Your privacy, your choice

We use essential cookies to make sure the site can function. We also use optional cookies for advertising, personalisation of content, usage analysis, and social media.

By accepting optional cookies, you consent to the processing of your personal data - including transfers to third parties. Some third parties are outside of the European Economic Area, with varying standards of data protection.

See our privacy policy for more information on the use of your personal data.

for further information and to change your choices.
Skip to main content
Download PDF

Factors influencing Nirmatrelvir/Ritonavir concentration in patients with COVID-19

BMC Infectious Diseases volume 24, Article number: 1425 (2024) Cite this article

Abstract

Background

In the filed of antiviral therapy, effective therapeutic concentration is beneficial to shorten the recovery time of patients and reduce the transmission rate.The aim of this study is to retrospectively analyze the factors that lead to the drug concentration of Nirmatrelvir /Ritonavir (NMV/RTV) not reaching the standard.

Methods

In this study, the NMV/RTV drug concentration(Cnmv/rtv) data (n = 114) of COVID-19 patients over 18 years old were collected from May 2022 to July 2022, and the results of the patients were retrospectively compared. According to the analysis of the early study of NMV/RTV, combined with the research results at home and abroad, according to whether the measured drug concentration > 987 ng/ml, the patients were divided into target group and non-target group,The non-target group was defined as not reaching the trough concentration level.

Results

Serum NMV/RTV concentration in adult patients was correlated with prognostic nutritional index [PNI, (P < 0.05)], height (P < 0.05), weight (P < 0.05) and creatinine clearance [Crcl, (P < 0.05)]. Multivariate analysis showed that height, weight, PNI, lymphocyte (LYM) and CrCl were independent influencing factors of NMV/RTV trough concentration. However, after the correction of BMI calculation, there was no correlation between NMV/RTV and BMI, so in the clinical medication plan, the drug was not adjusted according to the height and weight.

Conclusions

The serum NMV/RTV concentration of adult patients gradually decreased with the increase of CrCl. For patients with high and low CrCl, the trough concentration of NMV/RTV should be continuously monitored and the dosing regimen should be adjusted to achieve the target trough concentration in these patients to reduce the effect of CrCl. PNI is also a key factor affecting drug concentration. For poor nutritional status, drug concentration should be closely monitored and the dose should be adjusted.

Peer Review reports

Background

Coronavirus disease 2019 (COVID-19) infection has caused serious harm to the world. As of July 2022, the pathogen had spread throughout the world, with more than 572 million confirmed cases of COVID-19, including more than 6 million deaths [1]. Caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the SARS-CoV-2 genome encodes four major structural proteins:spike (S) surface glycoprotein, membrane (M) protein, envelope (E) protein, and nucleocapsid (N) protein, in addition to other nonstructural proteins.

At present, a variety of antiviral drugs, monoclonal antibodies and immunomodulatory drugs have been proposed as treatment methods for SARS-CoV-2 infection. The main mechanism is to prevent virus entry into host cells and inhibit intracellular viral replication.Examples include Remdesivir, Favipiravir, Molnupiravir, paxilovid, etc.Nirmatrelvir /ritonavir(paxilovid) is an effective and safe oral antiviral drug, which is recommended by WHO for the treatment of adult patients with mild to moderate coronavirus disease 2019 with high risk factors for progression to severe disease.In a real-world study of 180 351 critically ill patients, Paxlovid was found to be associated with a significant reduction in the incidence or mortality of severe COVID-19 [2]. It has been urgently and widely used for COVID-19 treatment during the Omicron pandemic in China in 2022.The mechanism of action of NMV is to block the major protease (Mpro) in the replication process of SARS-CoV-2, and it can also significantly reduce the risk of hospitalization and death associated with COVID-19 [3].

