An analytical study of drug utilization, disease progression, and adverse events among 165 COVID-19 patients

Introduction

The outbreak of coronavirus disease 2019 (COVID-19) has quickly swept across the world (1,2), and has been declared a Public Health Emergency of International Concern (PHEIC) since January 30, 2020 (3,4). As of April 20, 2020, 210 countries and territories worldwide have reported a total of 2,481,026 confirmed cases and a death toll of 170,423. This situation already poses a serious global public health risk.

In the early stages of the outbreak, despite facing many challenges in understanding and treating COVID-19, especially a lack of specific antiviral agents, attempts at medication strategies had already been introduced into clinical practice by Chinese front-line physicians (5-9). To date, the 7^th updated version of the official diagnosis and treatment guidelines has already been published (10-14), and some achievements have been made in improving case fatality and enhancing the cure rate of COVID-19 patients. However, some concerns, including medication choices and combination and safety issues, have inevitably been raised (9,15-18). Previous studies have only described general epidemiological findings, clinical presentation, and clinical outcomes of COVID-19 patients (5-9,19-22). Furthermore, few of these studies have systematically characterized the drug utilization of COVID-19 patients. Therefore, our study's objectives were to give a full description of drug utilization, disease progression, and adverse drug events (ADEs) of COVID-19. We present the following article following the MDAR reporting checklist (available at http://dx.doi.org/10.21037/atm-20-4960).

Methods

Participants and data sources

This retrospective, single-center case series study enrolled 165 consecutive COVID-19 patients initially hospitalized at Zhongnan Hospital of Wuhan University in Wuhan, China, from December 19, 2019, to February 2, 2020. All patients were followed up to March 25, 2020, and were ≥18 years old and not diagnosed with bacterial pneumonia. Zhongnan Hospital is one of the major tertiary teaching hospitals in Wuhan, Hubei Province, and has been responsible for treating COVID-19 patients assigned by the government. According to the World Health Organization (WHO) interim guidance, all patients enrolled in this study were confirmed to be COVID-19 positive by viral test on admission (WHO) interim guidance (23,24).

The participants’ predefined information was extracted from electronic medical records (EMR), including demographics, treatment, and prognosis. A trained team of physicians and clinical pharmacists reviewed all data for accuracy and completeness. The research database was composed of 3 parts: (I) baseline characteristics, including demographics, COVID-19 contact history, underlying comorbidities; (II) diagnosis and treatment, including symptoms and signs, laboratory markers, chest computed tomographic (CT) scans, and medication (i.e., dosage, initial, and prescription and discontinuation date); (III) prognosis (death, recovery, or remained in hospital).

Medications and outcomes

We mainly focused on 9 classes of treatments according to the different versions of the guidelines for diagnosis and treatment of COVID-19 (Table S1): antivirals for systemic use [Anatomical Therapeutic Chemical (ATC) classification codes starting with J05], antibacterials for systemic use (J01), glucocorticoids for systemic use (H02AB), antimycotics for systemic use (J02), traditional Chinese medicines (TCM, identified by using drug name), general nutrients (V06), vasoactive drugs (C01DA, C01CA, and C04AB01), intestinal microecological regulators (A07F), and immunoglobulins (J06BA). The total kinds of medications (according to generic names) used per person during hospitalization were also calculated—each prescription interval accumulated the total treatment duration for specific classes/kinds of drugs.

According to the guidelines, patient baseline condition severity was classified into 4 levels: mild, general, severe, and critically severe (12). The first 2 levels were further combined as the non-severe subgroup, and the latter 2 as the severe subgroup. Disease exacerbation was defined as the measure of disease condition getting worse at any time after admission.

Blood samples were tested for creatinine (reference value <90 µmol/L), alanine aminotransferase (ALT, reference value <45 U/L), and aspartate aminotransferase (AST, reference value <40 U/L). Urine samples were tested for albumin (normal sign with “negative”). The creatinine result was used in an equation with the patient’s age, race, and sex to calculate the glomerular filtration rate (GFR, normal range of ≥90 mL/min/1.73 m²) (25). Laboratory abnormalities were used to define elevated serum aminotransferase levels and impaired renal function.

