Efficacy Of Remdesivir For Hospitalized COVID-19 Patients With End Stage Renal Disease Ⅱ
Dec 04, 2023
Data collection
Data were obtained from the Epic Electronic Medical Record system and recorded in a standardized form. Demographic data, laboratory findings, maximum oxygen requirements in Liters Per Minute (LPM), length of stay (LOS), and comorbid conditions were ascertained. Outcome measures were assessed through the date of study completion, hospital discharge or death; whichever came first.
CISTANCHE DIETARY SUPPLEMENT SEXUAL ENHANCEMENT PHENYLETHANOID GLYCOSIDES 75% ECHINACOSIDE 30% ACTEOSIDE 12%
Statistical analysis
To compare rates of oxygen and ventilator use, generalized linear modeling was used. Estimation was by maximum likelihood using SAS proc genmod software[5]. Mean oxygen use was modeled first as a normal distribution with an identity link, and the progression to mechanical ventilation was modeled as a binomial distribution with a logit link. For the length of stay and patient disposition, survival analysis was used, with estimation by SAS proc phreg[6]. Here the length of stay is modeled as a ratio for patients who discharge vs patients who do not survive. The complete outcome data was available for both the cases and controls until death or discharge from the hospital. The risk of patient health deterioration as a function of time is modeled given covariates. Model selection was based on expert medical knowledge as well as the visual examination of residual plots.
Patient experience of COVID-19 pneumonia is highly variable, differences between patients were modeled as conditional on patient health status. Comparisons were made between patients with diabetes because this is a known risk population that would be highly susceptible to disease. Additionally, to identify the specific patients with severe conditions, comparisons were also made based on d dimers. Grouping patients by rate of d dimers was selected because there were clear groupings among respondents. The histogram demonstrated a bimodal distribution, with some patients having very few d dimers, and some having many (skew = 2.64, kurtosis = 7.30). To account for this, patients above the mean were classified as "high d dimer" and patients below the mean classified as "low d dimer." The three-way interaction could then be modeled as a 2 (remdesivir or control) × 2 (diabetic or not diabetic) × 2 (high or low d dimer) ANOVA style design with interactions. While there were data available on corticosteroids, the observational nature of the study raised concerns that this may be a biased estimate because treatments were not given at random. As the research question mainly focused on the clinical outcomes with use of remdesivir, only patients' health characteristics were used as control variables, rather than introducing the complexity of various drug interactions within a small study sample.
Before analyzing the data, a brief power analysis was done to calibrate the limitations of the sample size. This was accomplished using G × Power software and the equations provided by Schoenfeld[7]. For the general regression models (oxygen, ventilator use), it was estimated that the effect of remdesivir needed to be large to be significant, accounting for 28% of the variance (2% is considered small, 13% medium, and 26% large). The effects of the additional covariates would also need to be large, accounting for an additional 25% of the variance. The survival analysis had better power, was sensitive to a small to moderate effect size, risk ratio 2.32 (convention is 1.68 small, 3.47 medium, 6.71 Large)[8]. While the sample is smaller than would be preferred, the urgency of this research question outweighs the risk of statistical power.
RESULTS
A total of 108 charts were reviewed, of which only 45 met the inclusion criteria. A total of 20 patients received remdesivir while 25 patients were in the control group. Baseline statistics are reported in Table 1. There was no significant difference in length of stay in patients who received remdesivir (M = 13.00 ± 7.35 d) compared to patients who did not receive remdesivir (M = 12.16 ± 8.38 d). Table 2 has the main effect parameter estimates for the primary research questions and covariates, and Table 3 provides the estimated means by risk group for all three endpoints. Oxygen usage was considered first. The main effect of remdesivir was significant and the parameter was negative, indicating that across patients, those who were on remdesivir tended to use less oxygen (beta = -25.93, X2 (1) = 6.65, P = 0.0099). That said, the three-way interaction term was significant (X2 (1) = 6.37, P = 0.0116), indicating that the means varied based on patient risk conditions. Comparing remdesivir and control groups within risk groups, differences were only significant among patients who did not have diabetes (see Table 3).