A multiscale mathematical model assessing population-level benefits of expanded use of the antiviral drug Paxlovid against SARS-CoV-2 Omicron variant infections in the U.S.Treatment of 20% of patients with symptomatic cases with Paxlovid within 300 days could save lives and costs and, under low transmission, US $56.95 billion [4]. A data of 5287 patients confirmed a decrease in rehospitalization 5 to 15 days after the end of the NMV/RTV course, which could be explained by its ability to inhibit progression to severe COVID-19 [5]. It has been shown that NMV/RTV retains consistent and potent antiviral activity in vitro in SARS-CoV-2 variants, including the Omicron variant. Such as SARS-CoV-2 Alpha, Beta, Gamma, Delta, Lambda, Mu and Omicron BA-1 variants, which are the advantages of NMV antiviral [6]. With the continuous mutation of the virus, NMV/RTV is not easy to fail, because the mutation mainly occurs in the spike protein [7, 8]. The metabolism of NMV is mainly involved in cytochrome P450 (CYP) 3A4, and CYP3A4 is able to metabolize about 50% of marketed drugs.Therefore, when combined with RVT, a potent CYP3A4 inhibitor, the duration of NMV action can be significantly increased,it was maintained at more than 90% of the daily effective concentration [9]. Therefore, the treatment regimen was NMV 300 mg (150 mg × 2 tablets) combined with RTV 100 mg (100 mg x l tablet) administered orally every 12 h for 5 days.In addition, studies have shown that Paxlovid is effective and safe for COVID-19, and the safety issue is mainly related to the combination of drugs, such as tacrolimus, voriconazole, cyclosporine, which are affected by CYP3A4 enzyme [2, 10,11,12].

In the process of clinical treatment, effective therapeutic concentration is beneficial to shorten the recovery time of patients. Therefore, this study is to retrospectively analyze the factors that lead to the drug concentration of NMV/RTV not reaching the standard, so as to provide experience for clinical treatment in the future.

Materials and methods

General material

A retrospective analysis was performed on 114 patients who were admitted to the COVID-19 department of Shanghai Public Health Clinical Center from May 2022 to July 2022 through electronic medical records and had NMV/RTV drug concentration monitored. The variables involved included: gender, age, height, weight, blood drug concentration data, laboratory indicators, comorbidities, and disease severity classification. Inclusion criteria: (1)Age ≥ 18 years old, meeting the diagnostic criteria of 2019-ncov infection;(2) According to NMV/RTV (trade name: Paxlovid, manufacturer: Nirmatrelvir tablets company name: Pfizer Manufacturing Deutschland GmbH, Germany; Ritonavir Tablets Company Name: Hetero Labs Limited, India, Approval No. Nematavir 300 mg (150 mg × 2 tablets) combined with ritonavir 100 mg (100 mg × 1 tablet), oral administration every 12 h for 5 days, may be used for nasal feeding in some critically ill patients. (3)after at least 1 day of administration of nemmatavir/ritonavir and monitoring of random concentrations after administration. Exclusion criteria: (1)no blood drug concentration was detected; (2)patients undergoing hemodialysis; (3)Pregnant and lactating patients; (4)Allergic reactions occurred during the use of drugs; (5) incomplete medication information records. This study met the requirements of medical ethics and was approved by the Ethics committee of our hospital (ethical approval number: 2021-S070-02).

Groups

According to the inclusion and exclusion criteria, 114 patients were included in the final study. According to the existing research and product information [6, 13], the trough concentration of NMV/RTV was set to 987 ng/ml, which was considered to be the minimum concentration of the drug. If the drug concentration did not reach this value, it was considered that the drug did not reach the standard. Therefore, according to whether the drug concentration reached 987 ng/ml, the drug was divided into the standard group (group A,n = 74) and the failure group (group A,n = 40). According to the clinical diagnosis of COVID-19, the patients were divided into mild (n = 21), moderate (n = 53), severe (n = 29), and critical (n = 11) types. According to CURB-65 classification, the patients were divided into low risk group (n = 56), moderate risk group (n = 40) and high risk group (n = 18).

Determination of plasma concentration of NMV/RTV

Plasma was precipitated by methanol and acetonitrile in proportion, and NMV/RTV and its internal standard were detected by multiple reaction monitoring (MRM) positive ion mode. Therapeutic drug monitoring (TDM) in patients with COVID-19 was performed using a validated UHPLC-MS/MS.

Validation: UHPLC-MS/MS was validated according to the US Food and Drug Administration (FDA) guidelines, including selectivity, linearity, precision and accuracy, matrix effects, extraction recovery, and stability.

