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Objectives: This analysis was conducted to develop a comprehensive list of ICD-10 CM codes for underlying conditions identified by the CDC as being associated with high-risk of developing severe COVID-19 and assessed the consistency of these codes when applied to large US based datasets. Method(s): The comprehensive list of ICD 10-CM codes for CDC-defined high-risk underlying conditions were mapped from CDC references and FDA Sentinel code lists. These codes were subsequently applied to Optum's de-identified Clinformatics Data Mart Database (claims) and the Optum de-identified Electronic Health Record (EHR) database across 3 years (2018, 2019 and 2020) among continuously enrolled subjects >= 12 years of age to determine the performance and consistency in identifying these high-risk underlying conditions annually over these years. Result(s): A total of 10,276 ICD-10 codes were mapped to 21 underlying conditions. Within the claims data, 62.7% of subjects >= 12 years had >= 1 CDC-defined high-risk condition (excluding age) with 26.6% of patients >= 65 years while in the EHR data 38% had >= 1 high-risk underlying condition (excluding age) with 14.4% >= 65 years. These results were similar and consistent in both datasets across all years. Patients aged 12-64 years in the claims data had a higher rate of >=1 high risk underlying condition relative to the EHR data, 49.3% and 34%, respectively. The top 5 conditions among the >= 65 were identical across both databases: hypertension, immunocompromised status, heart conditions, diabetes (type 1 or 2), and overweight/obesity. The top 5 conditions among the 12-64 age group were also similar among the databases and included: immunocompromised status, hypertension, overweight/obesity, smoking (current or former), and mental health conditions. Conclusion(s): These findings present a comprehensive list of codes that can be used by researchers, clinicians and policy makers to identify and characterize patients that may be at high-risk for severe COVID-19 outcomes.Copyright © 2023
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BACKGROUND: Paxlovid (nirmatrelvir/ritonavir) has received a US Emergency Use Authorization for patients >=12 years with mild-to- moderate COVID-19 at high-risk of progression to severe disease. DDI studies conducted with Paxlovid implicate the PK enhancer ritonavir as the main perpetrator of DDIs. Ritonavir is a potent inhibitor of CYP3A4, CYP2D6, and P-gp. The Paxlovid Fact Sheet1 identifies contraindicated drugs and those with a potentially important interaction. METHOD(S): A retrospective analysis was conducted using RWE from the Optum Clinformatics Data Mart. Patients were identified based on CDC criteria for high-risk COVID-19 and confirmed continuous insurance enrollment from Jan 1 to Dec 31, 2019 with >=1 prescription claim. Excluding non-drug claims (e.g., vaccines), the top 100 drugs were selected and ranked based on total patient counts. DDI potential with Paxlovid was evaluated using US Prescribing and DailyMed Information or relevant literature for each drug. RESULT(S): Of the top 100, 70 drugs are not expected to have a DDI with Paxlovid. These drugs are eliminated unchanged in urine, cleared by enzymes other than CYP3A4 or CYP2D6, are not P-gp substrates, or are cleared by multiple pathways. The remaining 30 drugs expected to have a DDI are represented in the Paxlovid Fact Sheet. The top four drug classes expected to interact with Paxlovid include corticosteroids, narcotic analgesics, anticoagulants, and statins. One drug, simvastatin, is contraindicated. The mechanism of interaction with Paxlovid, or lack thereof, will be presented in detail for each drug. CONCLUSION(S): Paxlovid DDI management is important to ensure the right patients receive this antiviral. This analysis provides an understanding of Paxlovid interactions with the top 100 drugs likely to be used in high-risk COVID-19 patients and serves as an additional DDI management resource.
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Background. Due to the coronavirus disease 2019 (COVID-19) pandemic in the United States (US), public health officials sought to reduce transmission. However, the psychosocial impact associated with COVID-19 has received less attention. This study describes psychosocial burden among adults diagnosed with COVID-19 and assesses the unique impact on those who had a COVID-19 hospitalization. Methods. This cross-sectional retrospective study used 2021 US National Health and Wellness Survey (NHWS;N=75,098) data. NHWS is an annual web-based selfreport survey of the US general adult population (aged >= 18 years). Results were weighted to reflect the population on age, gender, race/ethnicity, and education based on US Census. Among adults who self-reported a COVID-19 diagnosis, those with COVID-related hospitalization, emergency room (ER) visit/no hospitalization, and no hospitalization/no ER visit were descriptively compared on demographics, health characteristics, and psychosocial burden measures. Results. Almost 16 million adults had a COVID-19 diagnosis in the past year;of these, 8% had a COVID-related hospitalization, and 6% had a COVID-related ER visit/ no hospitalization. Compared to adults with no ER visit/no hospitalization or ER visit/no hospitalization, those with a hospitalization were more often male, college educated, and employed. Relative to those with no ER visit/no hospitalization, adults with a hospitalization were more often diagnosed, either pre- or post-COVID-19 diagnosis, with allergies (47% vs 38%), asthma (20% vs 11%), pain (37% vs. 25%), headache (25% vs 16%), migraine (27% vs 15%), type 2 diabetes (16% vs 10%), dry eye (25% vs 12%), and sleep apnea (15% vs 11%). Adults with a hospitalization had lower mental, physical, and general health-related quality of life, 2-3.4 times higher work/nonwork impairment, and 2 times higher positive depression screen rate than those with no ER visit/no hospitalization. Conclusion. US adults with a COVID-related hospitalization had higher psychosocial burden than those without a hospitalization on several domains. Accordingly, reducing COVID-related hospitalizations, particularly among the employed and those with comorbidities, will be vital to help mitigate this burden.