Fourteen-days Evolution of COVID-19 Symptoms During the Third Wave in Non-vaccinated Subjects and Effects of Hesperidin Therapy: A randomized, double-blinded, placebo-controlled study
Bibliographic record
Abstract
ABSTRACT COVID-19 symptoms can cause substantial disability, yet no therapy can currently reduce their frequency or duration. We conducted a double-blind placebo-controlled trial of hesperidin 1000 mg once-daily for 14 days in 216 symptomatic non-vaccinated COVID-19 subjects. Thirteen symptoms were recorded after 3, 7, 10 and 14 days. The primary endpoint was the proportion of subjects with any of four cardinal (group A) symptoms: fever, cough, shortness of breath or anosmia. At baseline, symptoms in decreasing frequency were: cough (53.2%), weakness (44.9%), headache (42.6%), pain (35.2%), sore throat (28.7%), runny nose (26.9%), chills (22.7%), shortness of breath (22.2%), anosmia (18.5%), fever (16.2%), diarrhea (6.9%), nausea/vomiting (6.5%) and irritability/confusion (3.2%). Group A symptoms in the placebo vs hesperidin group was 88.8% vs 88.5% (day 1) and reduced to 58.5 vs 49.4 % at day 14 (OR 0.69, 95% CI 0.38–1.27, p = 0.23). At day 14, 15 subjects in the placebo group and 28 in the hesperidin group failed to report their symptoms. In an attrition bias analysis imputing “no symptoms” to missing values, the hesperidin group shows reduction of 14.5 % of group A symptoms from 50.9% to 36.4% (OR: 0.55, 0.32–0.96, p = 0.03). Anosmia, the most frequent persisting symptom (29.3%), was lowered by 7.3% at 25.3 % in the hesperidin group vs 32.6% in the placebo group (p = 0.29). Mean number of symptoms in placebo and hesperidin was 5.10 ± 2.26 vs 5.48 ± 2.35 (day 1) and 1.40 ± 1.65 vs 1.38 ± 1.76 (day 14) (p = 0.92). In conclusion, most non-vaccinated COVID-19 infected subjects remain symptomatic after 14 days with anosmia being the most frequently persisting symptom. Hesperidin 1g daily may help reduce group A symptoms. Earlier treatment of longer duration and/or higher dosage should be tested.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".