Data analysis

SPSS 26.0 software was used to analyze the data. The measurement data were tested for normality and expressed as mean ± standard deviation. The t test was used to analyze the difference between the two groups of normally distributed clinical data, and the nonparametric rank sum test was used to analyze the difference between the two groups of non-normally distributed clinical data. Count data were expressed as frequency (percentage), and the difference between groups was analyzed by chi-square analysis. The correlation between drug concentration and clinical data was explored. Spearman rank correlation analysis was used because the normal distribution was not satisfied. Multivariate logistic regression analysis was used to identify the risk factors for insufficient plasma concentration of NMV/RTV. The receiver operating characteristic (ROC) curve was drawn to evaluate the predictive value of each risk factor for drug insufficiency in COVID-19 patients. P < 0.05 was considered statistically significant.

Results

The data of the two groups were compared (Table 1)

Table 1 The data of the two groups were compared
Full size table

A total of 114 patients were included in the study, including 40 patients in the standard drug concentration group (group B) and 74 patients in the substandard drug concentration group (groupA). The drug concentration of the standard group was 3842.84 ± 2658.61 ng/ml, and the drug concentration of the substandard group was 443.1 ± 263.62 ng/ml. There was a difference between the two groups. There were no significant differences in Cnmv/rtv, BMI, age, female, nucleic acid value, Hemoglobin (HGB), C-reactive protein (CRP),Prothrombin time (PT), cardiovascular disease, cancer, surgery and other indicators between the two groups.

Correlation analysis between NMV concentration and clinical indicators (Table 2)

Table 2 The scores and diagnostic grades of the two groups were compared
Full size table

According to the difference analysis between groups, bivariate analysis showed that the drug concentration was correlated with CrCl, diabetes, height and weight (P < 0.01).

Multivariate regression analysis of drug concentration insufficiency (Table 3)

Table 3 Multivariate regression analysis of drug concentration insufficiency
Full size table

According to the difference analysis between groups, multivariate regression analysis was performed on the indicators with differences between groups, and the results showed that except LYM, the other indicators were significant (P < 0.01).

ROC prediction curve, predicting insufficient concentration (Table 4 Fig. 1) Areas under the curve (AUC) of Height, Weight, Crcl.

Table 4 ROC prediction curve, predicting insufficient concentration
Full size table
Fig. 1
figure 1

ROC prediction curve, predicting insufficient NMV concentrations

Full size image

Analysis and discussion

In a foreign study on the risk of progression to severe Covid-19 in 2246 patients within 28 days, NMV/RTV could reduce the risk by 89%. Patients who started treatment within 3 days and 5 days after symptom onset had relative risk reductions of 88.9% and 87.8%, respectively [14]. NMV/RTV has been shown to be a promising therapeutic option for treating patients with mild to moderate COVID-19 who are at risk of hospitalization or progression to severe disease [15]. Due to the high pharmacokinetic variability of NMV, insufficient concentrations increase the risk of treatment failure. Therefore, TDM monitoring is particularly important for clinical decision making. Considering the stability of the drug, this study screened the drug concentration for at least 1 day of treatment. Combined with the basic study results of 300/100 mg bid administration simulating NMV/RTV, it was shown that more than 90% of the subjects would achieve a target free Cmin above the in vitro EC90 (Effective Concentration 90) after the first and subsequent doses.The interindividual variability in clearance ballooned to 60%. The predicted median Cmin at day 1 and steady-state was 987 ng/mL and 1800 ng/mL, respectively, approximately 3-and sixfold higher than in vitro. In this way, we believe that when the drug concentration does not reach the trough concentration after the first day, it is considered that the drug has not reached the effective concentration, so it is divided into the substandard group and the standard group. In the between-group analysis, the study found that there was a difference in the negative conversion time of nucleic acid between the substandard group and the standard group (P < 0.05). In order to ensure the accuracy of the results, we compared the basic characteristics of the patients between the two groups, and the nucleic acid viral load was double-well. There was no significant difference between the two groups (P = 0.2, P = 0.3). In order to exclude the influence of the severity of the disease on this phenomenon, we divided the disease into mild, moderate, severe and critical types according to the diagnosis and treatment of COVID-19. At the same time, we classified the severity of the disease according to CURB-65 score, and found that there was no difference between the groups. CURB-65 included 5 items, each with 1 point, including disturbance of consciousness, blood urea nitrogen level (> 7 mmol/L), respiratory rate (≥ 30 breathe/min), blood pressure (systolic blood pressure < 90 mmHg or diastolic blood pressure ≤ 60 mmHg), and age (≥ 65 years). The score was used to guide treatment decisions: 0–1 was defined as low risk; 2 was defined as moderate risk; 3–5 was classified as high risk.Therefore, the negative conversion time of nucleic acid after taking medicine represents the effect of drug treatment, and the negative conversion time of the substandard group is longer. We collected clinical data on drug concentration, and other laboratory indicators were the results of blood indicators within 3 days of concentration. We collected clinical data on drug concentration, and other laboratory indicators were the results of blood indicators within 3 days of concentration, including the following items, such as inflammatory indicators (LYM, high-sensitivity C-reactive protein, etc.), liver function (transaminase, bilirubin, protein, etc.), renal function (creatinine, urea, creatinine clearance rate, etc.). Myocardial markers (isoenzymes, BNP, etc.), nutritional indicators (prealbumin, PNI, etc.), basic characteristics (height, weight, age, gender, etc.), comorbidities such as cardiovascular disease, liver disease, kidney disease, surgery, diabetes, malignant tumors, etc. The differences between the two groups were only in height, weight, PNI, LYM, CrCl, and diabetes (P < 0.05). After standardized by BMI, there was no difference in BMI between the two groups. Therefore, further correlation analysis and multivariate regression analysis showed that PNI and Crcl were parameters that we need to pay attention to.

