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Observational research from large population databases may be affected by unmeasured confounding and time-related biases, such as immortal time bias. Modern causal inference practice applies propensity score-based methods, new-user designs, and other strategies to mitigate bias. The degree to which these methodologic approaches adequately address bias for any particular study may be difficult to measure. Recently, the incorporation of positive and negative controls has been identified as a means to assess for the impacts of residual confounding and/or time-related biases. The objective of this commentary is to describe the role of positive and negative controls in observational research. We offer recommendations for incorporating controls into critical appraisal and observational research projects.
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OBJECTIVE: To describe people with gout who were diagnosed with coronavirus disease 2019 (COVID-19) and hospitalized and to characterize their outcomes. METHODS: Data on patients with gout hospitalized for COVID-19 between March 12, 2020, and October 25, 2021, were extracted from the COVID-19 Global Rheumatology Alliance registry. Descriptive statistics were used to describe the demographics, comorbidities, medication exposures, and COVID-19 outcomes including oxygenation or ventilation support and death. RESULTS: One hundred sixty-three patients with gout who developed COVID-19 and were hospitalized were included. The mean age was 63 years, and 85% were male. The majority of the group lived in the Western Pacific Region (35%) and North America (18%). Nearly half (46%) had two or more comorbidities, with hypertension (56%), cardiovascular disease (28%), diabetes mellitus (26%), chronic kidney disease (25%), and obesity (23%) being the most common. Glucocorticoids and colchicine were used pre-COVID-19 in 11% and 12% of the cohort, respectively. Over two thirds (68%) of the cohort required supplemental oxygen or ventilatory support during hospitalization. COVID-19-related death was reported in 16% of the overall cohort, with 73% of deaths documented in people with two or more comorbidities. CONCLUSION: This cohort of people with gout and COVID-19 who were hospitalized had high frequencies of ventilatory support and death. This suggests that patients with gout who were hospitalized for COVID-19 may be at risk of poor outcomes, perhaps related to known risk factors for poor outcomes, such as age and presence of comorbidity.
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OBJECTIVE: Wrong drug product errors occurring in community pharmacies often originate at the transcription stage. Electronic prescribing and automated product selection are strategies to reduce product selection errors. However, it is unclear how often automated product selection succeeds in outpatient pharmacy platforms. MATERIALS AND METHODS: The intake of over 800 e-prescriptions was observed at baseline and after intervention to assess the rate of automated product selection success. A dispensing accuracy audit was performed at baseline and postintervention to determine whether enhanced automated product selection would result in greater accuracy; data for both analyses were compared by 2x2 Chi square tests. In addition, an anonymous survey was sent to a convenience sample of 60 area community pharmacy managers. RESULTS: At baseline, 79.8% of 888 e-prescriptions achieved automated product selection. After the intervention period, 84.5% of 903 e-prescriptions achieved automated product selection (P = .008). Analysis of dispensing accuracy audits detected a slight but not statistically significant improvement in accuracy rate (99.3% versus 98.9%, P = .359). Fourteen surveys were returned, revealing that other community pharmacies experience similar automated product selection failure rates. DISCUSSION: Our results suggest that manual product selection by pharmacy personnel is required for a higher than anticipated proportion of e-prescriptions received and filled by community pharmacies, which may pose risks to both medication safety and efficiency. CONCLUSION: The question of how to increase automated product selection rates and enhance interoperability between prescriber and community pharmacy platforms warrants further investigation.