Examining the covariates, the only significant finding at alpha = 0.05 was for sex, such that women tended to have lower oxygen need on average (beta = -9.49, X2 (1) = 4.43, P = 0.0198). In addition, there was a trend for older patients and patients who used tobacco toward higher oxygen use (age: beta = 0.32, X2 (1) = 3.25, P = 0.0712; tobacco use: beta = 8.49, X2 (1) = 3.82, P = 0.0507). We anticipate that with larger sample size these results would reach the threshold of statistical significance.
PE stands for parameter estimate. For Max O2, this is the average difference between the specified group and the overall mean. For ventilation, this represents the log odds difference between the specified group and the overall odds of being on a ventilator. For time to mortality, this represents the difference in risk of mortality as a function of time for the specified group relative to the overall risk of mortality for coronavirus disease 2019 patients. Because age was specified as a continuous value, the values in PE represent the change in mean, odds, or risk for a one-year increase or decrease in age.
Next, the progression to mechanical ventilation was considered. As before, remdesivir use was associated with a much better outcome (beta = -28.52, X2 (1) = 22.98, P < 0.0001). The three-way interaction term was not significant, reducing the model fit overall, however, the interactions between remdesivir and each of diabetes and high d dimer status was significant (P < 0.0001), indicating dependencies between patient characteristics and health outcomes. Examining the conditional probabilities of mechanical ventilation need, remdesivir was found to be helpful for patients who were not diabetic and had low d dimer values (P < 0.0001). No covariates showed a statistically significant association with the risk of needing a ventilator; the female sex reached very close to statistical significance (X2 (1) = 3.80, P = 0.0511), indicating less risk of ventilator use on average (beta = 2.94).
Finally, the time to mortality was examined, providing similar results to the previous analyses. The main effect of remdesivir was significant (X2 (1) = 7.41, P = 0.0065) indicating on average patients on remdesivir had a better prognosis (beta = - 5.03). The three-way interaction was not significant (X2 (1) = 0.63, P = 0.4262), however, all two-way interactions were significant or close to significant (redeliver-high d dimers: X2 (1) = 3.56, P = 0.0591; redeliver-diabetes: X2 (1) = 4.59, P = 0.0322; high d dimers-diabetes: X2 (1) = 4.58, P = 0.0324) indicating dependent risks given patient characteristics. Again, it was specifically patients who did not have diabetes and had low d dimers for whom remdesivir demonstrated to significantly reduced risk (P = 0.0032, risk ratio < 0.01). No covariates demonstrated significant association with COVID-19 pneumonia prognosis.
DISCUSSION
Our study demonstrated a trend towards lesser oxygen requirement in the group of ESRD patients on HD who received remdesivir for the treatment of COVID-19 pneumonia. There was also a trend towards lower progression to mechanical ventilation in patients with COVID-19 who received remdesivir as compared to the control group. There was a trend towards better prognosis in terms of mortality in patients who received remdesivir compared to patients in the control group. However, due to the smaller number this trend did not reach statistical significance. None of the patients' treatment was interrupted due to hepatotoxicity. To our knowledge, only case series have been previously published on the safety of remdesivir in COVID-19 patients with ESRD.
Remdesivir is a monophosphoramidate prodrug of a nucleoside analog and an inhibitor of the viral RNA-dependent RNA polymerase (RDRP). Intracellularly, the prodrug is rapidly converted into GS-704277 and subsequently into a monophosphate form that is finally converted into the active triphosphate form. Dephosphorylation of the monophosphate form produces the nucleoside core (GS-441524), which becomes the predominant circulating plasma metabolite. The triphosphate form acts as an analog of adenosine triphosphate (ATP) and competes for incorporation by RDRP, causing premature chain termination and inhibition of viral replication. Originally developed as an investigational drug for Ebola virus, redeliver has potent in vitro inhibitory activity against SARS-CoV1, MERS coronavirus, and SARS-CoV2. Remdesivir is usually intravenously administered at a dose of 200 mg once followed by 100 mg daily for a total of 5-10 d in adults and children ≥ 40 kg. The plasma t1/2 of parent redeliver is 1-2 hours, however the t1/2 of GS-441524 is approximately 20-25 hours[9,10]. .
