Examination of Medication Use Patterns by Age Group, Comorbidity, and Month in COVID-19 Positive Patients in a Large State-wide Health System During the Pandemic in 2020
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Abstract
Objectives
Main objective was to systematically determine most frequently used medications among COVID-19 patients overall and by hospitalization status. Secondary objective was to measure use patterns of medications considered potential therapeutic options
Design
Retrospective cohort study.
Setting
The five academic medical centers of University of California Health.
Participants
University of California COVID Research Data Set (UC CORDS) patients between March 10, 2020 and December 31, 2020.
Exposure(s)
Confirmed COVID-19 positive by SARS-CoV-2 nucleic acid amplification.
Main Outcome(s) and Measure(s)
Main outcomes were percentages of patients prescribed medications, overall, by age group, and by comorbidity based on hospitalization status. Use percentage by month of COVID-19 diagnosis was measured. Cumulative count of potential therapeutic options was measured over time.
Results
Dataset included 22897 unique patients with COVID-19 (mean [SD] age, 42.4 [20.4] years; 12154 [53%] female). Among the sample, 6326 28%) were non-Hispanic White, 8475 (37%) were Hispanic, 1562 (7%) Asian, and 1313 (6%) Black. A COVID-related hospitalization occurred in 3546 patients. Of the hospitalized patients, more than 30% had baseline comorbidities of hypertension (48%), hyperlipidemia (37%), and type 2 diabetes (35%). Most frequently used medications in patients overall were acetaminophen (21.2%), albuterol (14.9%), ondansetron (13.9%), and enoxaparin (10.8%). Medications used were generally similar across ages and comorbidities. Prior to May, dexamethasone was rarely used, with well under 50 COVID-19 patients that had been hospitalized to that point receiving the medication. By mid-August, more than 500 patients to that point had received dexamethasone. Hydroxychloroquine use effectively halted in COVID-19 hospitalized patients after May. Throughout the period of March to December 2020, enoxaparin was used in the most patients to that point at any instance. By mid-December, more than 2000 in the analysis cohort of hospitalized patients had received enoxaparin.
Conclusions and Relevance
In this retrospective cohort study, across age and comorbidity groups, predominant utilization was for supportive care therapy. Dexamethasone and remdesivir experienced large increases in use. Conversely, hydroxychloroquine and azithromycin use markedly dropped. Medication utilization rapidly shifted towards more evidence-concordant treatment of patients with COVID-19 as rigorous study findings emerged.
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SciScore for 10.1101/2021.07.15.21259539: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: 10–12 UC CORDS was operationalized by UC Health as ‘non-human subjects research’ and analyses are considered institutional review board exempt. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Medications used for each patient were determined from the EHR by measurement of all medication active ingredients utilized within 30 days of COVID-19 positive test based on the RxNorm standardized nomenclature for clinical drugs from the National Library of Medicine.17 Given the assumption, in context of COVID-19, of a similar therapeutic class effect of angiotensin … SciScore for 10.1101/2021.07.15.21259539: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: 10–12 UC CORDS was operationalized by UC Health as ‘non-human subjects research’ and analyses are considered institutional review board exempt. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Medications used for each patient were determined from the EHR by measurement of all medication active ingredients utilized within 30 days of COVID-19 positive test based on the RxNorm standardized nomenclature for clinical drugs from the National Library of Medicine.17 Given the assumption, in context of COVID-19, of a similar therapeutic class effect of angiotensin converting enzyme-2 inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) usage of these medications was collapsed to the overall category of ‘ACEIs/ARBs’. RxNormsuggested: (RxNorm, RRID:SCR_006645)Data were extracted with module pyodbc, version 4.0.30 in Python, version 3.8.3 (Python Software Foundation). Pythonsuggested: (IPython, RRID:SCR_001658)All analyses performed in R, version 3.6.3 (R Project for Statistical Computing). R Project for Statisticalsuggested: (R Project for Statistical Computing, RRID:SCR_001905)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Limitations: Outpatient medications for patients in CORDS may require at least a month for complete capture. Use rates are conservative estimates for the non-hospitalized patients since medications for COVID-19 positive patients prescribed medications outside of UC Health are not present in CORDS. While the study demographics were consistent with California overall, given, that this state has a large minority population this may influence generalizability to the US. Consequently, the percentage of COVID-19 positive cases that were Non-Hispanic White in CORDS (28%) was lower than that observed in US national estimates (56%). Hispanics were 37% of the positive cases in our dataset and 21% in the US. A smaller percentage of COVID-19 positive patients were black (6%) than observed in national estimates (12.2%). Asians were 7% of the COVID-19 positive patients in CORDS compared to 4% in US estimates.25
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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