PNI is called prognostic nutritional index, which is mainly calculated by measuring serum albumin and peripheral blood lymphocytes. It can comprehensively reflect the nutritional status and immune status of patients. Several studies have shown that malnutrition can lead to changes in the immune system, suppress immune responses and increase susceptibility to infections such as COVID-19. In particular, elderly patients and those with underlying diseases are more likely to suffer from malnutrition [16,17,18]. Other studies have found that the proportion of malnutrition in critically ill patients can reach 70% and is closely related to death, length of hospital stay, and duration of mechanical ventilation [19]. Multiple systematic reviews and observational studies [18, 20, 21] have shown that PNI is a good evaluation index for predicting the severity and prognosis of the disease. Among 223 patients with severe COVID-19, the primary outcome indicator was the mortality during hospitalization. Through analysis, PNI and NLR were better than PLR and LMR in identifying the in-hospital mortality.

Multivariate analysis showed that PNI(40.2,P = 0.009) was an independent predictor of mortality in patients with severe COVID-19, and the AUC value of PNI for predicting in-hospital mortality in patients with severe COVID-19 was 0.91.

Secondly, in this study, we used Cockcroft-Gault (CG) common formula to calculate CrCl [22], CrCl (mL/min) = [(140-age) × body weight (kg)] / [0.818 × SCr (μmol/L)], if a female patient, the result × 0.85. Finally, the relationship between CrCl and drug concentration was found to be negative. Not only that, other studies have shown that NMV has a molecular weight of 499.5D, about 35% is excreted by the kidney, and 70% is bound to protein. Ritonavir is mainly metabolized by the liver and is 99% bound to proteins.The NMV/RTV dosing strategy in Chinese COVID-19 patients has recently been characterized by a single-compartment model of primary absorption with creatinine clearance as a significant covariate [23]. Therefore, NMV will accumulate with the decline of renal function [24].

We concluded that the trough concentration of NMV/RTV in adult patients gradually decreased with the decrease of PNI and the increase of CrCl. For such patients, we should pay attention to the trough concentration of NMV/RTV and adjust the dosing regimen to achieve the target trough concentration, so as to reduce the impact on clinical efficacy.In addition, other findings have shown no racial differences in pharmacokinetic of NMV [25]. Finally, there are some limitations in this study:1. This is a single-center study without multi-center study.2. Only single drug TDM monitoring is performed, and drug interactions are excluded [12].

Therefore, finally, for drugs affected by CYP3A4 enzyme, such as voriconazole, tacrolimus, digoxin, etc. clinical decision-making [26,27,28] needs to further consider drug interaction to evaluate the influencing factors of drug concentration substandard.

Data availability

Data is provided within the manuscript or supplementary information files.

References

  1. Krzych Ł J, Putowski Z, Gruca K, et al. Mortality in critically ill COVID‑19 patients with fungal infections: a comprehensive systematic review and meta‑analysis[J]. Pol Arch Intern Med. 2022;132(5):16221–33.

  2. Najjar-Debbiny R, Gronich N, Weber G, et al. Effectiveness of paxlovid in reducing severe coronavirus disease 2019 and mortality in high-risk patients. Clin Infect Dis. 2023;76(3):e342–9.