Cohen's d effect size is conventionally defined as small = 0.2, medium = 0.5, and large = 0.8. Effect sizes for risk ratios are conventionally defined as small = 0.60 or 1.68, medium = 0.29 or 3.47, and large = 0.15 or 6.71.
The intravenous preparation of remdesivir also contains a solubilizing agent, SBECD. Every 100 mg of remdesivir contains 3-6 g of SBECD (maximum recommended threshold dose 250 mg/kg per day)[11]. Animal studies have shown that SBECD accumulation may only cause hepatic and renal toxicity at doses 50 to 100 times higher than the present patients' exposure during a 5-to-10-day course of remdesivir[12,13]. SBECD does not undergo significant tubular reabsorption and remains in an ionized state after glomerular filtration. Only less than 10% of remdesivir is renally excreted while 49% is recovered in the urine as GS-441524. In a case series by Davis et al, remdesivir's half-life in 66% of the COVID-19 patients with ESRD was twice as long as in healthy volunteers. While there was a decline in remdesivir concentrations by the end of the dosing interval, GS-441524 levels were also considerably higher than reference values. Despite this, post-HD concentrations of GS-441524 were 45%-49% lower than pre-HD measurements[14].
The results from our feasibility study are hypothesis-generating. We see interesting trends towards lower oxygen requirements and reduced progression to mechanical ventilation in ESRD patients who received remdesivir as a part of the treatment for COVID-19. If remdesivir is an efficacious treatment as hypothesized, it would be expected that patients receiving this treatment would have better outcomes. This was observed in the data, at least for patients who were lower risk (i.e., not diabetic, low dimer rates). This provides early support for remdesivir, though larger studies could show the effect of remdesivir on these patient-centric outcomes.
Our study has many limitations. Firstly, only 68% of the patients in the control group received dexamethasone. However, all the patients in the remdesivir group received dexamethasone. This is mainly because some patients in the control group presented before July 2020 when dexamethasone use was not considered standard of care. In place of dexamethasone, alternative treatments such as hydroxychloroquine and convalescent plasma were used. Steroids were only used in these patients if they were in septic shock requiring vasopressors. Secondly, the sample size was relatively small. The study may not have been adequately powered to detect a significant difference. However, being a feasibility study, we did not expect the results to be statistically significant. Lastly, being a retrospective study, the study design has inherent biases such as selection and confounding biases.
CONCLUSION
The use of remdesivir in COVID-19 patients with ESRD showed a trend towards lesser oxygen requirements, lower progression to mechanical ventilation and longer. Our feasibility study is hypothesis generating and these patterns need further exploration with larger studies. Further research is also needed to study the clinical effects of remdesivir in COVID-19 patients with CKD stage 4 or 5 who are not on hemodialysis.
ARTICLE HIGHLIGHTS
Research background Little known information exists regarding the efficacy of remdesivir in COVID-19 patients with end-stage renal disease on dialysis.
Research motivation With the increasing use of remdesivir in COVID-19 patients we need more information about specific groups of patients who could potentially benefit from the use of this medication and its safety profile.
Research objectives To assess the clinical outcomes of use of remdesivir in adult patients with end-stage kidney failure on hemodialysis.
Research methods A multicenter, retrospective study was conducted on COVID-19 patients with end-stage renal disease on hemodialysis who were discharged from the hospital between April 1st and December 31st, 2020. The primary outcomes were oxygen requirements, time to mortality, and escalation of care needing mechanical ventilation.
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