Statistical analysis

We first compared the baseline characteristics (including age, gender, occupation, etc.), drug utilization (including types of drugs, combination patterns, the number of the medications, total treatment duration, dosage, etc.), and potential adverse events (AEs) between the non-severe and severe subgroups. Furthermore, basic characteristics were compared between patients that had ever used or never used specific classes/kinds of drugs to explore the potentially influential factors for drug selection.

Frequency and percentages were described for categorical variables, and χ² or Fisher’s exact test was used for comparing the proportions in different subgroups. Median and interquartile range (IQR) were reported for the count and continuous variables, and the two-sample median test (26) was used for comparing medians of different subgroups. A two-sided P value of less than 0.05 was considered statistically significant. All analyses were performed using the SAS software (version 9.4) and R software (version 3.6.2).

The study was conducted following the Declaration of Helsinki (as revised in 2013). The Institutional Ethics Board of Zhongnan Hospital of Wuhan University approved this study (No. 2020014). Written informed consent was waived for emerging infectious diseases.

Results

Baseline features

The study included 165 COVID-19 patients. The median age was 55 years (IQR, 42–66; range, 22–96 years), and 84 (50.9%) were men. Of these patients, 26 (15.8%) were in the severe subgroup, and 139 (84.2%) were in the non-severe subgroup at admission. Compared with the non-severe subgroup (Table 1), the severe patients were approximately 13 years older, with a higher proportion of comorbidities (84.6% vs. 44.6%). The most common comorbidities were hypertension (24.8%), cardiovascular disease (9.7%), diabetes (7.3%), and cancer (4.8%). A nonsignificant difference was detected in either sex, contact history, or other clinical features between the 2 groups, except that the severe subgroup had more frequent onsets of dyspnea or shortness of breath (23.1% vs. 4.3% for the non-severe subgroup) (Table S2).

Table 1 Baseline characteristics of 165 patients with coronavirus disease 2019 (COVID-19)
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Overall drug utilization

Among the 165 cases, antivirals (75.8% for oseltamivir, 43.0% for α-interferon, 13.9% for lopinavir/ritonavir), antibacterials, glucocorticoids, general nutrients, and TCM were received by 92.7%, 98.8%, 69.7%, 77.0%, and 61.2% of patients, respectively (Table 2). The combinations of the medications were quite diverse (Figure S1), and the top 4 medication combinations were antivirals combined with glucocorticoids and TCM (81, 49.1%), antivirals combined with glucocorticoids (23, 13.9%), only antivirals (27, 16.4%), and antivirals combined with TCM (22, 13.3%) without considering other coexisting medications (Table S3). A median of 17 (IQR, 10–29) kinds of drugs were prescribed to each patient. Patients with and without comorbidities took a median of 21 (IQR, 15–40) and 12 (IQR, 8–19) kinds of drugs, respectively, and the difference was statistically significant (P<0.001) (Figure 1A and Table S3). Most patients received only 1 kind of antiviral drug (IQR, 1–2), and only 5 patients took more than 3 kinds of antiviral drugs during hospitalization.

Table 2 Drug utilization and their duration for 165 patients with coronavirus disease 2019 (COVID-19)
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Figure 1 The total kinds of medications and disease progression for 165 patients with coronavirus disease 2019 (COVID-19). (A) The total kinds of medications grouped by disease severity and comorbidities. Total kinds of medications refer to the medications (generic names) per person used during the whole hospitalization. Antivirals were defined as Anatomical Therapeutic Chemical (ATC) classification codes starting with J05. (B) The disease progression for 165 patients since baseline. The patient’s baseline condition was classified into 4 levels according to the guidelines “Diagnostic and treatment protocol for Novel Coronavirus Pneumonia (trial version 5)”: mild, general, severe, and critically severe, respectively.

The median duration of antivirals was 8 days (IQR, 6–12), with 30.9% of patients taking antivirals longer than 10 days. Antibacterials and glucocorticoids were treated with a median of 12 days (IQR, 9–18) and 7 days (IQR, 4–12), respectively (Table 2). Regarding the doses of antivirals and glucocorticoids, the single-dose administrations mostly followed the guidelines (Table S4). Also, patients with comorbidities were less likely to receive TCM, whereas patients who were older or with more comorbidities were more likely to be administered other medications (Tables S5-S12).

