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1.
PLoS One ; 18(4): e0275356, 2023.
Article in English | MEDLINE | ID: covidwho-2293234

ABSTRACT

BACKGROUND: Pre-exposure prophylaxis for COVID-19 with tixagevimab/cilgavimab (T/C) received Emergency Use Authorization (EUA) based on results of a clinical trial conducted prior to the emergence of the Omicron variant. The clinical effectiveness of T/C has not been well described in the Omicron era. We examined the incidence of symptomatic illness and hospitalizations among T/C recipients when Omicron accounted for virtually all local cases. METHODS: Through retrospective electronic medical record chart review, we identified patients who received T/C between January 1 -July 31, 2022 within our quaternary referral health system. We determined the incidence of symptomatic COVID-19 infections and hospitalizations due to or presumed to be caused by early Omicron variants before and after receiving T/C (pre-T/C and post-T/C). Chi square and Mann-Whitney Wilcoxon two-sample tests were used to examine differences between the characteristics of those who got COVID-19 before or after T/C prophylaxis, and rate ratios (RR) and 95% confidence intervals (CI) were calculated to assess differences in hospitalization rates for the two groups. RESULTS: Of 1295 T/C recipients, 105 (8.1%) developed symptomatic COVID-19 infection before receiving T/C, and 102 (7.9%) developed symptomatic disease after receiving it. Of the 105 patients who developed symptomatic infection pre-T/C, 26 (24.8%) were hospitalized, compared with six of the 102 patients (5.9%) who were diagnosed with COVID-19 post-T/C (RR = 0.24; 95% CI = 0.10-0.55; p = 0.0002). Seven of the 105 (6.7%) patients infected pre-T/C, but none of the 102 infected post-T/C required ICU care. No COVID-related deaths occurred in either group. The majority of COVID-19 cases among those infected pre-T/C treatment occurred during the Omicron BA.1 surge, while the majority of post-T/C cases occurred when Omicron BA.5 was predominant. In both groups, having at least one dose of vaccine strongly protected against hospitalization (pre-T/C group RR = 0.31, 95% CI = 0.17-0.57, p = 0.02; post-T/C group RR = 0.15; 95% CI = 0.03-0.94; p = 0.04). CONCLUSION: We identified COVID-19 infections after T/C prophylaxis. Among patients who received T/C at our institution, COVID-19 Omicron cases occurring after T/C were one-fourth as likely to require hospitalization compared to those with Omicron prior to T/C. However, due to the presence of changing vaccine coverage, multiple therapies, and changing variants, the effectiveness of T/C in the Omicron era remains difficult to assess.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Retrospective Studies , SARS-CoV-2
4.
J Pharm Technol ; 38(2): 75-87, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1666613

ABSTRACT

Background: Understanding medication use patterns for patients with COVID-19 will provide needed insight into the evolution of COVID-19 treatment over the course of the SARS-CoV-2 pandemic and aid clinical management considerations. Objectives: To systematically determine most frequently used medications among COVID-19 patients overall and by hospitalization status. Secondary objective was use measurement of medications considered potential therapeutic options. Methods: Retrospective cohort study was performed using data from the University of California COVID Research Data Set (UC CORDS) patients between March 10, 2020, and December 31, 2020. Main outcomes were percentages of patients prescribed medications, overall, by age group, and by comorbidity based on hospitalization status for COVID-19 patients. Use percentage by month of COVID-19 diagnosis was measured. Cumulative count of potential therapeutic options was measured over time. Results: Dataset included 22 896 unique patients with COVID-19 (mean [SD] age, 42.4 [20.4] years; 12 154 [53%] women). Most frequently used medications in patients overall were acetaminophen (21.2%), albuterol (14.9%), ondansetron (13.9%), and enoxaparin (10.8%). Dexamethasone use increased from fewer than 50 total hospitalized patients through April who had received the medication, to more than 500 patients by mid-August. Cumulative count of enoxaparin users was the largest throughout the study period. Conclusion 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 toward more evidence-concordant treatment of patients with COVID-19 as rigorous study findings emerged.