    Article  CAS  PubMed  Google Scholar 

  3. Hung Y P, Lee J C, Chiu C W, et al. Oral Nirmatrelvir/Ritonavir Therapy for COVID-19: The Dawn in the Dark?. Antibiotics (Basel). 2022;11(2):220–7.

  4. Bai Y, Du Z, Wang L, et al. Public health impact of paxlovid as treatment for COVID-19, United States. Emerg Infect Dis. 2024;30(2):262–9.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Malden DE, Hong V, Lewin BJ, et al. Hospitalization and emergency department encounters for COVID-19 after paxlovid treatment - California, December 2021-May 2022. MMWR Morb Mortal Wkly Rep. 2022;71(25):830–3.

    Article  CAS  PubMed  Google Scholar 

  6. Qu Y, Su C, Xiang Z, et al. Population pharmacokinetic modeling and simulation for nirmatrelvir exposure assessment in Chinese older patients with COVID-19 infection. Eur J Pharm Sci. 2023;189: 106535.

    Article  CAS  PubMed  Google Scholar 

  7. Chen SA, Arutyunova E, Lu J, et al. SARS-CoV-2 M(pro) protease variants of concern display altered viral substrate and cell host target galectin-8 processing but retain sensitivity toward antivirals. ACS Cent Sci. 2023;9(4):696–708.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Candido KL, Eich CR, De Fariña LO, et al. Spike protein of SARS-CoV-2 variants: a brief review and practical implications. Braz J Microbiol. 2022;53(3):1133–57.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Gerhart J, Cox DS, Singh RSP, et al. A comprehensive review of the clinical pharmacokinetics, pharmacodynamics, and drug interactions of Nirmatrelvir/Ritonavir. Clin Pharmacokinet. 2024;63(1):27–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Zheng Q, Ma P, Wang M, et al. Efficacy and safety of Paxlovid for COVID-19:a meta-analysis. J Infect. 2023;86(1):66–117.

    Article  CAS  PubMed  Google Scholar 

  11. Hashemian SMR, Sheida A, Taghizadieh M, et al. Paxlovid (Nirmatrelvir/Ritonavir): A new approach to Covid-19 therapy? Biomed Pharmacother. 2023;162: 114367.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Marzolini C, Kuritzkes DR, Marra F, et al. Recommendations for the Management of Drug-Drug Interactions Between the COVID-19 Antiviral Nirmatrelvir/Ritonavir (Paxlovid) and Comedications. Clin Pharmacol Ther. 2022;112(6):1191–200.

    Article  CAS  PubMed  Google Scholar 

  13. Singh RSP, Toussi SS, Hackman F, et al. Innovative Randomized Phase I Study and Dosing Regimen Selection to Accelerate and Inform Pivotal COVID-19 Trial of Nirmatrelvir. Clin Pharmacol Ther. 2022;112(1):101–11.

    Article  CAS  PubMed  Google Scholar 

  14. Hammond J, Leister-Tebbe H, Gardner A, et al. Oral nirmatrelvir for high-risk, nonhospitalized adults with Covid-19. N Engl J Med. 2022;386(15):1397–408.

    Article  CAS  PubMed  Google Scholar 

  15. Amani B, Amani B. Efficacy and safety of nirmatrelvir/ritonavir (Paxlovid) for COVID-19: A rapid review and meta-analysis. J Med Virol. 2023;95(2): e28441.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Zhang JJ, Dong X, Liu GH, et al. Risk and protective factors for COVID-19 morbidity, severity, and mortality. Clin Rev Allergy Immunol. 2023;64(1):90–107.

    Article  CAS  PubMed  Google Scholar 

  17. Antwi J, Appiah B, Oluwakuse B, et al. The Nutrition-COVID-19 Interplay: a Review. Curr Nutr Rep. 2021;10(4):364–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Karimi A, Shobeiri P, Kulasinghe A, et al. Novel systemic inflammation markers to predict COVID-19 prognosis. Front Immunol. 2021;12: 741061.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Abate SM, Chekole YA, Estifanos MB, et al. Prevalence and outcomes of malnutrition among hospitalized COVID-19 patients: A systematic review and meta-analysis. Clin Nutr ESPEN. 2021;43:174–83.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Wang ZH, Lin YW, Wei XB, et al. Predictive value of prognostic nutritional index on COVID-19 Severity. Front Nutr. 2020;7: 582736.