Drug utilization differences between severity groups

Compared with non-severe cases, more severe cases received glucocorticoids (88.5% vs. 66.2%, P=0.02) and vasoactive drugs (50.0% vs. 19.4%, P<0.001), but received less TCM (50.0% vs. 63.3%, P=0.20). The total kinds of drugs administered to the severe subgroup (27, IQR 18–41) was 12 more than the non-severe subgroup (15, IQR 10–27) regardless of comorbidities (Figure 1A, P<0.001). Severe cases were more likely to take a higher single dose (5 million U) of α-interferon, a longer glucocorticoid duration, or a shorter immunoglobulin treatment. All other features, in terms of duration or single-dose administrations, were not significantly different between the 2 severity groups (Table 2 and Table S4).

Patterns of disease progression

By March 25, 130 (78.8%) of the 165 patients had been discharged. Of all 165 patients, 24 (14.5%) patients had died, while the rest of the patients were still in the hospital or transferred to other hospitals. Figure 1B shows the cumulative outcomes of the patient cohort. It can be seen that 11.1% (1/9), 12.3% (16/130), 36.4% (8/22), and 25.0% (1/4) of the patients progressed to a worse condition or even death for those with baseline mild, general, severe, and critically severe levels, respectively. Compared with the non-severe subgroup, the patients in the severe subgroup experienced a significantly higher percentage of death (34.6% vs. 7.2%, P=0.001) and a shorter period from hospital admission to ICU admission (median, 3 vs. 6 days; IQR, 0–5 vs. 4–8 days, P<0.001). For the 24 death cases, a total of 16 patients (66.7%) deteriorated (7, 29.2%) or even died (9, 70.8%) within the first 7 days of hospitalization (Figure S2). There were no differences observed in the rate of disease exacerbation or death during hospitalization between patients who ever used antivirals, antibacterials, TCM, intestinal microecological regulators, and immunoglobulins (Table 3). In the patients who had disease exacerbation or died during hospitalization, ‘antivirals + glucocorticoids + TCM’ was the most common medication combination (Table 4).

Table 3 Outcomes of death or disease exacerbation after admission for patients using different drugs
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Table 4 Outcomes of death or disease exacerbation after admission for patients using different drug combinations
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Safety assessment

Two senior clinical pharmacists independently evaluated the association between AEs in patients and their medication regimens. The basic criteria for distinguishing AEs with COVID-19 related presentation included excluding any patient who had liver or kidney injury history and presented with abnormal liver or kidney function on admission. There were 53 (32.1%) cases of AEs, of which 13 patients (7.9%) had elevated liver enzymes, 49 patients (29.7%) presented with worsening kidney function, and 9 patients had both. A total of 157 tested patients without liver injury history presented an average AST level of 34.0 (22.0–61.0) U/L in blood. The number of cases with elevated blood AST enzymes was 7.9% (11/139) and 15.4% (4/26) in severe and non-severe patients, respectively, and the difference in the average level between the 2 groups was statistically significant (P=0.002). A total of 159 patients were subjected to ALT tests, and the average level was 30.0 (17.0–68.0) U/L. As for patients with abnormal blood ALT levels, the number of cases was also 7.9% (11/139) and 15.4% (4/26) for the 2 groups, respectively, and the difference in average level between the 2 groups was also statistically significant (P=0.003). Also, 45 (31.5%), 25 (42.4%), and 30 (66.7%) patients presented with worsening kidney function as determined by the 3 indicators of creatinine, EGFR, and urine protein, respectively, among 143, 59, and 45 patients tested without chronic kidney disease (CKD) history (Table 5).

Table 5 Test results and liver and kidney adverse events of COVID-19 patients
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Discussion

To our knowledge, this is one of the earliest studies to describe the detailed patterns of medication, disease progression, as well as safety issues for hospitalized patients with COVID-19. We also found that the prescriptions were diverse in practice, and most of the medications were prescribed considering the patient’s characteristics, including disease severity, age, comorbidities, and AEs. However, the almost universal use of antibacterials might have caused a significant proportion of liver injury or kidney injury. Our findings provide important clues for further explorations, especially regarding treatment timing and safety issues.

