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  • 1
    In: eBioMedicine, Elsevier BV, Vol. 96 ( 2023-10), p. 104799-
    Type of Medium: Online Resource
    ISSN: 2352-3964
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 2799017-5
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  • 2
    In: JAMA Network Open, American Medical Association (AMA), Vol. 6, No. 7 ( 2023-07-13), p. e2323349-
    Abstract: Current data identifying COVID-19 risk factors lack standardized outcomes and insufficiently control for confounders. Objective To identify risk factors associated with COVID-19, severe COVID-19, and SARS-CoV-2 infection. Design, Setting, and Participants This secondary cross-protocol analysis included 4 multicenter, international, randomized, blinded, placebo-controlled, COVID-19 vaccine efficacy trials with harmonized protocols established by the COVID-19 Prevention Network. Individual-level data from participants randomized to receive placebo within each trial were combined and analyzed. Enrollment began July 2020 and the last data cutoff was in July 2021. Participants included adults in stable health, at risk for SARS-CoV-2, and assigned to the placebo group within each vaccine trial. Data were analyzed from April 2022 to February 2023. Exposures Comorbid conditions, demographic factors, and SARS-CoV-2 exposure risk at the time of enrollment. Main Outcomes and Measures Coprimary outcomes were COVID-19 and severe COVID-19. Multivariate Cox proportional regression models estimated adjusted hazard ratios (aHRs) and 95% CIs for baseline covariates, accounting for trial, region, and calendar time. Secondary outcomes included severe COVID-19 among people with COVID-19, subclinical SARS-CoV-2 infection, and SARS-CoV-2 infection. Results A total of 57 692 participants (median [range] age, 51 [18-95] years; 11 720 participants [20.3%] aged ≥65 years; 31 058 participants [53.8%] assigned male at birth) were included. The analysis population included 3270 American Indian or Alaska Native participants (5.7%), 7849 Black or African American participants (13.6%), 17 678 Hispanic or Latino participants (30.6%), and 40 745 White participants (70.6%). Annualized incidence was 13.9% (95% CI, 13.3%-14.4%) for COVID-19 and 2.0% (95% CI, 1.8%-2.2%) for severe COVID-19. Factors associated with increased rates of COVID-19 included workplace exposure (high vs low: aHR, 1.35 [95% CI, 1.16-1.58]; medium vs low: aHR, 1.41 [95% CI, 1.21-1.65] ; P   & amp;lt; .001) and living condition risk (very high vs low risk: aHR, 1.41 [95% CI, 1.21-1.66]; medium vs low risk: aHR, 1.19 [95% CI, 1.08-1.32] ; P   & amp;lt; .001). Factors associated with decreased rates of COVID-19 included previous SARS-CoV-2 infection (aHR, 0.13 [95% CI, 0.09-0.19]; P   & amp;lt; .001), age 65 years or older (aHR vs age & amp;lt;65 years, 0.57 [95% CI, 0.50-0.64]; P   & amp;lt; .001) and Black or African American race (aHR vs White race, 0.78 [95% CI, 0.67-0.91]; P  = .002). Factors associated with increased rates of severe COVID-19 included race (American Indian or Alaska Native vs White: aHR, 2.61 [95% CI, 1.85-3.69]; multiracial vs White: aHR, 2.19 [95% CI, 1.50-3.20] ; P   & amp;lt; .001), diabetes (aHR, 1.54 [95% CI, 1.14-2.08]; P  = .005) and at least 2 comorbidities (aHR vs none, 1.39 [95% CI, 1.09-1.76]; P  = .008). In analyses restricted to participants who contracted COVID-19, increased severe COVID-19 rates were associated with age 65 years or older (aHR vs & amp;lt;65 years, 1.75 [95% CI, 1.32-2.31]; P   & amp;lt; .001), race (American Indian or Alaska Native vs White: aHR, 1.98 [95% CI, 1.38-2.83]; Black or African American vs White: aHR, 1.49 [95% CI, 1.03-2.14] ; multiracial: aHR, 1.81 [95% CI, 1.21-2.69]; overall P  = .001), body mass index (aHR per 1-unit increase, 1.03 [95% CI, 1.01-1.04]; P  = .001), and diabetes (aHR, 1.85 [95% CI, 1.37-2.49]; P   & amp;lt; .001). Previous SARS-CoV-2 infection was associated with decreased severe COVID-19 rates (aHR, 0.04 [95% CI, 0.01-0.14]; P   & amp;lt; .001). Conclusions and Relevance In this secondary cross-protocol analysis of 4 randomized clinical trials, exposure and demographic factors had the strongest associations with outcomes; results could inform mitigation strategies for SARS-CoV-2 and viruses with comparable epidemiological characteristics.
    Type of Medium: Online Resource
    ISSN: 2574-3805
    Language: English
    Publisher: American Medical Association (AMA)
    Publication Date: 2023
    detail.hit.zdb_id: 2931249-8
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  • 3
    Online Resource
    Online Resource
    American Society of Clinical Oncology (ASCO) ; 2017
    In:  Journal of Clinical Oncology Vol. 35, No. 15_suppl ( 2017-05-20), p. e18230-e18230
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 35, No. 15_suppl ( 2017-05-20), p. e18230-e18230
    Abstract: e18230 Background: Chemotherapy wait times can dramatically affect patient experience. MSK’s largest outpatient facility has 76 infusion spaces and 250-300 daily visits. A retrospective review of the facility’s infusion area wait times suggested that the lab (where all patients go to get their vitals and blood drawn) was a major bottleneck leading to process delays in infusion. Methods: We conducted a pilot program using a multi-pronged approach. Our goal was to decrease wait time from 40 minutes to an average of 15 minutes. Our initiative was defined as follows: (1) to redefine lab parameters that are relevant for toxicity and to only consider drawing those necessary labs; additionally, we created guidelines for timing of the labs prior to infusion treatment, (2) to introduce a program known as “ChemoExpress” which offers patients the opportunity to get blood work done prior to the day of their infusion appointment. After the labs result, the outpatient RN calls the patient, assesses symptoms and “clears them” for treatment cueing the pharmacy to prepare and “premix” the drug on the day of treatment. Results: 150 patients have enrolled in ChemoExpress. Patient satisfaction was high based on patient satisfaction surveys (n = 20). Average wait time was 9 minutes (76% less) in ChemoExpress participants as compared to an average wait of 39 minutes for those who did not participate in ChemoExpress. Conclusions: Implementing a process that enables patients to have their bloodwork drawn prior to the day of treatment and drugs prepared in advance of their treatment appointment results in greater efficiency in the overall workflow. It also offers the patient a lower wait time and a more efficient and satisfying experience.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2017
    detail.hit.zdb_id: 2005181-5
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