls at baseline, Week 8 and Week 16. Safety was assessed throughout. Results: At this interim analysis, 36 patients with SARS-CoV-2 post-viral fatigue syndrome had completed the two 8-week treatment periods. In Arm 1, trends toward improvements from baseline at Week 8 of C1-INH therapy were observed in BDI-II score (-8.7 points), mean FSS score (0.6 points), and mean McGill Pain Questionnaire score (-0.4 points). These improvements were either sustained or worsened at Week 16, following crossover to placebo. The outcomes in Arm 2 were compatible with those in Arm 1. Patients with SARS-CoV-2 post-viral fatigue syndrome had low levels of TLR-related signaling biomarkers compared with healthy controls. Conclusion: This proof-of-concept study demonstrates sustained dysregulation of the immune system after COVID-19 infection. Improvements in depression, fatigue, and pain were observed with C1-INH treatment in patients with SARS-CoV-2 post-viral fatigue syndrome, indicating C1-INH may be a potential therapeutic target. Clinical trial registration: The study was registered on September 21, 2024, with the identifier number NCT04705831.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".