The clinical features of patients with COVID-19 in our study were consistent with 4 recent reports, with fever as the predominant symptom (6-9). Compared with the non-severe patients, the severe subgroup cases were significantly older and were more likely to have comorbidities, and these findings were also compatible with 2 previous studies (6,9). Nearly all patients in this study received antibacterials, 92.7% received antivirals, and 69.7% received glucocorticoids. These results were following 3 recent investigations conducted in Wuhan (7-9), but were significantly higher than the 2 latest reports outside Wuhan (5,6). This inconsistency might be because patients outside Wuhan in the previous studies were at least 8 years younger, with less severe disease and comorbidities (5,6,8,9). An unsurprising finding of our study is that clinicians tried several drugs and even more drug combinations as potential pharmaceutical options against COVID-19, even within a single hospital. The diverse medication regimens might be because no specific treatment has been recommended for COVID-19 until now, and the evolution and revisions to the government guidelines (trial) for the diagnosis and treatment of COVID-19 are constant (10-13,27). Over 200 studies have already been registered on either ClinicalTrials.gov or Chictr.org, to test medications that fight other viruses (e.g., flu and HIV), TCM, stem cells, steroids, and plasma treatment. However, we have to accept that all treatment explorations require processes of a certain time frame (28) and that the current state of chaos will inevitably last for some time. Therefore, to sum up, it is critical to further investigate drug utilization and potential experiences promptly like our study in order to provide real-world evidence for clinical decision-makers.

A higher proportion and a longer duration of glucocorticoids are worth noting in this study. Current WHO guidance and several researchers have recommended that corticosteroids should not be used due to COVID-19-induced lung injury or shock (17,23). In contrast, an expert consensus statement developed by the Chinese Thoracic Society on February 11 points out that corticosteroids should not be abandoned in treating COVID-19 due to inconclusive clinical evidence (19). According to this statement, the dose should be low-to-moderate (≤0.5–1 mg/kg per day methylprednisolone or equivalent), and the duration should be short (≤7 days). Our study indicated that almost all the single doses of corticosteroids were already consistent with this statement. This might due to this hospital having developed rapid guidelines before January 29 (27), with a weak recommendation that 40 to 80 mg of methylprednisolone per day could be considered. However, approximately half of the patients were treated with corticosteroids for more than 7 days, which was more serious in severe patients. This finding was consistent with 2 previous studies completed before developing the expert consensus statement (8). The main reason is most likely due to the rapid development of this hospital's guidelines, which did not mention the duration. The current national guidelines recommend that glucocorticoids should be restricted within 3–5 days (6,10-13) if needed. Considering corticosteroid treatment is a ‘double-edged sword’ (19), our finding is worthy of front-line physicians’ and researchers’ attention.

Another phenomenon that should be noted is the almost universal empirical antibacterial treatment. This result was in agreement with 3 studies conducted in Wuhan (6,7,9) but was twice the level of the latest study outside Wuhan (5). The difference in the distribution of age and comorbidities between Xu et al.’s study and ours might partially explain this gap in the antibacterial usage rate (5). Also, inadequate supplies of specific detection kits in Wuhan during late January and early February 2020 brought about difficulties in making rapid etiology diagnoses of COVID-19 in patients on admission, resulting in requests for empirical antibacterial treatment to rule out a bacterial infection, and consequently increased antibacterial usage rates. All COVID-19 treatment statements in China emphasized to avoid inappropriate use of antibacterials, especially the combination of broad-spectrum antibacterials (10-13,27). In this study, we observed possible AEs in the liver and kidney at a common level (over 5%).

Interestingly, these safety signals have also been reported by some antibacterial instructions and previous studies (29-31). The kidneys’ potential harm was also well summarized in previous studies for amoxicillin (30) and cloxacillin sodium (31). The widespread use of antibacterials, together with multiple drugs, should alert clinicians to pay attention to the potential ADEs (32).

Our study focused on drug utilization and disease progression from real-world data. Some limitations should be noted in this study. First, only 165 patients from a single hospital were included, and 3.0% of patients were still hospitalized at the time of database locking. However, despite this, the results of this study permitted an early assessment. Second, with the limited number of non-severe cases, only age, sex, and the number of comorbidities were taken into consideration, and additional confounders might still have existed. Although almost all antivirals and antibacterials (the most common treatments in our study) were not over-the-counter medications in China (33), it is unknown what percentage of patients obtained the drugs from outpatient services. Therefore, the percentage of pre-hospitalization medications should be further considered in future investigations.

