Early experience with modified dose nirmatrelvir/ritonavir in dialysis patients with coronavirus disease-2019
Bibliographic record
Abstract
Abstract Introduction Nirmatrelvir/Ritonavir was approved for use in high risk outpatients with coronavirus disease (COVID-19). However, patients with severe chronic kidney disease, including patients on dialysis, were excluded from the phase 3 trial, and currently the drug is not recommended below a glomerular filtration rate of 30 ml/min/1.73m 2 . Based on available pharmacological data and principles, we developed a modified dose which was lower, and administered at longer intervals.We administered nirmatrelvir/ritonavir as 300/100 mg on day one, followed by 150/100 mg daily from day two to day five. In this case series, we report the initial experience with this modified dose regimen. Methods This is a retrospective chart review, conducted after obtaining institutional board approval. Demographic and outcome data was abstracted from the electronic medical record for dialysis patients who developed COVID-19 during the period of study and received nirmatrelvir/ritonavir. The principal outcomes we describe are symptom resolution, and safety data with the modified dose regimen in the dialysis patients. Results 19 patients developed COVID-19 during the period of study of whom 15 received nirmatrelvir/ritonavir. 47% of them were female and 67% had diabetes. Most patients had received three doses of the vaccine (80%) while 13% were unvaccinated. Potential drug interactions concerns were common (median 2 drugs per patient) with amlodipine and atorvastatin being the commonest drugs requiring dose modification. Nirmatrelvir/ritonavir use was associated with symptom resolution in all patients, and was well tolerated. One patient had a rebound of symptoms, which improved in 2 more days. There were no COVID-19 related hospitalizations or deaths in any of the patients. Conclusion In this case series of 15 hemodialysis patients with COVID-19, a modified dose of nirmatrelvir/ritonavir use, with pharmacist support for drug interaction management, was associated with symptom resolution, and was well tolerated with no serious adverse effects.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".