5.
J Med Internet Res ; 23(12): e23571, 2021 12 03.
Article in English | MEDLINE | ID: covidwho-1596242

ABSTRACT

BACKGROUND: There is a pressing need for digital tools that can leverage big data to help clinicians select effective antibiotic treatments in the absence of timely susceptibility data. Clinical presentation and local epidemiology can inform therapy selection to balance the risk of antimicrobial resistance and patient risk. However, data and clinical expertise must be appropriately integrated into clinical workflows. OBJECTIVE: The aim of this study is to leverage available data in electronic health records, to develop a data-driven, user-centered, clinical decision support system to navigate patient safety and population health. METHODS: We analyzed 5 years of susceptibility testing (1,078,510 isolates) and patient data (30,761 patients) across a large academic medical center. After curating the data according to the Clinical and Laboratory Standards Institute guidelines, we analyzed and visualized the impact of risk factors on clinical outcomes. On the basis of this data-driven understanding, we developed a probabilistic algorithm that maps these data to individual cases and implemented iBiogram, a prototype digital empiric antimicrobial clinical decision support system, which we evaluated against actual prescribing outcomes. RESULTS: We determined patient-specific factors across syndromes and contexts and identified relevant local patterns of antimicrobial resistance by clinical syndrome. Mortality and length of stay differed significantly depending on these factors and could be used to generate heuristic targets for an acceptable risk of underprescription. Combined with the developed remaining risk algorithm, these factors can be used to inform clinicians' reasoning. A retrospective comparison of the iBiogram-suggested therapies versus the actual prescription by physicians showed similar performance for low-risk diseases such as urinary tract infections, whereas iBiogram recognized risk and recommended more appropriate coverage in high mortality conditions such as sepsis. CONCLUSIONS: The application of such data-driven, patient-centered tools may guide empirical prescription for clinicians to balance morbidity and mortality with antimicrobial stewardship.


Subject(s)
Anti-Infective Agents , Decision Support Systems, Clinical , Anti-Bacterial Agents/therapeutic use , Anti-Infective Agents/therapeutic use , Humans , Retrospective Studies
10.
Open Forum Infectious Diseases ; 7(Supplement_1):S286-S287, 2020.
Article in English | Oxford Academic | ID: covidwho-1010495
11.
Open Forum Infectious Diseases ; 7(Supplement_1):S257-S257, 2020.
Article in English | Oxford Academic | ID: covidwho-1010451
12.
J Am Med Inform Assoc ; 27(6): 853-859, 2020 06 01.
Article in English | MEDLINE | ID: covidwho-631869

ABSTRACT

OBJECTIVE: To describe the implementation of technological support important for optimizing clinical management of the COVID-19 pandemic. MATERIALS AND METHODS: Our health system has confirmed prior and current cases of COVID-19. An Incident Command Center was established early in the crisis and helped identify electronic health record (EHR)-based tools to support clinical care. RESULTS: We outline the design and implementation of EHR-based rapid screening processes, laboratory testing, clinical decision support, reporting tools, and patient-facing technology related to COVID-19. DISCUSSION: The EHR is a useful tool to enable rapid deployment of standardized processes. UC San Diego Health built multiple COVID-19-specific tools to support outbreak management, including scripted triaging, electronic check-in, standard ordering and documentation, secure messaging, real-time data analytics, and telemedicine capabilities. Challenges included the need to frequently adjust build to meet rapidly evolving requirements, communication, and adoption, and to coordinate the needs of multiple stakeholders while maintaining high-quality, prepandemic medical care. CONCLUSION: The EHR is an essential tool in supporting the clinical needs of a health system managing the COVID-19 pandemic.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Electronic Health Records , Medical Records Systems, Computerized , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , Telemedicine , User-Computer Interface , Academic Medical Centers/organization & administration , COVID-19 , California/epidemiology , Coronavirus Infections/diagnosis , Coronavirus Infections/therapy , Databases, Factual , Decision Support Systems, Clinical , Humans , Medical Informatics , Patient Care Team/organization & administration , Pneumonia, Viral/diagnosis , Pneumonia, Viral/therapy , SARS-CoV-2
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