    Article  PubMed  Google Scholar 

  21. Açıksarı G, Koçak M, Çağ Y, et al. Prognostic value of inflammatory biomarkers in patients with severe COVID-19: A single-center retrospective study. Biomark Insights. 2021;16:11772719211027022.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Shahbaz H, Rout P, Gupta M: Creatinine Clearance, StatPearls, Treasure Island (FL) ineligible companies. Disclosure: Preeti Rout declares no relevant financial relationships with ineligible companies. Disclosure: Mohit Gupta declares no relevant financial relationships with ineligible companies.: StatPearls Publishing Copyright © 2024, StatPearls Publishing LLC., 2024.

  23. Yang P, Liu W, Ying Y, et al. Population pharmacokinetics of nirmatrelvir in Chinese patients with COVID-19: Therapeutic drug monitoring and dosing regimen selection in clinical practice. Int J Antimicrob Agents. 2024;64(2):107199.

    Article  CAS  PubMed  Google Scholar 

  24. Hiremath S, Mcguinty M, Argyropoulos C, et al. Prescribing Nirmatrelvir/Ritonavir for COVID-19 in Advanced CKD. Clin J Am Soc Nephrol. 2022;17(8):1247–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Zeng L, Chen R, Jiang X, et al. Population pharmacokinetics and pharmacodynamics of nirmatrelvir in Chinese patients with COVID-19. Fundam Clin Pharmacol. 2024;38(4):767–79.

    Article  CAS  PubMed  Google Scholar 

  26. Abraham S, Nohria A, Neilan TG, et al. Cardiovascular drug interactions with Nirmatrelvir/Ritonavir in patients with COVID-19: JACC review topic of the week. J Am Coll Cardiol. 2022;80(20):1912–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Lemaitre F, Budde K, Van Gelder T, et al. Therapeutic drug monitoring and dosage adjustments of immunosuppressive drugs when combined with Nirmatrelvir/Ritonavir in patients With COVID-19. Ther Drug Monit. 2023;45(2):191–9.

    Article  CAS  PubMed  Google Scholar 

  28. Dewey KW, Yen B, Lazo J, et al. Nirmatrelvir/ritonavir use with tacrolimus in lung transplant recipients: a single-center case series[J]. Transplantation. 2023;107(5):1200–5.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We sincerely thank the management and ethics committees of all participating hospitals for granting us data access for this study.

Conflict of interests

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding

This work was supported by the Fund for Shanghai Public Health Clinical Center, Hospital Project(KY-GW-2023–19).

Author information

Authors and Affiliations

  1. Department of Respiratory and Critical Care Medicine, Shanghai Public Health Clinical Center, Shanghai, 201508, People’s Republic of China

    Ping Xu & Qingguo Wu

  2. Department of Clinical Research, Shanghai Public Health Clinical Center, Shanghai, 201508, People’s Republic of China

    Lijun Zhang

Authors
  1. Ping Xu
    View author publications

    Search author on:PubMed Google Scholar

  2. Lijun Zhang
    View author publications

    Search author on:PubMed Google Scholar

  3. Qingguo Wu
    View author publications

    Search author on:PubMed Google Scholar

Contributions

Zhang lijun and Wu qingguo designed the study. Xu ping collected the clinical data and analyzed the data. All authors contributed to the manuscript and approved the submitted version. All authors reviewed the manuscript.

Corresponding authors

Correspondence to Lijun Zhang or Qingguo Wu.

Ethics declarations

Ethics approval and consent to participate

This study is a retrospective cohort study, but not a clinical trial, thus the clinical trial number is not applicable.

Ethical approval was obtained from the Ethics Committee ofShanghai Public Health Clinical Center on July 26, 2022 (Granted number: 2021-S070-02), all procedures were in accordance with ethical standards, and informed consent was waived for this retrospective review.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xu, P., Zhang, L. & Wu, Q. Factors influencing Nirmatrelvir/Ritonavir concentration in patients with COVID-19. BMC Infect Dis 24, 1425 (2024). https://doi.org/10.1186/s12879-024-10291-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12879-024-10291-6

Keywords

BMC Infectious Diseases

ISSN: 1471-2334

Contact us