Conclusions

In summary, the drug utilization for hospitalized patients with COVID-19 was diverse and generally complied with China’s existing guidelines. Also, AEs should not be ignored in the process of drug prescriptions. Given our preliminary investigation, there is a need for multicenter research with larger sample size and longer follow-up period in the future in order to promote a more solid basis for medication recommendations.

Acknowledgments

Funding: This study was supported by the National Key Technology R&D Program of China (grant number 2020YFC0840800), National Natural Science Foundation of China (grant number 81973146), Fundamental Research Funds for the Central Universities (grant number 2042020kf1019), Special Research Fund of PKUHSC for Prevention and Control of COVID-19 (grant number BMU2020HKYZX010) and the Fundamental Research Funds for the Central Universities. The funders had no role in study design, data collection, data analysis, data interpretation, writing of the manuscript, and decision to submit.

Footnote

Reporting Checklist: The authors have completed the MDAR checklist. Available at http://dx.doi.org/10.21037/atm-20-4960

Data Sharing Statement: Available at http://dx.doi.org/10.21037/atm-20-4960

Peer Review File: Available at http://dx.doi.org/10.21037/atm-20-4960

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/atm-20-4960). Dr. SZ reports grants from National Key Technology R&D Program of China, grants from National Natural Science Foundation of China, grants from Special Project for Major Infectious Diseases of Peking University Health Science Center, during the conduct of the study. Dr. YC reports grants from Fundamental Research Funds for the Central Universities, during the conduct of the study. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The corresponding author had access to all data in the study and had final responsibility for the decision to submit for publication. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This study was approved by the Institutional Ethics Board of Zhongnan Hospital of Wuhan University (No. 2020014). Written informed consent was waived for emerging infectious diseases.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Lu R, Zhao X, Li J, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet 2020;395:565-74. [Crossref] [PubMed]
2. Zhu N, Zhang D, Wang W, et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med 2020;382:727-33. [Crossref] [PubMed]
3. Phelan AL, Katz R, Gostin LO. The Novel Coronavirus Originating in Wuhan, China: Challenges for Global Health Governance. JAMA 2020;323:709-10. [Crossref] [PubMed]
4. Wang C, Horby PW, Hayden FG, et al. A novel coronavirus outbreak of global health concern. Lancet 2020;395:470-3. [Crossref] [PubMed]
5. Xu XW, Wu XX, Jiang XG, et al. Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: retrospective case series. BMJ 2020;368:m606. [Crossref] [PubMed]
6. Guan WJ, Ni ZY, Hu Y, et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med 2020;382:1708-20. [Crossref] [PubMed]
7. Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020;395:497-506. [Crossref] [PubMed]
8. Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 2020;395:507-13. [Crossref] [PubMed]
9. Wang D, Hu B, Hu C, et al. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA 2020;323:1061-9. [Crossref] [PubMed]
10. General Office of the National Health Commission. General Office of Administration of Traditional Chinese Medicine. Diagnostic and treatment protocol for Novel Coronavirus Pneumonia (trial third version). January 22, 2020. Available online: http://www.gov.cn/zhengce/zhengceku/2020-01/23/content_5471832.htm. Accessed February 12, 2020.
11. General Office of the National Health Commission. General Office of Administration of Traditional Chinese Medicine. Diagnostic and treatment protocol for Novel Coronavirus Pneumonia (trial fourth version). January 27, 2020. Available online: http://www.gov.cn/zhengce/zhengceku/2020-01/28/content_5472673.htm. Accessed February 12, 2020.
12. General Office of the National Health Commission. General Office of Administration of Traditional Chinese Medicine. Diagnostic and treatment protocol for Novel Coronavirus Pneumonia (trial fifth version). February 4, 2020. Available online: http://www.nhc.gov.cn/yzygj/s7653p/202002/3b09b894ac9b4204a79db5b8912d4440.shtml. Accessed February 12, 2020.
13. General Office of the National Health Commission. General Office of Administration of Traditional Chinese Medicine. Diagnostic and treatment protocol for Novel Coronavirus Pneumonia (trial sixth version). February 18, 2020. Available online: http://www.nhc.gov.cn/jkj/s3577/202003/4856d5b0458141fa9f376853224d41d7.shtml. Accessed February 18, 2020.
14. General Office of the National Health Commission. General Office of Administration of Traditional Chinese Medicine. Diagnostic and treatment protocol for Novel Coronavirus Pneumonia (trial seventh version). March 3, 2020. Available online: http://www.nhc.gov.cn/cms-search/xxgk/getManuscriptXxgk.htm?id=318683cbfaee4191aee29cd774b19d8d. Accessed March 6, 2020.
15. Supe S, Kohse F, Gembardt F, et al. Therapeutic time window for angiotensin-(1-7) in acute lung injury. Br J Pharmacol 2016;173:1618-28. [Crossref] [PubMed]
16. Richardson P, Griffin I, Tucker C, et al. Baricitinib as potential treatment for 2019-nCoV acute respiratory disease. Lancet 2020;395:e30-e31. [Crossref] [PubMed]
17. Russell CD, Millar JE, Baillie JK. Clinical evidence does not support corticosteroid treatment for 2019-nCoV lung injury. Lancet 2020;395:473-5. [Crossref] [PubMed]
18. Wang FS, Zhang C. What to do next to control the 2019-nCoV epidemic? Lancet 2020;395:391-3. [Crossref] [PubMed]
19. Shang L, Zhao J, Hu Y, et al. On the use of corticosteroids for 2019-nCoV pneumonia. Lancet 2020;395:683-4. [Crossref] [PubMed]
20. Yang X, Yu Y, Xu J, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med 2020;8:475-81. [Crossref] [PubMed]
21. Chen H, Guo J, Wang C, et al. Clinical characteristics and intrauterine vertical transmission potential of COVID-19 infection in nine pregnant women: a retrospective review of medical records. Lancet 2020;395:809-15. [Crossref] [PubMed]
22. Chang D, Lin M, Wei L, et al. Epidemiologic and Clinical Characteristics of Novel Coronavirus Infections Involving 13 Patients Outside Wuhan, China. JAMA 2020;323:1092-3. [Crossref] [PubMed]
23. World Health Organization. Clinical management of severe acute respiratory infection when Novel coronavirus (2019-nCoV) infection is suspected: Interim Guidance. January 28, 2020. Available online: https://www.who.int/docs/default-source/coronaviruse/clinical-management-of-novel-cov.pdf?sfvrsn=bc7da517_2. Accessed January 31, 2020.
24. Deng SQ, Peng HJ. Characteristics of and Public Health Responses to the Coronavirus Disease 2019 Outbreak in China. J Clin Med 2020;9:575. [Crossref] [PubMed]
25. Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009;150:604-12. [Crossref] [PubMed]
26. Wolfe DA. Two-stage two-sample median test. Technometrics 1977;19:495-501. [Crossref]
27. Jin YH, Cai L, Cheng ZS, et al. A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version). Mil Med Res 2020;7:4. [Crossref] [PubMed]
28. Horton R. Offline: 2019-nCoV Outbreak-Early Lessons. Lancet 2020;395:322. [Crossref] [PubMed]
29. Haverkamp W, Kruesmann F, Fritsch A, et al. Update on the cardiac safety of moxifloxacin. Curr Drug Saf 2012;7:149-63. [Crossref] [PubMed]
30. Guzman-Limon M, Molony D. In older patients with UTIs, trimethoprim vs amoxicillin was linked to higher risk for AKI at 14 d. Annals of internal medicine 2018;168:JC58. [Crossref] [PubMed]
31. Lavergne A, Vigneau C, Polard E, et al. Acute Kidney Injury During Treatment With High-Dose Cloxacillin: A Report of 23 Cases and Literature Review. Int J Antimicrob Agents 2018;52:344-9. [Crossref] [PubMed]
32. Fan Z, Chen L, Li J, et al. Clinical Features of COVID-19-Related Liver Functional Abnormality. Clin Gastroenterol Hepatol 2020;18:1561-6. [Crossref] [PubMed]
33. General Office of the National Health Commission. Notice of the general office of China National Health Commission on the continuous management of the clinical application of antibiotics. March 29, 2019. Available online: http://www.nhc.gov.cn/yzygj/s7659/201903/1d487eb7b7c74abc9fcb104f8b0905f2.shtml. Accessed February 5, 2020.